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Current Topics in Medicinal Chemistry


ISSN (Print): 1568-0266
ISSN (Online): 1873-4294

Review Article

Intelligently Applying Artificial Intelligence in Chemoinformatics

Author(s): Sahil Sharma and Deepak Sharma*

Volume 18, Issue 20, 2018

Page: [1804 - 1826] Pages: 23

DOI: 10.2174/1568026619666181120150938

Price: $65


The intertwining of chemoinformatics with artificial intelligence (AI) has given a tremendous fillip to the field of drug discovery. With the rapid growth of chemical data from high throughput screening and combinatorial synthesis, AI has become an indispensable tool for drug designers to mine chemical information from large compound databases for developing drugs at a much faster rate as never before. The applications of AI have gone beyond bioactivity predictions and have shown promise in addressing diverse problems in drug discovery like de novo molecular design, synthesis prediction and biological image analysis. In this article, we provide an overview of all the algorithms under the umbrella of AI, enlist the tools/frameworks required for implementing these algorithms as well as present a compendium of web servers, databases and open-source platforms implicated in drug discovery, Quantitative Structure-Activity Relationship (QSAR), data mining, solvation free energy and molecular graph mining.

Keywords: Chemoinformatics, Drug discovery, Artificial intelligence, Machine learning, Deep learning, QSAR analysis, Generative models, Data/graph mining.

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