Browsing by Author "Onufriev, Alexey V."
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- Accelerating Electrostatic Surface Potential Calculation with Multiscale Approximation on Graphics Processing UnitsAnandakrishnan, Ramu; Scogland, Thomas R. W.; Fenley, Andrew T.; Gordon, John; Feng, Wu-chun; Onufriev, Alexey V. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2009)Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. This paper demonstrates how one can take advantage of graphic processing units (GPUs) available in today’s typical desktop computer, together with a multiscale approximation method, to significantly speedup such computations. Specifically, the electrostatic potential computation, using an analytical linearized Poisson Boltzmann (ALPB) method, is implemented on an ATI Radeon 4870 GPU in combination with the hierarchical charge partitioning (HCP) multiscale approximation. This implementation delivers a combined 1800-fold speedup for a 476,040 atom viral capsid.
- Advanced Time Integration Methods with Applications to Simulation, Inverse Problems, and Uncertainty QuantificationNarayanamurthi, Mahesh (Virginia Tech, 2020-01-29)Simulation and optimization of complex physical systems are an integral part of modern science and engineering. The systems of interest in many fields have a multiphysics nature, with complex interactions between physical, chemical and in some cases even biological processes. This dissertation seeks to advance forward and adjoint numerical time integration methodologies for the simulation and optimization of semi-discretized multiphysics partial differential equations (PDEs), and to estimate and control numerical errors via a goal-oriented a posteriori error framework. We extend exponential propagation iterative methods of Runge-Kutta type (EPIRK) by [Tokman, JCP 2011], to build EPIRK-W and EPIRK-K time integration methods that admit approximate Jacobians in the matrix-exponential like operations. EPIRK-W methods extend the W-method theory by [Steihaug and Wofbrandt, Math. Comp. 1979] to preserve their order of accuracy under arbitrary Jacobian approximations. EPIRK-K methods extend the theory of K-methods by [Tranquilli and Sandu, JCP 2014] to EPIRK and use a Krylov-subspace based approximation of Jacobians to gain computational efficiency. New families of partitioned exponential methods for multiphysics problems are developed using the classical order condition theory via particular variants of T-trees and corresponding B-series. The new partitioned methods are found to perform better than traditional unpartitioned exponential methods for some problems in mild-medium stiffness regimes. Subsequently, partitioned stiff exponential Runge-Kutta (PEXPRK) methods -- that extend stiffly accurate exponential Runge-Kutta methods from [Hochbruck and Ostermann, SINUM 2005] to a multiphysics context -- are constructed and analyzed. PEXPRK methods show full convergence under various splittings of a diffusion-reaction system. We address the problem of estimation of numerical errors in a multiphysics discretization by developing a goal-oriented a posteriori error framework. Discrete adjoints of GARK methods are derived from their forward formulation [Sandu and Guenther, SINUM 2015]. Based on these, we build a posteriori estimators for both spatial and temporal discretization errors. We validate the estimators on a number of reaction-diffusion systems and use it to simultaneously refine spatial and temporal grids.
- Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation AlgorithmWang, Shuo (Virginia Tech, 2016-10-06)Stochastic effects in cellular systems are usually modeled and simulated with Gillespie's stochastic simulation algorithm (SSA), which follows the same theoretical derivation as the chemical master equation (CME), but the low efficiency of SSA limits its application to large chemical networks. To improve efficiency of stochastic simulations, Haseltine and Rawlings proposed a hybrid of ODE and SSA algorithm, which combines ordinary differential equations (ODEs) for traditional deterministic models and SSA for stochastic models. In this dissertation, accuracy analysis, efficient implementation strategies, and application of of Haseltine and Rawlings's hybrid method (HR) to a budding yeast cell cycle model are discussed. Accuracy of the hybrid method HR is studied based on a linear chain reaction system, motivated from the modeling practice used for the budding yeast cell cycle control mechanism. Mathematical analysis and numerical results both show that the hybrid method HR is accurate if either numbers of molecules of reactants in fast reactions are above certain thresholds, or rate constants of fast reactions are much larger than rate constants of slow reactions. Our analysis also shows that the hybrid method HR allows for a much greater region in system parameter space than those for the slow scale SSA (ssSSA) and the stochastic quasi steady state assumption (SQSSA) method. Implementation of the hybrid method HR requires a stiff ODE solver for numerical integration and an efficient event-handling strategy for slow reaction firings. In this dissertation, an event-handling strategy is developed based on inverse interpolation. Performances of five wildly used stiff ODE solvers are measured in three numerical experiments. Furthermore, inspired by the strategy of the hybrid method HR, a hybrid of ODE and SSA stochastic models for the budding yeast cell cycle is developed, based on a deterministic model in the literature. Simulation results of this hybrid model match very well with biological experimental data, and this model is the first to do so with these recently available experimental data. This study demonstrates that the hybrid method HR has great potential for stochastic modeling and simulation of large biochemical networks.
- Applying the Newmark Method to the Discontinuous Deformation AnalysisPeng, Bo (Virginia Tech, 2014-12-08)Discontinuous deformation analysis (DDA) is a newly developed simulation method for discontinuous systems. It was designed to simulate systems with arbitrary shaped blocks with high efficiency while providing accurate solutions for energy dissipation. But DDA usually exhibits damping effects that are inconsistent with theoretical solutions. The deep reason for these artificial damping effects has been an open question, and it is hypothesized that these damping effects could result from the time integration scheme. In this thesis two time integration methods are investigated: the forward Euler method and the Newmark method. The work begins by combining the Newmark method and the DDA. An integrated Newmark method is also developed, where velocity and acceleration do not need to be updated. In simulations, two of the most widely used models are adopted to test the forward Euler method and the Newmark method. The first one is a sliding model, in which both the forward Euler method and the Newmark method give accurate solutions compared with analytical results. The second model is an impacting model, in which the Newmark method has much better accuracy than the forward Euler method, and there are minimal damping effects.
- Architecture-Aware Mapping and Optimization on Heterogeneous Computing SystemsDaga, Mayank (Virginia Tech, 2011-04-27)The emergence of scientific applications embedded with multiple modes of parallelism has made heterogeneous computing systems indispensable in high performance computing. The popularity of such systems is evident from the fact that three out of the top five fastest supercomputers in the world employ heterogeneous computing, i.e., they use dissimilar computational units. A closer look at the performance of these supercomputers reveals that they achieve only around 50% of their theoretical peak performance. This suggests that applications that were tuned for erstwhile homogeneous computing may not be efficient for today's heterogeneous computing and hence, novel optimization strategies are required to be exercised. However, optimizing an application for heterogeneous computing systems is extremely challenging, primarily due to the architectural differences in computational units in such systems. This thesis intends to act as a cookbook for optimizing applications on heterogeneous computing systems that employ graphics processing units (GPUs) as the preferred mode of accelerators. We discuss optimization strategies for multicore CPUs as well as for the two popular GPU platforms, i.e., GPUs from AMD and NVIDIA. Optimization strategies for NVIDIA GPUs have been well studied but when applied on AMD GPUs, they fail to measurably improve performance because of the differences in underlying architecture. To the best of our knowledge, this research is the first to propose optimization strategies for AMD GPUs. Even on NVIDIA GPUs, there exists a lesser known but an extremely severe performance pitfall called partition camping, which can affect application performance by up to seven-fold. To facilitate the detection of this phenomenon, we have developed a performance prediction model that analyzes and characterizes the effect of partition camping in GPU applications. We have used a large-scale, molecular modeling application to validate and verify all the optimization strategies. Our results illustrate that if appropriately optimized, AMD and NVIDIA GPUs can provide 371-fold and 328-fold improvement, respectively, over a hand-tuned, SSE-optimized serial implementation.
- Binding of regulatory proteins to nucleosomes is modulated by dynamic histone tailsPeng, Yunhui; Li, Shuxiang; Onufriev, Alexey V.; Landsman, David; Panchenko, Anna R. (2021-09-06)Little is known about the roles of histone tails in modulating nucleosomal DNA accessibility and its recognition by other macromolecules. Here we generate extensive atomic level conformational ensembles of histone tails in the context of the full nucleosome, totaling 65 microseconds of molecular dynamics simulations. We observe rapid conformational transitions between tail bound and unbound states, and characterize kinetic and thermodynamic properties of histone tail-DNA interactions. Different histone types exhibit distinct binding modes to specific DNA regions. Using a comprehensive set of experimental nucleosome complexes, we find that the majority of them target mutually exclusive regions with histone tails on nucleosomal/linker DNA around the super-helical locations +/- 1, +/- 2, and +/- 7, and histone tails H3 and H4 contribute most to this process. These findings are explained within competitive binding and tail displacement models. Finally, we demonstrate the crosstalk between different histone tail post-translational modifications and mutations; those which change charge, suppress tail-DNA interactions and enhance histone tail dynamics and DNA accessibility. The intrinsic disorder of histone tails poses challenges in their characterization. Here the authors apply extensive molecular dynamics simulations of the full nucleosome to show reversible binding to DNA with specific binding modes of different types of histone tails, where charge-altering modifications suppress tail-DNA interactions and may boost interactions between nucleosomes and nucleosome-binding proteins.
- Biologically relevant small variations of intra-cellular pH can have significant effect on stability of protein-DNA complexes, including the nucleosomeOnufriev, Alexey V. (Frontiers, 2023-04)Stability of a protein-ligand complex may be sensitive to pH of its environment. Here we explore, computationally, stability of a set of protein-nucleic acid complexes using fundamental thermodynamic linkage relationship. The nucleosome, as well as an essentially random selection of 20 protein complexes with DNA or RNA, are included in the analysis. An increase in intracellular/intra-nuclear pH destabilizes most complexes, including the nucleosome. We propose to quantify the effect by Delta Delta G(0.3)- the change in the binding free energy due to pH increase of 0.3 units, corresponding to doubling of the H+ activity; variations of pH of this amplitude can occur in living cells, including in the course of the cell cycle, and in cancer cells relative to normal ones. We suggest, based on relevant experimental findings, a threshold of biological significance of 12 k(B)T (similar to 0.3 kcal/mol) for changes of stability of chromatin-related protein-DNA complexes: a change in the binding affinity above the threshold may have biological consequences. We find that for 70% of the examined complexes,Delta Delta G(0.3) > 12 k(B)T (for 10%,Delta Delta G(0.3) is between 3 and 4 k(B)T). Thus, small but relevant variations of intra-nuclear pH of 0.3 may have biological consequences for many protein-nucleic acid complexes. The binding affinity between the histone octamer and its DNA, which directly affects the DNA accessibility in the nucleosome, is predicted to be highly sensitive to intranuclear pH. A variation of 0.3 units results in Delta Delta G(0.3) similar to 10k(B)T (similar to 6 kcal/mol); for spontaneous unwrapping of 20 bp long entry/exit fragments of the nucleosomal DNA,Delta Delta G(0.3) = 2.2k(B)T; partial disassembly of the nucleosome into the tetrasome is characterized by Delta Delta G(0.3) = 5.2k(B)T. The predicted pH -induced modulations of the nucleosome stability are significant enough to suggest that they may have consequences relevant to the biological function of the nucleosome. Accessibility of the nucleosomal DNA is predicted to positively correlate with pH variations during the cell cycle; an increase in intra-cellular pH seen in cancer cells is predicted to lead to a more accessible nucleosomal DNA; a drop in pH associated with apoptosis is predicted to make nucleosomal DNA less accessible. We speculate that processes that depend on accessibility to the DNA in the nucleosomes, such as transcription or DNA replication, might become upregulated due to relatively small, but nevertheless realistic increases of intranuclear pH.
- Biologically-Interpretable Disease Classification Based on Gene Expression DataGrothaus, Gregory (Virginia Tech, 2005-05-13)Classification of tissues and diseases based on gene expression data is a powerful application of DNA microarrays. Many popular classifiers like support vector machines, nearest-neighbour methods, and boosting have been applied successfully to this problem. However, it is difficult to determine from these classifiers which genes are responsible for the distinctions between the diseases. We propose a novel framework for classification of gene expression data based on notion of condition-specific clusters of co-expressed genes called xMotifs. Our xMotif-based classifier is biologically interpretable: we show how we can detect relationships between xMotifs and gene functional annotations. Our classifier achieves high-accuracy on leave-one-out cross-validation on both two-class and multi-class data. Our technique has the potential to be the method of choice for researchers interested in disease and tissue classification.
- Bounds on Absolute Gypsy Moth (Lymantria dispar dispar) (Lepidoptera: Erebidae) Population Density as Derived from Counts in Single Milk Carton TrapsOnufrieva, Ksenia S.; Onufriev, Alexey V.; Hickman, Andrea D.; Miller, James R. (MDPI, 2020-10-03)Estimates of absolute pest population density are critical to pest management programs but have been difficult to obtain from capture numbers in pheromone-baited monitoring traps. In this paper, we establish a novel predictive relationship for a probability (spTfer(r)) of catching a male located at a distance r from the trap with a plume reach D.
- Charge State of the Globular Histone Core Controls Stability of the NucleosomeFenley, Andrew T.; Adams, D. A.; Onufriev, Alexey V. (CELL PRESS, 2010-09-01)Presented here is a quantitative model of the wrapping and unwrapping of the DNA around the histone core of the nucleosome that suggests a mechanism by which this transition can be controlled: alteration of the charge state of the globular histone core. The mechanism is relevant to several classes of posttranslational modifications such as histone acetylation and phosphorylation; several specific scenarios consistent with recent in vivo experiments are considered. The model integrates a description based on an idealized geometry with one based on the atomistic structure of the nucleosome, and the model consistently accounts for both the electrostatic and nonelectrostatic contributions to the nucleosome free energy. Under physiological conditions, isolated nucleosomes are predicted to be very stable (38 +/- 7 kcal/mol). However, a decrease in the charge of the globular histone core by one unit charge, for example due to acetylation of a single lysine residue, can lead to a significant decrease in the strength of association with its DNA. In contrast to the globular histone core, comparable changes in the charge state of the histone tail regions have relatively little effect on the nucleosome's stability. The combination of high stability and sensitivity explains how the nucleosome is able to satisfy the seemingly contradictory requirements for thermodynamic stability while allowing quick access to its DNA informational content when needed by specific cellular processes such as transcription.
- Chromosome–nuclear envelope attachments affect interphase chromosome territories and entanglementKinney, Nicholas A.; Sharakhov, Igor V.; Onufriev, Alexey V. (2018-01-22)Background It is well recognized that the interphase chromatin of higher eukaryotes folds into non-random configurations forming territories within the nucleus. Chromosome territories have biologically significant properties, and understanding how these properties change with time during lifetime of the cell is important. Chromosome–nuclear envelope (Chr–NE) interactions play a role in epigenetic regulation of DNA replication, repair, and transcription. However, their role in maintaining chromosome territories remains unclear. Results We use coarse-grained molecular dynamics simulations to study the effects of Chr–NE interactions on the dynamics of chromosomes within a model of the Drosophila melanogaster regular (non-polytene) interphase nucleus, on timescales comparable to the duration of interphase. The model simulates the dynamics of chromosomes bounded by the NE. Initially, the chromosomes in the model are prearranged in fractal-like configurations with physical parameters such as nucleus size and chromosome persistence length taken directly from experiment. Time evolution of several key observables that characterize the chromosomes is quantified during each simulation: chromosome territories, chromosome entanglement, compactness, and presence of the Rabl (polarized) chromosome arrangement. We find that Chr–NE interactions help maintain chromosome territories by slowing down and limiting, but not eliminating, chromosome entanglement on biologically relevant timescales. At the same time, Chr–NE interactions have little effect on the Rabl chromosome arrangement as well as on how chromosome compactness changes with time. These results are rationalized by simple dimensionality arguments, robust to model details. All results are robust to the simulated activity of topoisomerase, which may be present in the interphase cell nucleus. Conclusions Our study demonstrates that Chr–NE attachments may help maintain chromosome territories, while slowing down and limiting chromosome entanglement on biologically relevant timescales. However, Chr–NE attachments have little effect on chromosome compactness or the Rabl chromosome arrangement.
- A Computational Framework for Interacting with Physical Molecular Models of the Polypeptide ChainChakraborty, Promita (Virginia Tech, 2014-05-08)Although nonflexible, scaled molecular models like Pauling-Corey's and its descendants have made significant contributions in structural biology research and pedagogy, recent technical advances in 3D printing and electronics make it possible to go one step further in designing physical models of biomacromolecules: to make them conformationally dynamic. We report the design, construction, and validation of a flexible, scaled, physical model of the polypeptide chain, which accurately reproduces the bond rotational degrees-of-freedom in the peptide backbone. The coarse-grained backbone model consists of repeating amide and alpha-carbon units, connected by mechanical bonds (corresponding to phi and psi angles) that include realistic barriers to rotation that closely approximate those found at the molecular scale. Longer-range hydrogen-bonding interactions are also incorporated, allowing the chain to easily fold into stable secondary structures. This physical model can serve as the basis for linking tangible bio-macromolecular models directly to the vast array of existing computational tools to provide an enhanced and interactive human-computer interface. We have explored the boundaries of this direction at the interface of computational tools and physical models of biological macromolecules at the nano-scale. Using a CAD-biocomputational framework, we have provided a methodology to design and build physical protein models focusing on shape and dynamics. We have also developed a workflow and an interface implemented for such bio-modeling tools. This physical-digital interface paradigm, at the intersection of native state proteins (P), computational models (C) and physical models (P), provides new opportunities for building an interactive computational modeling tool for protein folding and drug design. Furthermore, this model is easily constructed with readily obtainable parts and promises to be a tremendous educational aid to the intuitive understanding of chain folding as the basis for macromolecular structure.
- A computational study of nucleosomal DNA flexibilityRuscio, Jory Z.; Onufriev, Alexey V. (CELL PRESS, 2006-12-01)Molecular dynamics simulations of the nucleosome core particle and its isolated DNA free in solution are reported. The simulations are based on the implicit solvent methodology and provide insights into the nature of large-scale structural fuctuations and flexibility of the nucleosomal DNA. In addition to the kinked regions previously identified in the x-ray structure of the nucleosome, the simulations support the existence of a biochemically identified distorted region of the DNA. Comparison of computed relative free energies shows that formation of the kinks is associated with little, if any, energy cost relative to a smooth, ideal conformation of the DNA superhelix. Isolated nucleosomal DNA is found to be considerably more flexible than expected for a 147 bp stretch of DNA based on its canonical persistence length of 500 A. Notably, the significant bending of the DNA observed in our simulations occurs without breaking of Watson-Crick bonds. The computed relative stability of bent conformations is sensitive to the ionic strength of the solution in the physiological range; the sensitivity suggests possible experiments that might provide further insights into the structural origins of the unusual flexibility of the DNA.
- Correlation Between Computed Equilibrium Secondary Structure Free Energy and siRNA EfficiencyBhattacharjee, Puranjoy (Virginia Tech, 2009-08-06)We have explored correlations between the measured efficiency of the RNAi process and several computed signatures that characterize equilibrium secondary structure of the participating mRNA, siRNA, and their complexes. A previously published data set of 609 experimental points was used for the analysis. While virtually no correlation with the computed structural signatures are observed for individual data points, several clear trends emerge when the data is averaged over 10 bins of N ~ 60 data points per bin. The strongest trend is a positive linear (r² = 0.87) correlation between ln(remaining mRNA) and ΔGms, the combined free energy cost of unraveling the siRNA and creating the break in the mRNA secondary structure at the complementary target strand region. At the same time, the free energy change ΔGtotal of the entire process mRNA + siRNA → (mRNA – siRNA)complex is not correlated with RNAi efficiency, even after averaging. These general findings appear to be robust to details of the computational protocols. The correlation between computed ΔGms and experimentally observed RNAi efficiency can be used to enhance the ability of a machine learning algorithm based on a support vector machine (SVM) to predict effective siRNA sequences for a given target mRNA. Specifically, we observe modest, 3 to 7%, but consistent improvement in the positive predictive value (PPV) when the SVM training set is pre- or post-filtered according to a ΔGms threshold.
- Developing Fast and Accurate Water Models for Atomistic Molecular Dynamics SimulationsXiong, Yeyue (Virginia Tech, 2021-09-15)Water models are of great importance for different fields of studies such as fluid mechanics, nano materials, and biomolecule simulations. In this dissertation, we focus on the water models applied in atomistic simulations, including those of biomolecules such as proteins and DNA. Despite water's simple structure and countless studies carried out over the decades, the best water models are still far from perfect. Water models are normally divided into two types--explicit model and implicit model. Here my research is mainly focused on explicit models. In explicit water models, fixed charge n-point models are most widely used in atomistic simulations, but have known accuracy drawbacks. Increasing the number of point charges, as well as adding electronic polarizability, are two common strategies for accuracy improvements. Both strategies come at considerable computational cost, which weighs heavily against modest possible accuracy improvements in practical simulations. With a careful comparison between the two strategies, results show that adding polarizability is a more favorable path to take. Optimal point charge approximation (OPCA) method is then applied along with a novel global optimization process, leading to a new polarizable water model OPC3-pol that can reproduce bulk liquid properties of water accurately and run at a speed comparable to 3- and 4-point non-polarizable water models. For practical use, OPC3-pol works with existing non-polarizable AMBER force fields for simulations of globular protein or DNA. In addition, for intrinsically disordered protein simulations, OPC3-pol fixes the over-compactness problem of the previous generation non-polarizable water models.
- Exploring optimization strategies for improving explicit water models: Rigid n-point model and polarizable model based on Drude oscillatorXiong, Yeyue; Onufriev, Alexey V. (PLOS, 2019-11-14)Rigid n-point water models are widely used in atomistic simulations, but have known accuracy drawbacks. Increasing the number of point charges, as well as adding electronic polarizability, are two common strategies for accuracy improvements. Both strategies come at considerable computational cost, which weighs heavily against modest possible accuracy improvements in practical simulations. In an effort to provide guidance for model development, here we have explored the limiting accuracy of “electrostatically globally optimal” npoint water models in terms of their ability to reproduce properties of water dimer—a mimic of the condensed state of water. For a given n, each model is built upon a set of reference multipole moments (e.g. ab initio) and then optimized to reproduce water dimer total dipole moment. The models are then evaluated with respect to the accuracy of reproducing the geometry of the water dimer. We find that global optimization of the charge distribution alone can deliver high accuracy of the water model: for n = 4 or n = 5, the geometry of the resulting water dimer can be almost within 50 of the ab initio reference, which is half that of the experimental error margin. Thus, global optimization of the charge distribution of classical n-point water models can lead to high accuracy models. We also find that while the accuracy improvement in going from n = 3 to n = 4 is substantial, the additional accuracy increase in going from n = 4 to n = 5 is marginal. Next, we have explored accuracy limitations of the standard practice of adding electronic polarizability (via a Drude particle) to a “rigid base”—pre-optimization rigid n-point water model. The resulting model (n = 3) shows a relatively small improvement in accuracy, suggesting that the strategy of merely adding the polarizability to an inferior accuracy water model used as the base cannot fix the defects of the latter. An alternative strategy in which the parameters of the rigid base model are globally optimized along with the polarizability parameter is much more promising: the resulting 3-point polarizable model out-performs even the 5-point optimal rigid model by a large margin. We suggest that future development efforts consider 3- and 4-point polarizable models where global optimization of the “rigid base” is coupled to optimization of the polarizability to deliver globally optimal solutions.
- A General Probabilistic Model of the PCR ProcessSaha, Nilanjan; Watson, Layne T.; Kafadar, Karen; Onufriev, Alexey V.; Ramakrishnan, Naren; Vasquez-Robinet, Cecilia; Watkinson, Jonathan (Department of Computer Science, Virginia Polytechnic Institute & State University, 2004)This paper rigorously derives a general probabilistic model for the PCR process; this model includes as a special case the Velikanov-Kapral model where all nucleotide reaction rates are the same. In this model the probability of binding of deoxy-nucleoside triphosphate (dNTP) molecules with template strands is derived from the microscopic chemical kinetics. A recursive solution for the probability distribution of binding of dNTPs is developed for a single cycle and is used to calculate expected yield for a multicycle PCR. The model is able to reproduce important features of the PCR amplification process quantitatively. With a set of favorable reaction conditions, the amplification of the target sequence is fast enough to rapidly outnumber all side products. Furthemore, the final yield of the target sequence in a multicycle PCR run always approaches an asymptotic limit that is less than one. The amplification process itself is highly sensitive to initial concentrations and the reaction rates of addition to the template strand of each type of dNTP in the solution.
- A Gillespie-Type Algorithm for Particle Based Stochastic Model on LatticeLiu, Weigang (Virginia Tech, 2019)In this thesis, I propose a general stochastic simulation algorithm for particle based lattice model using the concepts of Gillespie's stochastic simulation algorithm, which was originally designed for well-stirred systems. I describe the details about this method and analyze its complexity compared with the StochSim algorithm, another simulation algorithm originally proposed to simulate stochastic lattice model. I compare the performance of both algorithms with application to two different examples: the May-Leonard model and Ziff-Gulari-Barshad model. Comparison between the simulation results from both algorithms has validate our claim that our new proposed algorithm is comparable to the StochSim in simulation accuracy. I also compare the efficiency of both algorithms using the CPU cost of each code and conclude that the new algorithm is as efficient as the StochSim in most test cases, while performing even better for certain specific cases.
- H++3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulationsAnandakrishnan, Ramu; Aguilar, Boris; Onufriev, Alexey V. (2012-07)The accuracy of atomistic biomolecular modeling and simulation studies depend on the accuracy of the input structures. Preparing these structures for an atomistic modeling task, such as molecular dynamics (MD) simulation, can involve the use of a variety of different tools for: correcting errors, adding missing atoms, filling valences with hydrogens, predicting pK values for titratable amino acids, assigning predefined partial charges and radii to all atoms, and generating force field parameter/topology files for MD. Identifying, installing and effectively using the appropriate tools for each of these tasks can be difficult for novice and time-consuming for experienced users. H++ (http://biophysics.cs.vt.edu/) is a free open-source web server that automates the above key steps in the preparation of biomolecular structures for molecular modeling and simulations. H++ also performs extensive error and consistency checking, providing error/warning messages together with the suggested corrections. In addition to numerous minor improvements, the latest version of H++ includes several new capabilities and options: fix erroneous (flipped) side chain conformations for HIS, GLN and ASN, include a ligand in the input structure, process nucleic acid structures and generate a solvent box with specified number of common ions for explicit solvent MD.
- H++: a server for estimating pK(a)s and adding missing hydrogens to macromoleculesGordon, John C.; Myers, Jonathan B.; Folta, Timothy; Shoja, Valia; Heath, Lenwood S.; Onufriev, Alexey V. (2005-07-01)The structure and function of macromolecules depend critically on the ionization (protonation) states of their acidic and basic groups. A number of existing practical methods predict protonation equilibrium pK constants of macromolecules based upon their atomic resolution Protein Data Bank (PDB) structures; the calculations are often performed within the framework of the continuum electrostatics model. Unfortunately, these methodologies are complex, involve multiple steps and require considerable investment of effort. Our web server http://biophysics.cs.vt.edu/H++ provides access to a tool that automates this process, allowing both experts and novices to quickly obtain estimates of pKs as well as other related characteristics of biomolecules such as isoelectric points, titration curves and energies of protonation microstates. Protons are added to the input structure according to the calculated ionization states of its titratable groups at the user-specified pH; the output is in the PQR (PDB + charges + radii) format. In addition, corresponding coordinate and topology files are generated in the format supported by the molecular modeling package AMBER. The server is intended for a broad community of biochemists, molecular modelers, structural biologists and drug designers; it can also be used as an educational tool in biochemistry courses.
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