| Literature DB >> 34225615 |
Nour El-Huda Daoud1, Pobitra Borah2, Pran Kishore Deb3, Katharigatta N Venugopala4, Wafa Hourani3, Muhammed Alzweiri5, Sanaa K Bardaweel5, Vinod Tiwari6.
Abstract
In the drug discovery setting, undesirable ADMET properties of a pharmacophore with good predictive power obtained after a tedious drug discovery and development process may lead to late-stage attrition. The earlystage ADMET profiling has brought a new dimension to lead drug development. Although several high-throughput in vitro models are available for ADMET profiling, the in silico methods are gaining more importance because of their economic and faster prediction ability without the requirements of tedious and expensive laboratory resources. Nonetheless, in silico ADMET tools alone are not accurate, and therefore, ideally adopted along with in vitro and or in vivo methods in order to enhance the predictability power. This review summarizes the significance and challenges associated with the application of in silico tools as well as the possible scope of in vitro models for integration to improve the ADMET predictability power of these tools. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.Entities:
Keywords: ADMET profiling; In silico; computational tools.; drug discovery; in vitro; molecular descriptors; predictive tools
Mesh:
Year: 2021 PMID: 34225615 DOI: 10.2174/1389200222666210705122913
Source DB: PubMed Journal: Curr Drug Metab ISSN: 1389-2002 Impact factor: 3.731