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A Structure-Based Drug Discovery Paradigm.

ABSTRACT: Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the "big data" generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data sets by statistical machine learning methods. Advanced AI-based sophisticated machine learning tools have a significant impact on the drug discovery process including medicinal chemistry. In this review, we focus on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.

SUBMITTER: Batool M

PROVIDER: S-EPMC6601033 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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A Structure-Based Drug Discovery Paradigm.

Batool Maria M Ahmad Bilal B Choi Sangdun S

International journal of molecular sciences 20190606 11

Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the "big data" generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data ...[more]

PMID: 31174387

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