Dataset Information

Determination of side-chain-rotamer and side-chain and backbone virtual-bond-stretching potentials of mean force from AM1 energy surfaces of terminally-blocked amino-acid residues, for coarse-grained simulations of protein structure and folding. II. Results, comparison with statistical potentials, and implementation in the UNRES force field.

ABSTRACT: Using the harmonic-approximation approach of the accompanying article and AM1 energy surfaces of terminally blocked amino-acid residues, we determined physics-based side-chain rotamer potentials and the side-chain virtual-bond-deformation potentials of 19 natural amino-acid residues with side chains. The potentials were approximated by analytical formulas and implemented in the UNRES mesoscopic dynamics program. For comparison, the corresponding statistical potentials were determined from 19,682 high-resolution protein structures. The low free-energy region of both the AM1-derived and the statistical potentials is determined by the valence geometry and the L-chirality, and its size increases with side-chain flexibility and decreases with increasing virtual-bond-angle theta. The differences between the free energies of rotamers are greater for the AM1-derived potentials compared with the statistical potentials and, for alanine and other residues with small side chains, a region corresponding to the C(ax)(7) conformation has remarkably low free-energy for the AM1-derived potentials, as opposed to the statistical potentials. These differences probably result from the interactions between neighboring residues and indicate the need for introduction of cooperative terms accounting for the coupling between side-chain rotamer and backbone interactions. Both AM1-derived and statistical virtual-bond-deformation potentials are multimodal for flexible side chains and are topologically similar; however, the regions of minima of the statistical potentials are much narrower, which probably results from imposing restraints in structure determination. The force field with the new potentials was preliminarily optimized using the FBP WW domain (1E0L) and the engrailed homeodomain (1ENH) as training proteins and assessed to be reasonably transferable.

SUBMITTER: Kozlowska U

PROVIDER: S-EPMC2849738 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Determination of side-chain-rotamer and side-chain and backbone virtual-bond-stretching potentials of mean force from AM1 energy surfaces of terminally-blocked amino-acid residues, for coarse-grained simulations of protein structure and folding. II. Results, comparison with statistical potentials, and implementation in the UNRES force field.

Kozłowska Urszula U Maisuradze Gia G GG Liwo Adam A Scheraga Harold A HA

Journal of computational chemistry 20100401 6

Using the harmonic-approximation approach of the accompanying article and AM1 energy surfaces of terminally blocked amino-acid residues, we determined physics-based side-chain rotamer potentials and the side-chain virtual-bond-deformation potentials of 19 natural amino-acid residues with side chains. The potentials were approximated by analytical formulas and implemented in the UNRES mesoscopic dynamics program. For comparison, the corresponding statistical potentials were determined from 19,682 ...[more]

PMID: 20017135

Similar Datasets

Project description:The UNited RESidue (UNRES) model of polypeptide chains is a coarse-grained model in which each amino-acid residue is reduced to two interaction sites, namely, a united peptide group (p) located halfway between the two neighboring ?-carbon atoms (C?s), which serve only as geometrical points, and a united side chain (SC) attached to the respective C?. Owing to this simplification, millisecond molecular dynamics simulations of large systems can be performed. While UNRES predicts overall folds well, it reproduces the details of local chain conformation with lower accuracy. Recently, we implemented new knowledge-based torsional potentials (Krupa et al. J. Chem. Theory Comput. 2013, 9, 4620–4632) that depend on the virtual-bond dihedral angles involving side chains: C?···C?···C?···SC (?(1)), SC···C?···C?···C? (?(2)), and SC···C?···C?···SC (?(3)) in the UNRES force field. These potentials resulted in significant improvement of the simulated structures, especially in the loop regions. In this work, we introduce the physics-based counterparts of these potentials, which we derived from the all-atom energy surfaces of terminally blocked amino-acid residues by Boltzmann integration over the angles ?(1) and ?(2) for rotation about the C?···C? virtual-bond angles and over the side-chain angles ?. The energy surfaces were, in turn, calculated by using the semiempirical AM1 method of molecular quantum mechanics. Entropy contribution was evaluated with use of the harmonic approximation from Hessian matrices. One-dimensional Fourier series in the respective virtual-bond-dihedral angles were fitted to the calculated potentials, and these expressions have been implemented in the UNRES force field. Basic calibration of the UNRES force field with the new potentials was carried out with eight training proteins, by selecting the optimal weight of the new energy terms and reducing the weight of the regular torsional terms. The force field was subsequently benchmarked with a set of 22 proteins not used in the calibration. The new potentials result in a decrease of the root-mean-square deviation of the average conformation from the respective experimental structure by 0.86 Å on average; however, improvement of up to 5 Å was observed for some proteins.

Project description:The UNited RESidue (UNRES) coarse-grained model of polypeptide chains, developed in our laboratory, enables us to carry out millisecond-scale molecular-dynamics simulations of large proteins effectively. It performs well in ab initio predictions of protein structure, as demonstrated in the last Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP10). However, the resolution of the simulated structure is too coarse, especially in loop regions, which results from insufficient specificity of the model of local interactions. To improve the representation of local interactions, in this work we introduced new side-chain-backbone correlation potentials, derived from a statistical analysis of loop regions of 4585 proteins. To obtain sufficient statistics, we reduced the set of amino-acid-residue types to five groups, derived in our earlier work on structurally optimized reduced alphabets, based on a statistical analysis of the properties of amino-acid structures. The new correlation potentials are expressed as one-dimensional Fourier series in the virtual-bond-dihedral angles involving side-chain centroids. The weight of these new terms was determined by a trial-and-error method, in which Multiplexed Replica Exchange Molecular Dynamics (MREMD) simulations were run on selected test proteins. The best average root-mean-square deviations (RMSDs) of the calculated structures from the experimental structures below the folding-transition temperatures were obtained with the weight of the new side-chain-backbone correlation potentials equal to 0.57. The resulting conformational ensembles were analyzed in detail by using the Weighted Histogram Analysis Method (WHAM) and Ward's minimum-variance clustering. This analysis showed that the RMSDs from the experimental structures dropped by 0.5 Å on average, compared to simulations without the new terms, and the deviation of individual residues in the loop region of the computed structures from their counterparts in the experimental structures (after optimum superposition of the calculated and experimental structure) decreased by up to 8 Å. Consequently, the new terms improve the representation of local structure.

Project description:A major bottleneck in protein structure determination via nuclear magnetic resonance (NMR) is the lengthy and laborious process of assigning resonances and nuclear Overhauser effect (NOE) cross peaks. Recent studies have shown that accurate backbone folds can be determined using sparse NMR data, such as residual dipolar couplings (RDCs) or backbone chemical shifts. This opens a question of whether we can also determine the accurate protein side-chain conformations using sparse or unassigned NMR data. We attack this question by using unassigned nuclear Overhauser effect spectroscopy (NOESY) data, which records the through-space dipolar interactions between protons nearby in three-dimensional (3D) space. We propose a Bayesian approach with a Markov random field (MRF) model to integrate the likelihood function derived from observed experimental data, with prior information (i.e., empirical molecular mechanics energies) about the protein structures. We unify the side-chain structure prediction problem with the side-chain structure determination problem using unassigned NMR data, and apply the deterministic dead-end elimination (DEE) and A* search algorithms to provably find the global optimum solution that maximizes the posterior probability. We employ a Hausdorff-based measure to derive the likelihood of a rotamer or a pairwise rotamer interaction from unassigned NOESY data. In addition, we apply a systematic and rigorous approach to estimate the experimental noise in NMR data, which also determines the weighting factor of the data term in the scoring function derived from the Bayesian framework. We tested our approach on real NMR data of three proteins: the FF Domain 2 of human transcription elongation factor CA150 (FF2), the B1 domain of Protein G (GB1), and human ubiquitin. The promising results indicate that our algorithm can be applied in high-resolution protein structure determination. Since our approach does not require any NOE assignment, it can accelerate the NMR structure determination process.

Dataset Information

Publications

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets