Success in high-resolution protein–protein docking requires accurate modeling of side-chain conformations at the interface. Most current methods either leave side chains fixed in the conformations observed in the unbound protein structures or allow the side chains to sample a set of discrete rotamer conformations. Here we describe a rapid and efficient method for sampling off-rotamer side-chain conformations by torsion space minimization during protein–protein docking starting from discrete rotamer libraries supplemented with side-chain conformations taken from the unbound structures, and show that the new method improves side-chain modeling and increases the energetic discrimination between good and bad models. Analysis of the distribution of side-chain interaction energies within and between the two protein partners shows that the new method leads to more native-like distributions of interaction energies and that the neglect of side-chain entropy produces a small but measurable increase in the number of residues whose interaction energy cannot compensate for the entropic cost of side-chain freezing at the interface. The power of the method is highlighted by a number of predictions of unprecedented accuracy in the recent CAPRI (Critical Assessment of PRedicted Interactions) blind test of protein–protein docking methods.

Motivation: Motion is inherent in molecular interactions. Molecular flexibility must be taken into account in order to develop accurate computational techniques for predicting interactions. Energy-based methods currently used in molecular modeling (i.e. molecular dynamics, Monte Carlo algorithms) are, in practice, only able to compute local motions while accounting for molecular flexibility. However, large-amplitude motions often occur in biological processes. We investigate the application of geometric path planning algorithms to compute such large motions in flexible molecular models. Our purpose is to exploit the efficacy of a geometric conformational search as a filtering stage before subsequent energy refinements.

Here we carry out an examination of shape complementarity as a criterion in protein--protein docking and binding. Specifically, we examine the quality of shape complementarity as a critical determinant not only in the docking of 26 protein--protein "bound", complexed cases, but in particular, of 19 "unbound" protein--protein cases, where the structures have been determined separately. In all cases, entire molecular surfaces are utilized in the docking, with no consideration of the location of the active site, or of particular residues/atoms in either the receptor or the ligand which participate in the binding. To evaluate the goodness of the strictly geometry-based shape complementarity in the docking process as compared to the main favorable and unfavorable energy components, we study systematically a potential correlation between each of these components and the RMSD of the "unbound" protein--protein cases. Specifically, we examine the non-polar buried surface area, polar b...

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This article gives an overview of recent progress in protein-protein docking and it identifies several directions for future research. Recent results from the CAPRI blind docking experiments show that docking algorithms are steadily improving in both reliability and accuracy. Current docking algorithms employ a range of efficient search and scoring strategies, including e.g. fast Fourier transform correlations, geometric hashing, and Monte Carlo techniques. These approaches can often produce a relatively small list of up to a few thousand orientations, amongst which a near-native binding mode is often observed. However, despite the use of improved scoring functions which typically include models of desolvation, hydrophobicity, and electrostatics, current algorithms still have difficulty in identifying the correct solution from the list of false positives, or decoys. Nonetheless, significant progress is being made through better use of bioinformatics, biochemical, and biophysical information such as e.g. sequence conservation analysis, protein interaction databases, alanine scanning, and NMR residual dipolar coupling restraints to help identify key binding residues. Promising new approaches to incorporate models of protein flexibility during docking are being developed, including the use of molecular dynamics snapshots, rotameric and off-rotamer searches, internal coordinate mechanics, and principal component analysis based techniques. Some investigators now use explicit solvent models in their docking protocols. Many of these approaches

We propose a parallel hyzwC genetic algorithm for flexible protein-protein docking in order to improve the conventional "rigid-body models to manipulate protein-protein interactions. he proposed hyPKR algorithm is a combination of an evolutionary algorithm with a simulated annealing one,ye,TPKC a powerful protein-complex conformation-searching engine. Parallelization of the procedure makes possible to reach high algorithm performance, in both, execution times and size of treated monomers and complexes. Knowledge on side chain flexibility is extracted by means of an exhaustiveanalyPT ofcryPzKT"K[w[#Ty data on proteins and protein complexes. Results demonstrate the competency of the algorithm since comparison of calculated andcryRwwGT"KGC[#T data accounts for a maximum of 2.5 A in RMS difference, including side chain conformation. he syTP allows routine analyeT of this fundamental molecularbiology problem important to elucidate bio-macromolecular function in biophyophT and biochemical mechanisms involving molecular recognition and interaction,yeracti simultaneously clues for designing new proteins andenzyGz directed to different purposes.

Here,weintroducea new approach tomacromoleculardockingwhich combinesthecontinuousglobaloptimizationalgorithmCGU [6,22]withthegrid-basedconformationalsearch engineDOT [24]. W e alsodetailtheuseofthismethod todock acetylcholineintothefasciculin-acetylcholinesterase complex.Fasciculinblo cksaccesstothelong,narrow pathway leadingtotheactivesite,which islocatedintheinterior oftheacetylcholinesterase.Forthisreason,flndingthelocationcomputationallyisrathernon -trivial.W enotonlysuccessfullyidentifledtheoptimaldockingconflguration, but wereabletodo soina matterofhours. Acknowledgments The authorswouldliketothankthefollowingindividualsfor theiradviceand enlighteningdiscussions:Nathan Baker, Ken Dill,PhilipGill,JefireyMandell,Andy McCammon, MichaelPique,VictoriaRobertsand IgorTsigelny.

docking with multiple residue

ABSTRACT Interactions between proteins are often sufficiently weak that their study through the use of conventional structural techniques becomes problematic. Of the few techniques capable of providing experimental measures of weak protein-protein interactions, perhaps the most useful is the second virial coefficient, B 22, which quantifies a protein solution’s deviations from ideal behavior. It has long been known that B 22 can in principle be computed, but only very recently has it been demonstrated that such calculations can be performed using protein models of true atomic detail (Biophys. J. 1998, 75:2469–2477). The work reported here extends these previous efforts in an attempt to develop a transferable energetic model capable of reproducing the experimental trends obtained for two different proteins over a range of pH and ionic strengths. We describe protein-protein interaction energies by a combination of three separate terms: (i) an electrostatic interaction term based on the use of effective charges, (ii) a term describing the electrostatic desolvation that occurs when charged groups are buried by an approaching protein partner, and (iii) a solvent-accessible surface area term that is used to describe contributions from van der Waals and hydrophobic interactions. The magnitude of the third term is governed by an adjustable, empirical parameter, �, that is altered to optimize agreement between calculated and experimental values of B 22. The model is applied separately to the proteins lysozyme and chymotrypsinogen, yielding optimal values of � that are almost identical. There are, however, clear difficulties in reproducing B 22 values at the extremes of pH. Explicit calculation of the protonation states of ionizable amino acids in the 200 most energetically favorable protein-protein structures suggest that

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