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.