Journal articles: 'KNApSAck database'

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Prabasari, Kartika, Nia Kurnianingsih, and Nia Kurniawan. "In silico Exploration of Bioactive Compounds from Withania somnifera as Inhibitor for Alpha Delta Bungarotoxin of Bungarus candidus Venom." Biotropika: Journal of Tropical Biology 11, no. 2 (2023): 64–73. http://dx.doi.org/10.21776/ub.biotropika.2023.011.02.01.

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The antivenom for Malayan krait (Bungarus candidus) venom has not yet been available in Indonesia, leading to many fatal snakebite cases. Alternative treatment approaches using medicinal plants are needed to be explored. This study investigated the potential of medicinal plants natural bioactive compounds as toxic alpha-delta protein bungarotoxin inhibitor in B. candidus venom. The approach taken is using the 3D structure of the alpha-delta protein of bungarotoxin B. candidus predicted by SWISS-MODEL. Knapsack Family Database and PubChem were used for bioactive compounds datamining.

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Kibinge, Nelson, Shun Ikeda, Naoaki Ono, Md Altaf-Ul-Amin, and Shigehiko Kanaya. "Integration of Residue Attributes for Sequence Diversity Characterization of Terpenoid Enzymes." BioMed Research International 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/753428.

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Progress in the “omics” fields such as genomics, transcriptomics, proteomics, and metabolomics has engendered a need for innovative analytical techniques to derive meaningful information from the ever increasing molecular data. KNApSAcK motorcycle DB is a popular database for enzymes related to secondary metabolic pathways in plants. One of the challenges in analyses of protein sequence data in such repositories is the standard notation of sequences as strings of alphabetical characters. This has created lack of a natural underlying metric that eases amenability to computation. In view of this requirement, we applied novel integration of selected biochemical and physical attributes of amino acids derived from the amino acid index and quantified in numerical scale, to examine diversity of peptide sequences of terpenoid synthases accumulated in KNApSAcK motorcycle DB. We initially generated a reduced amino acid index table. This is a set of biochemical and physical properties obtained by random forest feature selection of important indices from the amino acid index. Principal component analysis was then applied for characterization of enzymes involved in synthesis of terpenoids. The variance explained was increased by incorporation of residue attributes for analyses.

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Febriyandi, Nuvandaru Fajar Dzikra, Ahmad Shobrun Jamil, and M. Artabah Muchlisin. "Discovery New Drug Cycela barbata in Alcohol Use Disorder Using Pharmacological Methods." Proceedings of International Pharmacy Ulul Albab Conference and Seminar (PLANAR) 3 (November 13, 2023): 194. http://dx.doi.org/10.18860/planar.v3i0.2485.

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Alcohol use disorder (AUD) is a medical condition characterized by an impaired ability to stop or control alcohol use including conditions that some refer to as alcohol abuse, alcohol dependence, alcohol addiction, and the colloquial term, alcoholism. The aim of this research is to find the potential of grass jelly (Cyclea barbata) for treating alcohol. The method used is in silico pharmacological network analysis. Secondary metabolite compound data was obtained from the Knapsack database, prediction of the ability to penetrate the blood brain barrier using the Boiled-Egg method in SwissADME. Prediction of proteins related to C. barbata used SwisstTargetPrediction. Pharmacological network analysis using StringDB and Disease Gene methods. The screening results from KnapSack showed 18 compounds, and only three compounds, namely beta-Cyclanoline, (-)-N-Methylcoclaurine, and (+)-Coclaurine, were predicted to be able to penetrate the blood-brain barrier using Boiled-EGG. From SwissTargetPrediction, 125 proteins related to C. barbata were obtained. From pharmacological network analysis, it was found that 6 proteins were related to alcohol use disorder, namely DRD3, HTR2A, SLC6A3, DRD2, OPRM1, and SLC6A4. So it can be concluded that C. barbata has potential as a plant that can be used to treat AUD.

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Akiyama, Kenji, Eisuke Chikayama, Hiroaki Yuasa, et al. "PRIMe: A Web Site That Assembles Tools for Metabolomics and Transcriptomics." In Silico Biology: Journal of Biological Systems Modeling and Multi-Scale Simulation 8, no. 3-4 (2008): 339–45. https://doi.org/10.3233/isb-00362.

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PRIMe (http://prime.psc.riken.jp/), the Platform for RIKEN Metabolomics, is a Web site that has been designed and implemented to support research and analysis workflows ranging from metabolome to transcriptome analysis. The site provides access to a growing collection of standardized measurements of metabolites obtained by using NMR, GC-MS, LC-MS, and CE-MS, and metabolomics tools that support related analyses (SpinAssign for the identification of metabolites by means of NMR, KNApSAcK for searches within metabolite databases). In addition, the transcriptomics tools provide Correlated Gene Search, and Cluster Cutting for the analysis of mRNA expression. Use of the tools and database can contribute to the analysis of biological events at the levels of metabolites and gene expression, and we describe one example of such an analysis for Arabidopsis thaliana using the batch-learning self-organizing map (BL-SOM), which is provided via the Web site.

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Primadhanty. R. S. Bhadra, Mardiana, Ahmad Fiqri, Ummi Rinandari, Didik H. Utomo, and Muhammad Eko Irawanto. "Analisis In Silico Potensi Minyak Kedelai (Glycine max) dalam Terapi Dermatitis Atopik." MEDICINUS 34, no. 2 (2021): 21–25. http://dx.doi.org/10.56951/medicinus.v34i2.63.

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Minyak kedelai (Glycine max) mengandung berbagai fitokimia bioaktif seperti phenolic acid, flavonoid, isoflavone, saponin, phytosterol, dan sphingolipid yang diduga memiliki manfaat pada pengobatan dermatitis atopik (DA). Penelitian ini bertujuan untuk mengevaluasi potensi kandungan dari minyak kedelai menggunakan analisis in silico secara komputasional pada pengobatan dermatitis atopik. Senyawa aktif dari minyak kedelai diekstraksi dari database KNApSAcK. Hasil yang didapatkan yaitu terdapat potensi bioaktivitas minyak kedelai sebagai imunosupresan, antiinflamasi, perbaikan barrier kulit, antieczema, dan inhibitor histamin. Potensi tertinggi minyak kedelai adalah sebagai antiinflamasi dengan rata-rata nilai probable to be active (Pa) 0,684; senyawa aktif yang memiliki potensi tinggi adalah alpha-tocopherol (Pa:0,956).

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Wijaya, Sony Hartono, Husnawati Husnawati, Farit Mochamad Afendi, et al. "Supervised Clustering Based on DPClusO: Prediction of Plant-Disease Relations Using Jamu Formulas of KNApSAcK Database." BioMed Research International 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/831751.

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Indonesia has the largest medicinal plant species in the world and these plants are used as Jamu medicines. Jamu medicines are popular traditional medicines from Indonesia and we need to systemize the formulation of Jamu and develop basic scientific principles of Jamu to meet the requirement of Indonesian Healthcare System. We propose a new approach to predict the relation between plant and disease using network analysis and supervised clustering. At the preliminary step, we assigned 3138 Jamu formulas to 116 diseases of International Classification of Diseases (ver. 10) which belong to 18 classes of disease from National Center for Biotechnology Information. The correlation measures between Jamu pairs were determined based on their ingredient similarity. Networks are constructed and analyzed by selecting highly correlated Jamu pairs. Clusters were then generated by using the network clustering algorithm DPClusO. By using matching score of a cluster, the dominant disease and high frequency plant associated to the cluster are determined. The plant to disease relations predicted by our method were evaluated in the context of previously published results and were found to produce around 90% successful predictions.

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Ginoga, Muh Fadhil Al-Haaq, Wisnu Ananta Kusuma, and Mushthofa Mushthofa. "Prediksi Interaksi Drug Target pada Gen Kanker Menggunakan Metode Lasso-XGBoost." Jurnal Teknologi Informasi dan Ilmu Komputer 10, no. 3 (2023): 531–42. http://dx.doi.org/10.25126/jtiik.20231036603.

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Pengobatan kanker saat ini sering dilakukan dengan kemoterapi menggunakan obat kimia dan dapat menyebabkan efek samping. Alternatif pengobatan dapat menggunakan senyawa herbal yang diketahui memiliki efek samping lebih sedikit. Analisis Drug Target Interaction (DTI) dapat dilakukan untuk mengetahui interaksi senyawa herbal terhadap protein kanker. Pada penelitian ini dilakukan perancangan model prediksi DTI dengan melakukan seleksi fitur pada dataset menggunakan Least Absolute Shrinkage and Selection Operator (LASSO) lalu dilakukan penyeimbangan data dengan Synthetic Minority Oversampling Technique (SMOTE) dan diprediksi menggunakan Extreme Gradient Boosting (XGBoost). Data protein terkait kanker didapatkan dari daftar Cancer Gene Census, dari daftar tersebut dilakukan penelusuran pada database GDSC, DrugCentral, dan DrugBank untuk menghasilkan daftar senyawa obat yang berinteraksi dengan protein tersebut. Selain itu, senyawa herbal dihasilkan dari database HerbalDB dan Knapsack. Pengujian dilakukan pada beberapa jenis ekstraksi fitur seperti CTD, DC, PseAAC, dan PSSM. Hasil prediksi menunjukkan beberapa senyawa herbal seperti andrographolide, ursolic acid dan oleanolic acid memiliki interaksi pada protein terkait kanker. Selain itu, LASSO-XGBoost dapat memprediksi DTI pada kanker dengan skor F1 0,861; AUROC 0,927; recall 0,85; precision 0,866; dan accuracy 0,897. AbstractCurrently, cancer treatment is usually done with chemotherapy using chemical drugs that can cause side effects. An alternative treatment can use herbal compounds that known have fewer side effects. Drug Target Interaction analysis (DTI) can be performed to determine the interaction of herbal compounds with cancer proteins. In this study, a DTI prediction model is built by selecting features on the data set using Least Absolute Shrinkage and Selection Operator (LASSO) then data balancing performed with Synthetic Minority Oversampling Technique (SMOTE) and Extreme Gradient Boosting (XGBoost) performed to predict the interaction. The cancer-associated protein data were obtained from the Cancer Gene Census list, then the list used to search on the GDSC, DrugCentral and DrugBank databases to generate a list of drug compounds that interact with these proteins. In addition, plant compounds to be generated from the HerbalDB and Knapsack databases. Tests were performed on several types of feature extraction such as CTD, DC, PseAAC and PSSM. Predictive results suggest that several herbal compounds such as andrographolide, ursolic acid and oleanolic acid interact with cancer-associated proteins. In addition, LASSO-XGBoost was able to predict DTI in cancer with score of F1 0,861; AUROC 0,927; recall 0,857, precision 0,866; and accuracy 0,897.

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Ginoga, Muh Fadhil Al-Haaq, Wisnu Ananta Kusuma, and Mushthofa Mushthofa. "Prediksi Interaksi Drug Target pada Gen Kanker Menggunakan Metode Lasso-XGBoost." Jurnal Teknologi Informasi dan Ilmu Komputer 10, no. 3 (2023): 531–42. https://doi.org/10.25126/jtiik.2023106603.

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Pengobatan kanker saat ini sering dilakukan dengan kemoterapi menggunakan obat kimia dan dapat menyebabkan efek samping. Alternatif pengobatan dapat menggunakan senyawa herbal yang diketahui memiliki efek samping lebih sedikit. Analisis Drug Target Interaction (DTI) dapat dilakukan untuk mengetahui interaksi senyawa herbal terhadap protein kanker. Pada penelitian ini dilakukan perancangan model prediksi DTI dengan melakukan seleksi fitur pada dataset menggunakan Least Absolute Shrinkage and Selection Operator (LASSO) lalu dilakukan penyeimbangan data dengan Synthetic Minority Oversampling Technique (SMOTE) dan diprediksi menggunakan Extreme Gradient Boosting (XGBoost). Data protein terkait kanker didapatkan dari daftar Cancer Gene Census, dari daftar tersebut dilakukan penelusuran pada database GDSC, DrugCentral, dan DrugBank untuk menghasilkan daftar senyawa obat yang berinteraksi dengan protein tersebut. Selain itu, senyawa herbal dihasilkan dari database HerbalDB dan Knapsack. Pengujian dilakukan pada beberapa jenis ekstraksi fitur seperti CTD, DC, PseAAC, dan PSSM. Hasil prediksi menunjukkan beberapa senyawa herbal seperti andrographolide, ursolic acid dan oleanolic acid memiliki interaksi pada protein terkait kanker. Selain itu, LASSO-XGBoost dapat memprediksi DTI pada kanker dengan skor F1 0,861; AUROC 0,927; recall 0,85; precision 0,866; dan accuracy 0,897. AbstractCurrently, cancer treatment is usually done with chemotherapy using chemical drugs that can cause side effects. An alternative treatment can use herbal compounds that known have fewer side effects. Drug Target Interaction analysis (DTI) can be performed to determine the interaction of herbal compounds with cancer proteins. In this study, a DTI prediction model is built by selecting features on the data set using Least Absolute Shrinkage and Selection Operator (LASSO) then data balancing performed with Synthetic Minority Oversampling Technique (SMOTE) and Extreme Gradient Boosting (XGBoost) performed to predict the interaction. The cancer-associated protein data were obtained from the Cancer Gene Census list, then the list used to search on the GDSC, DrugCentral and DrugBank databases to generate a list of drug compounds that interact with these proteins. In addition, plant compounds to be generated from the HerbalDB and Knapsack databases. Tests were performed on several types of feature extraction such as CTD, DC, PseAAC and PSSM. Predictive results suggest that several herbal compounds such as andrographolide, ursolic acid and oleanolic acid interact with cancer-associated proteins. In addition, LASSO-XGBoost was able to predict DTI in cancer with score of F1 0,861; AUROC 0,927; recall 0,857, precision 0,866; and accuracy 0,897.

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Saputro, Dominyda Vebrianto, Ahmad Shobrun Jamil, M. Artabah Muchlisin, and Irsan Fahmi Almuhtarihan. "A Network Pharmacology of Lemongrass (Cymbopogon citratus) on COVID-19 Cases." Proceedings of International Pharmacy Ulul Albab Conference and Seminar (PLANAR) 3 (November 13, 2023): 49. http://dx.doi.org/10.18860/planar.v3i0.2471.

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Various ways and treatment efforts are carried out to avoid the severe impact of COVID-19 cases, one of which is using plants as natural immunomodulatory agents. One of the plants that is proven to act as a natural immunomodulator is lemongrass (Cymbopogon citratus). This study aimed to determine the protein tissue associated with the body's immune system activated by C. citratus. The secondary metabolites of C. citratus were identified using the KNApSAck and Dr. Duke databases. Target proteins associated with plant-secondary metabolite compounds from the SwissTargetPrediction database and immunomodulatory-associated target proteins were obtained from the GeneCards database. The intersected proteins were put into StringDB and analyzed using KEGG to obtain network pharmacology. 98 secondary metabolite compounds of C. citratus were obtained from the database. Proteins associated with C. citratus contain 1096 compounds, and those related to immunomodulators contain 1380 proteins. The intersection results obtained 244 proteins predicted to interact with C. citratus and are related to immunomodulators. From the results of KEGG analysis, five pathways related to C. citratus were obtained, namely PD-L1 expression and PD-1 checkpoint pathway in cancer, Fc epsilon RI signaling pathway, Th17 cell differentiation, T cell receptor signaling pathway, and IL-17 signaling pathway. MAPK 1, MAPK 3, and MAPK 14 proteins are predicted to be in all five related pathways, and Mol 13 compounds are predicted to be able to interact with these three proteins. Thus, it can be concluded that the compound Mol 13 is the compound that plays the most role in acting as an immunomodulator in C. citratus.

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Huma, Qureshi, Anwar Tauseef, Khan Sadiqullah, Fatimah Hina, and Waseem Muhammad. "Phytochemical constituents of Broussonetia papyrifera (L.) L'He'r. ex Vent: An overview†." Journal of Indian Chemical Society Vol. 97, Jan 2020 (2020): 55–65. https://doi.org/10.5281/zenodo.5651019.

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Department of Biological Sciences (Botany Program), Gomal University, Dera Ismail Khan-29050, Pakistan Department of Botany, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi-46300, Pakistan E-mail: humaqureshi8@gmail.com Department of Environmental Science, Gomal University, Dera Ismail Khan-29050, Pakistan Department of Biology, Allama Iqbal Open University, Islamabad-46000, Pakistan Manuscript received online 15 October 2019, revised and accepted 06 January 2020 Phytochemistry is an important field of plant biology with a number of applied research applications. Whole metabolome based phytochemical analysis of plants is a technique that requires profiling of known compounds from the plant. In this paper, we present a detailed review of known phytochemistry of paper mulberry tree after a thorough survey of available literature as well as different databases (KnapSack, Plant metabolome database (PMDB), PubChem, ChemSpider) in favor of whole metabolome based phytochemical analysis. A detailed account of known phytochemistry of Broussonetia papyrifera sheds light on the multipurpose economic importance (medicinal, high quality fiber, severe pollen allergy, phytotoxic, invasive) of plant.

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Setiani, Lusi Agus, Wisnu Ananta Kusuma, and Fitria Nadiatul Rizal. "Exploring the Potential Mechanism of “X” Jamu Capsule in Treating Hypertension Based on Network Pharmacology." FITOFARMAKA: JURNAL ILMIAH FARMASI 14, no. 2 (2024): 99–109. https://doi.org/10.33751/jf.v14i2.11.

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Jamu is a traditional medicine derived from plants, animals, minerals, and galenic preparations that are used empirically as a treatment. Hypertension is a condition when the systolic blood pressure is > 140 mmHg and the diastolic blood pressure is > 90 mmHg. The purpose of this research is to describe the mechanism of action of Jamu which consists of six plants, namely Apium Graveolens, Orthosiphon aristatus, Imperatae cylindrica, Phyllanthus niruri, Centella asiatica, and Curcuma xanthorrhiza as antihipertensive using network pharmacology because the herbs are formula with multi-components and multi-targets. This research was conducted by searching for compounds in each plant using the knapsack and IJAH Analytic databases, 187 compounds were obtained and filtered based on oral bioavailability (OB) and drug-likeness (DL) values yielded 40, searched for the target protein obtained 2198 proteins in Swisstargetprediction database, searching for hypertension target proteins in the OMIM and Uniprot databases found 338 proteins, then for compound target proteins and hypertension targets searched for protein overlap manually in the cytoscape application obtained 10 proteins, then these proteins were analyzed using the Database for Annotation Visualization and Integrated Discovery (DAVID) it was found that the most significant signaling is PI3K-Akt, which is associated with increased NO production, resulting in vascular relaxation and influencing blood pressure. The signaling is influenced by the work of JAK2, MDM2, INSR, NOS3, and VEGFA proteins. These proteins are the target proteins of 10 compounds contained in the plants Orthosiphon aristatus, Phyllanthus niruri, Centella asiatica, and Curcuma xanthorrhiza.

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Adianingsih, Oktavia Rahayu, Fifi Farida Fajrin, and Christopher Kuncoro Johan. "Exploring the mechanism of Glycyrrhiza glabra and Curcuma domestica against skin photoaging based on network pharmacology." Indonesian Journal of Biotechnology 29, no. 2 (2024): 98. http://dx.doi.org/10.22146/ijbiotech.93332.

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Excessive exposure to UV radiation results in skin photoaging, which may be prevented or treated using natural plant compounds. Herbal cosmetics and medicines have grown in popularity due to the abundance of relatively safe compounds. This research aims to explore the network pharmacology of Glycyrrhiza glabra (GG) and Curcuma domestica (CD) against skin photoaging. Active compounds from GG‐CD were sourced from databases including TCSMP, KnapSack, TCMID, and published literature, while disease targets were collected from GeneCards and OMIM databases. The STRING database was utilized to construct the protein‐protein interaction (PPI) network. Enrichment analyses for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed using Metascape. The herb‐compounds‐target‐pathway‐disease (H‐C‐T‐P‐D) network was visualized using Cytoscape software. A total of 529 compounds, 2,335 active compound targets, and 120 skin aging targets were obtained. GO enrichment revealed 1,635 biological processes, 67 cellular components, and 121 molecular functions. The study suggests that GG and CD have the potential to treat skin photoaging by targeting multiple targets, such as TP53, TNF, AKT1, IL6, and IL‐1B, as well as multiple pathways, such as those in cancer, apoptosis, TNF, IL‐17, and the AGE‐RAGE signaling pathway. Experiment validation is necessary to confirm the preliminary network pharmacology results.

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Oishi, Takashi, Ken-ichi Tanaka, Takuya Hashimoto, et al. "An approach to peak detection in GC-MS chromatograms and application of KNApSAcK database in prediction of candidate metabolites." Plant Biotechnology 26, no. 1 (2009): 167–74. http://dx.doi.org/10.5511/plantbiotechnology.26.167.

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Liu, K., Md Altaf-Ul-Amin, A. A. Abdullah, A. H. Morita, M. Shiraishi, and S. Kanaya. "A novel plant classification method based on similarities in chemical structures of metabolite contents obtained from the KNApSAcK database." Acta Horticulturae, no. 1169 (July 2017): 139–50. http://dx.doi.org/10.17660/actahortic.2017.1169.21.

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Kumar, Rajeev. "Algorithms for Selecting the Optimum Dataset While Providing Personalized Privacy and Compensation to its Participants." International Journal of Operations Research and Information Systems 8, no. 4 (2017): 43–58. http://dx.doi.org/10.4018/ijoris.2017100103.

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The privacy preserving microdata sharing literature has proposed several techniques that allow a database administrator to share a dataset in a privacy preserving manner. This paper considers the implications of adding a market layer to that setting. In this setting, individuals (data providers) can receive a market-determined compensation in exchange for their information while they also receive a personalized privacy protection. The computational burdens of satisfying a variety of privacy requirements of individuals (sellers) and dataset requirements of the data receiver (buyer) are analyzed in this paper. The author presents a polynomial time reformulation procedure that proves that the “optimum information product” creation problem reduces to multiple-choice knapsack problem, which is a weakly NP hard problem. The problem of various instance sizes is solved using FICO Xpress 7.0 optimization software. The insights presented in the paper can be utilized for creating a market of individual information in different settings.

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Supratik, Adhikary, and Aditi Nayak Dr. "In Silico Analysis of Secondary Metabolite Biosynthesis Clusters in the Genome of Panicum virgatum." International Journal of Scientific Development and Research 8, no. 7 (2023): 552–63. https://doi.org/10.5281/zenodo.8374134.

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A biosynthetic gene cluster (BGC) is a group of genes in a genome that collectively encode the enzymes responsible for producing a specific natural product, such as a secondary metabolite or a bioactive compound with diverse biological activities, including antibiotics, antifungals, antiviral agents. Understanding the structure and function of these biosynthetic gene clusters is important for developing new pharmacological compounds. By studying these clusters, it would be beneficial in identifying the potential targets for drug development and strategies to prevent the spread of antibiotic resistance. In this study, we identified biosynthetic gene clusters in Panicum virgatum. The plant possess various medicinal properties. Using KNApSAck database, we identified the secondary metabolites present in the plant. PlantiSMASH is a bioinformatics tool that can be used to identify biosynthetic gene clusters (BGCs) in plant genomes. Using PlantiSMASH, BGCs in Panicum virgatum genomes were predicted. This study gives an insights into the secondary metabolism of Panicum virgatum, and identify potential targets for genetic engineering to improve the nutritional value or other properties of the plant. Hence, the Biosynthetic gene clusters in Panicum virgatum offer a promising avenue for improving the productivity, nutritional value, and health benefits.

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Arrohmah, Robiatus Sholichah, Afina Anjani Ibtisam, Siti Malihatus Sa’adah, Fensy Rania Putri, and Fitriyah Fitriyah. "Bioactivity mapping of secondary metabolite compounds of Pandanus amaryllifolius leaves as anti-inflammatory using in silico." Journal of Natural Sciences and Mathematics Research 9, no. 1 (2023): 50–59. http://dx.doi.org/10.21580/jnsmr.2023.9.1.16215.

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Inflammation is one of the primary responses of the immune system to infection and irritation. Anti-inflammatory drugs generally cause side effects. Anti-inflammatory developed by reducing side effects use many natural materials such as plants. The parts of the plant used include fruits, leaves, stem bark, rhizomes, and flowers. One of the plants that can be used as an anti-inflammatory is Pandanus amaryllifolius. P. amaryllifolius leaves contain several materials, such as flavonoids, alkaloids, saponins, tannins, polyphenols, and dyes. This study aimed to determine the anti-inflammatory potential of the secondary metabolites of Pandanus amaryllifolius leaves using the in silico method. The research used a descriptive exploratory method and was conducted from December 2022 – January 2023. In silico mapping of the bioactivity of active compounds was carried out using several software or websites: knapsack database (www.knapsackfamily.com), NCBI PubChem database (https://pubchem.ncbi.nlm.nih.gov/), PASS Online Way 2 Drug (http://www.way2drug.com/passonline/) and ADME Swiss Analysis (http://www.swissadme.ch/). The result shows P. amarylifolius has 31 active compounds. The compounds were then analyzed using Pass Online with 18 anti-inflammatory parameters. It explained that 3 compounds met the rules for Pa values 0.7, namely compounds 6E-Pandanamine (0.758), Pandamenyamine (0.735), and Pandamarilactone 1 (0.709). The results of pharmacokinetic tests using Lipinski

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Ramadhan, Dwi Syah Fitra, Taufik Muhammad Fakih, and Arfan Arfan. "Activity Prediction of Bioactive Compounds Contained in Etlingera elatior Against the SARS-CoV-2 Main Protease: An In Silico Approach." Borneo Journal of Pharmacy 3, no. 4 (2020): 235–42. http://dx.doi.org/10.33084/bjop.v3i4.1634.

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The COVID-19 pandemic has become a serious problem today, with its prevalence increasing every day. The SARS-CoV-2 main protease (MPro) is a promising therapeutic target to inhibit replicating and spreading the virus that causes COVID-19. The compounds contained in the Etlingera elatior plant has the potential. This study aimed to examine the compounds' activity in E. elatior against SARS-CoV-2 MPro using in silico methods. A total of seven compounds contained in E. elatior were obtained from the Knapsack database. The compounds were then docked into the SARS-CoV-2 MPro receptor's active site with the PDB ID 6LU7. Afterward, the biological activities were predicted by the PASS prediction webserver. The molecular docking results showed that ergosterol peroxide and sitostenone had the best binding energy with -10.40 kcal/mol and -9.17 kcal/mol, respectively. The in silico PASS prediction showed it has potential as antiviral therapy. It concluded ergosterol peroxide and sitostenone has the potential as SARS-CoV-2 MPro inhibitor candidate.

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Hadi, Samsul, Deni Setiawan, Kunti Nastiti, Muhammad R. Ridha, and Yustinus Maladan. "Screening for Alcohol Dehydrogenase Inhibitors from Dendrobium Using the In-silico Method." INTERNATIONAL JOURNAL OF DRUG DELIVERY TECHNOLOGY 13, no. 02 (2022): 568–75. http://dx.doi.org/10.25258/ijddt.13.2.17.

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The incidence of acute kidney failure has become a concern and needs preventive action as soon as possible. Fomepizole and ethanol are the treatment options for acute kidney injury (AKI). The development approach is carried out through structural approaches to fomepizole or ethanol, anti-inflammatory activity, and chelate formation. Dendrobium is a potential plant with various activities and many secondary metabolites such as bibenzyl, alkaloids, sesquiterpenes, and phenanthrenes. This study aims to find compounds that have the potential to be ADH inhibitors from Dendrobium using the in-silico method. To identify potential natural compounds, 94 compounds from Dendrobium were taken from the KNApSAcK family database. Files from the receptor were prepared with YASARA software. Protox-II used to predict compound toxicity. Three compounds were obtained: o-succinyl benzoic acid, 3,4’-Dihydroxy-5-methoxybibenzyl, and gigantol. All of them interact stably with ADH based on energy binding values. O-succinyl benzoic acid as the strongest, followed by gigantol, and 3,4’-Dihydroxy-5-methoxybibenzyl.

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Annisadila, Shindy, Ahmad Shobrun Jamil, and M. Artabah Muchlisin. "Bioavaibility Evaluation and Molecular Docking of Cananga odorata Plant as Anti-Inflammatory Potential Against Crohn’s Disease." Proceedings of International Pharmacy Ulul Albab Conference and Seminar (PLANAR) 3 (November 13, 2023): 126. http://dx.doi.org/10.18860/planar.v3i0.2478.

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Crohn's disease is a chronic inflammatory bowel disease (IBD) that affects the digestive tract. One of the potential targets for this disease is LRRK2. Kenanga (Cananga odorata) is known to have anti-inflammatory effects. The study aims to identify the potential of the secondary metabolite compounds found in C. odorata against LRRK2 in silico. The KnapSack database was used to identify the secondary metabolite compounds of C. odorata, SwissADME was used to find the compound with high bioavailability with the Boiled-EGG method, and PyRx with the AutoDock was used for molecular docking. According to the docking results, three compounds are potentially inhibiting LRRK2, namely (+)-Reticuline with a binding energy of -9.04 kcal/mol and a prediction of inhibition constant (pKi) of 237.71 nM, benzyl benzoate with a binding energy of -8.19 kcal/mol and a prediction of inhibition constant (pKi) of 994.29 nM and benzyl salicylate with a bonding energy of -8.22 kcal/mol and a prediction of inhibition constant (pKi) of 942.48 nM.

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Prasetyorini, Budi Eko, Arie Kusumawardani, Fatimah Fitriani, Putri Ooktriana Rachman, Nathania Amelinda, and Anggia Ramadhani. "Analisis In Silico Senyawa Aktif Batang Kayu Bajakah (Spatholobus littoralis Hassk) Sebagai Terapi Psoriasis." Herb-Medicine Journal 5, no. 1 (2022): 26. http://dx.doi.org/10.30595/hmj.v5i2.12744.

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Background : Innovative topical psoriasis therapy continues to be developed, Spatholobus littoralis Hassk or Bajakah has antipsoriatic activity so can be used as a topical herbal medicine in reducing the severity of psoriasis. In silico is a computational experiment which is analogous to biological experiments in vivo and in vitro. Objective : To evaluate content of Spatholobus littoralis Hassk using in silico analysis in the treatment of psoriasis. Methods : The active compound Spatholobus littoralis Hassk extracted from the knapsack database. The simplified molecular input line entry system (SMILE) format was taken from the pubchem database. Prediction in antioxidants, antiinflammatory, antipruritic and immunosuppressive was done using a pass server. The molecular mechanism of active compounds in human body was taken from search tool for interacting chemicals (STITCH) which was predicted experimentally, then analyzed computationally. Further pathway analysis using cytoscape software. Results : There are 14 active compounds in Spatholobus littoralis Hassk have potential as antioxidants, anti-inflammatory, antipruritic and immunosuppressive are predicted to have ability test computationally tested activity but laboratory tests have not been proven or have little potential. The highest bioactivity potential of Spatholobus littoralis Hassk is antioxidants where the most important role is dihydrokaemferol with an average probable to be active (Pa) value of 0.691, the compound has ability to computationally test but in laboratory tests it has not been proven or has a small potential. Conclusions : Spatholobus littoralis Hassk is a good choice for the treatment of psoriasis. Latar belakang : Terapi psoriasis topikal inovatif terus dikembangkangkan, Spatholobus littoralis Hassk atau bajakah memiliki aktivitas antipsoriatik sehingga dapat digunakan sebagai obat herbal topikal dalam mengurangi keparahan psoriasis. In silico merupakan percobaan komputasi yang analog dengan percobaan biologis secara in vivo dan in vitro. Tujuan : Untuk mengevaluasi kandungan Spatholobus littoralis Hassk menggunakan analisis in silico pada pengobatan psoriasis. Metode : Senyawa aktif Spatholobus littoralis Hassk yang diekstraksi dari database knapsack. Format simplified molecular input line entry system (SMILE) diambil dari basis data pubchem. Prediksi dalam antioksidan, antiinflamasi, antipruritus dan immunosupresor dilakukan menggunakan pass server. Mekanisme molekuler senyawa aktif dalam tubuh manusia diambil dari search tool for interacting chemicals (STITCH) yang diprediksi secara eksperimental, kemudian dianalisis secara komputasional. Analisis pathway lebih lanjut menggunakan perangkat lunak cytoscape. Hasil : Terdapat 14 senyawa aktif pada Spatholobus littoralis Hassk yang memilik potensi sebagai antioksidan, antiinflamasi, antipruritus dan immunosupresor diprediksi memiliki kemampuan pada aktivitas yang diuji secara komputasional, namun secara uji laboratorium belum terbukti atau memiliki potensi kecil. Potensi bioaktivitas Spatholobus littoralis Hassk tertinggi adalah antioksidan dimana yang paling berperan adalah dihydrokaemferol dengan ata-rata nilai probable to be active (Pa) 0,691 dimana senyawa tersebut secara komputasional memiliki kemampuan pada aktivitas yang diuji namun secara uji laboratorium belum terbukti atau memiliki potensi kecil. Kesimpulan : Spatholobus littoralis Hassk merupakan pilihan yang baik untuk terapi psoriasis karena memiliki efek antioksidan, antiinflamasi, antipruritus dan immunosupresor serta menguntungkan dari segi ketersediaan serta keamanan.

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Setiawan, Risma Ayu, Ahmad Shobrun Jamil, Siti Rofida, and M. Artabah Muchlisin. "Melaleuca leucadendra Pharmacological Network for Identifying Potential Target of Alcohol Dependence." Proceedings of International Pharmacy Ulul Albab Conference and Seminar (PLANAR) 3 (November 13, 2023): 111. http://dx.doi.org/10.18860/planar.v3i0.2477.

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Melaleuca leucadendra (ML) contains a compound that is potentially a candidate for alcohol dependence. Alcohol dependence is defined by desire, tolerance, anxiety with alcohol, and continuing to drink even though the consequences are dangerous. The study aims to analyze the potential of the ML compound content for alcohol dependence therapy within silico-based pharmacological chain analysis. ML compound data is obtained from the Knapsack database, screening of absorption, distribution, metabolism, and excretion (ADME) of the compounds ML with SwissADME, prediction of the protein of the target compounder ML with the Swiss TargetpPrediction, Gene cards, venny, analysis of the pharmacological network with String-DB and its visualization with Cytoscape version 3.10.0. The pathways correlated with therapy are dopamine receptors, dopamine carriers, serotonin, gamma-aminobutyric acid receptors, and toll-like receptors for known therapeutic target proteins: OPRM1, DRD2, ALDH2, ADH1B, ADH1A, ADH1C, ADH4, SLC6A3, CNR1, POMC, ARRB2, and NCS1. Alcohol-dependent therapies include alpha-Campholenal, Benzaldehyde, trans-Pinocarveol, Borneol, linalool, alfa-Terpineol, (-)-alpha-Bisabolol oxide B, alphaterpine acetate, and Caryophylla-4(148),15-dien-5alphaol.

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Wijaya, Johanna Fransiska, Linda Chiuman, Hariyadi Dharmawan Syahputra, et al. "Investigation of Potential Molecular Targets of Zanthoxylum acanthopodium in Ovarian Cancer Using Network Pharmacology Assessments." Journal of Multidisciplinary Applied Natural Science 5, no. 2 (2025): 630–43. https://doi.org/10.47352/jmans.2774-3047.268.

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Ovarian cancer is a serious disease that affects the ovaries, and its early detection is challenging due to vague symptoms often dismissed as minor ailments. Currently, natural sources have gained attention for their potential role in anticancer treatment. This study aimed to utilize network pharmacology to explore the potential targets and mechanisms of Zanthoxylum acanthopodium in the treatment of ovarian cancer. This study utilized the KNApSAcK and Swiss Target Prediction to identify active compounds and target genes. Additionally, ovarian cancer-specific target genes were sourced from the GEO database. To identify possible key target genes, the network interaction between protein-protein using the STRING database and visualized them in Cytoscape. Subsequent analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enabled us to focus on primary therapeutic targets. Our investigation into Zanthoxylum acanthopodium revealed 10 active compounds that pass Lipinski rule of five and oral bioavailability with acceptable pharmacokinetic profiles, 88 therapeutic targets, and identified 5 hub genes: SRC, CCNB2, MMP9, PTGS2, and PTPRC, which are strongly associated with ovarian cancer progression. Pathway enrichment analysis highlighted several pathways significantly related to the pathogenesis of ovarian cancer. This study elucidates the therapeutic potential and mechanisms of action of Z. acanthopodium as a promising candidate for ovarian cancer treatment. However, further research, including both in vitro and in vivo studies, is necessary to understand its molecular mechanisms comprehensively.

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Yongpisanphop, J. "Searching for a plant species having a potent bioherbicide using in silico approach." Research Journal of Chemistry and Environment 26, no. 1 (2021): 97–103. http://dx.doi.org/10.25303/2601rjce97103.

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Toxic herbicide residue in the environment is one of the most important problems in the world, especially in the agricultural country. To solve this problem, an effectively new bioherbicide needs to be discovered urgently. This motivated to search the novel bioherbicide. In silico technique has been accepted as a promising tool to discover new active compounds. Based on 2D structural similarity, 18 new natural compounds were obtained from the KNApSAcK database. Among the structural leads, 12 natural phyto-compounds were selected to calculate the lowest free energy of binding value using molecular docking. Comp_7 and Comp_10 showed the lowest free energy of binding -7.84 and -7.43 kcal/mol respectively which were similar to glyphosate (-8.49 kcal/mol). Based on the binding interaction using ProteinsPlus program, a natural phyto-compound (Comp_7: L-2- Aminoadipate) was identified as a potential bioherbicide. It could be found in Medicago sativa L. Significantly, this procedure becomes a high powerful tool to increase the probability to discover the new potent bioherbicide and identify the plant host species for weed control. Moreover, M. sativa should be extracted to test the property of weed control for further study.

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Anwar, La Ode Muhammad, Anas Kiki Anugrah, Embriana Dinar Pramestyani, et al. "Studi Farmakokinetik dan Toksisitas Senyawa Biji Jintan Hitam (Nigella sativa)." Jurnal Mandala Pharmacon Indonesia 10, no. 2 (2024): 736–42. https://doi.org/10.35311/jmpi.v10i2.661.

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Studi farmakokinetik dan toksisitas merupakan salah satu parameter dalam pengembangan obat. Parameter farmakokinetik meliputi nilai absorbs, distribusi, metabolisme dan eliminasi obat sedangkan nilai toksisitas merupakan factor keamanan pada suatu komponen senyawa atau sediaan. Tujuan dari penelitian ini adalah untuk melihat nilai farmakokinetik dan toksisitas pada tanaman jintan hitam (Nigella sativa). Database senyawa diperoleh pada situs Take out "JAMU" of KNApSAcK dan dianalsis kode SMILES pada platfrom PubChem. Selanjutnya dilakukan analisis farmakokinetik dan toksisitas menggunakan situs pkCSM kemudian dievaluasi menggunakan kaidah aturan Lipinski. Hasil penelitian didapatkan sebanyak 26 senyawa metabolit. Nilai absorbsi pada intestinal menunjukan semua senyawa terabsorbsi menyeluruh, sedangkan 4 senyawa terabsorbsi pada P-glycoprotein. Terdapat 24 senyawa yang tidak dapat menembus Blood-Brain Barrier (BBB) dan 10 senyawa tidak mampu menembus SSP. Semua senyawa bukan menjadi substrat CYP2D6 dan 9 senyawa yang menjadi substrat CYP3A4. Nilai total clearance antara -0.016 sampai 1.991 dengan 1 senyawa yang menjadi substrat OCT2. Uji toksisitas menunjukan terdapat 8 senyawa mutagenic dan 5 senyawa bersifat hepatotoksik. Evaluasi menggunakan aturan Lipinski terdapat 10 senyawa yang memenuhi syarat. Dapat disimpulkan bahwa, 10 senyawa yang terdapat pada biji jintan hitam memenuhi syarat dalam pengembangan obat baru.

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Widyaswari, Meidyta Sinantryana, Iis Noventi, and Herdiantri Supriyana. "Anti-eczema Mechanism of Action of Nigella sativa for Atopic Dermatitis: Computer-aided Prediction and Pathway Analysis Based on Protein-chemical Interaction Networks." Biomolecular and Health Science Journal 2, no. 2 (2019): 68. http://dx.doi.org/10.20473/bhsj.v2i2.15007.

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Introduction: Black cumin (Nigella sativa) is widely used to treat various diseases. It is also believed to relief skin conditions accompanied by itching symptom, such as atopic dermatitis (AD) or eczema. However, the anti-eczema mechanism of action is still unclear. The aims of this syudy was to identify anti-eczema mechanism of action of N. sativa for AD using computer aided prediction and pathway analysis based on protein-chemical networks. Methods: We utilized dataset consisting chemical compounds of N. sativa from KNApSAcK. It is a comprehensive species-metabolite relationship database. Using canonical SMILES strings that encode molecular structures of each compound, we predicted the probabilities of activity (Pa) for anti-eczema effect based on PASS algorithms. The compounds with Pa >0.7 were included for pathway analysis based on protein-chemical interaction networks in STITCH database. We selected interactomes built by experimental data, gene co-expression, closest gene position, fusion, co-occurence, computational prediction, and other secondary data. Results: Thirty-five active compounds of N. sativa have been utilized and 19 of them have potential anti-eczema effects. Oleic acid and lauric acid were predicted with Pa-value of 0.947 and 0.920 for anti-eczema effect, respectively. However, only lauric acid was confirmed having a plausible mechanism of action via LY96-TLR4- PIK3R1 pathway for lipopolysaccharide receptor activity (false discovery rate [FDR] = 0.0243) and low-density lipoprotein particle receptor binding (FDR = 0.0118). Conclusion: Lauric acid in N. sativa has potential antieczema effect to prevent relaps in AD patients by controlling opportunistic bacterial infection that aggravates itching symptom in this condition.

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Handayani, Vitri Aprilla, Farit Mochamad Afendi, and Wisnu Ananta Kusuma. "Penguraian Mekanisme Kerja Jamu Berdasarkan Jejaring Bahan Aktif-Protein Target-Gene Ontology." Jurnal Jamu Indonesia 1, no. 3 (2016): 18–28. http://dx.doi.org/10.29244/jji.v1i3.21.

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Jamu merupakan obat tradisional Indonesia. Pada dasarnya obat herbal yang dibuat dari bahan-bahan alami yang diambil dari beberapa bagian dari tanaman obat yang mengandung beberapa zat dan senyawa yang penting dan bermanfaat bagi tubuh. Sejauh ini, khasiat untuk beberapa jenis jamu secara empiris telah terbukti. Dalam peneitian ini, kami bermaksud untuk menguraikan mekanisme kerja jamu menggunakan pendekatan komputasi. Penelitian ini berfokus pada ramuan jamu type 2 diabetesyang terdiri dari empat tanaman, yaitu: jahe, bratawali, sembung, dan pare. Kerangka analisis awal dengan membentuk 3 komponen jejaring yang terdiri dari: (1) bahan aktif tanaman (diperoleh dari Knapsack: 58 senyawa aktif), (2) protein target (diperoeh dari database pubchem: 416 protein target), dan (3) gene ontoogy(diperoeh dari database DAVID: 3104 GO). Selanjutnya, kami menerapkan analisis klaster-klasterdengan menggunakan konsep graf tri-partite. Graf tri-partite digunakan untuk mengelompokkan komponen-komponen penyusun jejaring dari empat tanaman yang disebutkandiatas, sehingga diperoleh system bagian-bagian penyusun ramuan jamu. Hal ini dilakukan untuk mengungkapkan mekanisme kerja jamu. Menggunakan metode fuzzy clustering pada data jejaring, kami memperoleh 15 senyawa aktif yang diduga potensial sebagai antidiabetes berada dalam kelompok berbeda. Pada 15 senyawa aktif memiliki nilai peluang cukup tinggi terbagi dalam kelompok yang berbeda, setiap kelompok terdiri dari pasangan bahan aktif yang memiliki efek sinergis tinggi. Berdasarkan koneksi antara klaster-klasterprotein dan GO-BP, penelitianini memperoleh informasi protein-protein yang menyebabkan T2D dan mekanisme proses biologis yang terkait. T2D bukan hanya disebabkan oleh protein kelainan sekresi insulin (insulin-merendahkan enzim isoform 1) saja, tetapi juga disebabkan oleh protein lain yang terlibat dalam penghambatan insulin di pankreas.

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Aprilla Handayani, Vitri, Farit Mochamad Afendi, and Wisnu Ananta Kusuma. "Penguraian Mekanisme Kerja Jamu Berdasarkan Jejaring Bahan Aktif-Protein Target-Gene Ontology." Jurnal Jamu Indonesia 1, no. 3 (2016): 18–28. http://dx.doi.org/10.29244/jjidn.v1i3.30640.

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Jamu merupakan obat tradisional Indonesia. Pada dasarnya obat herbal yang dibuat dari bahan-bahan alami yang diambil dari beberapa bagian dari tanaman obat yang mengandung beberapa zat dan senyawa yang penting dan bermanfaat bagi tubuh. Sejauh ini, khasiat untuk beberapa jenis jamu secara empiris telah terbukti. Dalam peneitian ini, kami bermaksud untuk menguraikan mekanisme kerja jamu menggunakan pendekatan komputasi. Penelitian ini berfokus pada ramuan jamu type 2 diabetesyang terdiri dari empat tanaman, yaitu: jahe, bratawali, sembung, dan pare. Kerangka analisis awal dengan membentuk 3 komponen jejaring yang terdiri dari: (1) bahan aktif tanaman (diperoleh dari Knapsack: 58 senyawa aktif), (2) protein target (diperoeh dari database pubchem: 416 protein target), dan (3) gene ontoogy(diperoeh dari database DAVID: 3104 GO). Selanjutnya, kami menerapkan analisis klaster-klasterdengan menggunakan konsep graf tri-partite. Graf tri-partite digunakan untuk mengelompokkan komponen-komponen penyusun jejaring dari empat tanaman yang disebutkandiatas, sehingga diperoleh system bagian-bagian penyusun ramuan jamu. Hal ini dilakukan untuk mengungkapkan mekanisme kerja jamu. Menggunakan metode fuzzy clustering pada data jejaring, kami memperoleh 15 senyawa aktif yang diduga potensial sebagai antidiabetes berada dalam kelompok berbeda. Pada 15 senyawa aktif memiliki nilai peluang cukup tinggi terbagi dalam kelompok yang berbeda, setiap kelompok terdiri dari pasangan bahan aktif yang memiliki efek sinergis tinggi. Berdasarkan koneksi antara klaster-klasterprotein dan GO-BP, penelitianini memperoleh informasi protein-protein yang menyebabkan T2D dan mekanisme proses biologis yang terkait. T2D bukan hanya disebabkan oleh protein kelainan sekresi insulin (insulin-merendahkan enzim isoform 1) saja, tetapi juga disebabkan oleh protein lain yang terlibat dalam penghambatan insulin di pankreas.

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Mardiana, Primadhanty B, Adniana N, et al. "Analisis In Silico pada VCO untuk Terapi Dermatitis Atopik." MEDICINUS 33, no. 3 (2020): 32–37. http://dx.doi.org/10.56951/medicinus.v33i3.74.

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Latar belakang: Analisis in silico digunakan pada tahap awal penelitian dalam penemuan obat baru untuk efisiensi biaya dan waktu. Virgin Coconut Oil (VCO) merupakan salah satu pilihan terapi pada kasus dermatitis atopik karena memiliki fungsi memperbaiki barrier kulit dan antiinflamasi. Tujuan: Untuk mengevaluasi kandungan VCO menggunakan analisis in silico secara komputasional pada pengobatan dermatitis atopik. Metode: Senyawa aktif Cocos nucifera yang diekstraksi dari database KNApSAcK diprediksi secara eksperimental dan dianalisis secara komputasi menggunakan Simplified Molecular-Input Line-Entry System (SMILES), Prediction of Activity Spectra for biologically active Substances (PASS) server, dan Search Tool for Interactions of Chemicals (STITCH). Hasil: Terdapat 19 senyawa aktif yang ditemukan pada VCO. Hasil analisis menunjukkan VCO memiliki target protein free fatty acid (FFA) yang bertindak sebagai reseptor untuk fatty acid saturated dan fatty acid unsaturated dengan rantai lemak panjang atau medium. Potensi bioaktivitas senyawa aktif VCO tertinggi yaitu sebagai antieczema, dengan komponen yang paling berperan adalah linoleic acid dengan rata-rata nilai probable to be active (Pa) 0,872, dan diprediksi memiliki potensi yang tinggi secara komputasi maupun uji laboratorium. Kesimpulan: Berdasarkan penelitian ini kami menyarankan penggunaan VCO sebagai terapi pada dermatitis atopik karena VCO memiliki potensi bioaktivitas antiinflamasi, inhibitor histamin, memperbaiki fungsi barrier kulit dan antieczema sehingga menghambat terjadinya dermatitis atopik.

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Maretha, Tri Luthfiana, Ahmad Shobrun Jamil, Siti Rofida, and M. Artabah Muchlisin. "Network Pharmacology Analysis of Cananga odorata as a Treatment for Anxiety Disorders." Proceedings of International Pharmacy Ulul Albab Conference and Seminar (PLANAR) 3 (November 13, 2023): 137. http://dx.doi.org/10.18860/planar.v3i0.2479.

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Anxiety disorder is a psychological disorder associated with the existence of mental disorders and experiencing constant anxiety. In C. odorata, part of the flower has the potential as a sedative for the nervous system and for dealing with anxiety. The study aims to analyze the potential compound content in Cananga odorata for treating anxiety disorders with In silico-based pharmacological network analysis. CO compound data from the KNApSAck database, Absorption, Distribution, Metabolism, and Excretion (ADME) screening using SwissADME, predicted target proteins using Swiss Target Prediction, GeneCards, Venny, String DB pharmacological network analysis, Visualization with Cytoscape version 3.10.0, and Way2drug. The results of the pharmacological tissue analysis of the compound content in C. odorata obtained 45 compounds, and 18 known active components meet the criteria of Absorption, Distribution, Metabolism, and Excretion (ADME) that correspond to the drug compounder (Drug Likeness/DL). Based on the pathway that correlates with anxiety disorder therapy are the neurotransmitter systems like serotonin receptors and dopamine receptors. The known therapeutic target proteins are HTR1A, HTR2A, SLC6A4, NR3C1, MAOA, DRD4, HSP90AA1, JUN, ten active compounds associated with C. odorata namely Anonaine, (+)-Reticuline, linalool, (-)-Coreximine, Micheline A, (-)-Ushinsunine beta-N-oxide, 4-Terpineol, alpha-Terpeneol, Sampangine, Anaxagoreine. Based on the results of research, C. odorata is potentially a treatment for anxiety disorder.

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Jamil, Ahmad Shobrun, Sri Widyarti, Meddy Setiawan, and Muhaimin Rifa’i. "The pharmacological network of Tinospora cordifolia: Its role in regulating ınflammation and cathelicidin production." Journal of Research in Pharmacy 29, no. 3 (2024): 903–17. https://doi.org/10.12991/jrespharm.1693737.

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This study aims to promote a pharmacological network strategy to investigate the potential antiinflammatory activity and molecular mechanisms of the bioactive compounds in Tinospora cordifolia (TC) for controlling inflammation and regulating the production of the antimicrobial peptide cathelicidin. Using the Knapsack database and several recent research findings, SwissADME, PubChem, and PASS Online, we screened the drug-likeness of various TC compounds. Utilizing the SwissTargetPrediction, String-DB, GeneCards, and Venny Diagram, we identified 468 potential targets related to inflammation target protein and cathelicidin production. Further refinement using Cytoscape with CytoHubba highlighted 15 core targets, including BCL2, JUN, STAT3, HSP90AA1, MTOR, AKT1, ESR1, SRC, BCL2L1, TNF, MDM2, PTGS2, HSP90AB1, MMP9, and MMP2. GO and KEGG pathway analysis revealed that the core targets for inflammation control and cathelicidin production are predominantly enriched in TLR, NOD, MAPK, and NFKB inflammatory pathways. Molecular docking conducted with Autodock confirmed strong binding between TC ligands and several proteins in these pathways, such as JAK1, AKT1, IKBKB, and IRAK4. Overall, these findings suggest that TC is predicted to inhibit inflammation by inhibiting the activity of these four target proteins in the inflammatory pathways. This research provides a theoretical basis for understanding the molecular mechanisms of TC in inhibiting inflammation and controlling the production of the antimicrobial peptide cathelicidin.

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Naraevskii, О., and T. Chernomorova. "On the optimal use of material for manufacturing products by a metal construction plant." Bulletin of Science and Practice, no. 4 (April 15, 2017): 115–22. https://doi.org/10.5281/zenodo.546280.

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As part work, the task of optimising the production of road safety products at the North Caucasian Plant of Metal Constructions LLC is being solved. As a conceptual model, the problem of a backpack from decision theory has been chosen. In this paper, we use and compare the results of two methods: a simple search and a method of branches and boundaries. It is necessary to make the maximum number of road signs of a certain type from sheets of metal of various dimensions while minimising production waste. The original algorithm executed on the Oracle 11g database platform in the built-in PL/SQL language is demonstrated.

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Widyananda, Muhammad Hermawan, Septian Tri Wicaksono, Kurnia Rahmawati, et al. "A Potential Anticancer Mechanism of Finger Root (Boesenbergia rotunda) Extracts against a Breast Cancer Cell Line." Scientifica 2022 (September 5, 2022): 1–17. http://dx.doi.org/10.1155/2022/9130252.

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Breast cancer is the most common type of cancer women suffer from worldwide in 2020 and the 4th leading cause of cancer death. Boesenbergia rotunda is an herb with high potential as an anticancer agent. This study explores the potential bioactive compounds in B. rotunda as anti-breast cancer agents using in silico and in vitro approaches. The in silico study was used for active compound analysis, selection of anticancer compound candidates, prediction of target protein, functional annotation, molecular docking, and molecular dynamics simulation, respectively. The in vitro study was conducted by measurement toxicity, rhodamine 123, and apoptosis assays on T47D cells. Based on the KNApSAcK database, B. rotunda contained 20 metabolites, which are dominated by chalcone and flavonoid groups. Seven of them were predicted to have anticancer activity, namely, sakuranetin, cardamonin, alpinetin, 2S-pinocembrin, 7.4′-dihydroxy-5-methoxyflavanone, 5.6-dehydrokawain, and pinostrobin chalcone. These compounds targeted proteins related to cancer progression pathways such as the PI3K/Akt, FOXO, JAK/STAT, and estrogen signaling pathways. Therefore, these compounds are predicted to inhibit growth and induce apoptosis of cancer cells through their interactions with MMP12, MMP13, CDK4, JAK3, VEGFR1, VEGFR2, and KCNA3. Anticancer activity of B. rotunda through in vitro study confirmed that B. rotunda extract is strong cytotoxic and induces apoptosis of breast cancer cell lines. This study concludes that Boesenbergia rotunda has potency as an anticancer candidate.

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Khoirunnisa, Azka, Ahmad Shobrun Jamil, and Muhammad Artabah Muchlisin. "Network Pharmacology Analysis of Secondary Metabolites of Ciplukan (Physalis angulata L.) Against Lung Cancer." Majalah Farmaseutik 20, no. 2 (2024): 282. http://dx.doi.org/10.22146/farmaseutik.v20i2.96275.

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Lung cancer is the most common and high-risk type of cancer. Ciplukan (Physalis angulata L.) has antibacterial, anti-inflammatory, and anticancer activities, as well as cytotoxic ability and inhibits cancer cell growth. Research that discusses the molecular cellular mechanism of P. angulata's potential as an anti-lung cancer has not been widely informed, especially on the network pharmacology aspect of this plant's active compounds. This study reveals the prediction of the molecular mechanism of active compounds of P. angulata as anti-lung cancer using several tools including: Compound database retrieval with Knapsack and PubChem. Absorption Distribution Metabolism and Excretion (ADME) screening with SwissADME. Target protein identification with Gene Card, SwissTargetPrediction and Venny Diagram. Network pharmacology construction with String-DB and Cytoscape. Network pharmacology analysis using Gene Ontology (GO), and Cellular Component and Molecular Function. Based on the results of the analysis of P. angulata protein potential based on Maximal Clique Centrality (MCC) on CytoHubba in Cytoscape application, it shows that the Protein-protein Interaction (PPI) network has 10 main targets, namely ERBB2, KRAS, TP53, PTEN, CDKN2A, NRAS, PIK3CA, BRAF, NF1, and EGFR which interact with each other to regulate cell growth, differentiation, and survival. The results of this study can be concluded that the secondary metabolite compounds of P. angulata have the potential to control and alternative for lung cancer therapy.

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Rahayu, Premy Puspitawati, Manik Eirry Sawitri, Dwi Setiawan, and Citra Nurma Yunita. "Interaction of Sambiloto (Andrographis paniculata) Bioactive Compound with Milk Protein (Whey and Casein) Through Molecular Docking and Molecular Dynamics Simulation as a Basis for Encapsulation." Jurnal Penelitian Pendidikan IPA 10, no. 7 (2024): 4129–38. http://dx.doi.org/10.29303/jppipa.v10i7.7696.

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This research aims for developing immune-boosting products necessary. The active ingredient in Andrographis paniculate (AP) acts as an immunostimulant which can improve the work of the immune system. The first stage of research was a collection of bioactive compounds from KnapSack database of Kanaya, Dr. Duke's Phytochemical and Ethnobotanical were compiled and selected based on the online pass results of each bioactive compound as an immunomodulator and 10 active compounds were obtained which will be continued. The second stage of research was a docking molecular between whey proteins (β-lactoglobulin and α-lactalbumin) with active compounds from AP and casein (α-Casein, β-Casein, and κ-Casein). The highest binding affinity was obtained for α-Casein with Neoandrographolide at -9.2 Kcal/mol. The results of the complex α-Casein with Neoandrographolide (CC) and α-Casein with Neoandrographolide ultraheat (CCT) support the research, namely to function α-Casein as an encapsulant well as a transporter or drug delivery of Neoandrographolide without changing the conformation of casein and disturbing its function. However, the conformation of casein will change drastically during ultraheat treatment to maintain the conformation and binding with the Neoandrographolide ligand. In addition, it supports the simulation results of single α-Casein at ultraheat temperatures which show conformational stability that is not much different from single α-casein and complexes at physiological temperatures

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Liyaajul, Pratasyah, Miftahul Mushlih, Chylen Setiyo Rini, and Jamilatur Rohmah. "Analysis Of The Inhibitory Ability Of Spike Attachment Of The Delta Variant Of Sars Cov-2 With Ace2 By The Active Compound In Turmeric (Curcuma longa L.) In Silico." Medicra (Journal of Medical Laboratory Science/Technology) 6, no. 1 (2023): 19–24. http://dx.doi.org/10.21070/medicra.v6i1.1703.

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Turmeric (Curcuma longa L.) is an herbal plant that has many benefits as a treatment, including during the COVID-19 pandemic, one of the mechanisms of inhibition of SARS CoV-2 is to inhibit the attachment of ACE2 with Spike. The binding of the spike protein to the ACE2 receptor will produce conformational changes in the S protein, this study was conducted using an in silico method (computational analysis) which aims to determine the potential efficacy of Turmeric and its effectiveness in inhibiting the Delta variant of SARS CoV-2. The active compound contained in Turmeric (Curcuma longa L. ) obtained from the KNApSAcK database To determine compounds that can have potential and have good effectiveness in inhibition of the Delta Variant of SARS CoV-2, an analysis was carried out by looking at the binding energy and conformation changes that occur at the sticky point in each compound. Three-dimensional structure of SARS CoV-2 Varian Delta downloaded from the Protein Data Bank with PDB code 7V8B. Based on the analysis carried out, it was found that the compound (E)-nuciferoll has the lowest binding energy value of -1212.59 kcal / mol and is located at the initial attachment but cannot change the conformation, but from the sticky point of the compound (E)-nuciferol lies in the initial attachment of RBD-ACE2.

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Awwaluddin, Faiznanda, Ahmad Shobrun Jamil, Siti Rofida, and M. Artabah Muchlisin. "The Therapeutic Role of Olea europaea in Alcohol Dependence Base in Network Pharmacology Analysis." Proceedings of International Pharmacy Ulul Albab Conference and Seminar (PLANAR) 3 (November 13, 2023): 201. http://dx.doi.org/10.18860/planar.v3i0.2486.

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Alcohol dependence is a state of alcohol becoming a vital part of the life of a person who consumes it; when discontinued, it can lead to a wide range of physical and mental health disorders as well as a decrease in life productivity in people with alcohol dependence. Olea Europaea (OE) is a plant capable of treating alcohol dependence. The method used in silico-based pharmacological grid analysis to determine the ability of the OE compound to treat alcohol dependence. EO compound data is obtained from the KnapSack database, absorption, distribution, metabolism, and excretion (ADME) screening using SwissADME, target protein prediction using SwissTargetPrediction, Gene cards, venny, pharmacological grid analysis with String-DB, visualization with Cytoscape 3.10.0. Results are obtained from 63 OE compounds, and 17 have ADME criteria matching the drug compounder (Drug Likeness/DL). The pathways that correlate with therapy are dopamine receptors, dopamine transporter, serotonin receptor, gamma-aminobutyric acid receptor, and toll-like receptors for known therapeutic target proteins: OPRM1, DRD2, ALDH2, ADH1B, ADH1A, ADH1C, ADH4, ADH7, SLC6A3, CNR1, POMC, ARRB2, and NCS1. Compounds associated with alcohol dependency therapy include Hexanal, Nonadienal, Octanal, 3-Hexenal, 3-Methyl-butanal, Methyl nominate, Cinchonidine, cinchonine, (9S)-10,11-Dihydrocinchonan-9-ol, Oleuropeic acid, Butyl acetate, cis-3-hexenyl acetate, and (S)-2,3-Epoxysqualene. Based on the findings, OE is a potential drug candidate for alcohol dependence.

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Fauzan, Irfan Anwar, Ditta Putri Kumalasari, and Nisrina Fitri Nurjannah. "In Silico Screening of Ruellia tuberosa Phytochemicals as Neuroimmune-Modulating Drug Candidates for Multiple Sclerosis Therapy." International Journal of Research and Review 12, no. 6 (2025): 536–40. https://doi.org/10.52403/ijrr.20250661.

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Multiple sclerosis (MS) is a chronic autoimmune disease characterized by neuroinflammation, demyelination, and progressive neurological decline. Current pharmacotherapies offer limited efficacy and often induce adverse effects, highlighting the need for safer, multi-target alternatives. This study employed an in silico approach to evaluate phytochemical compounds from Ruellia tuberosa as potential neuroimmune-modulating drug candidates for MS therapy. Five bioactive compounds, which are hentriacontane, nonacosane, campesterol, β-sitosterol, and stigmasterol, were identified through the KNApSAcK database and assessed for drug-likeness via Lipinski’s Rule of Five. All fulfilled key criteria, though high LogP values were noted. ProTox-II analysis indicated acceptable toxicity profiles for campesterol, β-sitosterol, and stigmasterol, warranting further exploration. SwissTargetPrediction and PASS Online analyses revealed that these compounds interact predominantly with nuclear receptors, cytochrome P450 enzymes, and oxidoreductases, pathways strongly implicated in MS pathophysiology. The predicted pharmacological activities included immunosuppression, caspase-3 stimulation, prostaglandin-E2 9-reductase inhibition, and HMOX1 expression enhancement. These mechanisms are relevant to modulating neuroinflammation, oxidative stress, and steroid hormone regulation in MS. Collectively, these findings highlight the potential of Ruellia tuberosa phytochemicals as orally active, multi-target agents that may serve as complementary therapies in MS management. Further in vitro and in vivo validation is recommended to substantiate their efficacy and pharmacokinetic properties. Keywords: Ruellia tuberosa, multiple sclerosis, in silico screening, phytochemicals, natural drug candidate

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Widyananda, Muhammad Hermawan, Coni Anggie Kurniasari, Fajar Mustika Alam, et al. "Exploration of Potentially Bioactive Compounds from Fingerroot (Boesenbergia rotunda L.) as Inhibitor of Atherosclerosis-Related Proteins (CETP, ACAT1, OSC, sPLA2): An in silico Study." Jordan Journal of Pharmaceutical Sciences 16, no. 3 (2023): 550–64. http://dx.doi.org/10.35516/jjps.v16i3.1609.

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Boesenbergia rotunda L., commonly known as fingerroot, is recognized as one of Indonesia's medicinal plants with significant potential for treating various diseases, including atherosclerosis. This study aims to analyze the anti-atherosclerosis potential of bioactive compounds found in fingerroot by assessing their inhibitory effects on four proteins associated with atherosclerosis (CETP, ACAT1, OSC, and sPLA2). Bioactive compounds from B. rotunda were retrieved from the KnapSack database. The drug-likeness properties were predicted using the SwissADME web server, and the bioactivity of the compounds was assessed using the PASSOnline server. The identification of active sites on proteins and the validation of protein structures were performed using the SCFBio web server and Autodock Vina. Specific docking simulations between fingerroot compounds and the target proteins were carried out using AutoDock Vina. The analysis revealed that fingerroot contains 20 bioactive compounds with favorable drug-like properties. Among these, dihydrochrysin, sakuranetin, isopimaric acid, 2S-pinocembrin, 5,7-dihydroxy-8-C-geranylflavanone, 7,4'-dihydroxy-5-methoxyflavanone, and 5,7-dihydroxy-8,7-methoxy-5-hydroxy-8-geranylflavanone were predicted to exhibit anti-atherosclerosis activities. In the interactions with CETP, rubranine and (-)-4-hydroxypanduratin A showed the lowest binding affinity scores. Meanwhile, in interactions with ACAT1, OSC, and sPLA2, rubranine and 5,7-dihydroxy-8-C-geranylflavanone displayed the lowest binding affinities. In conclusion, fingerroot exhibits high potential as an anti-atherosclerosis agent through the inhibition of four proteins associated with atherosclerosis, as predicted through in silico analysis.

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Федорец, О. В., та Н. С. Солошенко. "О практической значимости информетрической модели Брэдфорда для прогнозирования рассеяния статей и оптимизации отбора журналов". Научно-техническая информация. Серия 2: Информационные процессы и системы, № 1 (1 січня 2024): 34–44. https://doi.org/10.36535/0548-0027-2024-01-3.

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Исследовано рассеяние статей в реферативной базе данных ВИНИТИ РАН в период 2020-2022 гг. на примере трёх тематических фрагментов: Химия и химическая технология, Машиностроение, Металлургия и сварка. Для вычисления количества журналов в третьей зоне рассеяния использовались математические формулировки С. Брэдфорда и Б. Викери. Сделан вывод, что закон рассеяния публикаций Брэдфорда-Викери позволяет прогнозировать минимальное количество журналов, охватывающих более 90% статей по определенной тематике. Оптимизация отбора журналов сведена к известной задаче о рюкзаке (ранце), для решения которой предложено ранжировать журналы по тематической релевантности. В отличие от модели Брэдфорда, нацеленной на отбор наиболее продуктивных журналов, предлагаемая модель предназначена для отбора наиболее релевантных журналов. The scattering of articles in the abstract database of VINITI RAS in the period 2020-2022 has been studied on the example of three thematic fragments: Chemistry and Chemical Technology, Mechanical Engineering, Metallurgy and Welding. The mathematical formulations of S. Bradford and B. Vickery were used to calculate the number of journals in the third scattering zone. Vickery. It is concluded that the Bradford-Vickery law of publication scattering allows predicting the minimum number of journals covering more than 90% of articles on a certain subject. Optimisation of journal selection is reduced to the well-known knapsack (satchel) problem, for the solution of which it is proposed to rank journals by thematic relevance. Unlike the Bradford model, which aims to select the most productive journals, the proposed model is designed to select the most relevant journals.

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Ikeda, Shun, Takashi Abe, Yukiko Nakamura, et al. "Systematization of the Protein Sequence Diversity in Enzymes Related to Secondary Metabolic Pathways in Plants, in the Context of Big Data Biology Inspired by the KNApSAcK Motorcycle Database." Plant and Cell Physiology 54, no. 5 (2013): 711–27. http://dx.doi.org/10.1093/pcp/pct041.

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Fatiningtyas, Fairuz Andini, Riswanto Napitupulu, Amarila Malik, and Is Helianti. "In Silico and In Vitro Inhibitory Activity of Indonesian Herbal Compound Extracts against SARS-COV-2 Recombinant Papain-Like Protease." HAYATI Journal of Biosciences 32, no. 2 (2024): 356–66. https://doi.org/10.4308/hjb.32.2.356-366.

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The SARS-CoV-2 papain-like protease (PLpro) is essential for viral replication and a promising target for drug discovery. This study explored the inhibitory potential of compounds from Indonesia herbals Butterfly pea flower (Clitoria ternatea L), Star fruit leaves (Averrhoa carambola L.), and Java plum leaves (Syzygium cumini (L.) Skeels) against PL pro through molecular docking and in vitro assays. The molecular docking method utilized the target protein PLpro (PDB ID: 7CMD), with the native ligand obtained from compounds identified in these plant extracts. The compounds were identified using the KNApSAcK database and analyzed for drug-likeness based on Lipinski's Rule of Five. The physicochemical characteristics affecting absorption, distribution, metabolism, excretion, and toxicity (ADMET) were determined using the pkCSM descriptor algorithm protocol. Validation was performed using the redocking method, achieving an RMSD score of 0.728 Å, which indicated validity (RMSD <2.0 Å). The results identified four ligands with the lowest binding affinities from these extracts: (-)-Epicatechin 3-O-gallate, folic acid, petunidin 3-glucoside, and ellagic acid, with binding scores of -8.6, -8.3, -7.1, and -7.1 kcal/mol, respectively. Prior to conducting the PLpro in vitro inhibition assay, a fluorescence-based inhibition assay was performed using Z-RLRGG-AMC as the substrate and GRL0617as the control inhibitor. All extracts were subjected to 70% ethanol maceration. The IC50 value of GRL0617 was 3.38 μM, while fluorescence tests showed that Java plum leaf extract exhibited the highest inhibition percentage at 66.10±3.22%. These findings indicate that all three plant extracts contain compounds capable of inhibiting PLpro activity.

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Yasmin, Rafida, Wulan Usfi Mafiroh, Anggiresti Kinasih, Aulia Noor Ramadhani, Rachmi Putri, and Endang Semiarti. "Potential of Orchids Secondary Metabolites as Anti-Cancer and Antimicrobial Based on Prediction of Phytochemical Activity with Online PASS-Software." Journal of Agromedicine and Medical Sciences 8, no. 1 (2022): 25. http://dx.doi.org/10.19184/ams.v8i1.26848.

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Abstract Orchidology is part of the branch of botany, it deals with a large family of monocotyledonous plants, Orchidaceae. Orchids have been used as traditional herbal medicines in Indonesia which are believed to be antimicrobial and anti-cancer. Orchids are able to produce secondary metabolites as their protective agent due to the extreme environment. Orchids have great diversity and potential to be the object of research, not only in experimental studies but also in a computational studies like in silico. Nowadays, molecular or metabolite data are available on the official-standard website as an international database. This study was conducted by analyzing web-based data to provide information about the potential of orchids that have been trusted as herbal medicines. In this study, secondary metabolite from Vanilla spp., Dendrobium spp., and Vanda spp., were selected in the existing literature as antimicrobial and anti-cancer drugs. Secondary metabolites obtained from the KNApSAck-3D core system and Phytochemical and Prediction of Substance Activity Spectrum (PASS) were performed to determine the potential anti-cancer and antimicrobial activity. Based on in silico analysis through PASS online, the secondary metabolites of orchids that have potential as antimicrobials in this study were Dendroside E and Dendromonilised D from Dendrobium also Parviflorin, Licoisoflavone and Luteine extracted from Vanda spp. The secondary metabolite of Vanilla planifolia which has potential as anti-cancer for further research is 4-Hydroxybenzoic acid as a Chlordecone reductase inhibitor extracted from shoots.  Keywords: orchid, antimicrobial, anticancer, secondary metabolite, PASS online

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Askar, Muhammad. "Computational quest to inhibit enoyl-acyl carrier protein reductase (InhA) enzyme in Mycobacterium tuberculosis from Lannea coromandelica (Houtt.) Merr. metabolite via molecular docking and dynamics." Pharmacia 71 (August 2, 2024): 1–10. http://dx.doi.org/10.3897/pharmacia.71.e129151.

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This research is a computational exploration to look for natural compounds that can inhibit enoyl-acyl carrier protein reductase (InhA) enzyme from Mycobacterium tuberculosis (MTB). One of Indonesia’s native plants that has been reported to inhibit InhA from MTB is the Lannea coromandelica (Houtt.) Merr., known to contain various active metabolites. However, the molecular activity of the metabolites has not been determined. The aim of this research is the discovery and testing computationally of the binding of metabolites from Lannea coromandelica (Houtt.) Merr. The metabolite ligands are obtained from the natural compound database KNApSAcK, and the 3D structure of the receptor is obtained from the PDB website with the code 1BVR. Subsequently, molecular docking is performed using MGL Tools v.1.5.6 and AutoDock Tools v.4.2.3 software. High-performance computers are used for molecular dynamics simulations with the Gromacs 2016.3 software for a duration of 100 nanoseconds (ns). The docking simulation results show that metabolites show a negative binding energy and close to the value of the native ligand. Moreover, molecular dynamics simulation analysis revealed significant stability of the C1436 ((2R,3R)-3-Hydroxy-5,7,4’-trimethoxyflavanone)-InhA complex over 100 nanoseconds. Molecular dynamics simulations demonstrate that from MM-PBSA value compound C1436 showed MMPBSA binding energy −104.995 kJ/mol, closely approaching the value of the native ligand, which is −142.999 kJ/mol. Furthermore, from the molecular dynamics simulation analysis, C1436 compound demonstrates stability very similar to the native ligand, as observed from the RMSD, RMSF, Rg, RDF, SASA, and PCA analysis. In conclusion, the compound from Lannea coromandelica (Houtt.) Merr. has the potential to serve as a lead compound for inhibiting InhA in MTB.

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Journal articles on the topic 'KNApSAck database'

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