Simple and general criterion for "in silico" screening of candidate HIV drugs

Highly active antiretroviral therapy (HAART) dramatically has changed the course of HIV infection. Currently, this therapy involves the use of agents from at least two distinct classes of antivirals: a protease inhibitor in combination with two nucleoside/nucleotide reverse transcriptase inhibitors (N(t)RTIs), or a non-nucleoside reverse transcriptase inhibitor (NNRTI) in combination with NRTIs. Recently, the third family of antivirals started to be used clinically, with the advent of enfuvirtide, the first fusion inhibitor. This broad spectrum of anti-HIV agents recently was extended with compounds inhibiting HIV integrase and vital entry. But these advances did not come without a cost: there were the short- and long-term drug toxicities, emergence of drug resistance, and persistence of viral reservoirs. For these reasons, there is a pressing need for novel anti-HIV drugs, particularly those that have a novel action mechanism, as these might be less likely to show cross-resistance with current therapies. The field of bioinformatics has become a major part of the drug discovery pipeline playing a key role in improvement and acceleration of the time and money consuming process of the drug development. Here we review the application of the EIIP/AQVN (Electron-Ion Interaction Potential, EIIP; Average Quasi Valence Number, AQVN) bioinformatics concept in the development of new anti-HIV drugs and propose a simple theoretical criterion for a virtual screening of molecular libraries for promising lead anti-HIV compounds and refinement of selected lead compounds in order to increase their biological activity.