Dynamics of Rnase Sa: A Simulation Perspective Complementary to NMR/X-ray

Combining docking and molecular dynamic simulations in drug design

A rational approach is needed to maximize the chances of finding new drugs, and to exploit the opportunities of potential new drug targets emerging from genomic and proteomic initiatives, and from the large libraries of small compounds now readily available through combinatorial chemistry. Despite a shaky early history, computer-aided drug design techniques can now be effective in reducing costs and speeding up drug discovery. This happy outcome results from development of more accurate and reliable algorithms, use of more thoughtfully planned strategies to apply them, and greatly increased computer power to allow studies with the necessary reliability to be performed. Our review focuses on applications and protocols, with the main emphasis on critical analysis of recent studies where docking calculations and molecular dynamics (MD) simulations were combined to dock small molecules into protein receptors. We highlight successes to demonstrate what is possible now, but also point out drawbacks and future directions. The review is structured to lead the reader from the simpler to more compute-intensive methods. Thus, while inexpensive and fast docking algorithms can be used to scan large compound libraries and reduce their size, more accurate but expensive MD simulations can be applied when a few selected ligand candidates remain. MD simulations can be used: during the preparation of the protein receptor before docking, to optimize its structure and account for protein flexibility; for the refinement of docked complexes, to include solvent effects and account for induced fit; to calculate binding free energies, to provide an accurate ranking of the potential ligands; and in the latest developments, during the docking process itself to find the binding site and correctly dock the ligand a priori.

Specificity in lipases: a computational study of transesterification of sucrose

Computational conformational searches of putative transition states of the reaction of sucrose with vinyl laurate catalyzed by lipases from Candida antarctica B and Thermomyces lanuginosus have been carried out. The dielectric of the media have been varied to understand the role of protein plasticity in modulating the observed regioselective transesterification. The binding pocket of lipase from Candida adapts to the conformational variability of the various substates of the substrates by small, local adjustments within the binding pocket. In contrast, the more constrained pocket of the lipase from Thermomyces adapts by adjusting through concerted global motions between subdomains. This leads to the identification of one large pocket in Candida that accommodates both the sucrose and the lauroyl moieties of the transition state, whereas in Thermomyces the binding pocket is smaller, leading to the localization of the two moieties in two distinct pockets; this partly rationalizes the broader specificity of the former relative to the latter. Mutations have been suggested to exploit the differences towards changing the observed selectivities.

Multiple Loop Conformations of Peptides Predicted by Molecular Dynamics Simulations Are Compatible with Nuclear Magnetic Resonance†

The affinity and selectivity of protein-protein interactions can be fine-tuned by varying the size, flexibility, and amino acid composition of involved surface loops. As a model for such surface loops, we study the conformational landscape of an octapeptide, whose flexibility is chemically steered by a covalent ring closure integrating an azobenzene dye into and by a disulfide bridge additionally constraining the peptide backbone. Because the covalently integrated azobenzene dyes can be switched by light between a bent cis state and an elongated trans state, six cyclic peptide models of strongly different flexibilities are obtained. The conformational states of these peptide models are sampled by NMR and by unconstrained molecular dynamics (MD) simulations. Prototypical conformations and the free-energy landscapes in the high-dimensional space spanned by the phi/psi angles at the peptide backbone are obtained by clustering techniques from the MD trajectories. Multiple open-loop conformations are shown to be predicted by MD particularly in the very flexible cases and are shown to comply with the NMR data despite the fact that such open-loop conformations are missing in the refined NMR structures.