Protein structure refinement of CASP target proteins using GNEIMO torsional dynamics method.
ABSTRACT: A longstanding challenge in using computational methods for protein structure prediction is the refinement of low-resolution structural models derived from comparative modeling methods into highly accurate atomistic models useful for detailed structural studies. Previously, we have developed and demonstrated the utility of the internal coordinate molecular dynamics (MD) technique, generalized Newton-Euler inverse mass operator (GNEIMO), for refinement of small proteins. Using GNEIMO, the high-frequency degrees of freedom are frozen and the protein is modeled as a collection of rigid clusters connected by torsional hinges. This physical model allows larger integration time steps and focuses the conformational search in the low frequency torsional degrees of freedom. Here, we have applied GNEIMO with temperature replica exchange to refine low-resolution protein models of 30 proteins taken from the continuous assessment of structure prediction (CASP) competition. We have shown that GNEIMO torsional MD method leads to refinement of up to 1.3 Å in the root-mean-square deviation in coordinates for 30 CASP target proteins without using any experimental data as restraints in performing the GNEIMO simulations. This is in contrast with the unconstrained all-atom Cartesian MD method performed under the same conditions, where refinement requires the use of restraints during the simulations.
Project description:The challenge in protein structure prediction using homology modeling is the lack of reliable methods to refine the low resolution homology models. Unconstrained all-atom molecular dynamics (MD) does not serve well for structure refinement due to its limited conformational search. We have developed and tested the constrained MD method, based on the generalized Newton-Euler inverse mass operator (GNEIMO) algorithm for protein structure refinement. In this method, the high-frequency degrees of freedom are replaced with hard holonomic constraints and a protein is modeled as a collection of rigid body clusters connected by flexible torsional hinges. This allows larger integration time steps and enhances the conformational search space. In this work, we have demonstrated the use of torsional GNEIMO method without using any experimental data as constraints, for protein structure refinement starting from low-resolution decoy sets derived from homology methods. In the eight proteins with three decoys for each, we observed an improvement of ~2 Å in the rmsd in coordinates to the known experimental structures of these proteins. The GNEIMO trajectories also showed enrichment in the population density of native-like conformations. In addition, we demonstrated structural refinement using a "freeze and thaw" clustering scheme with the GNEIMO framework as a viable tool for enhancing localized conformational search. We have derived a robust protocol based on the GNEIMO replica exchange method for protein structure refinement that can be readily extended to other proteins and possibly applicable for high throughput protein structure refinement.
Project description:All-atom molecular dynamics simulations are widely used to study the flexibility of protein conformations. However, enhanced sampling techniques are required for simulating protein dynamics that occur on the millisecond timescale. In this work, we show that torsional molecular dynamics simulations enhance protein conformational sampling by performing conformational search in the low-frequency torsional degrees of freedom. In this article, we use our recently developed torsional-dynamics method called Generalized Newton-Euler Inverse Mass Operator (GNEIMO) to study the conformational dynamics of four proteins. We investigate the use of the GNEIMO method in simulations of the conformationally flexible proteins fasciculin and calmodulin, as well as the less flexible crambin and bovine pancreatic trypsin inhibitor. For the latter two proteins, the GNEIMO simulations with an implicit-solvent model reproduced the average protein structural fluctuations and sample conformations similar to those from Cartesian simulations with explicit solvent. The application of GNEIMO with replica exchange to the study of fasciculin conformational dynamics produced sampling of two of this protein's experimentally established conformational substates. Conformational transition of calmodulin from the Ca(2+)-bound to the Ca(2+)-free conformation occurred readily with GNEIMO simulations. Moreover, the GNEIMO method generated an ensemble of conformations that satisfy about half of both short- and long-range interresidue distances obtained from NMR structures of holo to apo transitions in calmodulin. Although unconstrained all-atom Cartesian simulations have failed to sample transitions between the substates of fasciculin and calmodulin, GNEIMO simulations show the transitions in both systems. The relatively short simulation times required to capture these long-timescale conformational dynamics indicate that GNEIMO is a promising molecular-dynamics technique for studying domain motion in proteins.
Project description:Internal coordinate molecular dynamics (ICMD) methods provide a more natural description of a protein by using bond, angle, and torsional coordinates instead of a Cartesian coordinate representation. Freezing high-frequency bonds and angles in the ICMD model gives rise to constrained ICMD (CICMD) models. There are several theoretical aspects that need to be developed to make the CICMD method robust and widely usable. In this article, we have designed a new framework for (1) initializing velocities for nonindependent CICMD coordinates, (2) efficient computation of center of mass velocity during CICMD simulations, (3) using advanced integrators such as Runge-Kutta, Lobatto, and adaptive CVODE for CICMD simulations, and (4) cancelling out the "flying ice cube effect" that sometimes arises in Nosé-Hoover dynamics. The Generalized Newton-Euler Inverse Mass Operator (GNEIMO) method is an implementation of a CICMD method that we have developed to study protein dynamics. GNEIMO allows for a hierarchy of coarse-grained simulation models based on the ability to rigidly constrain any group of atoms. In this article, we perform tests on the Lobatto and Runge-Kutta integrators to determine optimal simulation parameters. We also implement an adaptive coarse-graining tool using the GNEIMO Python interface. This tool enables the secondary structure-guided "freezing and thawing" of degrees of freedom in the molecule on the fly during molecular dynamics simulations and is shown to fold four proteins to their native topologies. With these advancements, we envision the use of the GNEIMO method in protein structure prediction, structure refinement, and in studying domain motion.
Project description:A molecular dynamics (MD) simulation based protocol for structure refinement of template-based model predictions is described. The protocol involves the application of restraints, ensemble averaging of selected subsets, interpolation between initial and refined structures, and assessment of refinement success. It is found that sub-microsecond MD-based sampling when combined with ensemble averaging can produce moderate but consistent refinement for most systems in the CASP targets considered here.
Project description:Internal coordinates such as bond lengths, bond angles, and torsion angles (BAT) are natural coordinates for describing a bonded molecular system. However, the molecular dynamics (MD) simulation methods that are widely used for proteins, DNA, and polymers are based on Cartesian coordinates owing to the mathematical simplicity of the equations of motion. However, constraints are often needed with Cartesian MD simulations to enhance the conformational sampling. This makes the equations of motion in the Cartesian coordinates differential-algebraic, which adversely impacts the complexity and the robustness of the simulations. On the other hand, constraints can be easily placed in BAT coordinates by removing the degrees of freedom that need to be constrained. Thus, the internal coordinate MD (ICMD) offers an attractive alternative to Cartesian coordinate MD for developing multiscale MD method. The torsional MD method is a special adaptation of the ICMD method, where all the bond lengths and bond angles are kept rigid. The advantages of ICMD simulation methods are the longer time step size afforded by freezing high frequency degrees of freedom and performing a conformational search in the more important low frequency torsional degrees of freedom. However, the advancements in the ICMD simulations have been slow and stifled by long-standing mathematical bottlenecks. In this review, we summarize the recent mathematical advancements we have made based on spatial operator algebra, in developing a robust long time scale ICMD simulation toolkit useful for various applications. We also present the applications of ICMD simulations to study conformational changes in proteins and protein structure refinement. We review the advantages of the ICMD simulations over the Cartesian simulations when used with enhanced sampling methods and project the future use of ICMD simulations in protein dynamics.
Project description:Molecular dynamics modeling of complex biological systems is limited by finite simulation time. The simulations are often trapped close to local energy minima separated by high energy barriers. Here, we introduce Hamiltonian replica exchange (H-REMD) with torsional flattening in the Binding Energy Distribution Analysis Method (BEDAM), to reduce energy barriers along torsional degrees of freedom and accelerate sampling of intramolecular degrees of freedom relevant to protein-ligand binding. The method is tested on a standard benchmark (T4 Lysozyme/L99A/p-xylene complex) and on a library of HIV-1 integrase complexes derived from the SAMPL4 blind challenge. We applied the torsional flattening strategy to 26 of the 53 known binders to the HIV Integrase LEDGF site found to have a binding energy landscape funneled toward the crystal structure. We show that our approach samples the conformational space more efficiently than the original method without flattening when starting from a poorly docked pose with incorrect ligand dihedral angle conformations. In these unfavorable cases convergence to a binding pose within 2-3 Å from the crystallographic pose is obtained within a few nanoseconds of the Hamiltonian replica exchange simulation. We found that torsional flattening is insufficient in cases where trapping is due to factors other than torsional energy, such as the formation of incorrect intramolecular hydrogen bonds and stacking. Work is in progress to generalize the approach to handle these cases and thereby make it more widely applicable.
Project description:The focus of this paper is to examine whether conformational search using constrained molecular dynamics (MD) method is more enhanced and enriched toward "native-like" structures compared to all-atom MD for the protein folding as a model problem. Constrained MD methods provide an alternate MD tool for protein structure prediction and structure refinement. It is computationally expensive to perform all-atom simulations of protein folding because the processes occur on a time scale of microseconds. Compared to the all-atom MD simulation, constrained MD methods have the advantage that stable dynamics can be achieved for larger time steps and the number of degrees of freedom is an order of magnitude smaller, leading to a decrease in computational cost. We have developed a generalized constrained MD method that allows the user to "freeze and thaw" torsional degrees of freedom as fit for the problem studied. We have used this method to perform all-torsion constrained MD in implicit solvent coupled with the replica exchange method to study folding of small proteins with various secondary structural motifs such as, ?-helix (polyalanine, WALP16), ?-turn (1E0Q), and a mixed motif protein (Trp-cage). We demonstrate that constrained MD replica exchange method exhibits a wider conformational search than all-atom MD with increased enrichment of near-native structures. "Hierarchical" constrained MD simulations, where the partially formed helical regions in the initial stretch of the all-torsion folding simulation trajectory of Trp-cage were frozen, showed a better sampling of near-native structures than all-torsion constrained MD simulations. This is in agreement with the zipping-and-assembly folding model put forth by Dill and co-workers for folding proteins. The use of hierarchical "freeze and thaw" clustering schemes in constrained MD simulation can be used to sample conformations that contribute significantly to folding of proteins.
Project description:BACKGROUND/AIMS: Few studies have investigated normal response characteristics of torsional optokinetic nystagmus (tOKN). The authors have investigated the effect of stimulus velocity and central/peripheral stimulation on tOKN. METHODS: Torsional OKN was elicited using a sinusoidal grating rotating at velocities of 3 degrees /s to 1000 degrees /s in clockwise and anticlockwise directions. To investigate the effect of central stimulation, stimulus size was varied from 2.86 degrees to 50.8 degrees. An artificial scotoma placed over a 50.8 degrees stimulus was varied from 2.86 degrees to 43.2 degrees to investigate peripheral stimulation. Eight subjects participated in each experiment and torsional eye movements were recorded using video-oculography. The mean slow phase velocity (MSPV) and gain were calculated. RESULTS: The maximum gain occurred in response to 8 degrees /s stimulation. The MSPV increased up to a stimulus velocity of 200 degrees /s achieving a maximum of 3 degrees /s in both directions. MSPV was linearly correlated with the log of stimulus velocity. The smallest field size, rotating at 40 degrees /s, evoked 10% of the gain elicited by the largest display. When the most peripheral stimulus was used, the gain was maintained at 50% of the gain evoked when the full display was used. CONCLUSIONS: A wide range of stimulus velocities can elicit tOKN and peripheral field stimulation contributes significantly to its response.
Project description:F(o)F(1)-ATPase is a rotary motor protein synthesizing ATP from ADP driven by a cross-membrane proton gradient. The proton flow through the membrane-embedded F(o) generates the rotary torque that drives the rotation of the asymmetric shaft of F(1). Mechanical energy of the rotating shaft is used by the F(1) catalytic subunit to synthesize ATP. It was suggested that elastic power transmission with transient storage of energy in some compliant part of the shaft is required for the observed high turnover rate. We used atomistic simulations to study the spatial distribution and structural determinants of the F(1) torsional elasticity at the molecular level and to comprehensively characterize the elastic properties of F(1)-ATPase. Our fluctuation analysis revealed an unexpected heterogeneity of the F(1) shaft elasticity. Further, we found that the measured overall torsional moduli of the shaft arise from two distinct contributions, the intrinsic elasticity and the effective potential imposed on the shaft by the catalytic subunit. Separation of these two contributions provided a quantitative description of the coupling between the rotor and the catalytic subunit. This description enabled us to propose a minimal quantitative model of the F(1) energetics along the rotary degrees of freedom near the resting state observed in the crystal structures. As opposed to the usually employed models where the motor mechanical progression is described by a single angular variable, our multidimensional treatment incorporates the spatially inhomogeneous nature of the shaft and its interactions with the stator and offers new insight into the mechanoenzymatics of F(1)-ATPase.
Project description:Protein allostery requires dynamical structural correlations. Physical origin of which, however, remain elusive despite intensive studies during last two and half decades. Based on analysis of molecular dynamics (MD) simulation trajectories for ten proteins with different sizes and folds, we found that nonlinear backbone torsional pair (BTP) correlations, which are mainly spatially long-ranged and are dominantly executed by loop residues, exist extensively in most analyzed proteins. Examination of torsional motion for correlated BTPs suggested that such nonlinear correlations are mainly associated aharmonic torsional state transitions and in some cases strongly anisotropic local torsional motion of participating torsions, and occur on widely different and relatively longer time scales. In contrast, correlations between backbone torsions in stable ? helices and ? strands are mainly linear and spatially short-ranged, and are more likely to associate with harmonic local torsional motion. Further analysis revealed that the direct cause of nonlinear contributions are heterogeneous linear correlations. These findings implicate a general search strategy for novel allosteric modulation sites of protein activities.