ReviewExpert review of molecular diagnostics2007
Bioinformatic approaches for modeling the substrate specificity of HIV-1 protease: an overview.
Review in Expert review of molecular diagnostics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- The importance of physicochemical characteristics and nonlinear classifiers in determining HIV-1 protease specificity.Bioengineered · 2016Article
- Feature Selection Combined with Neural Network Structure Optimization for HIV-1 Protease Cleavage Site Prediction.BioMed research international · 2015Article
- Article
- How to find simple and accurate rules for viral protease cleavage specificities.BMC bioinformatics · 2009Article
- A genetic approach for building different alphabets for peptide and protein classification.BMC bioinformatics · 2008Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
HIV-1 protease has a broad and complex substrate specificity, which hitherto has escaped a simple comprehensive definition. This, and the relatively high mutation rate of the retroviral protease, makes it challenging to design effective protease inhibitors. Several attempts have been made during the last two decades to elucidate the enigmatic cleavage specificity of HIV-1 protease and to predict cleavage of novel substrates using bioinformatic analysis methods. This review describes the methods that have been utilized to date to address this important problem and the results achieved. The data sets used are also reviewed and important aspects of these are highlighted.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.