A Review on Applications of Computational Methods in Drug Screening and Design
By Xiaoqian Lin, Xiu Li, Xubo Lin. Molecules, 2020
536 citations recorded by the source corpus.
Drug development is one of the most significant processes in the pharmaceutical industry. Various computational methods have dramatically reduced the time and cost of drug discovery. In this review, we firstly discussed roles of multiscale biomolecular simulations in identifying drug binding sites on the target macromolecule and elucidating drug action mechanisms. Then, virtual screening methods (e.g., molecular docking, pharmacophore modeling, and QSAR) as well as structure- and ligand-based classical/de novo drug design were introduced and discussed. Last, we explored the development of machine learning methods and their applications in aforementioned computational methods to speed up the drug discovery process. Also, several application examples of combining various methods was discussed. A combination of different methods to jointly solve the tough problem at different scales and dimensions will be an inevitable trend in drug screening and design.
Subfields: Computational Theory and Mathematics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/8a8492ffdea7ac2d4ad36b5670662927f0e9b57d
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In Computational Theory and Mathematics
In Molecular Biology
Citations in the corpus
- Building a knowledge graph to enable precision medicine (2022, background): “…phenotyping 5–7 , disease etiology 8 , disease similarity 9 , disease diagnosis 10–12 , disease treatments 13 , drug-disease relationships 14–16 , mechanisms of drug action 17 , drug repurposing 18–20 , drug discovery 21,22 , adverse drug events 23,24 , combination drug therapies 25 , and so forth.”