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Mini-Reviews in Medicinal Chemistry

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ISSN (Print): 1389-5575
ISSN (Online): 1875-5607

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Multi-Scale Modeling in Drug Discovery Against Infectious Diseases

Author(s): Alejandro Speck-Planche*

Volume 19, Issue 19, 2019

Page: [1560 - 1563] Pages: 4

DOI: 10.2174/138955751919191024110000

Abstract

This work discusses the idea that drug discovery, instead of being performed through a series of filtering-based stages, should be viewed as a multi-scale optimization problem. Here, the most promising multi-scale models are analyzed in terms of their applications, advantages, and limitations in the search for more potent and safer chemicals against infectious diseases. Multi-scale de novo drug design is highlighted as an emerging paradigm, able to accelerate the discovery of more effective antimicrobial agents.

Keywords: Antimicrobial, infectious diseases, mtk-QSBER, multi-scale de novo drug design, pharmacokinetic, toxicity.

« Previous Next »
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Speck-Planche, A.; Cordeiro, M.N.D.S. Multitasking models for quantitative structure-biological effect relationships: Current status and future perspectives to speed up drug discovery. Expert Opin. Drug Discov., 2015, 10(3), 245-256.
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Speck-Planche, A.; Cordeiro, M.N.D.S. Simultaneous modeling of antimycobacterial activities and ADMET profiles: a chemoinformatic approach to medicinal chemistry. Curr. Top. Med. Chem., 2013, 13(14), 1656-1665.
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Speck-Planche, A.; Cordeiro, M.N.D.S. Simultaneous virtual prediction of anti-Escherichia coli activities and ADMET profiles: A chemoinformatic complementary approach for high-throughput screening. ACS Comb. Sci., 2014, 16(2), 78-84.
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Speck-Planche, A.; Cordeiro, M.N.D.S. Enabling virtual screening of potent and safer antimicrobial agents against noma: Mtk-QSBER model for simultaneous prediction of antibacterial activities and ADMET properties. Mini Rev. Med. Chem., 2015, 15(3), 194-202.
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Speck-Planche, A.; Cordeiro, M.N.D.S. Speeding up early drug discovery in antiviral research: A fragment-based in silico approach for the design of virtual anti-hepatitis C leads. ACS Comb. Sci., 2017, 19(8), 501-512.
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