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Open Access Publications from the University of California

Scholarly Works (12 results)

  • Thesis
  • Peer Reviewed
UC San Diego Electronic Theses and Dissertations (2018)

The field of molecular dynamics is rapidly advancing as new theoretical techniques, software optimizations and computer architectures are unveiled seemingly daily. In this dissertation, I first review the best practices and recent developments in molecular dynamics based alchemical free energy calculations in the AMBER molecular dynamics suite. I then present a graphics processor enabled implementation of alchemical free energy calculations with performance 360 times that of the existing CPU implementation, while maintaining equivalent accuracy through the judicious use of a combination of floating point and fixed precision. Next, I discuss the application of constant pH molecular dynamics to investigate the role of water in beta secretase-1 catalysis. This protein has a known pH dependence and is a key target in the fight against Alzheimer’s Disease. I present a hypothesis for the role of the flap region in regulating beta secretase-1 catalysis. Finally, I have investigated benzene egress from the binding pocket of the L99A mutant of T4 lysozyme using accelerated molecular dynamics. It is found that benzene exits the binding pocket by a multistep process from the buried cavity to ultimate release through an opening between the F/G, H and I helices.

    Cover page: Improvements and Applications of Alchemical Free Energy, Constant pH and Accelerated Molecular Dynamics Calculations in the AMBER Molecular Dynamics Suite.
    • Article
    • Peer Reviewed
    UC San Diego Previously Published Works (2019)
    Beta-secretase 1 (BACE-1) is an aspartyl protease implicated in the overproduction of β-amyloid fibrils responsible for Alzheimer disease. The process of β-amyloid genesis is known to be pH dependent, with an activity peak between solution pH of 3.5 and 5.5. We have studied the pH-dependent dynamics of BACE-1 to better understand the pH dependent mechanism. We have implemented support for graphics processor unit (GPU) accelerated constant pH molecular dynamics within the AMBER molecular dynamics software package and employed this to determine the relative population of different aspartyl dyad protonation states in the pH range of greatest β-amyloid production, followed by conventional molecular dynamics to explore the differences among the various aspartyl dyad protonation states. We observed a difference in dynamics between double-protonated, mono-protonated, and double-deprotonated states over the known pH range of higher activity. These differences include Tyr 71-aspartyl dyad proximity and active water lifetime. This work indicates that Tyr 71 stabilizes catalytic water in the aspartyl dyad active site, enabling BACE-1 activity.
      • Thesis
      • Peer Reviewed
      UC San Diego Electronic Theses and Dissertations (2018)

      As technology moves forward with newer hardware, new computational techniques, and new algorithms, it is important for science to keep up with these advances. Without people maintaining code to the latest standards and modifying the underlying algorithms to closely match the shifting hardware landscape, scientific software easily becomes outdated and deprecated on the latest architectures. Similarly as technology advances and acapability increases so the underlying methods should be adapted, extended or replaced in order to fully realize the scientific potential of the underlying improvements in the hardware. This research focuses on developing faster and higher accuracy free energy prediction methods as well as the development of simulation techniques necessary to improve the sampling efficiency of all atom, condensed phase, molecular dynamics simulations on exa-scale computational hardware. Specifically, it will cover efforts to develop GPU accelerated thermodynamic integration algorithms, low level code optimization on next generation CPU architectures, techniques for more efficient 3D domain decomposition and work to explore more efficient sampling techniques. These methods have been implemented as part of this work within the Amber software package. Additionally, to show the accuracy and performance of the code, comparisons against previous Amber versions as well as existing free energy prediction packages such as Schrodinger's FEP+ will be analyzed and discussed.

        Cover page: Effective Utilization of Next Generation Hardware for Complex Molecular Dynamics Simulations
        • Article
        • Peer Reviewed
        UC San Diego Previously Published Works (2013)
        Alchemical transformations are widely used methods to calculate free energies. Amber has traditionally included support for alchemical transformations as part of the sander molecular dynamics (MD) engine. Here we describe the implementation of a more efficient approach to alchemical transformations in the Amber MD package. Specifically we have implemented this new approach within the more computational efficient and scalable pmemd MD engine that is included with the Amber MD package. The majority of the gain in efficiency comes from the improved design of the calculation, which includes better parallel scaling and reduction in the calculation of redundant terms. This new implementation is able to reproduce results from equivalent simulations run with the existing functionality, but at 2.5 times greater computational efficiency. This new implementation is also able to run softcore simulations at the λ end states making direct calculation of free energies more accurate, compared to the extrapolation required in the existing implementation. The updated alchemical transformation functionality will be included in the next major release of Amber (scheduled for release in Q1 2014) and will be available at http://ambermd.org, under the Amber license.
          • Article
          • Peer Reviewed
          UC San Diego Previously Published Works (2018)
          Alchemical free energy (AFE) calculations based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD-based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER. © 2018 Wiley Periodicals, Inc.
            • Article
            • Peer Reviewed
            UC San Diego Previously Published Works (2014)
            Accelerated molecular dynamics (aMD) simulations greatly improve the efficiency of conventional molecular dynamics (cMD) for sampling biomolecular conformations, but they require proper reweighting for free energy calculation. In this work, we systematically compare the accuracy of different reweighting algorithms including the exponential average, Maclaurin series, and cumulant expansion on three model systems: alanine dipeptide, chignolin, and Trp-cage. Exponential average reweighting can recover the original free energy profiles easily only when the distribution of the boost potential is narrow (e.g., the range ≤20kBT) as found in dihedral-boost aMD simulation of alanine dipeptide. In dual-boost aMD simulations of the studied systems, exponential average generally leads to high energetic fluctuations, largely due to the fact that the Boltzmann reweighting factors are dominated by a very few high boost potential frames. In comparison, reweighting based on Maclaurin series expansion (equivalent to cumulant expansion on the first order) greatly suppresses the energetic noise but often gives incorrect energy minimum positions and significant errors at the energy barriers (∼2-3kBT). Finally, reweighting using cumulant expansion to the second order is able to recover the most accurate free energy profiles within statistical errors of ∼kBT, particularly when the distribution of the boost potential exhibits low anharmonicity (i.e., near-Gaussian distribution), and should be of wide applicability. A toolkit of Python scripts for aMD reweighting "PyReweighting" is distributed free of charge at http://mccammon.ucsd.edu/computing/amdReweighting/.
              Cover page: Improved Reweighting of Accelerated Molecular Dynamics Simulations for Free Energy Calculation
              • Article
              • Peer Reviewed
              UC San Diego Previously Published Works (2018)
              It is important to determine the binding pathways and mechanisms of ligand molecules to target proteins to effectively design therapeutic drugs. Molecular dynamics (MD) is a promising computational tool that allows us to simulate protein-drug binding at an atomistic level. However, the gap between the time scales of current simulations and those of many drug binding processes has limited the usage of conventional MD, which has been reflected in studies of the HIV protease. Here, we have applied a robust enhanced simulation method, Gaussian accelerated molecular dynamics (GaMD), to sample binding pathways of the XK263 ligand and associated protein conformational changes in the HIV protease. During two of 10 independent GaMD simulations performed over 500-2500 ns, the ligand was observed to successfully bind to the protein active site. Although GaMD-derived free energy profiles were not fully converged because of insufficient sampling of the complex system, the simulations still allowed us to identify relatively low-energy intermediate conformational states during binding of the ligand to the HIV protease. Relative to the X-ray crystal structure, the XK263 ligand reached a minimum root-mean-square deviation (RMSD) of 2.26 Å during 2.5 μs of GaMD simulation. In comparison, the ligand RMSD reached a minimum of only ∼5.73 Å during an earlier 14 μs conventional MD simulation. This work highlights the enhanced sampling power of the GaMD approach and demonstrates its wide applicability to studies of drug-receptor interactions for the HIV protease and by extension many other target proteins.
                • Article
                • Peer Reviewed
                UC San Diego Previously Published Works (2016)
                The CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 system recently emerged as a transformative genome-editing technology that is innovating basic bioscience and applied medicine and biotechnology. The endonuclease Cas9 associates with a guide RNA to match and cleave complementary sequences in double stranded DNA, forming an RNA:DNA hybrid and a displaced non-target DNA strand. Although extensive structural studies are ongoing, the conformational dynamics of Cas9 and its interplay with the nucleic acids during association and DNA cleavage are largely unclear. Here, by employing multi-microsecond time scale molecular dynamics, we reveal the conformational plasticity of Cas9 and identify key determinants that allow its large-scale conformational changes during nucleic acid binding and processing. We show how the "closure" of the protein, which accompanies nucleic acid binding, fundamentally relies on highly coupled and specific motions of the protein domains, collectively initiating the prominent conformational changes needed for nucleic acid association. We further reveal a key role of the non-target DNA during the process of activation of the nuclease HNH domain, showing how the nontarget DNA positioning triggers local conformational changes that favor the formation of a catalytically competent Cas9. Finally, a remarkable conformational plasticity is identified as an intrinsic property of the HNH domain, constituting a necessary element that allows for the HNH repositioning. These novel findings constitute a reference for future experimental studies aimed at a full characterization of the dynamic features of the CRISPR-Cas9 system, and-more importantly-call for novel structure engineering efforts that are of fundamental importance for the rational design of new genome-engineering applications.
                  • Article
                  • Peer Reviewed
                  UC San Diego Previously Published Works (2017)
                  CRISPR-Cas9 has become a facile genome editing technology, yet the structural and mechanistic features underlying its function are unclear. Here, we perform extensive molecular simulations in an enhanced sampling regime, using a Gaussian-accelerated molecular dynamics (GaMD) methodology, which probes displacements over hundreds of microseconds to milliseconds, to reveal the conformational dynamics of the endonuclease Cas9 during its activation toward catalysis. We disclose the conformational transition of Cas9 from its apo form to the RNA-bound form, suggesting a mechanism for RNA recruitment in which the domain relocations cause the formation of a positively charged cavity for nucleic acid binding. GaMD also reveals the conformation of a catalytically competent Cas9, which is prone for catalysis and whose experimental characterization is still limited. We show that, upon DNA binding, the conformational dynamics of the HNH domain triggers the formation of the active state, explaining how the HNH domain exerts a conformational control domain over DNA cleavage [Sternberg SH et al. (2015) Nature, 527, 110-113]. These results provide atomic-level information on the molecular mechanism of CRISPR-Cas9 that will inspire future experimental investigations aimed at fully clarifying the biophysics of this unique genome editing machinery and at developing new tools for nucleic acid manipulation based on CRISPR-Cas9.
                    • Article
                    • Peer Reviewed
                    UC San Diego Previously Published Works (2012)
                    In this work, we critically assess the ability of the all-atom enhanced sampling method accelerated molecular dynamics (aMD) to investigate conformational changes in proteins that typically occur on the millisecond time scale. We combine aMD with the inherent power of graphics processor units (GPUs) and apply the implementation to the bovine pancreatic trypsin inhibitor (BPTI). A 500 ns aMD simulation is compared to a previous millisecond unbiased brute force MD simulation carried out on BPTI, showing that the same conformational space is sampled by both approaches. To our knowledge, this represents the first implementation of aMD on GPUs and also the longest aMD simulation of a biomolecule run to date. Our implementation is available to the community in the latest release of the Amber software suite (v12), providing routine access to millisecond events sampled from dynamics simulations using off the shelf hardware.
                      Cover page: Routine Access to Millisecond Time Scale Events with Accelerated Molecular Dynamics
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