Ab initio prediction of the solution structures and populations of a cyclic pentapeptide in DMSO based on an implicit solvation model

Using a recently developed statistical mechanics methodology, the solution structures and populations of the cyclic pentapeptide cyclo(D-Pro(1)-Ala(2) -Ala(3)-Ala(4)-Ala(5)) in DMSO are obtained ab initio, ie., without using e xperimental restraints. An important ingredient of this methodology is a no vel optimization of implicit solvation pararmeters, which in our previous p ublication [Baysal, C.; Meirovitch, H. J Am Chem Soc 1998 120, 800-812] has been applied to a cyclic hexapeptide in DMSO. The molecule has been descri bed by the simplified energy function E-tot = E-GRO + Sigma(k)sigma(k)A(k), where E-GRO is the GROMOS force-field energy, sigma(k) and A(k) are the at omic solvation parameter (ASP) and the solvent accessible surface area of a tom k. This methodology, which relies on an extensive conformntional search , Monte Carlo simulations, and free energy calculations, is applied here wi th E-tot based on the ASPs derived in our previous work, and for comparison also with E-GRO alone. For both models, entropy effects are Sound to be si gnificant. For E-tot, the theoretical values of proton-proton distances and (3)J coupling constants agree very well with the NMR results [Mierke, D. F .; Kurz M.; Kessler; H. J Am Chern Soc 1994, 116, 1042-1049] while the resu lts for E-GRO are significantly worse. This suggests that our ASPs might be tranferrable to other cyclic peptides ill DMSO as well, making our methodo logy a reliable tool for an ab initio structure prediction; obviously, if n ecessary parrs of this methodology can also be incorporated in a best-fit a nalysis where experimental restraints are used. (C) 2000 John Wiley & Sons, Inc.