Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape.

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Genomics of clinal variation in Drosophila: disentangling the interactions of selection and demography.

Clines in phenotypes and genotype frequencies across environmental gradients are commonly taken as evidence for spatially varying selection. Classical examples include the latitudinal clines in various species of Drosophila, which often occur in parallel fashion on multiple continents. Today, genomewide analysis of such clinal systems provides a fantastic opportunity for unravelling the genetics of adaptation, yet major challenges remain. A well-known but often neglected problem is that demographic processes can also generate clinality, independent of or coincident with selection. A closely related issue is how to identify true genic targets of clinal selection. In this issue of Molecular Ecology, three studies illustrate these challenges and how they might be met. Bergland et al. report evidence suggesting that the well-known parallel latitudinal clines in North American and Australian D. melanogaster are confounded by admixture from Africa and Europe, highlighting the importance of distinguishing demographic from adaptive clines. In a companion study, Machado et al. provide the first genomic comparison of latitudinal differentiation in D. melanogaster and its sister species D. simulans. While D. simulans is less clinal than D. melanogaster, a significant fraction of clinal genes is shared between both species, suggesting the existence of convergent adaptation to clinaly varying selection pressures. Finally, by drawing on several independent sources of evidence, Bo?ičević et al. identify a functional network of eight clinal genes that are likely involved in cold adaptation. Together, these studies remind us that clinality does not necessarily imply selection and that separating adaptive signal from demographic noise requires great effort and care.