Relevant bibliographies by topics / ADME database

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'ADME database'

Author: Grafiati
Published: 2 June 2025
Last updated: 7 July 2025

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Journal articles on the topic "ADME database"

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Sun, L. Z., Z. L. Ji, X. Chen, J. F. Wang, and Y. Z. Chen. "ADME-AP: a database of ADME associated proteins." Bioinformatics 18, no. 12 (2002): 1699–700. http://dx.doi.org/10.1093/bioinformatics/18.12.1699.

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Deb, Subrata, Robert Hopefl, Anthony Allen Reeves, and Dena Cvetkovic. "ADME Gene-Related Pharmacogenomic Labeling of FDA-Approved Drugs: Comparison with Clinical Pharmacogenetics Implementation Consortium (CPIC) Evidence Levels." Medicines 11, no. 3 (2024): 6. http://dx.doi.org/10.3390/medicines11030006.

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Pharmacogenomics (PGx) can facilitate the transition to patient-specific drug regimens and thus improve their efficacy and reduce toxicity. The aim of this study was to evaluate the overlap of PGx classification for drug absorption, distribution, metabolism, and elimination (ADME)-related genes in the U.S. Food and Drug Administration (FDA) PGx labeling and in the Clinical Pharmacogenetics Implementation Consortium (CPIC) database. FDA-approved drugs and PGx labeling for ADME genes were identified in the CPIC database. Drugs were filtered by their association with ADME (pharmacokinetics)-related genes, PGx FDA labeling class, and CPIC evidence level. FDA PGx labeling was classified as either actionable, informative, testing recommended, or testing required, and varying CPIC evidence levels as either A, B, C, or D. From a total of 442 ADME and non-ADME gene–drug pairs in the CPIC database, 273, 55, and 48 pairs were excluded for lack of FDA labeling, mixed CPIC evidence level provisional classification, and non-ADME gene–drug pairs, respectively. The 66 ADME gene–drug pairs were classified into the following categories: 10 (15%) informative, 49 (74%) actionable, 6 (9%) testing recommended, and 1 (2%) testing required. CYP2D6 was the most prevalent gene among the FDA PGx labeling. From the ADME gene–drug pairs with both FDA and CPIC PGx classification, the majority of the drugs were for depression, cancer, and pain medications. The ADME gene–drug pairs with FDA PGx labeling considerably overlap with CPIC classification; however, a large number of ADME gene–drug pairs have only CPIC evidence levels but not FDA classification. PGx actionable labeling was the most common classification, with CYP2D6 as the most prevalent ADME gene in the FDA PGx labeling. Health professionals can impact therapeutic outcomes via pharmacogenetic interventions by analyzing and reconciling the FDA labels and CPIC database.
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Ravi, Kumar K. 1. *. Archana Giri 1. Rama Rao Nadendla 2. "INSILICO ADME PROFILING OF CDK9 INHIBITORS." Journal of Scientific Research in Pharmacy 7, no. 3 (2018): 30–34. https://doi.org/10.5281/zenodo.1207094.

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<strong><em>ABSTRACT</em></strong> <strong><em>S</em></strong><em>everal drug targets have been identified in fighting against cancer. Inhibition of Cell cycle is one of the strategies used in anti-cancer research.&nbsp;&nbsp; CDKs [Cyclin Dependent Kinases] were found to be one of the promising drug targets. This work aims to find a potential molecule to inhibit CDKs that are involved in cell cycle progression. CDK 9 was chosen as potential drug target for cancer.&nbsp; Virtual screening was carried out against CDK 9 protein using Molecular Docking tools with molecules from ZINC database. Molecules were shortlisted based on their docking score, rerank score and energies. Insilico Toxicity and ADME [Absorption, Distribution, Metabolism and Excretion] analysis was carried to know the efficacy of the molecules before proceeding to invitro and invivo assays. Molecules under study were analyzed for ADME properties using Molinspiration, preAdmet and Swissadme servers.&nbsp;&nbsp; ADME profiles were evaluated and most of the molecules were found to be suitable for further studies. Insilico ADMET analysis is proved to be a good tool in drug discovery. </em> <strong><em>KEYWORDS:</em></strong><em> CDK, Cancer, Toxicity, ADME, Virtual Screening.</em>
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Prasad, Bhagwat, Marc Vrana, Prachi Jha, Vivek Nautiyal, Deepak Kumar Bhatt, and Jingtian Zheng. "ADME QPrOmicstm mrm database: A repository of validated LC-MS/MS methods for ADME protein quantification." Drug Metabolism and Pharmacokinetics 32, no. 1 (2017): S42. http://dx.doi.org/10.1016/j.dmpk.2016.10.180.

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Bououden, Walid, and Yacine Benguerba. "Designing, Cytotoxic Evaluation, Molecular Docking and in Silico Pharmacokinetic Prediction of New Hydrocortisone Derivatives as Anti-Asthmatics Drugs." Journal of Drug Delivery and Therapeutics 10, no. 4 (2020): 8–16. http://dx.doi.org/10.22270/jddt.v10i4.4128.

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A series of new 20 corticosteroids were subjected to molecular property prediction. The Molecular, Physicochemical, and Biological properties were determined using Molinspiration Cheminformatics software. These compounds were further subjected to Toxicity Predictions using the Osiris Software. The calculated drug-related properties of the designed molecules were similar to those found in most marketed drugs. Amongst the proposed molecules, fourteen promising candidates can be considered as promising structures for the synthesis of new and more effective anti-asthmatic drugs. Result indicates that the derivatives are orally active molecules. In-silico ADME and toxicity prediction was accomplished with the help of Swiss-ADMET tool provides the latest and most inclusive for diverse chemicals associated with known Absorption, Distribution, Metabolism, Excretion and Toxicity profiles. furthermore, BBB (Blood brain barrier) penetration, HIA (Human intestinal absorption), Caco-2 cell permeability and Ames test were calculated using ADMET web-based query tools incorporating a molecular build in interface enable the database to be queried by Smiles and structural similarity search. According to molecular docking results, derivatives No 4, 10 and 11 showed better docking Scores values compared to other derivatives and also dexamethasone and hydrocortisone.&#x0D; Keywords: Corticosteroids, Drug-likeness, Lipophilicity, Anti-asthmatic, ADME.
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Sharma, Aastha, Nitish Banga, Rakesh Kumar Marwaha, and Balasubramanian Narasimhan. "Identification of novel potential benzimidazole derivatives by pharmacophore generation, 3D-QSAR, virtual screening, molecular docking and ADME/ TOX analysis against breast cancer as targeted estrogen alpha receptor." Journal of Applied Pharmaceutical Research 13, no. 2 (2025): 149–63. https://doi.org/10.69857/joapr.v13i2.951.

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Background: The estrogen alpha receptor (ERα) is critical in breast carcinogenesis. Although selective estrogen receptor modulators like tamoxifen are clinically used, their adverse effects highlight the need for safer alternatives. The study uses computational methods to identify potential ERα inhibitors within a benzimidazole scaffold. Methodology: This study employed computational approaches, including pharmacophore generation, 3D-QSAR, virtual screening, molecular docking, and in silico ADME/Tox analysis. The best pharmacophore model (DDRRR_1) identified two hydrogen donors and three aromatic rings as critical features. Moreover, a rigorous external validation was used on decoy databases with optimized metrics (ROC, BEDROC, AUROC). A subsequent atom-based 3D-QSAR model with a high correlation coefficient (R² = 0.9), cross-validated coefficient (Q² = 0.8), and Fisher ratio (F = 80.1) was developed. Benzimidazole scaffolds from PubChem were screened, followed by docking against ERα (PDB ID: 3ERT) and ADMET profiling. Results and Discussion: The pharmacophore model validated the importance of the identified features. The 3D-QSAR model effectively screened benzimidazole scaffolds, with five component PLS factors, supporting the pharmacophore findings. This model effectively screened benzimidazole scaffolds obtained from the PubChem database, followed by molecular docking against the targeted protein ERα (PDB ID: 3ERT) and identified five promising compounds. ADME/Tox profiling revealed PubChem ID 3074802 (2-[2-(1H-indol-3-yl) ethyl]1H-benzimidazole) has favourable pharmacokinetics and a low toxicity profile. Conclusion: These findings indicate that PubChem ID 3074802 is a promising candidate for further therapeutic drug development in breast cancer treatment. It demonstrates the highest binding affinity (-9.842 kcal/mol) compared to the standard drug Tamoxifen (-5.357 kcal/mol) and exhibits a favorable ADME/Tox profile.
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R, Thirumalaisamy. "Comparative Anti–Alzheimer’s Potential Evaluation of Curcumin and Curcumin Analogues obtained from ZINC Database: An in-Silico Validation." TEXILA INTERNATIONAL JOURNAL OF PUBLIC HEALTH 9, no. 4 (2021): 269–83. http://dx.doi.org/10.21522/tijph.2013.09.04.art023.

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Curcumin and its eleven analogues obtained from the ZINC database were screened for its anti-Alzheimer’s potential validated through in silico approach. Curcumin, eleven curcumin analogues from the ZINC database, and six standard anti-Alzheimer’s drugs were obtained from SWISS ADME and Pub chem database. All obtained molecules were subjected to drug-likeness, molecular docking, and ADMET analysis. Curcumin and eleven curcumin analogues show no violations against five drug-likeness rules, whereas 2 standard drugs (CID¬_11269353, CID_46883536) out of 5 screened standard drug molecules shows violations in drug likeness property. Curcumin and curcumin analogues possess docking scores in the range of -7.5 to 9.9 Kcal/mol, whereas reference standard drugs docking score lies in the range of -6.4 to -11.0 Kcal/mol against all three Alzheimer’s disease molecular targets. Finally, our present study has proven that curcumin analogues possess some novel anti-Alzheimer’s properties over curcumin and standard reference drug. It needs to be validated and commercialized after in vivo preclinical trials.
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Aman, La Ode, Rahmana Emran Kartasasmita, and Daryono Hadi Tjahjono. "Virtual screening of curcumin analogues as DYRK2 inhibitor: Pharmacophore analysis, molecular docking and dynamics, and ADME prediction." F1000Research 10 (May 17, 2021): 394. http://dx.doi.org/10.12688/f1000research.28040.1.

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Background: Curcumin reduces the proliferation of cancer cells through inhibition of the DYRK2 enzyme, which is a positive regulator of the 26S proteasome. Methods: In the present work, curcumin analogues have been screened from the MolPort database using a pharmacophore model that comprised a ligand-based approach. The result of the screening was then evaluated by molecular docking and molecular dynamics based on binding the free energy of the interaction between each compound with the binding pocket of DYRK2. The hit compounds were then confirmed by absorption, distribution, metabolism, and excretion (ADME) prediction. Results: Screening of 7.4 million molecules from the MolPort database afforded six selected hit compounds. By considering the ADME prediction, three prospective curcumin analogues have been selected. These are: 2‐[2‐(1‐methylpyrazol‐4‐yl)ethyl]‐1H,5H,6H,7H,8H‐imidazo[4,5‐c]azepin‐4‐one (Molport-035-369-361), methyl 4‐(3‐hydroxy‐1,2‐oxazol‐5‐yl)piperidine‐1‐carboxylate (Molport-000-004-273) and (1S)‐1‐[5‐(furan‐3‐carbonyl)‐4H,6H,7H‐pyrazolo[1,5‐a]pyrazin‐2‐yl]ethanol (MolPort-035-585-822). Conclusion: Pharmacophore modelling, combined with molecular docking and molecular dynamics simulation, as well as ADME prediction were successfully applied to screen curcumin analogues from the MolPort database as DYRK2 inhibitors. All selected compounds that have better predicted pharmacokinetic properties than that of curcumin are considered for further study.
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Amaku, F. J., I. E. Otuokere, K. K. Igwe, and O. V. Ikpeazu. "Design of Potential SARS-CoV-2 Inhibitor." European Journal of Engineering Research and Science 5, no. 9 (2020): 1043–48. http://dx.doi.org/10.24018/ejers.2020.5.9.2058.

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This computational study comprises of pharmacophore-base virtual screening of the ZINC database, molecular docking of predicted ligands (pharmacophore agent) against the target protein, SARS-CoV-2 (PDB ID: 5r7y) and the prediction of ADMET descriptors using Swiss ADME and PROTOX-II online web servers. Meanwhile, remdesivir, ZINC72392503, ZINC72809903, ZINC06560017, ZINC76101700, ZINC88423098 and ZINC91600695 had a docking scores of -2.0 Kcal/mol, -6.7 Kcal/mol, -6.4 Kcal/mol, -6.0 Kcal/mol, -6.0 Kcal/mol, -6.0 Kcal/mol and-6.0 Kcal/mol respectively. Meanwhile, ZINC72392503 was selected as the lead molecule and was observed to interact with LUE 27, THR 25, CYS 145, THR 26, SER 46, GLY 143, ASN 142, HIS 163, HIS 41, MET 165, GLU 166, ARG 188, GLN 189, HIS 41, MET 49, SER 46 amino acids. The ADME descriptor revealed that the lead molecule was soluble, druggable, void of drug-drug interaction that may inhibit essential enzymatic reaction and was noticed to fall into PROTOX-II toxicity class 3. The lead molecule showed a good affinity for the target protein of SARS-CoV-2, hence, may have a physiological implication that can inhibit a protein responsible for the replication of SARS-CoV-2.
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Amaku, F. J., I. E. Otuokere, K. K. Igwe, and O. V. Ikpeazu. "Design of Potential SARS-CoV-2 Inhibitor." European Journal of Engineering and Technology Research 5, no. 9 (2020): 1043–48. http://dx.doi.org/10.24018/ejeng.2020.5.9.2058.

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This computational study comprises of pharmacophore-base virtual screening of the ZINC database, molecular docking of predicted ligands (pharmacophore agent) against the target protein, SARS-CoV-2 (PDB ID: 5r7y) and the prediction of ADMET descriptors using Swiss ADME and PROTOX-II online web servers. Meanwhile, remdesivir, ZINC72392503, ZINC72809903, ZINC06560017, ZINC76101700, ZINC88423098 and ZINC91600695 had a docking scores of -2.0 Kcal/mol, -6.7 Kcal/mol, -6.4 Kcal/mol, -6.0 Kcal/mol, -6.0 Kcal/mol, -6.0 Kcal/mol and-6.0 Kcal/mol respectively. Meanwhile, ZINC72392503 was selected as the lead molecule and was observed to interact with LUE 27, THR 25, CYS 145, THR 26, SER 46, GLY 143, ASN 142, HIS 163, HIS 41, MET 165, GLU 166, ARG 188, GLN 189, HIS 41, MET 49, SER 46 amino acids. The ADME descriptor revealed that the lead molecule was soluble, druggable, void of drug-drug interaction that may inhibit essential enzymatic reaction and was noticed to fall into PROTOX-II toxicity class 3. The lead molecule showed a good affinity for the target protein of SARS-CoV-2, hence, may have a physiological implication that can inhibit a protein responsible for the replication of SARS-CoV-2.
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Dissertations / Theses on the topic "ADME database"

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Szoltys, Kryštof. "Parametrické CAD systémy a databáze součástí." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217957.

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Autodesk Inventor is a full 3D CAD system. This system includes tools for working environment tool, component design tool including information data management and technical support. The target of the first part is to describe the most important new features brought by Autodesk Inventoru 2009 version. In of next chapters the work describes creation common iPart, which is basically different variants set (proportions, material …) of one entity, and preparation before correct publication to the content center, which is a virtual database of all iPart. Also there is presented how to create the content center, how to work with it and adjust data. The aim of work is then the creation database a stator and a rotor packet for the firm ATAS electromotor Náchod Inc. In the thesis there is described creation of the lamination as an iPart and their publication to the new content center.
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Ueal, Jr Ozell. "An Evaluation of Robotics in Nursing Homes to Reduce Adverse Drug Events." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/3330.

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Adverse drug events (ADE) cause many deaths annually in addition to affecting the quality of life of many others. The descriptive mixed methods approach, specifically exploratory case study and experimental design that guided this research utilized the survey and focus group methods to evaluate perceptions about robotic technology (RT) to reduce the rate of ADEs in U.S. nursing homes (NH). There is a lack of scholarly research into whether a conceptual approach rooted in RT can be implemented to assist with drug administrations in NHs. The purpose of this study was twofold. The first purpose was to evaluate the causes of ADEs specifically related to tablets, capsules, and pills. The second purpose was to evaluate the perceptions of nurses and administrators relative to the use of RT to assist in reducing ADEs. In the quantitative part, the sample means from 102 surveys from nurses and administrators were evaluated with the t test and the paired t test; while in the qualitative part, survey results, reported errors, and focus group data was assessed collectively. The research results did not indicate any new causes of ADEs and showed that the participants had a favorable perception of RT. Based on the results of this research, RT may be tailored in such a way that it can significantly reduce ADE occurrences for citizens in U.S. NHs.
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Books on the topic "ADME database"

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Cao, Longbing. Advanced Data Mining and Applications: 6th International Conference, ADMA 2010, Chongqing, China, November 19-21, 2010, Proceedings, Part II. Springer Berlin Heidelberg, 2010.

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Zhou, Shuigeng. Advanced Data Mining and Applications: 8th International Conference, ADMA 2012, Nanjing, China, December 15-18, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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ADMI 2010 (2010 Toronto, Ont.). Agents and data mining interaction: 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, Toronto, On, Canada, May 11, 2010 : revised selected papers. Springer, 2010.

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Kim, Chi-in. Yumul chŏngbo kwalli teit'ŏbeisŭ ŭi kwan'gye hyŏng model kwa kaech'e chihyang hyŏng model pigyo yŏn'gu: Model KJI-ADB1 kwa model KJI-ADBE chesi : munhak sŏksa hagwi nonmun. 2000.

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Ling, Charles X., Nick Cercone, Xiaofang Zhou, Xue Li, and Changjie Tang. Advanced Data Mining and Applications: 4th International Conference, ADMA 2008, Chengdu, China, October 8-10, 2008, Proceedings. Springer, 2008.

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Wang, Sen, Jianxin Li, Shuliang Wang, Xue Li, and Shaowen Qin. Advanced Data Mining and Applications: 15th International Conference, ADMA 2019, Dalian, China, November 21–23, 2019, Proceedings. Springer, 2019.

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Li, Jianzhong, Hong Gao, Reda Alhajj, Xue Li, and Osmar R. Zaiane. Advanced Data Mining and Applications: Third International Conference, ADMA 2007, Harbin, China, August 6-8, 2007 Proceedings. Springer London, Limited, 2007.

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Gan, Guojun, Shuliang Wang, Xue Li, and Bohan Li. Advanced Data Mining and Applications: 14th International Conference, ADMA 2018, Nanjing, China, November 16–18, 2018, Proceedings. Springer, 2018.

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Li, Xue, Osmar R. Zaiane, and Zhanhuai Li. Advanced Data Mining and Applications: Second International Conference, ADMA 2006, Xi'an, China, August 14-16, 2006, Proceedings. Springer London, Limited, 2006.

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Wang, Shuliang, Zhao Yang Dong, and Xue Li. Advanced Data Mining and Applications: First International Conference, ADMA 2005, Wuhan, China, July 22-24, 2005, Proceedings. Springer London, Limited, 2003.

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Book chapters on the topic "ADME database"

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Joy, Christy, and Marria C. Cyriac. "Phytochemicals as Potential Drug Candidates for SARS Cov-2: An RDRp Based In-Silico Drug Designing." In Proceedings of the Conference BioSangam 2022: Emerging Trends in Biotechnology (BIOSANGAM 2022). Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-020-6_7.

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AbstractThe global pandemic that the world is currently witnessing, COVID-19, even with vaccines available, the test positivity rate (TPR) tends to remain highly threatening. This research focuses on identifying phytochemicals, previously known for their broad-spectrum antiviral properties which can be potential drug candidates for theSARS-CoV-2. A total of 225 phytocompounds (downloaded from PubChem database) are docked against targetprotein (downloaded from PDB database) of SARS-CoV-2using the POAP pipeline. The target protein is the RDRp complex. They are screened according to their binding affinity values and the filtered phytochemicals are then subjected to various analyses including ADME properties (preADMET, swissADME), bioactivity score, and molecular properties (molinspiration), drug-likeness (preADMET), lipophilicity, water solubility, and pharmacokinetics (swissADME). The receptor-ligand interactions and the amino acid positions are obtained using Discovery Studio Visualiser. Molecular dynamic simulation studies are performed to reveal key receptor-drug interactions that must be formed to achieve tight drug binding and also to predict stability. Out of the 225, 10 phytochemicals showed the best scores and more probability of drug action. Compounds that showed promising drug action potential include oriciacridone, corilagin, cinchophyllamine, sophaline D, amentoflavone, cryptomisrine, ginkgetin, hypericin, pseudojervine, dieckol, hinokiflavone, robustaflavone, solamargine. The research herein provides new possibilities for in vitro and in vivo analyses of the proposed ligands to develop new drugs againstSARS-CoV-2.
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Olmedo-Aguirre, Oscar, Karina Escobar-Vázquez, Giner Alor-Hernández, and Guillermo Morales-Luna. "ADM: An Active Deductive XML Database System." In MICAI 2004: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24694-7_15.

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Gao, Ya, Shaoxiong Ji, Tongxuan Zhang, Prayag Tiwari, and Pekka Marttinen. "Contextualized Graph Embeddings for Adverse Drug Event Detection." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-26390-3_35.

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AbstractAn adverse drug event (ADE) is defined as an adverse reaction resulting from improper drug use, reported in various documents such as biomedical literature, drug reviews, and user posts on social media. The recent advances in natural language processing techniques have facilitated automated ADE detection from documents. However, the contextualized information and relations among text pieces are less explored. This paper investigates contextualized language models and heterogeneous graph representations. It builds a contextualized graph embedding model for adverse drug event detection. We employ different convolutional graph neural networks and pre-trained contextualized embeddings as the building blocks. Experimental results show that our methods can improve the performance by comparing recent ADE detection models, suggesting that a text graph can capture causal relationships and dependency between different entities in a document.
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Tang, Yu, Zhigang Kan, Dequan Sun, et al. "ADMMiRNN: Training RNN with Stable Convergence via an Efficient ADMM Approach." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67661-2_1.

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Chen, ChungMin Melvin, and Nicholas Roussopoulos. "The implementation and performance evaluation of the ADMS query optimizer: Integrating query result caching and matching." In Advances in Database Technology — EDBT '94. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-57818-8_61.

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Santhanavanich, Thunyathep, Rosanny Sihombing, Pithon Macharia Kabiro, Patrick Würstle, and Sabo Kwado Sini. "Storing and Visualising Dynamic Data in the Context of Energy Analysis in the Smart Cities." In iCity. Transformative Research for the Livable, Intelligent, and Sustainable City. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92096-8_16.

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AbstractThere is increased activity in developing workflows and implementations in the context of urban energy analysis simulation based on 3D city models in smart cities. At the University of Applied Sciences Stuttgart (HFT Stuttgart), an urban energy simulation platform called ‘SimStadt’ has successfully been developed. It uses the CityGML 3D city model to simulate the heat demand, photovoltaic potential, and other scenarios that provide dynamic simulation results in both space and time dimensions. Accordingly, a tool for managing dynamic data of the CityGML models is required. Earlier, the CityGML Application Domain Extension (ADE) had been proposed to support additional attributes of the CityGML model; however, there is still a lack of open-source tools and platforms to manage and distribute the CityGML ADE data efficiently. This article evaluates and compares alternative methods to manage dynamic simulation results of the 3D city model and visualise these data on the 3D web-based smart city application, including the use of SimStadt web services, databases, and OGC SensorThings API standard.
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Zhang, Xianbin, and Caihong Wang. "Exploration on Anti-Depression Mechanism of Baihe Zhimu Decoction Based on Network Pharmacology and Molecular Docking." In Studies in Health Technology and Informatics. IOS Press, 2023. http://dx.doi.org/10.3233/shti230868.

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Objective: To analyze anti-depression mechanism of Baihe Zhimu decoction (BZD) based on network pharmacology method, which provides reference for the development of new drugs and the clinical application of classical prescriptions. Method: The main chemical components and targets of Baihe and Zhimu were obtained through traditional Chinese medicine pharmacology system technology platform (TCMSP) database, and the active components of TCM were filtered according to ADME; Major targets for anti-depression were get through Gencards, OMIM and DRUGBANK databases; Protein interaction analysis was performed using the String platform; Build PPI networks and mine potential protein functional modules in the network; The Metascape platform was used to analyze the “drug-ingredients-target” and its involved biological processes and pathways; Finally, the molecular docking validation was performed by Systems Dock Web Site. Results: The core active ingredients of BZD treating depression are kaempferol and Stigmasterol, The core targets are AKT1, TNF, TP53, PTGS2, and CASP3. The biological pathway of the anti-depression mainly acts on Lipid and atherosclerosis, Chemical carcinogenesis and receptor activation. Molecular docking results showed that AKT1, TNF and TP53 have good affinity with components kaempferol and Stigmasterol. Conclusion: This study initially revealed the mechanism of multicomponent, multiple target and multiple pathway of anti-depression, which may be related to neuroactive ligand-receptor interaction, atherosclerotic, PI3K-Akt and TNF signaling pathway.
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A. Badria, Farid, and Mohamed Foda. "Perspective Chapter: Integrated Network Pharmacology and Multiomics Approach to Elucidate the Repositioning of Fatal Food Toxins to Lifesaving Anticancer Drug." In Poisoning - Prevention, Diagnosis, Treatment and Poison Repurposing. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.112789.

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This research investigates repurposing potato glycoalkaloids as lifesaving anticancer drugs. There is integration of network pharmacology with multiomics. Solanine, chaconine, and their hydrolysis products’ pharmacokinetics were tested using SwissADME. Solanine and chaconine targets were identified via reverse pharmacophore mapping. Through database mining, 26 solanine and chaconine targets were found in cancer genes. To understand gene function, KEGG and GO analyses were done. STRING was used to create a protein-protein interaction network to find similarities between chemicals and cancer. To find prognostic genes in various cancers, CytoHubba in Cytoscape identified hub genes and GEPIA2 did survival analysis. ADME testing for solanine and chaconine medication candidates failed. Their glycosylation boosted solubility and P-glycoprotein inhibition. Cancer targets shared by both drugs were elevated in cancer-related pathways such as Pi3k-Akt1 and HIF-1. Cell death control and programmed cell death genes were enriched in gene ontology study. We built a protein-protein interaction network with 26 nodes and 38 edges. The hub genes were STAT3, TLR4, FGF2, IL2, NFKB1, AR, CHUK, TRIM24, NOS3, and KDM1A. Survival research showed that these genes predict cancer prognosis. We found that solanine and chaconine may interact with cancer-related genes to fight cancer. Discovery of hub genes with prognostic significance sheds light on glycoalkaloids’ anticancer processes.
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Le Duff Franck, Burgun Anita, Pouliquen Bruno, Delamarre Denis, and Le Beux Pierre. "Automatic enrichment of the Unified Medical Language System starting from the ADM knowledge base." In Studies in Health Technology and Informatics. IOS Press, 1999. https://doi.org/10.3233/978-1-60750-912-7-881.

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The Unified Medical Language System (UMLS) project aims to provide a repository of terms, concepts and relationships from several medical classifications. This work describes the possibility to enrich automatically with meaningful links the UMLS database by using description of diseases from another knowledge base, in our case ADM (Aide au Diagnostic Medical). In spite of the constraints and the difficulties to qualify the interconcept links, the results show that it is possible to find and create new links from a french knowledge database to the UMLS one. One of the interests of this work is that the automated learning of the connections could be used with others knowledge databases like expert system databases.
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Lu, Chen, Limin Ma, Haozhen Wang, et al. "A Network Pharmacology Study to Explore Mechanism of the Drug Pair of Astragalus-Saposhnikoviae Radix in the Treatment of Allergic Rhinitis." In Computer Methods in Medicine and Health Care. IOS Press, 2021. http://dx.doi.org/10.3233/atde210242.

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Allergic rhinitis (AR) has now become one of the major diseases affecting people’s lives, and Traditional Chinese medicine (TCM) always has good efficacy in clinical treatment. In the present study, we analyzed the most frequently used drug pair of Astragalus-Saposhnikoviae Radix (SR) in prescriptions for the treatment of allergic rhinitis by network pharmacology to reveal the modern pharmacological mechanisms of drug prevention and treatment of the disease. Firstly, the 38 active ingredients with good ADME properties from the Astragalus-SR drug pair were collected from the database, and the collated drug targets of Astragalus and SR and the targets of allergic rhinitis were mapped against each other by the network visualization software Cytoscape, followed by the establishment of a “drug active ingredient-target-disease” network diagram and the construction of a high-confidence protein-protein interaction network. Then, the common targets obtained from the disease and drug active ingredients were imported by R language for GO enrichment analysis and KEGG pathway enrichment analysis. The KEGG pathways associated with the targets of Astragalus and SR for the treatment of allergic rhinitis obtained from R enrichment analysis were imported into Cytoscape, and the CytoNCA plug-in was loaded to construct a “target-pathway” network map, and the core target wogonin (FN1) was screened. These evidences suggest that the drug pair of Astragalus-SR works in a multi-component, multi-target and integrated modulation manner for the treatment of allergic rhinitis, which provides an important basis for the treatment of allergic rhinitis.
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Conference papers on the topic "ADME database"

1

Araújo, Louisy Carvalho, Marina Crispim Sarmento, Nicole Sarmento Queiroga, Lucas Vinicius Rafael Figueiredo, and Michelle Salles Barros de Aguiar. "Acute disseminated encephalomielite and Covid-19 - a literature review." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.396.

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Background: The infection caused by SARS-CoV-2 is associated with several neurological manifestations. Among these, acute disseminated encephalomyelitis (ADEM), an immune-mediated disease, has a reasonable incidence. In this context, the absence of direct viral infection of the CNS and late presentation of the condition corroborate to the hypothesis of an immune relationship. Objectives: Describe the relation between acute disseminated encephalomyelitis and COVID-19 infection. Design and setting: Literature review, held at the University Center of João Pessoa, located in the city of João Pessoa, Paraíba, Brazil. Methods: Through the PubMed database, using descriptors as follows: “acute disseminated encephalomyelitis” AND “COVID-19”, associated with time filter of the years 2020-2021. Results: The pathogenesis of ADEM in COVID-19 occurs through several mechanisms. One is a cross reaction between immune cells and nerve cells, which causes damage by activating the immune response and releasing protease enzymes. Another perspective is that the state of hyperinflammation activates like glial cells. In addition, an infection can trigger the production of autoantibodies against glial components, generating demyelinating lesions. In a series of cases that included 43 patients, nine had manifestations of ADEM, with a variety of clinical and radiological forms. Of these nine, on neuroimaging, all had multifocal, supratentorial white matter, four had hemorrhagic changes and two had myelitis. Conclusions: The coexistence between ADEM and COVID-19, although well established in some cases, still shows the need for studies that better clarify the relation between viral infection and brain lesions present in these clinical conditions.
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Garcia-Rodriguez de Guzman, I., M. Polo, and M. Piattini. "An ADM Approach to Reengineer Relational Databases towards Web Services." In 2007 14th Working Conference on Reverse Engineering. IEEE, 2007. http://dx.doi.org/10.1109/wcre.2007.9.

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Likaj, Ramë, Gëzim Hoxha, and Albi Macula. "Enhancing cost efficiency in manufacturing through 3c an excel based solution." In International Scientific and Technical Conference Automation of Discrete Production Engineering ADP 2025. Az-buki National Publishing House, 2025. https://doi.org/10.53656/adpe-2025.01.

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Manufacturing cost estimation is crucial for improving production efficiency and competitiveness. This paper describes a responsive and real Production Cost Program that is structured as an interactive form that incorporates data analysis for a variety of production processes such as milling, drilling, laser cutting, and water jet cutting. The system uses the supplied data to select the best processing methods, assuring accurate cost calculations. The user interface acts as a structured questionnaire, requiring users to enter essential parameters such as materials, machining procedures, and production volume. Once these inputs are entered, the system automatically computes the required cost factors in the background of the application by referencing pre-entered tabular data. This method reduces user effort while retaining high accuracy in cost estimation. The program that was built by using Microsoft Excel as a programming tool, leveraging its advanced formula-based calculations, macros, and Visual Basic for Applications (VBA) scripts to automate data processing. Its structured style enables dynamic cost analysis with real-time accuracy. Excel’s interaction with external databases extends functionality beyond standalone estimation. The program that we have created in this paper and its adaptability enables modification to industry requirements, streamline cost analysis and optimizing production planning. Excel’s automation and scalability increase resource allocation, waste reduction and adaptability to a wide range of manufacturing environments.
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Arroyos, Marina Roche, Xavier Bertolí, Fancisco Diaz, Didac Didac, Cano Pablo, and Salat Roger. "Virtual Modelling of Real- Driving Conditions for Early Evaluation and Validation of Vehicles Design." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2021-adm-130.

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"The vehicle validation at the end of the development process has to guarantee the vehicle will fulfill the expected reliability, consumption, emission, safety and performances in the variety of possible use- case scenarios, ranging from city to hilly roads and autobahnsmotorways, from extremely hot to extremely cold conditions and from gentle to aggressive driving. IDIADA is a leading company in validation for real- driving conditions, conducting over 15.000.000 km per year in the five continents. However, problem-solving in the validation phase is commonly difficult and expensive. For this reason, real- driving conditions are gaining relevance in the vehicle design phase, hence, the need arises to shift these real conditions to a model basedmodel-based development process in order to perform target setting and early virtual validation for real- driving conditions. For the modelling of the different real conditions a data collection process must be carried out. The data acquisition system and specific instrumentation typically represent a high- cost activity that hinders the data collection coverage. For this purpose, IDIADA has developed the NAVIMU-20, a cost- effective, versatile, compact and accurate data acquisition system that involves navigation and inertial measurements as well as logging functionality for collectingon all the data required to generate virtual mission profiles. This paper covers the development of this solution, starting with the measurements definition, standardization of the logs format for compatibility with the post-processing system, the comparison and verification with high- performance data acquisition systems to validate and ensure the data quality, the and algorithm development for the slope calculation with post- processing. Finally, the generated mission profiles are validated to calculate powertrain demand, through correlation between calculated operative point and measured torque for sample routes. As a result of the activity, the paper shows the application of a mission profile to virtually simulate the implications in real use of a combustion and a hybrid vehicle oin the same route. This methodology aims to build a real- driving usage profile database with wide coverage of the five continents suitable for early virtual evaluation of real- driving implications in powertrain in terms of consumption, emissions, durability, driveability, cooling and thermal comfort."
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Pratama, Galang Airlangga, Khaerul Manaf, and SW Pitara. "ANALISIS ARSITEKTUR ENTERPRISE MENGGUNAKAN TOGAF ADM VERSI 9.2 PADA PT. INDUSTRI TELEKOMUNIKASI INDONESIA (PERSERO)." In Seminar Sosial Politik, Bisnis, Akuntansi dan Teknik (SoBAT) ke-3. LPPM USB YPKP, 2021. http://dx.doi.org/10.32897/sobat3.2021.41.

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Pesatnya perkembangan teknologi informasi dan perubahan lingkungan organisasi memaksa perusahaan untuk beradaptasi agar mampu mempertahankan eksistensi organisasi dalam jangka panjang, sehingga diperlukan suatu model dalam perencanaan, perancangan dan pengelolaan organisasi. sistem informasi dan teknologi informasi untuk membantu mengoptimalkan. PT Industri Telekomunikasi Indonesia (Persero) juga dikenal sebagai PT. INTI (Persero) fokus pada lini bisnis di bidang manufaktur dan perakitan, layanan terkelola, layanan digital, dan integrator sistem. PT. INTI (Persero) telah menerapkan sistem informasi dan teknologi informasi untuk membantu jalannya proses bisnis yang ada, tetapi terdapat masalah di mana pembuatan aplikasi masih bersifat fungsional, terdapat aplikasi berbeda yang memiliki fitur sama dengan database berbeda dan terdapat aplikasi yang tidak digunakan lagi setelah tahap implementasi oleh sebab itu dibutuhkan arsitektur enterprise agar terwujudnya keselarasan antara strategi SI/TI dengan strategi bisnis dan untuk menghindari aplikasi yang berfokus ke organisasi fungsional saja.Dalam studi kasus ini, penulis memilih untuk menggunakan framework TOGAF dalam analisis arsitektur bisnis, meliputi fase pendahuluan, visi arsitektur, arsitektur bisnis, arsitektur sistem informasi, dan arsitektur teknologi. dan menghasilkan master architecture plan TOGAF ADM, dengan harapan rancangan enterprise architecture ini dapat membantu PT. INTI (Persero) dalam pengembangan dan perancangan sistem informasi dan teknologi informasi di masa yang akan datang.
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