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Protein Engineering, Vol. 13, No. 6, 413-421, June 2000
© 2000 Oxford University Press

Monte Carlo calculations on HIV-1 reverse transcriptase complexed with the non-nucleoside inhibitor 8-Cl TIBO: contribution of the L100I and Y181C variants to protein stability and biological activity

Marilyn B.Kroeger Smith1,2, Michelle L. Lamb3, Julian Tirado-Rives4, William L. Jorgensen4, Christopher J. Michejda1, Sandra K. Ruby5 and Richard H. Smith, Jr1,5

1 National Cancer Institute-FCRDC, P.O. Box B, Frederick, MD 21702, 3 Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94143, 4 Department of Chemistry, Yale University, New Haven, CT 06520 and 5 Western Maryland College, Westminster, MD 21157, USA

A computational model of the non-nucleoside inhibitor 8-Cl TIBO complexed with HIV-1 reverse transcriptase (RT) was constructed in order to determine the binding free energies. Using Monte Carlo simulations, both free energy perturbation and linear response calculations were carried out for the transformation of wild-type RT to two key mutants, Y181C and L100I. The newer linear response method estimates binding free energies based on changes in electrostatic and van der Waals energies and solvent-accessible surface areas. In addition, the change in stability of the protein between the folded and unfolded states was estimated for each of these mutations, which are known to emerge upon treatment with the inhibitor. Results from the calculations revealed that there is a large hydrophobic contribution to protein stability in the native, folded state. The calculated absolute free energies of binding from both the linear response, and also the more rigorous free energy perturbation method, gave excellent agreement with the experimental differences in activity. The success of the relatively rapid linear response method in predicting experimental activites holds promise for estimating the activity of the inhibitors not only against the wild-type RT, but also against key protein variants whose emergence undermines the efficacy of the drugs.


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