Abstract
Acylthiocarbamates (ATCs) have been identified as a class of potent non-nucleoside HIV-1 reverse transcriptase (RT) inhibitors. A computational strategy based on molecular docking studies followed by comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) was used to identify the most important features impacting ATC antiretroviral activity. The CoMSIA model proved to be the more predictive, with r(2)(ncv) = 0.89, r(cv)(2) = 0.38, standard error of estimate (SEE) = 0.494, F = 84, and r(2)(pred) = 0.81. The results of these studies will be useful in designing new ATCs with improved potency, also against clinically relevant resistant mutants.
Publication types
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Research Support, Non-U.S. Gov't
MeSH terms
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Algorithms
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Binding Sites
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Computer Simulation
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Crystallography, X-Ray
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HIV Reverse Transcriptase / chemistry*
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HIV Reverse Transcriptase / metabolism
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HIV-1 / drug effects
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Humans
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Hydrogen Bonding
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Hydrophobic and Hydrophilic Interactions
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Models, Molecular
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Molecular Structure
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Protein Binding
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Protein Structure, Tertiary
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Quantitative Structure-Activity Relationship
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Reverse Transcriptase Inhibitors / chemistry*
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Reverse Transcriptase Inhibitors / metabolism
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Reverse Transcriptase Inhibitors / pharmacology
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Static Electricity
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Thiocarbamates / chemistry*
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Thiocarbamates / metabolism
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Thiocarbamates / pharmacology
Substances
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Reverse Transcriptase Inhibitors
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Thiocarbamates
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acylthiocarbamate
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reverse transcriptase, Human immunodeficiency virus 1
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HIV Reverse Transcriptase