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Open Access Publications from the University of California

Scholarly Works (8 results)

  • Thesis
  • Peer Reviewed
UC Irvine Electronic Theses and Dissertations (2020)

Free energy perturbation methods serve an important role in drug discovery by providing accurate predictions of binding affinity, solubility, and other quantities.

However, in order for the free energy estimates to be accurate, the system must be able to sample all the relevant low energy states during the course of a simulation.

This proves to be challenging for binding affinity calculations in particular, since there can be many different potential binding modes, and binding modes are slow to interconvert at simulation timescales.

It is possible to treat each binding mode separately, perform a free energy calculation on each binding mode, and then combine the results into a total free energy prediction, but the computational cost of free energy calculations does make this parallelization approach feasible.

Another alternative approach would be to use a method that could sample between the different binding modes efficiently and produce accurate estimates of the populations of each of those binding modes.

This information, along with a binding free energy calculation on one of the binding modes, would allow the estimation of the overall binding free energy.

In order to sample between binding modes efficiently, I helped develop a new method that uses nonequilibrium candidate Monte Carlo (NCMC) to remove the ligand and reinsert it in a new binding site with a center of mass rotation to further improve sampling.

I validated this methodology on T4 lysozyme L99A, a model protein for binding, and was able to show that it enhanced the sampling of the binding modes of toluene and 3-iodotolune.

Following these results, I helped create the BLUES (Binding modes of Ligands Using Enhanced Sampling) software package to facilitate the use of this technique.

Originally BLUES only could further improve binding mode sampling with a center of mass rotation Monte Carlo (MC) move, which limited it's applicability to small, rigid ligands.

To further improve binding mode sampling, I also developed a new type of MC move called molecular Darting (MolDarting) to sample specific binding modes.

Through MolDarting it is possible to sample predefined conformations–obtained by docking, for example–and reversibly sample them in a MC framework.

MolDarting also opens up the ability to even sample ligand binding modes in separate binding sites.

We validated this move on an alanine-valine dipeptide system, as well the previouly explored T4 lysozyme and attempted to sample all the potential binding sites in HIV integrase.

    Cover page: Enhanced sampling of ligand binding modes through BLUES and molecular dartingCreative Commons 'BY' version 4.0 license
    • Article
    • Peer Reviewed
    UC Irvine Previously Published Works (2021)
    Sampling multiple binding modes of a ligand in a single molecular dynamics simulation is difficult. A given ligand may have many internal degrees of freedom, along with many different ways it might orient itself in a binding site or across several binding sites, all of which might be separated by large energy barriers. We have developed a novel Monte Carlo move called molecular darting (MolDarting) to reversibly sample between predefined binding modes of a ligand. Here, we couple this with nonequilibrium candidate Monte Carlo (NCMC) to improve acceptance of moves. We apply this technique to a simple dipeptide system, a ligand binding to T4 lysozyme L99A, and ligand binding to HIV integrase to test this new method. We observe significant increases in acceptance compared to uniformly sampling the internal and rotational/translational degrees of freedom in these systems.
      Cover page: Reversibly Sampling Conformations and Binding Modes Using Molecular Darting
      • Article
      • Peer Reviewed
      UC Irvine Previously Published Works (2019)
      Molecular simulations are a valuable tool for studying biomolecular motions and thermodynamics. However, such motions can be slow compared to simulation time scales, yet critical. Specifically, adequate sampling of side chain motions in protein binding pockets is crucial for obtaining accurate estimates of ligand binding free energies from molecular simulations. The time scale of side chain rotamer flips can range from a few ps to several hundred ns or longer, particularly in crowded environments like the interior of proteins. Here, we apply a mixed nonequilibrium candidate Monte Carlo (NCMC)/molecular dynamics (MD) method to enhance sampling of side chain rotamers. The NCMC portion of our method applies a switching protocol wherein the steric and electrostatic interactions between target side chain atoms and the surrounding environment are cycled off and then back on during the course of a move proposal. Between NCMC move proposals, simulation of the system continues via traditional molecular dynamics. Here, we first validate this approach on a simple, solvated valine-alanine dipeptide system and then apply it to a well-studied model ligand binding site in T4 lysozyme L99A. We compute the rate of rotamer transitions for a valine side chain using our approach and compare it to that of traditional molecular dynamics simulations. Here, we show that our NCMC/MD method substantially enhances side chain sampling, especially in systems where the torsional barrier to rotation is high (≥10 kcal/mol). These barriers can be intrinsic torsional barriers or steric barriers imposed by the environment. Overall, this may provide a promising strategy to selectively improve side chain sampling in molecular simulations.
        Cover page: Enhancing Side Chain Rotamer Sampling Using Nonequilibrium Candidate Monte Carlo.Creative Commons 'BY' version 4.0 license
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2019)
        A correct estimate of ligand binding modes and a ratio of their occupancies is crucial for calculations of binding free energies. The newly developed method BLUES combines molecular dynamics with nonequilibrium candidate Monte Carlo. Nonequilibrium candidate Monte Carlo generates a plethora of possible binding modes and molecular dynamics enables the system to relax. We used BLUES to investigate binding modes of caffeine in the active site of its metabolizing enzyme Cytochrome P450 1A2 with the aim of elucidating metabolite-formation profiles at different concentrations. Because the activation energies of all sites of metabolism do not show a clear preference for one metabolite over the others, the orientations in the active site must play a key role. In simulations with caffeine located in a spacious pocket above the I-helix, it points N3 and N1 to the heme iron, whereas in simulations where caffeine is in close proximity to the heme N7 and C8 are preferably oriented toward the heme iron. We propose a mechanism where at low caffeine concentrations caffeine binds to the upper part of the active site, leading to formation of the main metabolite paraxanthine. On the other hand, at high concentrations two molecules are located in the active site, forcing one molecule into close proximity to the heme and yielding metabolites theophylline and trimethyluretic acid. Our results offer an explanation of previously published experimental results.
          Cover page: Binding Modes and Metabolism of Caffeine
          • Article
          • Peer Reviewed
          UC Irvine Previously Published Works (2020)
          Flexible ligands often have multiple binding modes or bound conformations that differ by rotation of a portion of the molecule around internal rotatable bonds. Knowledge of these binding modes is important for understanding the interactions stabilizing the ligand in the binding pocket, and other studies indicate it is important for calculating accurate binding affinities. In this work, we use a hybrid molecular dynamics (MD)/nonequilibrium candidate Monte Carlo (NCMC) method to sample the different binding modes of several flexible ligands and also to estimate the population distribution of the modes. The NCMC move proposal is divided into three parts. The flexible part of the ligand is alchemically turned off by decreasing the electrostatics and steric interactions gradually, followed by rotating the rotatable bond by a random angle and then slowly turning the ligand back on to its fully interacting state. The alchemical steps prior to and after the move proposal help the surrounding protein and water atoms in the binding pocket relax around the proposed ligand conformation and increase move acceptance rates. The protein-ligand system is propagated using classical MD in between the NCMC proposals. Using this MD/NCMC method, we were able to correctly reproduce the different binding modes of inhibitors binding to two kinase targets-c-Jun N-terminal kinase-1 and cyclin-dependent kinase 2-at a much lower computational cost compared to conventional MD and umbrella sampling. This method is available as a part of the BLUES software package.
            Cover page: Sampling Conformational Changes of Bound Ligands Using Nonequilibrium Candidate Monte Carlo and Molecular Dynamics.
            • Multimedia
            Mobley Lab Datasets (2018)
            This is a talk/status report given on our BLUES technique for estimating fragment binding mode occupancies; it was presented at the OpenEye CUP Meeting in Santa Fe, NM, March 8, 2018. This work is in the area of structure-based drug design and we are working on modeling techniques to efficiently estimate populations of metastable ligand binding modes. The presentation is made available in PowerPoint and Keynote formats and includes movies, so the files are large.
            • 1 supplemental ZIP
            • 1 supplemental file
            Creative Commons 'BY' version 4.0 license
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2018)
            Accurately predicting protein-ligand binding affinities and binding modes is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation time scales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes. In this technique, the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over 2 orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step toward applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding modes of ligands using enhanced sampling (BLUES) package which is freely available on GitHub.
              • Article
              • Peer Reviewed
              UC Riverside Previously Published Works (2023)
              Measuring the metallicity and carbon-to-oxygen (C/O) ratio in exoplanet atmospheres is a fundamental step towards constraining the dominant chemical processes at work and, if in equilibrium, revealing planet formation histories. Transmission spectroscopy (for example, refs. 1,2) provides the necessary means by constraining the abundances of oxygen- and carbon-bearing species; however, this requires broad wavelength coverage, moderate spectral resolution and high precision, which, together, are not achievable with previous observatories. Now that JWST has commenced science operations, we are able to observe exoplanets at previously uncharted wavelengths and spectral resolutions. Here we report time-series observations of the transiting exoplanet WASP-39b using JWSTs Near InfraRed Camera (NIRCam). The long-wavelength spectroscopic and short-wavelength photometric light curves span 2.0-4.0 micrometres, exhibit minimal systematics and reveal well defined molecular absorption features in the planets spectrum. Specifically, we detect gaseous water in the atmosphere and place an upper limit on the abundance of methane. The otherwise prominent carbon dioxide feature at 2.8 micrometres is largely masked by water. The best-fit chemical equilibrium models favour an atmospheric metallicity of 1-100-times solar (that is, an enrichment of elements heavier than helium relative to the Sun) and a substellar C/O ratio. The inferred high metallicity and low C/O ratio may indicate significant accretion of solid materials during planet formation (for example, refs. 3,4,) or disequilibrium processes in the upper atmosphere (for example, refs. 5,6).
                Cover page: Early Release Science of the exoplanet WASP-39b with JWST NIRCam.
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