ArticleMethods in molecular biology (Clifton, N.J.)2022
In Silico Tools and Software to Predict ADMET of New Drug Candidates.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 37 citations in OpenAlex.
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- Fluorinated indeno-quinoxaline bearing thiazole moieties as hypoglycaemic agents targetingJournal of enzyme inhibition and medicinal chemistry · 2024Article
- Identifying Substructures That Facilitate Compounds to Penetrate the Blood-Brain Barrier via Passive Transport Using Machine Learning Explainer Models.ACS chemical neuroscience · 2024Article
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- Discovery of potential FGFR3 inhibitors via QSAR, pharmacophore modeling, virtual screening and molecular docking studies against bladder cancer.Journal of translational medicine · 2023Article
- Article
- Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.Beni-Suef University journal of basic and applied sciences · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Implication of computational techniques and in silico tools promote not only reduction of animal experimentations but also save time and money followed by rational designing of drugs as well as controlled synthesis of those "Hits" which show drug-likeness and possess suitable absorption, distribution, metabolism, excretion, and toxicity (ADMET) profile. With globalization of diseases, resistance of drugs over the time and modification of viruses and microorganisms, computational tools, and artificial intelligence are the future of drug design and one of the important areas where the principles of sustainability and green chemistry (GC) perfectly fit. Most of the new drug entities fail in the clinical trials over the issue of drug-associated human toxicity. Although ecotoxicity related to new drugs is rarely considered, but this is the high time when ecotoxicity prediction should get equal importance along with human-associated drug toxicity. Thus, the present book chapter discusses the available in silico tools and software for the fast and preliminary prediction of a series of human-associated toxicity and ecotoxicity of new drug entities to screen possibly safer drugs before going into preclinical and clinical trials.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.