Literature DB >> 19539482

Proteochemometrics mapping of the interaction space for retroviral proteases and their substrates.

Aleksejs Kontijevskis1, Ramona Petrovska, Sviatlana Yahorava, Jan Komorowski, Jarl E S Wikberg.   

Abstract

Understanding the complex interactions of retroviral proteases with their ligands is an important scientific challenge in efforts to achieve control of retroviral infections. Development of drug resistance because of high mutation rates and extensive polymorphisms causes major problems in treating the deadly diseases these viruses cause, and prompts efforts to identify new strategies. Here we report a comprehensive analysis of the interaction of 63 retroviral proteases from nine different viral species with their substrates and inhibitors based on publicly available data from the past 17years of retroviral research. By correlating physico-chemical descriptions of retroviral proteases and substrates to their biological activities we constructed a highly statistically valid 'proteochemometric' model for the interactome of retroviral proteases. Analysis of the model indicated amino acid positions in retroviral proteases with the highest influence on ligand activity and revealed general physicochemical properties essential for tight binding of substrates across multiple retroviral proteases. Hexapeptide inhibitors developed based on the discovered general properties effectively inhibited HIV-1 proteases in vitro, and some exhibited uniformly high inhibitory activity against all HIV-1 proteases mutants evaluated. A generalized proteochemometric model for retroviral proteases interactome has been created and analysed in this study. Our results demonstrate the feasibility of using the developed general strategy in the design of inhibitory peptides that can potentially serve as templates for drug resistance-improved HIV retardants.

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Year:  2009        PMID: 19539482     DOI: 10.1016/j.bmc.2009.05.045

Source DB:  PubMed          Journal:  Bioorg Med Chem        ISSN: 0968-0896            Impact factor:   3.641


  4 in total

1.  SARS-CoV 3CL protease cleaves its C-terminal autoprocessing site by novel subsite cooperativity.

Authors:  Tomonari Muramatsu; Chie Takemoto; Yong-Tae Kim; Hongfei Wang; Wataru Nishii; Takaho Terada; Mikako Shirouzu; Shigeyuki Yokoyama
Journal:  Proc Natl Acad Sci U S A       Date:  2016-10-31       Impact factor: 11.205

2.  Computer aided selection of candidate vaccine antigens.

Authors:  Darren R Flower; Isabel K Macdonald; Kamna Ramakrishnan; Matthew N Davies; Irini A Doytchinova
Journal:  Immunome Res       Date:  2010-11-03

3.  Significantly improved HIV inhibitor efficacy prediction employing proteochemometric models generated from antivirogram data.

Authors:  Gerard J P van Westen; Alwin Hendriks; Jörg K Wegner; Adriaan P Ijzerman; Herman W T van Vlijmen; Andreas Bender
Journal:  PLoS Comput Biol       Date:  2013-02-21       Impact factor: 4.475

4.  Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets.

Authors:  Gerard Jp van Westen; Remco F Swier; Isidro Cortes-Ciriano; Jörg K Wegner; John P Overington; Adriaan P Ijzerman; Herman Wt van Vlijmen; Andreas Bender
Journal:  J Cheminform       Date:  2013-09-24       Impact factor: 5.514

  4 in total

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