Novel paradigms for drug discovery: computational multitarget screening.
An established paradigm in current drug development is (i) to identify a single protein target whose inhibition is likely to result in the successful treatment of a disease of interest; (ii) to assay experimentally large libraries of small-molecule compounds in vitro and in vivo to identify promising inhibitors in model systems; and (iii) to determine whether the findings are extensible to humans. This complex process, which is largely based on trial and error, is risk-, time- and cost-intensive. Computational (virtual) screening of drug-like compounds simultaneously against the atomic structures of multiple protein targets, taking into account protein-inhibitor dynamics, might help to identify lead inhibitors more efficiently, particularly for complex drug-resistant diseases. Here we discuss the potential benefits of this approach, using HIV-1 and Plasmodium falciparum infections as examples. We propose a virtual drug discovery 'pipeline' that will not only identify lead inhibitors efficiently, but also help minimize side-effects and toxicity, thereby increasing the likelihood of successful therapies.
Jenwitheesuk
Ekachai
E
Department of Microbiology, School of Medicine, University of Washington, Box 357242, Seattle, WA 98195, USA.
Horst
Jeremy A
JA
Rivas
Kasey L
KL
Van Voorhis
Wesley C
WC
Samudrala
Ram
R
D000818:Animals; D019380:Anti-HIV Agents / Q000494:pharmacology; D000962:Antimalarials / Q000494:pharmacology; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D016503:Drug Delivery Systems / Q000379:methods*; D015195:Drug Design; D015497:HIV-1 / Q000187:drug effects; D006801:Humans; D010963:Plasmodium falciparum / Q000187:drug effects
D019380:Anti-HIV Agents; D000962:Antimalarials