Literature DB >> 24847659

Overcoming drug resistance through in silico prediction.

Pablo Carbonell, Jean-Yves Trosset.   

Abstract

Prediction tools are commonly used in pre-clinical research to assist target selection, to optimize drug potency or to predict the pharmacological profile of drug candidates. In silico prediction and overcoming drug resistance is a new opportunity that creates a high interest in pharmaceutical research. This review presents two main in silico strategies to meet this challenge: a structure-based approach to study the influence of mutations on the drug-target interaction and a system-biology approach to identify resistance pathways for a given drug. In silico screening of synergies between therapeutic and resistant pathways through biological network analysis is an example of technique to escape drug resistance. Structure-based drug design and in silico system biology are complementary approaches to reach few objectives at once: increase efficiency, reduce toxicity and overcoming drug resistance.

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Year:  2014        PMID: 24847659     DOI: 10.1016/j.ddtec.2014.03.012

Source DB:  PubMed          Journal:  Drug Discov Today Technol        ISSN: 1740-6749


  3 in total

1.  Reverse Chemical Genetics: Comprehensive Fitness Profiling Reveals the Spectrum of Drug Target Interactions.

Authors:  Lai H Wong; Sunita Sinha; Julien R Bergeron; Joseph C Mellor; Guri Giaever; Patrick Flaherty; Corey Nislow
Journal:  PLoS Genet       Date:  2016-09-02       Impact factor: 5.917

2.  Covalent docking and molecular dynamics simulations reveal the specificity-shifting mutations Ala237Arg and Ala237Lys in TEM beta-lactamase.

Authors:  Gabriel Monteiro da Silva; Jordan Yang; Bunlong Leang; Jessie Huang; Daniel M Weinreich; Brenda M Rubenstein
Journal:  PLoS Comput Biol       Date:  2022-06-27       Impact factor: 4.779

3.  Prodigiosin/PU-H71 as a novel potential combined therapy for triple negative breast cancer (TNBC): preclinical insights.

Authors:  Mohammed Moustapha Anwar; Manal Shalaby; Amira M Embaby; Hesham Saeed; Mona M Agwa; Ahmed Hussein
Journal:  Sci Rep       Date:  2020-09-07       Impact factor: 4.379

  3 in total

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