Molecular Dynamics with the United-Residue Model of Polypeptide Chains. II. Langevin and Berendsen-Bath Dynamics and Tests on Model α-Helical Systems

Khalili, Mey; Liwo, Adam; Jagielska, Anna; Scheraga, Harold A.

doi:10.1021/jp058007w

Cited by 151 publications

(376 citation statements)

References 61 publications

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“…In the first step, MREMD (20,31) simulations were carried out with the use of our coarse-grained UNRES force field (27)(28)(29)(30), with which a molecular dynamics method (26,45) and its multiplexed replica exchange extension (33) were implemented earlier. In the second step, the conformational ensembles obtained by coarse-grained MREMD simulations were analyzed by means of WHAM (34) to determine the heat-capacity profiles and conformational ensembles at any desired temperature, following the procedure described in our earlier work (28).…”

Section: Methodsmentioning

confidence: 99%

“…The integration time step was 4.89 fs and 20 million to 40 million steps per trajectory were run for each system. This corresponded to about 0.1-0.2 μs simulation time; however, because the fast degrees of freedom are averaged out in the coarsegrained treatment, this corresponds to 0.1-0.2 ms of real time (26). The Berendsen thermostat was used (48) with the coupling constant τ = 48:9 fs.…”

Section: Methodsmentioning

confidence: 99%

“…Enormous progress has been made in all-atom calculations, due to extensive use of world-distributed computing (20), implementation of all-atom molecular dynamics software on graphical processor units (21), and, most notably, the construction of dedicated machines (22). However, coarsegrained approaches (23)(24)(25), in which several atoms are merged into single interaction sites, are used very extensively, because they enable us to treat protein systems at time and dimensional scales, which are orders of magnitude larger (26) than those possible in all-atom computations. During the past 20 y, we have been developing (27)(28)(29)(30) a simplified model for proteins termed UNRES, in which two interaction sites per residue are defined, namely, a united side chain and a united peptide group.…”

Section: Significancementioning

confidence: 99%

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Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

Mozolewska

Krupa

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our laboratory for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilities of the conformational families determined by multiplexed replica-exchange simulations, from the 10th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP10). For target T0663, classified as a new fold, which consists of two α + β domains homologous to those of known proteins, UNRES predicted the correct symmetry of packing, in which the domains are rotated with respect to each other by 180°in the experimental structure. By contrast, models obtained by knowledge-based methods, in which each domain is modeled very accurately but not rotated, resulted in incorrect packing. Two UNRES models of this target were featured by the assessors. Correct domain packing was also predicted by UNRES for the homologous target T0644, which has a similar structure to that of T0663, except that the two domains are not rotated. Predictions for two other targets, T0668 and T0684_D2, are among the best ones by global distance test score. These results suggest that our physicsbased method has substantial predictive power. In particular, it has the ability to predict domain-domain orientations, which is a significant advance in the state of the art.protein folding | structure symmetry | multi-domain packing P rediction of protein structures from amino acid sequence still remains an unsolved problem of computational biology. Although, since the famous experiments by Anfinsen (1), it is known that a protein adopts the structure which is the (kinetically reachable) global minimum of the free energy of a system, it is not straightforward to implement this physical principle in practice because of the inaccuracy of existing force fields and because of the enormous difficulty to search the conformational space of the system. Therefore, the most effective methods for protein-structure prediction nowadays are knowledge-based approaches, in which database information is incorporated explicitly into the procedure (2). These methods can be divided into three categories, namely, comparative (homology) modeling (3-5), in which the target sequence is compared with the sequences for which experimental structures are known and those structures are usually selected as candidate models for which the greatest similarity is observed; threading (6-8), in which the target sequence is superposed on structures from a database, and those which give the highest score (lowest pseudoenergy) are selected as candidate predictions; and, finally, the fragment-assembly or minithreading method developed by David Baker and colleagues (9, 10), in which the predicted structure is assembled from nine-residue fragments extracted from a protein-structure database, and knowledge-and physicsbased filters are applied at each asse...

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Significancementioning

confidence: 99%

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Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

Mozolewska

Krupa

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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“…The coupling parameter was assumed to be τ = 1 mtu (where 1 mtu=48.9 fs) as in our earlier work. 39 The Velocity Verlet (VV) algorithm 73 with the variable time step extension developed in our earlier work 38 was used, and the basic time step in integrating the equations of motion was 5 fs. For 1E0L, MREMD simulations were run at 16 temperatures with 5 trajectories/ temperature and, for 1GAB, 1E0G, and the proteins used to test the force fields, MREMD simulations were run at 20 temperatures with 16 trajectories/temperature.…”

Section: Details Of Calculationsmentioning

confidence: 99%

Modification and Optimization of the United-Residue (UNRES) Potential Energy Function for Canonical Simulations. I. Temperature Dependence of the Effective Energy Function and Tests of the Optimization Method with Single Training Proteins

et al. 2006

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We report the modification and parameterization of the united-residue (UNRES) force field for energy-based protein-structure prediction and protein-folding simulations. We tested the approach on three training proteins separately: 1E0L (β), 1GAB (α), and 1E0G (α + β). Heretofore, the UNRES force field had been designed and parameterized to locate native-like structures of proteins as global minima of their effective potential-energy surfaces, which largely neglected the conformational entropy because decoys composed of only lowest-energy conformations were used to optimize the force field. Recently, we developed a mesoscopic dynamics procedure for UNRES, and applied it with success to simulate protein folding pathways. How ever, the force field turned out to be largely biased towards α-helical structures in canonical simulations because the conformational entropy had been neglected in the parameterization. We applied the hierarchical optimization method developed in our earlier work to optimize the force field, in which the conformational space of a training protein is divided into levels each corresponding to a certain degree of native-likeness. The levels are ordered according to increasing native-likeness; level 0 corresponds to structures with no native-like elements and the highest level corresponds to the fully native-like structures. The aim of optimization is to achieve the order of the free energies of levels, decreasing as their native-likeness increases. The procedure is iterative, and decoys of the training protein(s) generated with the energy-function parameters of the preceding iteration are used to optimize the force field in a current iteration. We applied the multiplexing replica exchange molecular dynamics (MREMD) method, recently implemented in UNRES, to generate decoys; with this modification, conformational entropy is taken into account. Moreover, we optimized the free-energy gaps between levels at temperatures corresponding to a predominance of folded or unfolded structures, as well as to structures at the putative folding-transition temperature, changing the sign of the gaps at the transition temperature. This enabled us to obtain force fields characterized by a single peak in the heat capacity at the transition temperature. Furthermore, we introduced temperature dependence to the UNRES force field; this is consistent with the fact that it is a free-energy and not a potential-energy function.

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“…Specifically the UNRES MD equation of motion (eq. 32 of reference 16 ) is modified as (17) where U [being U(x)] is the UNRES potential energy (U MD of eq. 2), q(t) are the generalized coordinates at time t, and G is the mass matrix (eq.…”

Section: Multicanonical Algorithm (Muca)mentioning

confidence: 99%

Replica Exchange and Multicanonical Algorithms with the Coarse-Grained United-Residue (UNRES) Force Field

Nanias

Czaplewski

Scheraga

2006

J. Chem. Theory Comput.

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Three algorithms, namely a Replica Exchange method (REM), a Replica Exchange Multicanonical method (REMUCA), and Replica Exchange Multicanonical with Replica Exchange (REMUCAREM), were implemented with the coarse-grained united-residue force field (UNRES) in both Monte Carlo and Molecular Dynamics versions. The MD algorithms use the constanttemperature Berendsen thermostat, with the velocity Verlet algorithm and variable time step. The algorithms were applied to one peptide (20 residues of Alanine with free ends; ala 20 ) and two small proteins, namely an α-helical protein of 46 residues (the B-domain of the staphylococal protein A; 1BDD), and an α+β-protein of 48 residues (the E. Coli Mltd Lysm Domain; 1E0G). Calculated thermodynamic averages, such as canonical average energy and heat capacity, are in good agreement among all simulations for poly-L-alanine, showing that the algorithms were implemented correctly, and that all three algorithms are equally effective for small systems. For protein A, all algorithms performed reasonably well, although some variability in the calculated results was observed whereas, for a more complicated α+β-protein (1E0G), only Replica Exchange was capable of producing reliable statistics for calculating thermodynamic quantities. Finally, from the Replica Exchange molecular dynamics results, we calculated free energy maps as functions of RMSD and radius of gyration for different temperatures. The free energy calculations show correct folding behavior for poly-L-alanine and protein A while, for 1E0G, the native structure had the lowest free energy only at very low temperatures. Hence, the entropy contribution for 1E0G is larger than that for protein A at the same temperature. A larger contribution from entropy means that there are more accessible conformations at a given temperature, making it more difficult to obtain an efficient coverage of conformational space to obtain reliable thermodynamic properties. At the same temperature, ala 20 has the smallest entropy contribution, followed by protein A, and then by 1E0G. IntroductionEfficient sampling algorithms have been an essential component of methods for studying protein structure and dynamics in structural biology and theoretical chemistry. A variety of sampling algorithms have been used in our laboratory and, depending on whether the goal is global optimization or folding simulations, they can be be categorized in the following way.For successful prediction of the three-dimensional structure of a protein (based solely on its amino acid sequence), several classes of algorithms have been used. The first class includes modifications of the Metropolis Monte Carlo procedure, 1,2 such as Monte Carlo-withMinimization (MCM), 3,4 electrostaticallydriven Monte Carlo (EDMC), 5,6 Conformational Corresponding author: Professor H.A. Scheraga, Tel: (607) 255-4034; fax: (607) 254-4700; e-mail: has5@cornell.edu. NIH Public Access NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptFamily Monte Carlo (CFMC), 7 and ...

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Molecular Dynamics with the United-Residue Model of Polypeptide Chains. II. Langevin and Berendsen-Bath Dynamics and Tests on Model α-Helical Systems

Cited by 151 publications

References 61 publications

Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

Modification and Optimization of the United-Residue (UNRES) Potential Energy Function for Canonical Simulations. I. Temperature Dependence of the Effective Energy Function and Tests of the Optimization Method with Single Training Proteins

Replica Exchange and Multicanonical Algorithms with the Coarse-Grained United-Residue (UNRES) Force Field

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