Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations

Ras Conformational Switching: Simulating Nucleotide-Dependent Conformational Transitions with Accelerated Molecular Dynamics

Ras mediates signaling pathways controlling cell proliferation and development by cycling between GTP- and GDP-bound active and inactive conformational states. Understanding the complete reaction path of this conformational change and its intermediary structures is critical to understanding Ras signaling. We characterize nucleotide-dependent conformational transition using multiple-barrier-crossing accelerated molecular dynamics (aMD) simulations. These transitions, achieved for the first time for wild-type Ras, are impossible to observe with classical molecular dynamics (cMD) simulations due to the large energetic barrier between end states. Mapping the reaction path onto a conformer plot describing the distribution of the crystallographic structures enabled identification of highly populated intermediate structures. These structures have unique switch orientations (residues 25–40 and 57–75) intermediate between GTP and GDP states, or distinct loop3 (46–49), loop7 (105–110), and α5 C-terminus (159–166) conformations distal from the nucleotide-binding site. In addition, these barrier-crossing trajectories predict novel nucleotide-dependent correlated motions, including correlations of α2 (residues 66–74) with α3-loop7 (93–110), loop2 (26–37) with loop10 (145–151), and loop3 (46–49) with α5 (152–167). The interconversion between newly identified Ras conformations revealed by this study advances our mechanistic understanding of Ras function. In addition, the pattern of correlated motions provides new evidence for a dynamic linkage between the nucleotide-binding site and the membrane interacting C-terminus critical for the signaling function of Ras. Furthermore, normal mode analysis indicates that the dominant collective motion that occurs during nucleotide-dependent conformational exchange, and captured in aMD (but absent in cMD) simulations, is a low-frequency motion intrinsic to the structure

Enhanced Lipid Diffusion and Mixing in Accelerated Molecular Dynamics

Accelerated molecular dynamics (aMD) is an enhanced sampling technique that expedites conformational space sampling by reducing the barriers separating various low-energy states of a system. Here, we present the first application of the aMD method on lipid membranes. Altogether, ∼1.5 μs simulations were performed on three systems: a pure POPC bilayer, a pure DMPC bilayer, and a mixed POPC:DMPC bilayer. Overall, the aMD simulations are found to produce significant speedup in trans–gauche isomerization and lipid lateral diffusion versus those in conventional MD (cMD) simulations. Further comparison of a 70-ns aMD run and a 300-ns cMD run of the mixed POPC:DMPC bilayer shows that the two simulations yield similar lipid mixing behaviors, with aMD generating a 2–3-fold speedup compared to cMD. Our results demonstrate that the aMD method is an efficient approach for the study of bilayer structural and dynamic properties. On the basis of simulations of the three bilayer systems, we also discuss the impact of aMD parameters on various lipid properties, which can be used as a guideline for future aMD simulations of membrane systems

Coupling Constant pH Molecular Dynamics with Accelerated Molecular Dynamics

An extension of the constant pH method originally implemented by Mongan et al. (J. Comput. Chem.2004, 25, 2038−2048) is proposed in this study. This adapted version of the method couples the constant pH methodology with the enhanced sampling technique of accelerated molecular dynamics, in an attempt to overcome the sampling issues encountered with current standard constant pH molecular dynamics methods. Although good results were reported by Mongan et al. on application of the standard method to the hen egg-white lysozyme (HEWL) system, residues which possess strong interactions with neighboring groups tend to converge slowly, resulting in the reported inconsistencies for predicted pKa values, as highlighted by the authors. The application of the coupled method described in this study to the HEWL system displays improvements over the standard version of the method, with the improved sampling leading to faster convergence and producing pKa values in closer agreement to those obtained experimentally for the more slowly converging residues

Using Selectively Applied Accelerated Molecular Dynamics to Enhance Free Energy Calculations

Accelerated molecular dynamics (aMD) has been shown to enhance conformational space sampling relative to classical molecular dynamics; however, the exponential reweighting of aMD trajectories, which is necessary for the calculation of free energies relating to the classical system, is oftentimes problematic, especially for systems larger than small poly peptides. Here, we propose a method of accelerating only the degrees of freedom most pertinent to sampling, thereby reducing the total acceleration added to the system and improving the convergence of calculated ensemble averages, which we term selective aMD. Its application is highlighted in two biomolecular cases. First, the model system alanine dipeptide is simulated with classical MD, all-dihedral aMD, and selective aMD, and these results are compared to the infinite sampling limit as calculated with metadynamics. We show that both forms of aMD enhance the convergence of the underlying free energy landscape by 5-fold relative to classical MD; however, selective aMD can produce improved statistics over all-dihedral aMD due to the improved reweighting. Then we focus on the pharmaceutically relevant case of computing the free energy of the decoupling of oseltamivir in the active site of neuraminidase. Results show that selective aMD greatly reduces the cost of this alchemical free energy transformation, whereas all-dihedral aMD produces unreliable free energy estimates

E9-Im9 Colicin DNase−Immunity Protein Biomolecular Association in Water: A Multiple-Copy and Accelerated Molecular Dynamics Simulation Study

Protein−protein transient and dynamic interactions underlie all biological processes. The molecular dynamics (MD) of the E9 colicin DNase protein, its Im9 inhibitor protein, and their E9-Im9 recognition complex are investigated by combining multiple-copy (MC) MD and accelerated MD (aMD) explicit-solvent simulation approaches, after validation with crystalline-phase and solution experiments. Im9 shows higher flexibility than its E9 counterpart. Im9 displays a significant reduction of backbone flexibility and a remarkable increase in motional correlation upon E9 association. Im9 loops 23−31 and 54−64 open with respect to the E9-Im9 X-ray structure and show high conformational diversity. Upon association a large fraction (∼20 nm2) of E9 and Im9 protein surfaces become inaccessible to water. Numerous salt bridges transiently occurring throughout our six 50 ns long MC-MD simulations are not present in the X-ray model. Among these Im9 Glu31−E9 Arg96 and Im9 Glu41−Lys89 involve interface interactions. Through the use of 10 ns of Im9 aMD simulation, we reconcile the largest thermodynamic impact measured for Asp51Ala mutation with Im9 structure and dynamics. Lys57 acts as an essential molecular switch to shift Im9 surface loop towards an ideal configuration for E9 inhibition. This is achieved by switching Asp60−Lys57 and Asp62−Lys57 hydrogen bonds to Asp51−Lys57 salt bridge. E9-Im9 recognition involves shifts of conformational distributions, reorganization of intramolecular hydrogen bond patterns, and formation of new inter- and intramolecular interactions. The description of key transient biological interactions can be significantly enriched by the dynamic and atomic-level information provided by computer simulations

Molecular dynamics simulations and drug discovery

This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role

Induced topological changes in DNA complexes: influence of DNA sequences and small molecule structures

Heterocyclic diamidines are compounds with antiparasitic properties that target the minor groove of kinetoplast DNA. The mechanism of action of these compounds is unknown, but topological changes to DNA structures are likely to be involved. In this study, we have developed a polyacrylamide gel electrophoresis-based screening method to determine topological effects of heterocyclic diamidines on four minor groove target sequences: AAAAA, TTTAA, AAATT and ATATA. The AAAAA and AAATT sequences have the largest intrinsic bend, whereas the TTTAA and ATATA sequences are relatively straight. The changes caused by binding of the compounds are sequence dependent, but generally the topological effects on AAAAA and AAATT are similar as are the effects on TTTAA and ATATA. A total of 13 compounds with a variety of structural differences were evaluated for topological changes to DNA. All compounds decrease the mobility of the ATATA sequence that is consistent with decreased minor groove width and bending of the relatively straight DNA into the minor groove. Similar, but generally smaller, effects are seen with TTTAA. The intrinsically bent AAAAA and AAATT sequences, which have more narrow minor grooves, have smaller mobility changes on binding that are consistent with increased or decreased bending depending on compound structure

Predictive Power of Molecular Dynamics Receptor Structures in Virtual Screening

Molecular dynamics (MD) simulation is a well-established method for understanding protein dynamics. Conformations from unrestrained MD simulations have yet to be assessed for blind virtual screening (VS) by docking. This study presents a critical analysis of the predictive power of MD snapshots to this regard, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations. Results from such VS predictions are discussed with respect to experimentally determined structures. In all cases, MD simulations provide snapshots that improve VS predictive power over known crystal structures, possibly due to sampling more relevant receptor conformations. Additionally, MD can move conformations previously not amenable to docking into the predictive range