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ROTAS: a rotamer-dependent, atomic statistical potential for assessment and prediction of protein structures.

Park J, Saitou K - BMC Bioinformatics (2014)

Bottom Line: The results show that ROTAS performs better than other competing potentials not only in native structure recognition, but also in best model selection and correlation coefficients between energy and model quality.The results show that ROTAS has improved ability to recognize native structure from decoy models compared to other potentials.The effectiveness of ROTAS may provide insightful information for the development of many applications which require accurate side-chain modeling such as protein design, mutation analysis, and docking simulation.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA. kazu@umich.edu.

ABSTRACT

Background: Multibody potentials accounting for cooperative effects of molecular interactions have shown better accuracy than typical pairwise potentials. The main challenge in the development of such potentials is to find relevant structural features that characterize the tightly folded proteins. Also, the side-chains of residues adopt several specific, staggered conformations, known as rotamers within protein structures. Different molecular conformations result in different dipole moments and induce charge reorientations. However, until now modeling of the rotameric state of residues had not been incorporated into the development of multibody potentials for modeling non-bonded interactions in protein structures.

Results: In this study, we develop a new multibody statistical potential which can account for the influence of rotameric states on the specificity of atomic interactions. In this potential, named "rotamer-dependent atomic statistical potential" (ROTAS), the interaction between two atoms is specified by not only the distance and relative orientation but also by two state parameters concerning the rotameric state of the residues to which the interacting atoms belong. It was clearly found that the rotameric state is correlated to the specificity of atomic interactions. Such rotamer-dependencies are not limited to specific type or certain range of interactions. The performance of ROTAS was tested using 13 sets of decoys and was compared to those of existing atomic-level statistical potentials which incorporate orientation-dependent energy terms. The results show that ROTAS performs better than other competing potentials not only in native structure recognition, but also in best model selection and correlation coefficients between energy and model quality.

Conclusions: A new multibody statistical potential, ROTAS accounting for the influence of rotameric states on the specificity of atomic interactions was developed and tested on decoy sets. The results show that ROTAS has improved ability to recognize native structure from decoy models compared to other potentials. The effectiveness of ROTAS may provide insightful information for the development of many applications which require accurate side-chain modeling such as protein design, mutation analysis, and docking simulation.

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Related in: MedlinePlus

The distance dependence of root mean square of (Pobs − Pexp) for angular parameters. The observed probability distribution is calculated over all pairs of atom types. The thin, dashed and dotted curves corresponds to θ, ϕ and ω, respectively.
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Fig4: The distance dependence of root mean square of (Pobs − Pexp) for angular parameters. The observed probability distribution is calculated over all pairs of atom types. The thin, dashed and dotted curves corresponds to θ, ϕ and ω, respectively.

Mentions: Although the distance bin between 14.5 and 15 Å was used as the cutoff in the construction of distance-dependent pairwise potential, we calculate the energy score within 10 Å and ignore the long-range tail of potentials beyond 10 Å. In fact, most physical interactions between atoms rapidly converge to zero beyond 8 ~ 10 Å. However, statistically derived potentials are likely to have fluctuations in the long-range, which inherently resulted from the statistical uncertainties. For example, Figures 4 reveals that the deviations of the observed probability from the expected probability for angular parameters do not consistently decrease as the atom-pair distance increases. It is noted that the root mean square of (Pobs(ϕ/d) − Pexp(ϕ/d)) increase after 12 Å. In addition, it was reported that distance-dependent pairwise potentials between hydrophobic atom pairs have either repulsive or attractive tail in the long range, even if no electrostatic interaction exists [7]. Thus it’s not always beneficial to include the long-range interactions in statistical potentials. We set the interaction cutoff to 10 Å without fine-tuning against a specific training dataset.Figure 4


ROTAS: a rotamer-dependent, atomic statistical potential for assessment and prediction of protein structures.

Park J, Saitou K - BMC Bioinformatics (2014)

The distance dependence of root mean square of (Pobs − Pexp) for angular parameters. The observed probability distribution is calculated over all pairs of atom types. The thin, dashed and dotted curves corresponds to θ, ϕ and ω, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4262145&req=5

Fig4: The distance dependence of root mean square of (Pobs − Pexp) for angular parameters. The observed probability distribution is calculated over all pairs of atom types. The thin, dashed and dotted curves corresponds to θ, ϕ and ω, respectively.
Mentions: Although the distance bin between 14.5 and 15 Å was used as the cutoff in the construction of distance-dependent pairwise potential, we calculate the energy score within 10 Å and ignore the long-range tail of potentials beyond 10 Å. In fact, most physical interactions between atoms rapidly converge to zero beyond 8 ~ 10 Å. However, statistically derived potentials are likely to have fluctuations in the long-range, which inherently resulted from the statistical uncertainties. For example, Figures 4 reveals that the deviations of the observed probability from the expected probability for angular parameters do not consistently decrease as the atom-pair distance increases. It is noted that the root mean square of (Pobs(ϕ/d) − Pexp(ϕ/d)) increase after 12 Å. In addition, it was reported that distance-dependent pairwise potentials between hydrophobic atom pairs have either repulsive or attractive tail in the long range, even if no electrostatic interaction exists [7]. Thus it’s not always beneficial to include the long-range interactions in statistical potentials. We set the interaction cutoff to 10 Å without fine-tuning against a specific training dataset.Figure 4

Bottom Line: The results show that ROTAS performs better than other competing potentials not only in native structure recognition, but also in best model selection and correlation coefficients between energy and model quality.The results show that ROTAS has improved ability to recognize native structure from decoy models compared to other potentials.The effectiveness of ROTAS may provide insightful information for the development of many applications which require accurate side-chain modeling such as protein design, mutation analysis, and docking simulation.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA. kazu@umich.edu.

ABSTRACT

Background: Multibody potentials accounting for cooperative effects of molecular interactions have shown better accuracy than typical pairwise potentials. The main challenge in the development of such potentials is to find relevant structural features that characterize the tightly folded proteins. Also, the side-chains of residues adopt several specific, staggered conformations, known as rotamers within protein structures. Different molecular conformations result in different dipole moments and induce charge reorientations. However, until now modeling of the rotameric state of residues had not been incorporated into the development of multibody potentials for modeling non-bonded interactions in protein structures.

Results: In this study, we develop a new multibody statistical potential which can account for the influence of rotameric states on the specificity of atomic interactions. In this potential, named "rotamer-dependent atomic statistical potential" (ROTAS), the interaction between two atoms is specified by not only the distance and relative orientation but also by two state parameters concerning the rotameric state of the residues to which the interacting atoms belong. It was clearly found that the rotameric state is correlated to the specificity of atomic interactions. Such rotamer-dependencies are not limited to specific type or certain range of interactions. The performance of ROTAS was tested using 13 sets of decoys and was compared to those of existing atomic-level statistical potentials which incorporate orientation-dependent energy terms. The results show that ROTAS performs better than other competing potentials not only in native structure recognition, but also in best model selection and correlation coefficients between energy and model quality.

Conclusions: A new multibody statistical potential, ROTAS accounting for the influence of rotameric states on the specificity of atomic interactions was developed and tested on decoy sets. The results show that ROTAS has improved ability to recognize native structure from decoy models compared to other potentials. The effectiveness of ROTAS may provide insightful information for the development of many applications which require accurate side-chain modeling such as protein design, mutation analysis, and docking simulation.

Show MeSH
Related in: MedlinePlus