title: Validating the vitality strategy for fighting drug resistance.
abstract: The current challenge in designing effective drugs against HIV-1 is to find novel candidates with high potency, but with a lower susceptibility to mutations associated with drug resistance. Trying to address this challenge, we developed in our previous study (Ishikita and Warshel, Angew Chem Int Ed Engl 2008; 47:697-700) a novel computational strategy for fighting drug resistance by predicting the likely moves of the virus through constraints on binding and catalysis. This has been based on calculating the ratio between the vitality values ((K(i) k(cat)/K(M))(mutant)/(K(i) k(cat)/K(M))(wild-type)) and using it as a guide for predicting the moves of the virus. The corresponding calculations of the binding affinity, K(i), were carried out using the semi-macroscopic version of the protein dipole Langevin dipole (PDLD/S) in its linear response approximation (LRA) in its β version (PDLD/S-LRA/β). We also calculate the proteolytic efficiency, k(cat)/K(M), by evaluating the transition state (TS) binding free energies using the PDLD/S-LRA/β method. Here we provide an extensive validation of our strategy by calculating the vitality of six existing clinical and experimental drug candidates. It is found that the computationally determined vitalities correlate reasonably well with those derived from the corresponding experimental data. This indicates that the calculated vitality may be used to identify mutations that would be most effective for the survival of the virus. Thus, it should be possible to use our approach in screening for mutations that would provide the most effective resistance to any proposed antiviral drug. This ability should be very useful in guiding the design of drug molecules that will lead to the slowest resistance.
authors.affiliation: Department of Chemistry, University of Southern California, Los Angeles, California 90089-1062, USA.
authors.forename: Nidhi
authors.initials: N
authors.lastname: Singh
authors.forename: Maria P
authors.initials: MP
authors.lastname: Frushicheva
authors.forename: Arieh
authors.initials: A
authors.lastname: Warshel
mesh_terms: D000998:Antiviral Agents / Q000737:chemistry / Q000494:pharmacology; D001381:Azepines; D002352:Carrier Proteins / Q000737:chemistry; D020134:Catalytic Domain; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D016208:Databases, Factual; D024882:Drug Resistance, Viral; D004789:Enzyme Activation; D016333:HIV Protease / Q000737:chemistry; D017320:HIV Protease Inhibitors / Q000737:chemistry / Q000494:pharmacology*; D015497:HIV-1 / Q000737:chemistry* / Q000187:drug effects / Q000201:enzymology; D006801:Humans; D019469:Indinavir / Q000737:chemistry / Q000494:pharmacology; D008024:Ligands; D015394:Molecular Structure; D055672:Static Electricity; D013816:Thermodynamics; D014508:Urea / Q000031:analogs & derivatives / Q000737:chemistry / Q000494:pharmacology
chemical_list: D000998:Antiviral Agents; D001381:Azepines; D002352:Carrier Proteins; D017320:HIV Protease Inhibitors; D008024:Ligands; D019469:Indinavir; D014508:Urea; D016333:HIV Protease; C514803:p16 protease, Human immunodeficiency virus 1; C085816:DMP 323