<p>Protein conformational transitions are fundamental to the functions of many proteins, and computational methods are valuable for elucidating the transitions that are not readily accessible by experimental techniques. Here we developed accelerated sampling methods to calculate optimized all-atom protein conformational transition paths. Adaptively biased path optimization (ABPO) is a computational simulation method to optimize the conformational transition path between two states. We first examined the transition paths of three systems with relatively simple transitions. The ways to define reduced variables were explored and transition paths were built at convergence of the optimizations. We constructed the all-atom conformational transition path between the active and the inactive states of the Src kinase domain. The C helix rotation was identified as the main free energy barrier in the all‑atom system, and the intermediate conformations and key interactions along the transition path were analyzed. This is the first demonstration of the robustness of a computational method for calculating protein conformational transitions without restraints to a specified path. We also evaluated protein‑peptide interactions using both molecular dynamics simulations and peptide docking. Long unbiased simulations were used to evaluate Src‑SSP interactions and complex stability in both implicit and explicit solvent. Molecular docking was used to build possible protein‑peptide interaction models, using both Src regulatory domain SH2 and the kinase domain. Possible Src‑SSP complexes were built as the first Src‑substrate complex structure models.</p>

We show that a single-copy tempering method is useful in protein-folding simulations of large scale and high accuracy (explicit solvent, atomic representation, and physics-based potential). The method uses a runtime estimate of the average potential energy from an integral identity to guide a random walk in the continuous temperature space. It was used for folding three mini-proteins, trpzip2 (PDB ID: 1LE1), trp-cage (1L2Y), and villin headpiece (1VII) within atomic accuracy. Further, using a modification of the method with a dihedral bias potential added on the roof temperature, we were able to fold four larger helical proteins: α3D (2A3D), α3W (1LQ7), Fap1-NRα (2KUB) and S-836 (2JUA). We also discuss how to optimally use simulation data through an integral identity. With the help of a general mean force formula, the identity makes better use of data collected in a molecular dynamics simulation and is more accurate and precise than the common histogram approach.

Protein mechanical responses play a critical role in a wide variety of biological phenomena, impacting events as diverse as muscle contraction and stem cell differentiation. Recent advances in both experimental and computational techniques have provided the opportunity to explore protein constitutive properties at the molecular level. However, despite these advances many questions remain about how proteins respond to applied mechanical forces, particularly as a function of load magnitude. In order to address these questions, relatively simple helical structures were computationally tested to determine the mechanisms and kinetics of unfolding at a range of physiologically relevant load magnitudes. Atomically detailed constant force molecular dynamics simulations combined with the Milestoning kinetic analysis framework revealed that the mean first passage time (MFPT) of the initiation of unfolding of long (~16nm) isolated helical domains was a non-monotonic function of the magnitude of applied tensile load. The unfolding kinetics followed a profile ranging from 2.5ns (0pN) to a peak of 3.75ns (20pN) with a decreasing MFPT beyond 40pN reflected by an MFPT of 1ns for 100pN. The application of the Milestoning framework with a coarse-grained network analysis approach revealed that intermediate loads (15pN-25pN) retarded unfolding by opening additional, slower unfolding pathways through non-native [pi]-helical conformations. Analysis of coiled-coil helical pairs revealed that the presence of the second neighboring helix delayed unfolding initiation by a factor of 20, with calculated MFPTs ranging from 55ns (0pN) to 85ns (25pN per helix) to 20ns (100pN per helix). The stability of the coiled-coil domains relative to the isolated helix was shown to reflect a decreased propensity to break flexibility restraining intra-helix hydrogen bonds, thereby delaying [psi] backbone dihedral angle rotation and unfolding. These results show for the first time a statistically determined profile of unfolding kinetics for an atomically detailed protein that is non-monotonic with respect to load caused by a change in the unfolding mechanism with load. Together, the methods introduced for analyzing the mechanical response of proteins as well as the timescales determined for the initiation of unfolding provide a framework for the determination of the constitutive properties of proteins and non-biological polymers with more complicated geometries. / text

This thesis describes the development a new swarm-enhanced sampling methodology and its application to the exploration of biologically relevant molecules. First, the development of a new multi-dimensional swarm-enhanced sampling molecular dynamics (msesMD) approach is detailed. Relative to the original swarm-enhanced sampling molecular dynamics (sesMD) methodology, the msesMD method demonstrates improved parameter transferability, resulting in more extensive sampling when scaling to larger systems such as alanine heptapeptide. The implementation and optimisation of the swarm-enhanced sampling algorithms in the AMBER software suite are also described. Through the use of the newer pmemd molecular dynamics (MD) engine and asynchronous MPI routines, speedups of up to three times the original sesMD implementation were achieved. The msesMD method is then applied to the investigation of carbohydrates, first looking at rare conformational changes in Lewis oligosaccharides. Validating against multi-microsecond unbiased MD trajectories and other enhanced sampling methods, the msesMD simulations identified rare conformational changes leading to the adoption of non-canonical unstacked core trisaccharide structures. Next, the use of msesMD as a tool to probe pyranose ring pucker events is explored. Evaluating against four benchmark monosaccharide systems, msesMD simulations accurately recover puckering details not easily obtained via multi-microsecond unbiased MD. This was followed by an exploration of the impact of ring substituents on conformation in glycosaminoglycan monosaccharides: through msesMD simulations, the influence of specific sulfation patterns were explored, finding that in some cases, such as 4-O-sulfation in N-acetyl-galactosamine, large changes in the relative stability of ring conformers can arise. Finally, the msesMD method was coupled with a thermodynamic integration scheme and used to evaluate solvation free energies for small molecule systems. Comparing against independent trajectory TI simulations, it was found that although the correct solvation free energies were obtained, the msesMD based method did not offer an advantage over unbiased MD for these small molecule systems. However, interesting discrepancies in free energy estimates arising from the use of hydrogen mass repartitioning were found.

Biophysical simulation can be an excellent complement to experimental techniques, but there are unresolved practical constraints to simulation. While computers have continued to improve, the scale of systems we wish to study has continued to increase. This has driven the use of approximate energy functions (force fields), compensating for relatively short simulations via careful structure preparation and accelerated sampling techniques. To address structure preparation, we developed the many-body dead end elimination (MB-DEE) optimizer. We first proved the MB-DEE algorithm on a set of PCNA crystal structures, and accelerated it on GPUs to optimize 472 homology models of proteins implicated in inherited deafness. Advanced physics has been clearly demonstrated to help optimize structures, and with GPU acceleration, this becomes a possibility for large numbers of structures. We also show the novel “simultaneous bookending” algorithm, which is a new approach to indirect free energy (IFE) methods. These first perform simulations under a cheaper “reference” potential, then correct the thermodynamics to a more sophisticated “target” potential, combining the speed of the reference potential with the accuracy of the target potential. Simultaneous bookending is shown as a valid IFE approach, and methods to realize speedups vs. the direct path are discussed. Finally, we are developing the Monte Carlo Orthogonal Space Random Walk (MC-OSRW) algorithm for high-performance alchemical free energy simulations, bypassing some of the difficulty in OSRW methods. This work helps prevent inaccuracies caused by simpler electrostatic models by making advanced polarizable force fields more accessible for routine simulation.

The correct function of cardiac sarcomeric proteins allow for people to maintain quality of life. However, mutations of the cardiac sarcomeric proteins can result in remodeling of the heart which typically results in death. I present a full atomistic cardiac thin filament model that I have developed and three studies that I conducted while at the University of Arizona, while pursuing my doctoral degree in chemistry The goal was to develop the model to be able to study the effects of the mutations on the thin filament proteins. First, I present the long process of developing the model that is still evolving as new information is available. Second, I present the study of two mutants, the troponin T R92L mutant and the tropomyosin D230N mutant. Molecular dynamics was used to simulate the wild–type and mutant versions of the model which resulted in a visualization of the change of interaction between the tropomyosin and troponin, specifically at the overlap region. Third, I present the study of calcium release which is the "gatekeeper" to cardiac contraction. Steered molecular dynamics was utilized to find a previously unseen molecular mechanism that alters the rate of calcium release depending on the mutant. Fourth, I present the study of the mechanism of the tropomyosin transition across the actin filament, in which a longitudinal transition is favored. The studies helped to provide an atomistic level understanding of the cardiac thin filament as well as the methodology to which the mutations disrupt the natural functions of the sarcomeric proteins. The new results of the research can provide new insight into how the effects of the disease causing mutations can be mitigated, potentially extending the life of people with the conditions.

The replica exchange method (REM) has been widely used in the computer simulation of complex systems, such as proteins, glasses, and atomic clusters, where conventional methods based on sampling the canonical ensemble struggle to attain ergodicity over a rugged energy landscape characterized by multiple minima separated by high energy barriers. While the standard temperature REM (tREM) has proven to be highly effective in the equilibrium sampling of stable single phase states, tREM is seriously challenged in the vicinity of a first-order phase transition. The generalized Replica Exchange Method (gREM) was developed to address these outstanding computational problems and provide a method for simulating strong phase transitions in condensed matter systems. The central idea behind gREM is to incorporate the merit of generalized ensemble sampling into the replica exchange paradigm. The key ingredients of gREM are parameterized effective sampling weights, which smoothly join ordered and disordered phases with a succession of unimodal energy distributions that transform unstable or metastable energy states of the canonical ensemble into stable states that can be fully characterized. The inverse mapping between the sampling weights and the effective temperature provides a sure way to design the effective sampling weights and achieve ergodic sampling. Various applications of gREM are presented, including studies of the solid-liquid phase change of an adapted Dzugutov model of glass formation, the mechanism of spinodal decomposition in the vapor-liquid transition of a simple fluid, and the apparent crossover from a first-order to continuous transition with increasing density in the freezing of a nanofilm of water confined between featureless and atomistic surfaces. Extensive gREM simulations combined with the Statistical Temperature Weighted Histogram Analysis Method (ST-WHAM) demonstrate the effectiveness of the approach and provide comprehensive characterization of thermodynamic and structural properties intrinsic to phase transitions in these diverse systems.

abstract: In a typical living cell, millions to billions of proteins—nanomachines that fluctuate and cycle among many conformational states—convert available free energy into mechanochemical work. A fundamental goal of biophysics is to ascertain how 3D protein structures encode specific functions, such as catalyzing chemical reactions or transporting nutrients into a cell. Protein dynamics span femtosecond timescales (i.e., covalent bond oscillations) to large conformational transition timescales in, and beyond, the millisecond regime (e.g., glucose transport across a phospholipid bilayer). Actual transition events are fast but rare, occurring orders of magnitude faster than typical metastable equilibrium waiting times. Equilibrium molecular dynamics (EqMD) can capture atomistic detail and solute-solvent interactions, but even microseconds of sampling attainable nowadays still falls orders of magnitude short of transition timescales, especially for large systems, rendering observations of such "rare events" difficult or effectively impossible. Advanced path-sampling methods exploit reduced physical models or biasing to produce plausible transitions while balancing accuracy and efficiency, but quantifying their accuracy relative to other numerical and experimental data has been challenging. Indeed, new horizons in elucidating protein function necessitate that present methodologies be revised to more seamlessly and quantitatively integrate a spectrum of methods, both numerical and experimental. In this dissertation, experimental and computational methods are put into perspective using the enzyme adenylate kinase (AdK) as an illustrative example. We introduce Path Similarity Analysis (PSA)—an integrative computational framework developed to quantify transition path similarity. PSA not only reliably distinguished AdK transitions by the originating method, but also traced pathway differences between two methods back to charge-charge interactions (neglected by the stereochemical model, but not the all-atom force field) in several conserved salt bridges. Cryo-electron microscopy maps of the transporter Bor1p are directly incorporated into EqMD simulations using MD flexible fitting to produce viable structural models and infer a plausible transport mechanism. Conforming to the theme of integration, a short compendium of an exploratory project—developing a hybrid atomistic-continuum method—is presented, including initial results and a novel fluctuating hydrodynamics model and corresponding numerical code. / Dissertation/Thesis / Doctoral Dissertation Physics 2017

No description available.

Simulações moleculares podem fornecer informações e detalhes mecanísticos que são difíceis de obter de experimentos. No entanto, fenômenos bioquímicos como formação de complexos proteína-ligante e desenovelamento de proteína são lentos e difíceis de amostrar na escala de tempo geralmente atingida por simulações de dinâmica molecular (MD) convencionais. Esses fenômenos moleculares foram estudados aqui pela combinação de simulações de MD com diversos métodos e aproximações para aumentar a amostragem configuracional: método de energia de interação linear (LIE), a aproximação de ensemble ponderado (WE) e dinâmica molecular dirigida (SMD). Uma equação foi parametrizada para prever afinidades entre pequenas moléculas e proteínas baseada na aproximação LIE, que foca a amostragem computacional nos estados complexado e não-complexado do ligante. A flexibilidade proteica foi introduzida usando ensembles de configurações obtidos de simulações de MD. Diferentes esquemas de média foram testados para obter afinidades totais de complexos proteína-ligante, revelando que muitas configurações de complexo contribuem para as afinidades de proteínas flexíveis, enquanto as afinidades de proteínas rígidas são dominadas por uma configuração de complexo. O mutante L99A da lisozima T4 (T4L) é provavelmente a proteína mais frequentemente usada para estudar complexação de ligantes. Estruturas cristalográficas mostram que a cavidade de ligação artificial criada pela mutação é pouco acessível, portanto movimentos proteicos ou uma respiração conformacional são necessários para permitir a entrada e saída de ligantes. Simulações de MD foram combinadas aqui com a aproximação de WE para aumentar a amostragem de eventos infrequentes de saída do benzeno de T4L. Quatro possíveis caminhos foram encontrados e movimentações de alfa-hélices e cadeias laterais envolvidas na saída do ligante foram caracterizadas. Os quatro caminhos correspondem a túneis da proteína previamente observados em simulações de MD longas de T4L apo, sugerindo que a heterogeneidade de caminhos ao longo de túneis intrínsecos é explorada por pequenas moléculas para sair de cavidades de ligação enterradas em proteínas. Experimentos de microscopia de força atômica revelaram informações detalhadas do desenovelamento forçado e da estabilidade mecânica da rubredoxina, uma proteína ferro-enxofre simples. O desenovelamento completo da rubredoxina envolve a ruptura de ligações covalentes. Portanto, o processo de desenovelamento foi simulado aqui por simulações de SMD acopladas a uma descrição clássica da dissociação de ligações. A amostragem de eventos de desenovelamento forçado foi aumentada pelo uso de velocidades rápidas de esticamento. Os resultados foram analisados usando um modelo teórico válido para regimes de desenovelamento forçado lentos e rápidos. As simulações revelaram que mudanças no ponto de aplicação de força ao longo da sequência da rubredoxina levam a diferentes mecanismos de desenovelamento, caracterizados por variáveis graus de rompimento de ligações de hidrogênio e estrutura secundária da proteína. / Molecular simulations may provide information and mechanistic insights that are difficult to obtain from experiments. However, biochemical phenomena such as ligand-protein binding and protein unfolding are slow and hard to sample on the timescales usually reached by conventional molecular dynamics (MD) simulations. These molecular phenomena were studied here by combining MD simulations with several methods or approximations to enhance configurational sampling: linear interaction energy (LIE) method, weighted ensemble (WE) approach and steered molecular dynamics (SMD). An equation was parametrized to predict affinities between small molecules and proteins based on the LIE approximation, which focus computational sampling in ligand bound and unbound states. Protein flexibility was introduced by using ensembles of configurations obtained from MD simulations. Different averaging schemes were tested to obtain overall affinities for ligand-protein complexes, revealing that many bound configurations contribute to affinities for flexible proteins, while affinities for rigid proteins are dominated by one bound configuration. T4 lysozyme (T4L) L99A mutant is probably the protein most often used to study ligand binding. Crystal structures show the artificial binding cavity created by the mutation has low accessibility, so protein movements or conformational breathing are necessary to allow the entry and egress of ligands. MD simulations were combined here with the WE approach to enhance sampling of infrequent benzene unbinding events from T4L. Four possible pathways were found and motions on alpha-helices and side chains involved in ligand egress were characterized. The four pathways correspond to protein tunnels previously observed in long MD simulations of apo T4L, suggesting that pathway heterogeneity along intrinsic tunnels is explored by small molecules to egress from binding cavities buried in proteins. Previous atomic force microscopy experiments revealed detailed information on the forced unfolding and mechanical stability of rubredoxin, a simple iron-sulfur protein. Complete unfolding of rubredoxin involves rupture of covalent bonds. Thus, the unfolding process was simulated here by SMD simulations coupled to a classical description of bond dissociation. Sampling of forced unfolding events was increased by using fast pulling velocities. Results were analyzed using a theoretical model valid for both slow and fast forced unfolding regimes. Simulations revealed that changing the points of force application along the rubredoxin sequence leads to different unfolding mechanisms, characterized by variable degrees of disruption of hydrogen bonds and secondary protein structure.