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Thematische Bibliographien / SILICO SCREENING / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „SILICO SCREENING“

Autor: Grafiati

Veröffentlicht am 26. Oktober 2023

Zuletzt aktualisiert am 31. Juli 2025

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1

Recanatini, Maurizio, Giovanni Bottegoni, and Andrea Cavalli. "In silico antitarget screening." Drug Discovery Today: Technologies 1, no. 3 (2004): 209–15. http://dx.doi.org/10.1016/j.ddtec.2004.10.004.

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2

Rudisser, Simon, and Wolfgang Jahnke. "NMR and In silico Screening." Combinatorial Chemistry & High Throughput Screening 5, no. 8 (2002): 591–603. http://dx.doi.org/10.2174/1386207023329987.

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3

Gallinger, Tom L., Samuel Y. Aboagye, Wiebke Obermann, et al. "First In Silico Screening of Insect Molecules for Identification of Novel Anti-Parasitic Compounds." Pharmaceuticals 15, no. 2 (2022): 119. http://dx.doi.org/10.3390/ph15020119.

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Schistosomiasis is a neglected tropical disease caused by blood flukes of the genus Schistosoma. In silico screenings of compounds for the identification of novel anti-parasitic drug candidates have received considerable attention in recent years, including the screening of natural compounds. For the first time, we investigated molecules from insects, a rather neglected source in drug discovery, in an in silico screening approach to find novel antischistosomal compounds. Based on the Dictionary of Natural Products (DNP), we created a library of 1327 insect compounds suitable for molecular dock

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4

Seifert, Markus H. J., Kristina Wolf, and Daniel Vitt. "Virtual high-throughput in silico screening." BIOSILICO 1, no. 4 (2003): 143–49. http://dx.doi.org/10.1016/s1478-5382(03)02359-x.

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5

Supratik, Kar, and Roy Kunal. "Predictive toxicology using QSAR : A perspective." Journal of Indian Chemical Society Vol. 87, Dec 2010 (2010): 1455–515. https://doi.org/10.5281/zenodo.5805067.

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Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata-700 032, India E-mail: kunalroy_in@yahoo.com Fax : 91-33-28371078 <em>Manuscript received 27 August 2010, accepted 30 August 2010</em> The need of in silico techniques In predicting toxicological and hazardous properties of chemicals are taking the central stage of attention day by day among the scientific community and the public. In silico methods are capable of providing information about the physicochemical properties of chemicals, their environmental fate as well as their

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Musto, Liam, Athanasios Saratzis, Mintu Nath, et al. "In-silico trials of targeted screening for abdominal aortic aneurysms using linked healthcare data: A study protocol." PLOS One 20, no. 7 (2025): e0327856. https://doi.org/10.1371/journal.pone.0327856.

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Background The NHS abdominal aortic aneurysm (AAA) screening programme (NAAASP) is both clinically and economically effective. One of the main determinants of this effectiveness is disease prevalence. AAA prevalence is decreasing over time, steadily reducing the efficiency of the current NAAASP screening policy. One alternative to whole population screening is targeted screening of high-risk groups. Whether this would detect a clinically and publicly acceptable proportion of disease, and whether it would improve cost-effectiveness are unknown. The aim of this research is to estimate the clinic

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Reddy, Bandi Deepa, and Ch M. Kumari Chitturi. "Screening and Identification of Microbial Derivatives for Inhibiting Legumain: An In silico Approach." Journal of Pure and Applied Microbiology 12, no. 3 (2018): 1623–30. http://dx.doi.org/10.22207/jpam.12.3.69.

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8

Ma, Dik-Lung, Victor Pui-Yan Ma, Daniel Shiu-Hin Chan, Ka-Ho Leung, Hai-Jing Zhong, and Chung-Hang Leung. "In silico screening of quadruplex-binding ligands." Methods 57, no. 1 (2012): 106–14. http://dx.doi.org/10.1016/j.ymeth.2012.02.001.

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9

Lin, Li-Chiang, Adam H. Berger, Richard L. Martin, et al. "In silico screening of carbon-capture materials." Nature Materials 11, no. 7 (2012): 633–41. http://dx.doi.org/10.1038/nmat3336.

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10

Arvidson, Kirk B., Luis G. Valerio, Marilyn Diaz, and Ronald F. Chanderbhan. "In Silico Toxicological Screening of Natural Products." Toxicology Mechanisms and Methods 18, no. 2-3 (2008): 229–42. http://dx.doi.org/10.1080/15376510701856991.

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11

Vidal, David, and Jordi Mestres. "In Silico Receptorome Screening of Antipsychotic Drugs." Molecular Informatics 29, no. 6-7 (2010): 543–51. http://dx.doi.org/10.1002/minf.201000055.

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12

Fukunishi, Yoshifumi, Satoru Kubota, and Haruki Nakamura. "Noise Reduction Method for Molecular Interaction Energy: Application to in Silico Drug Screening and in Silico Target Protein Screening." Journal of Chemical Information and Modeling 46, no. 5 (2006): 2071–84. http://dx.doi.org/10.1021/ci060152z.

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13

Vinod, Varmaan Yuawa Rani1 and VasudevaRao Avupati. "IN SILICO BASED VIRTUAL SCREENING FOR BIOACTIVE PPAR-γ AGONISTS". IAJPS,CSK PUBLICATIONS 03, № 10 (2016): 1237–50. https://doi.org/10.5281/zenodo.166359.

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<em>The predominance of multifactorial diseases has become an epidemic in the tropical and sub-tropical areas all over the world. According to the reports of the World Health Organization (WHO), around 250 million people are currently living with diabetes and this number is expected to be more than 366 million by 2030. Although, there are a number of naturally occurring and synthetic agents (glitazones) that activate PPARγ, the identity of the true natural ligand of this receptor is still unknown; this may be the reason for their lethal side effects. In silico virtual screening has presently b

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Fukunishi, Yoshifumi, Yoshiaki Mikami, Satoru Kubota, and Haruki Nakamura. "Multiple target screening method for robust and accurate in silico ligand screening." Journal of Molecular Graphics and Modelling 25, no. 1 (2006): 61–70. http://dx.doi.org/10.1016/j.jmgm.2005.11.006.

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15

Zaini, Vikra Ardiansyah, Purwantiningsih Sugita, Luthfan Irfana та Suminar Setiati Achmadi. "In Silico Screening Anticancer of Six Triterpenoids toward miR-494 and TNF-α Targets". Jurnal Kimia Sains dan Aplikasi 23, № 4 (2020): 117–23. http://dx.doi.org/10.14710/jksa.23.4.117-123.

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Hepatocellular carcinoma (HCC) accounts for up to 90% of all primary liver cancers worldwide. Cinobufagin is recognized to inhibit miR-494 as the HCC target. Increased expression of TNF-α results in an inadequate response to liver anticancer drugs. The models in this study were cinobufagin, cycloartenol, and ethyl acetate fractions of Ganoderma lucidum, 2–5. Seven docking targets in this study were Akt, ERK1, ERK2, PI3K, TNF-α, TNFR1, and TNFR2. Cycloartenol and compound 4 comply with Veber’s rules, Lipinski’s rule of 5, and demonstrate moderate toxicity. The action implies a potential docking

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KAMINUMA, ELI, NAOHIKO HEIDA, TAKESHI YOSHIZUMI, MIKI NAKAZAWA, MINAMI MATSUI, and TETSURO TOYODA. "IN SILICO PHENOTYPIC SCREENING METHOD OF MUTANTS BASED ON STATISTICAL MODELING OF GENETICALLY MIXED SAMPLES." Journal of Bioinformatics and Computational Biology 03, no. 06 (2005): 1281–93. http://dx.doi.org/10.1142/s0219720005001557.

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In comprehensive functional genomics projects, systematic analysis of phenotypes is vital. However, conventional phenotypic screening is done mainly by imprecise visual observation of qualitative traits, and, therefore, in silico screening techniques for quantitative traits are required. In this report, we propose in silico phenotypic screening method that utilizes a Gaussian mixture model for the trait distribution in the offspring of a mutagenized line and the likelihood ratio test between the estimated Gaussian mixture model and the wild-type single Gaussian model. In order to evaluate the

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Glisic, Sanja, Kristina Stevanovic, Andrej Perdih, et al. "Influenza a Virus Inhibition: Evaluating Computationally Identified Cyproheptadine Through In Vitro Assessment." International Journal of Molecular Sciences 26, no. 13 (2025): 5962. https://doi.org/10.3390/ijms26135962.

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Influenza is still a chronic global health threat, inducing a sustained search for effective antiviral therapeutics. Computational methods have played a pivotal role in developing small molecule therapeutics. In this study, we applied a combined in silico and in vitro approach to explore the potential anti-influenza activity of cyproheptadine, a clinically used histamine H1 receptor antagonist. Virtual screening based on the average quasivalence number (AQVN) and electron–ion interaction potential (EIIP) descriptors suggests similarities between cyproheptadine and several established anti-infl

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Tang, Min, Yang Fu, Ying Fan, Ming-Shui Fu, Zhi Zheng, and Xun Xu. "In-silico design of novel myocilin inhibitors for glaucoma therapy." Tropical Journal of Pharmaceutical Research 16, no. 10 (2017): 2527–33. http://dx.doi.org/10.4314/tjpr.v16i10.29.

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Purpose: To explore newer computational approaches in the design of novel myocilin inhibitors for the treatment of glaucoma.Methods: An in-silico virtual screening technique based on simulation of molecular docking was utilised to design a novel myocilin inhibitors for the treatment of glaucoma. The designed novel molecules were theoretically evaluated to predict their pharmacokinetic properties and toxic effects. Lead molecules were screened out in virtual screening technique on the basis of low binding energies obtained in AutoDock based molecular docking simulation.Results: Out of ten top l

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Hidayat, Aulia Fikri, Taufik Muhammad Fakih, Gita Cahya Eka Darma, and Ratu Choesrina. "In Silico Coformer Screening for Mefenamic Acid Cocrystallization." JURNAL INFO KESEHATAN 22, no. 1 (2024): 182–89. http://dx.doi.org/10.31965/infokes.vol22.iss1.1375.

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Cocrystallization is a widely used approach to enhance the solubility and dissolution characteristics of poorly soluble drugs. A pharmaceutical cocrystal is a multicomponent system composed of a solid active pharmaceutical ingredient (API) and a coformer, governed by non-covalent interactions. Screening for suitable coformers is essential to obtain an optimal cocrystal for specific drugs. This study aims to determine the drug-coformer interactions to select the most suitable coformer for cocrystal formation using the molecular docking method. Mefenamic acid, classified as a class II drug in th

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Luo, Cheng, Peng Xie, and Ronen Marmorstein. "Identification of BRAF Inhibitors through In Silico Screening." Journal of Medicinal Chemistry 51, no. 19 (2008): 6121–27. http://dx.doi.org/10.1021/jm800539g.

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21

Stepanovs, Dmitrijs, Ma̅ra Jure, Liudmila N. Kuleshova, Detlef W. M. Hofmann, and Anatoly Mishnev. "Cocrystals of Pentoxifylline: In Silico and Experimental Screening." Crystal Growth & Design 15, no. 8 (2015): 3652–60. http://dx.doi.org/10.1021/acs.cgd.5b00185.

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22

Li, Albert P., and Matthew Segall. "Early ADME/Tox studies and in silico screening." Drug Discovery Today 7, no. 1 (2002): 25–27. http://dx.doi.org/10.1016/s1359-6446(01)02117-1.

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23

Byler, Kendall G., Ifedayo Victor Ogungbe, and William N. Setzer. "In-silico screening for anti-Zika virus phytochemicals." Journal of Molecular Graphics and Modelling 69 (September 2016): 78–91. http://dx.doi.org/10.1016/j.jmgm.2016.08.011.

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24

Lindert, Steffen, Wei Zhu, Yi‐Liang Liu, Ran Pang, Eric Oldfield, and J. Andrew McCammon. "Farnesyl Diphosphate Synthase Inhibitors from In Silico Screening." Chemical Biology & Drug Design 81, no. 6 (2013): 742–48. http://dx.doi.org/10.1111/cbdd.12121.

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25

Byler, KG, and WN Setzer. "In-silico screening for anti-zika virus phytochemicals." Planta Medica 81, S 01 (2016): S1—S381. http://dx.doi.org/10.1055/s-0036-1596272.

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26

Takaya, Daisuke, Mayuko Takeda-Shitaka, Genki Terashi, Kazuhiko Kanou, Mitsuo Iwadate, and Hideaki Umeyama. "Bioinformatics Based Ligand-Docking and in-Silico Screening." CHEMICAL & PHARMACEUTICAL BULLETIN 56, no. 5 (2008): 742–44. http://dx.doi.org/10.1248/cpb.56.742.

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27

Feiler, Christian, Di Mei, Bahram Vaghefinazari, et al. "In silico screening of modulators of magnesium dissolution." Corrosion Science 163 (February 2020): 108245. http://dx.doi.org/10.1016/j.corsci.2019.108245.

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28

Spiliotopoulos, Dimitrios, and Amedeo Caflisch. "Fragment-based in silico screening of bromodomain ligands." Drug Discovery Today: Technologies 19 (March 2016): 81–90. http://dx.doi.org/10.1016/j.ddtec.2016.06.003.

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29

Islam, Rainul, Sumit Maji, Souparna Kabiraj, et al. "Role of in silico Drug Design in Pharmaceutical Sciences." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 2358–67. http://dx.doi.org/10.22214/ijraset.2022.42836.

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Abstract: In silico drug design is the study to identify, develop, analyze, optimize drugs or biologically cum pharmaceutically active compounds by using computerized software programs as well web servers. In silico drug design is commonly known as computer aided drug design or CADD in short. This technique shows a vital role in preclinical drug design and development. CADD can improve the speed of drug design. It reduces time as well as total cost of the experiments. Potent cum suitable molecules are prepared after performing in silico drug design including CADD. Various applications like con

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Medeiros, Isaiane, Ana Francisca Teixeira Gomes, Emilly Guedes Oliveira e Silva, et al. "Proteins and Peptides Studied In Silico and In Vivo for the Treatment of Diabetes Mellitus: A Systematic Review." Nutrients 16, no. 15 (2024): 2395. http://dx.doi.org/10.3390/nu16152395.

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Bioinformatics has expedited the screening of new efficient therapeutic agents for diseases such as diabetes mellitus (DM). The objective of this systematic review (SR) was to understand naturally occurring proteins and peptides studied in silico and subsequently reevaluated in vivo for treating DM, guided by the question: which peptides or proteins have been studied in silico for the treatment of diabetes mellitus? The RS protocol was registered in the International Prospective Register of Systematic Reviews database. Articles meeting the eligibility criteria were selected from the PubMed, Sc

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Jukič, Marko, Sebastjan Kralj, Anja Kolarič, and Urban Bren. "Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening." Pharmaceuticals 16, no. 8 (2023): 1170. http://dx.doi.org/10.3390/ph16081170.

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Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries’ display and

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Nguyen, Ha Thi, Thien-Y. Vu, A. Vijay Kumar та ін. "N-Aryl iminochromenes inhibit cyclooxygenase enzymes via π–π stacking interactions and present a novel class of anti-inflammatory drugs". RSC Advances 11, № 47 (2021): 29385–93. http://dx.doi.org/10.1039/d1ra04407a.

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Payra, Soumen, Arijit Saha, Chia-Ming Wu, et al. "Fe–SBA-15 catalyzed synthesis of 2-alkoxyimidazo[1,2-a]pyridines and screening of their in silico selectivity and binding affinity to biological targets." New Journal of Chemistry 40, no. 11 (2016): 9753–60. http://dx.doi.org/10.1039/c6nj02134d.

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34

Richards, William D., Yan Wang, Lincoln J. Miara, Jae Chul Kim, and Gerbrand Ceder. "Design of Li1+2xZn1−xPS4, a new lithium ion conductor." Energy & Environmental Science 9, no. 10 (2016): 3272–78. http://dx.doi.org/10.1039/c6ee02094a.

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35

Zang, Jie, Shangzhi Ma, Cuizhe Wang, et al. "Screening for active constituents in Turkish galls against ulcerative colitis by mass spectrometry guided preparative chromatography strategy:in silico,in vitroandin vivostudy." Food & Function 9, no. 10 (2018): 5124–38. http://dx.doi.org/10.1039/c8fo01439f.

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36

Stoner, Chad, Mathew Troutman, Hua Gao, et al. "Moving in Silico Screening into Practice: A Minimalist Approach to Guide Permeability Screening!!" Letters in Drug Design & Discovery 3, no. 8 (2006): 575–81. http://dx.doi.org/10.2174/157018006778194736.

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37

Decesari, Stefano, Simona Kovarich, Manuela Pavan, Arianna Bassan, Andrea Ciacci, and David Topping. "Evaluating the mutagenic potential of aerosol organic compounds using informatics-based screening." Atmospheric Chemistry and Physics 18, no. 3 (2018): 2329–40. http://dx.doi.org/10.5194/acp-18-2329-2018.

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Abstract. Whilst general policy objectives to reduce airborne particulate matter (PM) health effects are to reduce exposure to PM as a whole, emerging evidence suggests that more detailed metrics associating impacts with different aerosol components might be needed. Since it is impossible to conduct toxicological screening on all possible molecular species expected to occur in aerosol, in this study we perform a proof-of-concept evaluation on the information retrieved from in silico toxicological predictions, in which a subset (N = 104) of secondary organic aerosol (SOA) compounds were screene

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Deyon-Jung, Laurence, Christophe Morice, Florence Chéry, et al. "Fragment pharmacophore-based in silico screening: a powerful approach for efficient lead discovery." MedChemComm 7, no. 3 (2016): 506–11. http://dx.doi.org/10.1039/c5md00444f.

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Imai, Kento, Yuri Takeuchi, Kazunori Shimizu, and Hiroyuki Honda. "In Silico Screening of a Bile Acid Micelle Disruption Peptide for Oral Consumptions from Edible Peptide Database." Foods 10, no. 10 (2021): 2496. http://dx.doi.org/10.3390/foods10102496.

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Recently, many bioactive peptides have been identified using bioinformatics tools. Previously, our group developed a method to screen dual-functional peptides that have direct intestinal delivery with porous silica gel and bile acid micelle disruption. However, newly designed peptides were not found in any storage protein. Therefore, in this study, in silico screening was performed using a 350,000 edible peptide library consisting of 4- to 7-mer independent peptides. As an initial screening, all edible peptides were applied to the random forest model to select predicted positive peptides. For

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Zhong, Hai-Jing, Bo Ra Lee, Joshua William Boyle, et al. "Structure-based screening and optimization of cytisine derivatives as inhibitors of the menin–MLL interaction." Chemical Communications 52, no. 34 (2016): 5788–91. http://dx.doi.org/10.1039/c6cc01079b.

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Di Natale, Concetta, Giorgia Celetti, Pasqualina Liana Scognamiglio, et al. "Molecularly endowed hydrogel with an in silico-assisted screened peptide for highly sensitive small molecule harvesting." Chemical Communications 54, no. 72 (2018): 10088–91. http://dx.doi.org/10.1039/c8cc04943b.

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42

Balouch, Martin, Martin Šrejber, Marek Šoltys, Petra Janská, František Štěpánek, and Karel Berka. "In silico screening of drug candidates for thermoresponsive liposome formulations." Molecular Systems Design & Engineering 6, no. 5 (2021): 368–80. http://dx.doi.org/10.1039/d0me00160k.

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In silico methodology for compound suitability for liposomal formulation has been developed. Water–lipid partitioning and permeation of candidate compounds from the DrugBank were calculated, and the most appropriate targets validated experimentally.

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Singh, Arvinder Pal, Ankush Goyal, and Navjot Singh Sethi. "In-silico drug likeness predictions of novel 9-benzyl-6-(furan-2-yl)-2-(N,N dimethylamino)- 9H-purine compound." YMER Digital 21, no. 08 (2022): 305–20. http://dx.doi.org/10.37896/ymer21.08/26.

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In silico studies, are increasing now-a-days, as through computer mechanics, screening of novel compounds based upon their physicochemical properties is important to reduce the cost of synthesizing novel medicinal compounds. In silico studies by network analysis and throughout screening helps to know and calculate biological activity of medicinal compounds. Novel 9- benzylpurine derivatives synthesized previously are used to study its structure and bioavailability radar, physicochemical properties, lipophilicity, solubility, pharmacokinetics, drug likeness and medicinal chemistry properties. T

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Rifai, Eko Aditya, Hayun Hayun, and Arry Yanuar. "IN SILICO SCREENING OF ANTIMALARIAL FROM INDONESIAN MEDICINAL PLANTS DATABASE TO PLASMEPSIN TARGET." Asian Journal of Pharmaceutical and Clinical Research 10, no. 17 (2017): 130. http://dx.doi.org/10.22159/ajpcr.2017.v10s5.23115.

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Objective: Malaria is a disease that impacts millions of people annually. Among the enzymes, plasmepsin is the main enzyme in the plasmodium life cycle that degrades hemoglobin during the erythrocytic phase in the food vacuole. Recently, pharmaceutical industries have been trying to develop therapeutic agents that can cure malaria through the discovery of new plasmepsin inhibitor compounds. One of the developing approaches is the in silico method.Methods: The chosen in silico screening method in this experiment is a structure-based screening using GOLD software and the Indonesian medicinal pla

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Achar, S. S., L. Pethakamsetty, A. A. Pathan, N. R. Parine, and S. Vinjamuri. "ADME Analysis of Crude Extracts of Exacum bicolor Roxb. and in vitro Screening for Antioxidant, Antimicrobial and Cytotoxicity Assays." Asian Journal of Chemistry 34, no. 10 (2022): 2633–38. http://dx.doi.org/10.14233/ajchem.2022.23847.

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With the increase in medical pandemics caused by emerging and re-emerging microbial pathogens, topping multi drug resistance, there is always a dire requirement for the novel drugs to treat diseases. In view of the imperative need for lead molecules addressing ailments, the authors have extended their phytochemical studies on the crude extracts of Exacum bicolor Roxb, to in silico ADME analysis followed by in vitro screening for biological activities. In present study, the crude extracts of E. bicolor are subjected to GC-MS analysis and a total of 32 phytoconstituents were identified and consi

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Narasimhan, Gopinathan, Gokul kumar K, B. Balalji, Azhagu Naachiar, Khiren S, and Harikrishnan N. "Comprehensive investigation of two substituted benzimidazoles: Design, synthesis, biological assessment, and characterization." Current Trends in Pharmacy and Pharmaceutical Chemistry 6, no. 3 (2024): 106–13. http://dx.doi.org/10.18231/j.ctppc.2024.024.

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Benzimidazole is a bicyclic molecule that is mostly used in medicinal chemistry. The 2-substituted benzimidazoles that are now on the market include omeprazole, flubendazole, mebendazole, and albendazole. Antioxidants are compounds that impede the oxidation process, which is the chemical process that produces free radicals. A computational technique called "in-silico screening" is used in drug discovery to effectively estimate a molecule's likelihood of interacting with a target of interest. Antihelminthics are a class of antiparasitic drugs that either kill or paralyze internal parasites like

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Xie, Dewei, Yaling Shen, Erzheng Su, Lei Du, Jingli Xie та Dongzhi Wei. "The effects of angiotensin I-converting enzyme inhibitory peptide VGINYW and the hydrolysate of α-lactalbumin on blood pressure, oxidative stress and gut microbiota of spontaneously hypertensive rats". Food & Function 13, № 5 (2022): 2743–55. http://dx.doi.org/10.1039/d1fo03570c.

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Yogita Akash Shinde, Rabisankar Dash, Desh Deepak Pandey, et al. "In Silico Screening of Chrysin Derivatives as Drug Leads Against Covid-19." Journal of Advanced Zoology 44, S6 (2023): 1137–49. http://dx.doi.org/10.17762/jaz.v44is6.2394.

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The current investigation was aimed at in silico studies of some selected chrysin derivatives to evaluate their activity in attenuation of COVID 19. In this study 50 chrysin derivatives were selected and Remedesivir was used as standard in assessing the anti-viral activity. To assess the ADMET potential of compounds, primarily drug-like properties and bioactivity scores were calculated. Using PATCHDOCK software, binding fitness scores for SARS COV2 protease and Angiotensin Converting Enzyme proteins were determined using molecular docking studies. According to results of in silico studies, der

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Yim, Sung-Kun, Kian Kim, SangHo Chun, et al. "Screening of Human CYP1A2 and CYP3A4 Inhibitors from Seaweed In Silico and In Vitro." Marine Drugs 18, no. 12 (2020): 603. http://dx.doi.org/10.3390/md18120603.

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Phenolic compounds and carotenoids are potential inhibitors of cytochrome P450s. Sixteen known compounds, phenolic compounds and carotenoids from seaweed were examined for potential inhibitory capacity against CYP1A2 and CYP3A4 in silico and in vitro. Morin, quercetin, and fucoxanthin inhibited the enzyme activity of CYP1A2 and CYP3A4 in a dose-dependent manner. The IC50 values of morin, quercetin, and fucoxanthin were 41.8, 22.5, and 30.3 μM for CYP1A2 and 86.6, 16.1, and 24.4 μM for CYP3A4, respectively. Siphonaxanthin and hesperidin did not show any significant effect on CYP1A2, but they sl

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M. Patil, Vaishali, Neeraj Masand, and Satya P. Gupta. "GENIUS In Silico Screening Technology for HCV Drug Discovery." Current Drug Discovery Technologies 13, no. 4 (2016): 189–98. http://dx.doi.org/10.2174/1570163813666161006113011.

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