Human immunodeficiency virus (HIV) is the responsible causal agent of acquired immunodeficiency syndrome
(AIDS), a condition in humans where the immune system begins to fail, permitting the entry of diverse opportunistic
infections. Until now, there is currently no available vaccine or cure for HIV or AIDS. Thus, the search for new anti-HIV
therapies is a very active area. The viral infection takes place through a phenomenon called entry process, and proteins
known as gp120, CCR5 and CXCR4 are essential for the prevention of the HIV entry. Bioinformatics has emerged as a
powerful science to provide better understanding of biochemical or biological processes or phenomena, where 3D-QSAR
methodologies and molecular modeling techniques have served as strong support. The present review is focused on the
3D-QSAR methodologies and molecular modeling techniques as parts of Bioinformatics for the rational design of entry
inhibitors. Also, we propose here, a chemo-bioinformatic approach which is based on a model using substructural
descriptors and allowing the prediction of multi-target (mt) inhibitors against five proteins related with the HIV entry
process. By employing the model we calculated the quantitative contributions of some fragments to the inhibitory activity
against all the proteins. This allowed us to automatically extract the desirable fragments for design of new, potent and
versatile entry inhibitors.
Keywords: 3D-QSAR, Anti-HIV, CCR5, CXCR4, fragments, gp120, homology modeling, linear discriminant analysis,
molecular docking, QSAR, quantitative contributions.
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