Nicolas Baurin

Large-scale comparison of four binding site detection algorithms.

A large-scale evaluation and comparison of four cavity detection algorithms was carried out. The algorithms SiteFinder, fpocket, PocketFinder, and SiteMap were evaluated on a protein test set containing 5416 protein-ligand complexes and 9900 apo forms, corresponding to a subset of the set used earlier for benchmarking the PocketFinder algorithm. For the holo structures, all four algorithms correctly identified a similar amount of pockets (around 95%). SiteFinder, using optimized parameters, SiteMap, and fpocket showed similar pocket ranking performance, which was defined by ranking the correct binding site on rank 1 of the predictions or within the first 5 ranks of the predictions. On the apo structures, PocketFinder especially and also SiteFinder (optimized parameters) performed best, identifying 96% and 84% of all binding sites, respectively. The fpocket program predicts binding sites most accurately among the algorithms evaluated here. SiteFinder needed an average calculation time of 1.6 s compared with 2 min for SiteMap and around 2 s for fpocket.

Engineering Protein Therapeutics: Predictive Performances of a Structure-Based Virtual Affinity Maturation Protocol

The implementation of a structure based virtual affinity maturation protocol and evaluation of its predictivity are presented. The in silico protocol is based on conformational sampling of the interface residues (using the Dead End Elimination/A* algorithm), followed by the estimation of the change of free energy of binding due to a point mutation, applying MM/PBSA calculations. Several implementations of the protocol have been evaluated for 173 mutations in 7 different protein complexes for which experimental data were available: the use of the Boltzamnn averaged predictor based on the free energy of binding (ΔΔG(*)) combined with the one based on its polar component only (ΔΔE(pol*)) led to the proposal of a subset of mutations out of which 45% would have successfully enhanced the binding. When focusing on those mutations that are less likely to be introduced by natural in vivo maturation methods (99 mutations with at least two base changes in the codon), the success rate is increased to 63%. In another evaluation, focusing on 56 alanine scanning mutations, the in silico protocol was able to detect 89% of the hot-spots.