Literature DB >> 28132481

Tackling the problem of HIV drug resistance.

Irene T Weber1, Robert W Harrison2.   

Abstract

The virally-encoded HIV-1 protease is an effective target for antiviral drugs, however, treatment for HIV infections is limited by the prevalence of drug resistant viral mutants. In this review, we describe our three-pronged approach to analyze and combat drug resistance. Understanding the molecular basis for resistance due to protease inhibitors is a key initial step in this approach. This knowledge is being employed for the design of new, improved inhibitors with high affinity for resistant mutants as well as wild type enzyme. In parallel with experimental studies of diverse mutants and inhibitory compounds, we are developing efficient algorithms to predict drug resistance phenotype from genotype data. This approach has important practical applications in the clinic where genotyping is recommended for individuals with new infections.

Entities:  

Keywords:  HIV/AIDS; X-ray crystallography; bioinformatics machine learning; enzymes

Mesh:

Substances:

Year:  2016        PMID: 28132481

Source DB:  PubMed          Journal:  Postepy Biochem        ISSN: 0032-5422


  5 in total

Review 1.  Decoding HIV resistance: from genotype to therapy.

Authors:  Irene T Weber; Robert W Harrison
Journal:  Future Med Chem       Date:  2017-08-09       Impact factor: 3.808

2.  Visualizing Tetrahedral Oxyanion Bound in HIV-1 Protease Using Neutrons: Implications for the Catalytic Mechanism and Drug Design.

Authors:  Mukesh Kumar; Kalyaneswar Mandal; Matthew P Blakeley; Troy Wymore; Stephen B H Kent; John M Louis; Amit Das; Andrey Kovalevsky
Journal:  ACS Omega       Date:  2020-05-14

3.  Prediction and molecular field view of drug resistance in HIV-1 protease mutants.

Authors:  Baifan Wang; Yinwu He; Xin Wen; Zhen Xi
Journal:  Sci Rep       Date:  2022-02-21       Impact factor: 4.379

4.  Assessment of a Computational Approach to Predict Drug Resistance Mutations for HIV, HBV and SARS-CoV-2.

Authors:  Dharmeshkumar Patel; Suzane K Ono; Leda Bassit; Kiran Verma; Franck Amblard; Raymond F Schinazi
Journal:  Molecules       Date:  2022-08-24       Impact factor: 4.927

5.  An Innovative Sequence-to-Structure-Based Approach to Drug Resistance Interpretation and Prediction: The Use of Molecular Interaction Fields to Detect HIV-1 Protease Binding-Site Dissimilarities.

Authors:  Nuno G Alves; Ana I Mata; João P Luís; Rui M M Brito; Carlos J V Simões
Journal:  Front Chem       Date:  2020-04-29       Impact factor: 5.221

  5 in total

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