Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Prediction of HIV-1 protease inhibitor resistance by Molecular Modeling Protocols (MMPs) using GenMol software.

European journal of medicinal chemistry - 1 Nov 2008

Pèpe G, Courcambeck J, Perbost R, Jouanna P, Halfon P

Abstract excerpt

This paper investigates the contribution of Molecular Modeling to (i) predict and (ii) understand more fundamentally HIV drug resistance. Based on a new automated GenMol module, these goals are approached by Molecular Modeling Protocols (MMPs), respectively, (i) the Molecular Modeling Phenotype Protocol (MMPP) and (ii) the Molecular Modeling Phenotype-Genotype Protocol (MMGPP). Section 2 recalls clinical practice...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Drug Resistance, Viral
Share to Genotype
Share to HIV

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to HIV Protease

Share to HIV Protease Inhibitors

Share to Models, Molecular

Share to Molecular Structure

Share to Software

Source

Identifiers

PMID: 18455274
DOI: 10.1016/j.ejmech.2008.02.046

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Prediction of HIV-1 protease inhibitor resistance by Molecular Modeling Protocols (MMPs) using GenMol software.PMID 18455274Read ↗

Computational Prediction of HIV-1 Resistance to Protease Inhibitors.Semantic proximity Read ↗

The importance of bio-computational tools for predicting HIV drug resistance.Semantic proximity Read ↗

Decoding HIV resistance: from genotype to therapy.Semantic proximity Read ↗

Using drug exposure for predicting drug resistance - A data-driven genotypic interpretation tool.Semantic proximity Read ↗

Bioinformatics approach to predicting HIV drug resistance.Semantic proximity Read ↗

Characterizing early drug resistance-related events using geometric ensembles from HIV protease dynamicsSemantic proximity Read ↗

Interpreting resistance data for HIV-1 therapy management--know the limitations.Semantic proximity Read ↗

Geno2pheno: Estimating phenotypic drug resistance from HIV-1 genotypes.Semantic proximity Read ↗

Diversity and complexity of HIV-1 drug resistance: a bioinformatics approach to predicting phenotype from genotype.Semantic proximity Read ↗

Computational models for prediction of response to antiretroviral therapies.Semantic proximity Read ↗

Prediction of HIV-1 protease inhibitor resistance using a protein-inhibitor flexible docking approach.Semantic proximity Read ↗

Characterizing drug resistance using geometric ensembles from HIV protease dynamicsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.