Assessment of protein side-chain conformation prediction methods in different residue environments

Peterson, Lenna X.; Kang, Xuejiao; Kihara, Daisuke

doi:10.1002/prot.24552

Cited by 30 publications

(31 citation statements)

References 67 publications

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“…Alternate location is not discussed in assessing the side-chain packing programs, and normally alternate location atoms are deleted or only the atoms with alternate location indicator ‘A’ are considered20. However, some atoms only include indicators other than ‘A’, i.e.…”

Section: Resultsmentioning

confidence: 99%

“…Currently, the side-chain packing programs reported prediction accuracies of χ 1 and χ 1+2 dihedral angles between 80–90%20. Researchers are still arguing about how to improve the prediction by one or two percent accuracy.…”

Section: Discussionmentioning

confidence: 99%

“…Till now, protein side-chain packing methods have been widely benchmarked, considering the crystal environment19 or residue environments20. According to the conclusions of this analysis, we realized that the protein side-chain conformation prediction is not a single-answer problem and an urgent need is to reconsider the problem of side-chain packing and side-chain prediction assessment.…”

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confidence: 99%

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Quantifying side-chain conformational variations in protein structure

Miao

Cao

2016

Sci Rep

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Protein side-chain conformation is closely related to their biological functions. The side-chain prediction is a key step in protein design, protein docking and structure optimization. However, side-chain polymorphism comprehensively exists in protein as various types and has been long overlooked by side-chain prediction. But such conformational variations have not been quantitatively studied and the correlations between these variations and residue features are vague. Here, we performed statistical analyses on large scale data sets and found that the side-chain conformational flexibility is closely related to the exposure to solvent, degree of freedom and hydrophilicity. These analyses allowed us to quantify different types of side-chain variabilities in PDB. The results underscore that protein side-chain conformation prediction is not a single-answer problem, leading us to reconsider the assessment approaches of side-chain prediction programs.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Quantifying side-chain conformational variations in protein structure

Miao

Cao

2016

Sci Rep

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“…Although many methods such as RASP [17], OSCARstar [14], SIDEPRO [18], SCMF-PDRL [8], OPUS-Rota [16], CIS-RR [3], and SCWRL4 [11] have been proposed to deal with the PSCPP, comparison works have been rather scarce [19,17]. Most of the methods present only a brief comparison analysis of their new proposed method against previously proposed ones on particular test instances.…”

Section: Introductionmentioning

confidence: 96%

An Experimental Analysis of the Performance of SideChain Packing Algorithms

Brizuela

Corona

Lezcano

et al. 2015

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

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This paper presents a brief description of the protein side chain packing problem (PSCPP) and a performance assessment, on this problem, of three state-of-the-art algorithms: SCWRL4, OPUS-Rota, and CIS-RR. In order to perform a fair comparison, the algorithms are evaluated on three data sets, two of them were previously proposed in the literature and a set of 723 protein structures proposed here. Experimental results show that the achieved accuracy when evaluating the side chain's first torsion angle (χ1) is of approximately 86% and around 69% for the first and the second torsion angles (χ1+2), for all methods. Although all the algorithms achieve similar accuracies, SCWRL4 requires on average, less computation effort than the others. We highlight relevant aspects that need to be considered in order to verify whether or not this 86% is a theoretical upper bound for the algorithms' performance as well as what might become a promising direction to follow in case an improvement is possible.

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“…Several methods have been proposed and benchmarked . Among the best programs are OSCAR, SCWRL4, and RASP .…”

Section: Introductionmentioning

confidence: 99%

Protein side chain conformation predictions with an MMGBSA energy function

2016

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The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an "MMGBSA" energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803-819. © 2016 Wiley Periodicals, Inc.

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Assessment of protein side-chain conformation prediction methods in different residue environments

Cited by 30 publications

References 67 publications

Quantifying side-chain conformational variations in protein structure

Quantifying side-chain conformational variations in protein structure

An Experimental Analysis of the Performance of SideChain Packing Algorithms

Protein side chain conformation predictions with an MMGBSA energy function

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