The Impact of Side-Chain Packing on Protein Docking Refinement

Moghadasi, Mohammad; Mirzaei, Hanieh; Mamonov, Artem B.; Vakili, Pirooz; Vajda, Sándor; Paschalidis, Ioannis Ch.; Kozakov, Dima

doi:10.1021/ci500380a

Cited by 15 publications

(24 citation statements)

References 35 publications

(92 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, our primary goal was to increase the efficiency of the MCM method, which was achieved by introducing three algorithmic innovations. First, we have developed a novel distributed algorithm for adjusting side‐chain conformations in the MCM steps . Second, we have used a pre‐calculated structure‐dependent rotamer library that had relatively few rotamers for most side chains .…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

New additions to the ClusPro server motivated by CAPRI

et al. 2017

Self Cite

View full text Add to dashboard Cite

The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for Small Angle X-ray Scattering (SAXS) data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers. In addition, we have developed an extremely fast docking algorithm based on 5D rotational manifold FFT, and an algorithm for docking flexible peptides that include known sequence motifs. We feel that these developments will further improve the utility of ClusPro. However, CAPRI emphasized several shortcomings of the current server, including the problem of selecting the right energy parameters among the five options provided, and the problem of selecting the best models among the 10 generated for each parameter set. In addition, results convinced us that further development is needed for docking homology models. Finally we discuss the difficulties we have encountered when attempting to develop a refinement algorithm that would be computationally efficient enough for inclusion in a heavily used server.

show abstract

Section: Resultsmentioning

confidence: 99%

“…The method was based on a new representation of the search space, and increased the efficiency of local energy minimization within the steps of the MCM method . These innovations enabled us to test refinement by MCM for a substantial number of complexes . Unfortunately we have found the refinement algorithm not very useful.…”

Section: Resultsmentioning

confidence: 99%

New additions to the ClusPro server motivated by CAPRI

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, good results were also obtained by several methods that, similarly to ClusPro, perform global search assuming rigid proteins, including ZDOCK 53,77 , GRAMM 78 , and PatchDock 50 . Our own group’s “human” predictions are based on running ClusPro, followed by refinement and selection of most likely clusters” 79 , in some cases involving Monte Carlo minimization runs either using RosettaDock 67 or our own implementation of the Monte Carlo algorithm 80 . For a few targets the refinement improved medium accuracy structures into highly accurate ones, but generally the impact was moderate, and in 2016 we actually lost an acceptable prediction.…”

Section: Introductionmentioning

confidence: 99%

The ClusPro web server for protein–protein docking

et al. 2017

Self Cite

View full text Add to dashboard Cite

The ClusPro server (https://cluspro.org) is a widely used tool for protein-protein docking. The server provides a simple home page for basic use, requiring only two files in Protein Data Bank format. However, ClusPro also offers a number of advanced options to modify the search that include the removal of unstructured protein regions, applying attraction or repulsion, accounting for pairwise distance restraints, constructing homo-multimers, considering small angle X-ray scattering (SAXS) data, and finding heparin binding sites. Six different energy functions can be used depending on the type of proteins. Docking with each energy parameter set results in ten models defined by centers of highly populated clusters of low energy docked structures. This protocol describes the use of the various options, the construction of auxiliary restraints files, the selection of the energy parameters, and the analysis of the results. Although the server is heavily used, runs are generally completed in < 4 hours.

show abstract

“…). On the other hand, the side‐chain packing in protein docking has a number of features that are distinct from the side‐chain packing in protein design, and which allow development of specialized and efficient parallel algorithms . For example, when residue interaction graphs are constructed using lower limits for the

C_{α} - C_{α}

distances, inherent in the models of individual proteins, an algorithm based on tree decomposition yields a globally exact side‐chain assignment with computational complexity

O (N r^{c N^{2 / 3} \log N})

(where r is the average number of rotamers, and c is a constant) .…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Computational Feasibility of an Exhaustive Search of Side‐Chain Conformations in Protein‐Protein Docking

2018

View full text Add to dashboard Cite

Protein-protein docking procedures typically perform the global scan of the proteins relative positions, followed by the local refinement of the putative matches. Because of the size of the search space, the global scan is usually implemented as rigid-body search, using computationally inexpensive intermolecular energy approximations. An adequate refinement has to take into account structural flexibility. Since the refinement performs conformational search of the interacting proteins, it is extremely computationally challenging, given the enormous amount of the internal degrees of freedom. Different approaches limit the search space by restricting the search to the side chains, rotameric states, coarse-grained structure representation, principal normal modes, and so on. Still, even with the approximations, the refinement presents an extreme computational challenge due to the very large number of the remaining degrees of freedom. Given the complexity of the search space, the advantage of the exhaustive search is obvious. The obstacle to such search is computational feasibility. However, the growing computational power of modern computers, especially due to the increasing utilization of Graphics Processing Unit (GPU) with large amount of specialized computing cores, extends the ranges of applicability of the brute-force search methods. This proof-of-concept study demonstrates computational feasibility of an exhaustive search of side-chain conformations in protein pocking. The procedure, implemented on the GPU architecture, was used to generate the optimal conformations in a large representative set of protein-protein complexes. © 2018 Wiley Periodicals, Inc.

show abstract

The Impact of Side-Chain Packing on Protein Docking Refinement

Cited by 15 publications

References 35 publications

New additions to the ClusPro server motivated by CAPRI

New additions to the ClusPro server motivated by CAPRI

The ClusPro web server for protein–protein docking

Computational Feasibility of an Exhaustive Search of Side‐Chain Conformations in Protein‐Protein Docking

Contact Info

Product

Resources

About