Literature DB >> 28223231

The impact of in silico screening in the discovery of novel and safer drug candidates.

Didier Rognan1.   

Abstract

Drug discovery is a multidisciplinary and multivariate optimization endeavor. As such, in silico screening tools have gained considerable importance to archive, analyze and exploit the vast and ever-increasing amount of experimental data generated throughout the process. The current review will focus on the computer-aided prediction of the numerous properties that need to be controlled during the discovery of a preliminary hit and its promotion to a viable clinical candidate. It does not pretend to the almost impossible task of an exhaustive report but will highlight a few key points that need to be collectively addressed both by chemists and biologists to fuel the drug discovery pipeline with innovative and safe drug candidates.
Copyright © 2017 Elsevier Inc. All rights reserved.

Keywords:  Hit; Pharmacokinetics; Profile; Safety; Screening; Target

Mesh:

Year:  2017        PMID: 28223231     DOI: 10.1016/j.pharmthera.2017.02.034

Source DB:  PubMed          Journal:  Pharmacol Ther        ISSN: 0163-7258            Impact factor:   12.310


  20 in total

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2.  In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity.

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Journal:  Comput Toxicol       Date:  2021-09-09

3.  Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.

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4.  Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2.

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Review 6.  Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges.

Authors:  Isabella A Guedes; Felipe S S Pereira; Laurent E Dardenne
Journal:  Front Pharmacol       Date:  2018-09-24       Impact factor: 5.810

Review 7.  Chemoinformatics Strategies for Leishmaniasis Drug Discovery.

Authors:  Leonardo L G Ferreira; Adriano D Andricopulo
Journal:  Front Pharmacol       Date:  2018-11-01       Impact factor: 5.810

8.  Exponential consensus ranking improves the outcome in docking and receptor ensemble docking.

Authors:  Karen Palacio-Rodríguez; Isaias Lans; Claudio N Cavasotto; Pilar Cossio
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Review 9.  Synthetic and computational efforts towards the development of peptidomimetics and small-molecule SARS-CoV 3CLpro inhibitors.

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Review 10.  Molecular Modeling Targeting Transmembrane Serine Protease 2 (TMPRSS2) as an Alternative Drug Target Against Coronaviruses.

Authors:  Igor José Dos Santos Nascimento; Edeildo Ferreira da Silva-Júnior; Thiago Mendonça de Aquino
Journal:  Curr Drug Targets       Date:  2022       Impact factor: 2.937

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