Rommie E Amaro

University of California, San Diego, San Diego, California, United States

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Publications (78)316.78 Total impact

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    Full-text · Dataset · Dec 2015
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    Full-text · Dataset · Dec 2015
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    ABSTRACT: APOBEC3 family DNA cytosine deaminases provide overlapping defenses against pathogen infections. However, most viruses have elaborate evasion mechanisms such as the HIV-1 Vif protein, which subverts cellular CBF-β and a polyubiquitin ligase complex to neutralize these enzymes. Despite advances in APOBEC3 and Vif biology, a full understanding of this direct host-pathogen conflict has been elusive. We combine virus adaptation and computational studies to interrogate the APOBEC3F-Vif interface and build a robust structural model. A recurring compensatory amino acid substitution from adaptation experiments provided an initial docking constraint, and microsecond molecular dynamic simulations optimized interface contacts. Virus infectivity experiments validated a long-lasting electrostatic interaction between APOBEC3F E289 and HIV-1 Vif R15. Taken together with mutagenesis results, we propose a wobble model to explain how HIV-1 Vif has evolved to bind different APOBEC3 enzymes and, more generally, how pathogens may evolve to escape innate host defenses.
    Full-text · Article · Nov 2015 · Cell Reports
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    ABSTRACT: The protist parasite Trypanosoma brucei causes Human African trypanosomiasis (HAT), which threatens millions of people in sub-Saharan Africa. Without treatment the infection is almost always lethal. Current drugs for HAT are difficult to administer and have severe side effects. Together with increasing drug resistance this results in urgent need for new treatments. T. brucei and other trypanosomatid pathogens require a distinct form of post-transcriptional mRNA modification for mitochondrial gene expression. A multi-protein complex called the editosome cleaves mitochondrial mRNA, inserts or deletes uridine nucleotides at specific positions and re-ligates the mRNA. RNA editing ligase 1 (REL1) is essential for the re-ligation step and has no close homolog in the mammalian host, making it a promising target for drug discovery. However, traditional assays for RELs use radioactive substrates coupled with gel analysis and are not suitable for high-throughput screening of compound libraries. Here we describe a fluorescence-based REL activity assay. This assay is compatible with a 384-well microplate format and sensitive, satisfies statistical criteria for high-throughput methods and is readily adaptable for other polynucleotide ligases. We validated the assay by determining kinetic properties of REL1 and by identifying REL1 inhibitors in a library of small, pharmacologically active compounds.
    Full-text · Article · Sep 2015 · Nucleic Acids Research
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    ABSTRACT: The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.
    Full-text · Article · Sep 2015 · Frontiers in Physiology
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    ABSTRACT: The magnitude of the investment required to bring a drug to the market hinders medical progress, requiring hundreds of millions of dollars and years of research and development. Any innovation that improves the efficiency of the drug-discovery process has the potential to accelerate the delivery of new treatments to countless patients in need. "Virtual screening," wherein molecules are first tested in silico in order to prioritize compounds for subsequent experimental testing, is one such innovation. Although the traditional scoring functions used in virtual screens have proven useful, improved accuracy requires novel approaches. In the current work, we use the estrogen receptor to demonstrate that neural networks are adept at identifying structurally novel small molecules that bind to a selected drug target, ultimately allowing experimentalists to test fewer compounds in the earliest stages of lead identification while obtaining higher hit rates. We describe 39 novel estrogen-receptor ligands identified in silico with experimentally determined Ki values ranging from 460 nM to 20 µM, presented here for the first time.
    Full-text · Article · Aug 2015 · Journal of Chemical Information and Modeling
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    ABSTRACT: Ligand-induced protein allostery plays a central role in modulating cellular signalling pathways. Here using the conserved cyclic nucleotide-binding domain of protein kinase A's (PKA) regulatory subunit as a prototype signalling unit, we combine long-timescale, all-atom molecular dynamics simulations with Markov state models to elucidate the conformational ensembles of PKA's cyclic nucleotide-binding domain A for the cAMP-free (apo) and cAMP-bound states. We find that both systems exhibit shallow free-energy landscapes that link functional states through multiple transition pathways. This observation suggests conformational selection as the general mechanism of allostery in this canonical signalling domain. Further, we expose the propagation of the allosteric signal through key structural motifs in the cyclic nucleotide-binding domain and explore the role of kinetics in its function. Our approach integrates disparate lines of experimental data into one cohesive framework to understand structure, dynamics and function in complex biological systems.
    Full-text · Article · Jul 2015 · Nature Communications
  • Pek Ieong · Rommie E Amaro · Wilfred W Li
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    ABSTRACT: The antibody immunoglobulin (Ig) 2D1 is effective against the 1918 hemagglutinin (HA) and also known to cross-neutralize the 2009 pandemic H1N1 influenza HA through a similar epitope. However, the detailed mechanism of neutralization remains unclear. We conducted molecular dynamics (MD) simulations to study the interactions between Ig-2D1 and the HAs from the 1918 pandemic flu (A/South Carolina/1/1918, 18HA), the 2009 pandemic flu (A/California/04/2009, 09HA), a 2009 pandemic flu mutant (A/California/04/2009, 09HA_mut), and the 2006 seasonal flu (A/Solomon Islands/3/2006, 06HA). MM-PBSA analyses suggest the approximate free energy of binding (ΔG) between Ig-2D1 and 18HA is -74.4 kcal/mol. In comparison with 18HA, 09HA and 06HA bind Ig-2D1 ∼6 kcal/mol (ΔΔG) weaker, and the 09HA_mut bind Ig-2D1 only half as strong. We also analyzed the contributions of individual epitope residues using the free-energy decomposition method. Two important salt bridges are found between the HAs and Ig-2D1. In 09HA, a serine-to-asparagine mutation coincided with a salt bridge destabilization, hydrogen bond losses, and a water pocket formation between 09HA and Ig-2D1. In 09HA_mut, a lysine-to-glutamic-acid mutation leads to the loss of both salt bridges and destabilizes interactions with Ig-2D1. Even though 06HA has a similar ΔG to 09HA, it is not recognized by Ig-2D1 in vivo. Because 06HA contains two potential glycosylation sites that could mask the epitope, our results suggest that Ig-2D1 may be active against 06HA only in the absence of glycosylation. Overall, our simulation results are in good agreement with observations from biological experiments and offer novel mechanistic insights, to our knowledge, into the immune escape of the influenza virus. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.
    No preview · Article · Jun 2015 · Biophysical Journal
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    Lane W Votapka · Rommie E Amaro
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    ABSTRACT: The kinetic rate constants of binding were estimated for four biochemically relevant molecular systems by a method that uses milestoning theory to combine Brownian dynamics simulations with more detailed molecular dynamics simulations. The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value with Smoluchowski theory. We also calculated the kon rate constant for superoxide dismutase with its natural substrate, O2-, in a validation of a previous experiment using similar methods but with a number of important improvements. We also calculated the kon for a new system: the N-terminal domain of Troponin C with its natural substrate Ca2+. The kon calculated for the latter two systems closely resemble experimentally obtained values. This novel multiscale approach is computationally cheaper and more parallelizable when compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor.
    Preview · Article · May 2015 · Journal of biomolecular Structure & Dynamics
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    ABSTRACT: The ankyrin repeat and SOCS box (ASB) family is composed of 18 proteins and belongs to the suppressor of cytokine signaling (SOCS) box protein superfamily. The ASB proteins function as the substrate-recognition subunits of ECS-type (ElonginBC-Cullin-SOCS-box) Cullin RING E3 ubiquitin ligase (CRL) complexes that specifically transfer ubiquitin to cellular proteins targeting them for degradation by the proteasome. ASB9 binds to creatine kinase (CK) and targets it for degradation, however the way in which ASB9 interacts with CK is not yet known. We present complete characterization of the binding of ASB9 to CK. One ASB9 molecule binds to a dimer of CK. The binding affinity of ASB9(1-252) was extremely tight and no dissociation could be observed. Deletion of the N-terminal 34 amino acids forming ASB9(35-252) resulted in weakening of the binding so that a binding affinity of 2.6 nM could be measured. Amide hydrogen/deuterium exchange (HDXMS) experiments showed that both ASB9(1-252) and ASB9(35-252) protected the same region of CK, residues 182-203, which forms one side of the active site. The HDXMS experiments indicated that the N-terminal disordered region and first ankyrin repeat of ASB9 are protected from exchange in the complex. Molecular docking yielded a structural model consistent with all of the data that suggested the N-terminal residues of ASB9(1-252) may lie in one CK active site. This model was corroborated by enzymatic activity assays and mutational analysis.
    No preview · Article · Feb 2015 · Biochemistry

  • No preview · Article · Jan 2015 · Biophysical Journal
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    ABSTRACT: Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were selected for experimental evaluation. Twelve specific compounds isolated from these five plants were shown to inhibit neuraminidase, including two compounds with IC50 values less than 92 μM. Furthermore, four of the twelve isolated compounds had also been identified in the top 100 compounds from the virtual screen. Together, these results suggest an effective new approach for identifying bioactive plant species that will further the identification of new pharmacologically active compounds from diverse natural-product resources.
    Full-text · Article · Jan 2015 · Journal of Chemical Information and Modeling
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    ABSTRACT: It is widely accepted that protein receptors exist as an ensemble of conformations in solution. How best to incorporate receptor flexibility into virtual screening protocols used for drug discovery remains a significant challenge. Here, stepwise methodologies are described to generate and select relevant protein conformations for virtual screening in the context of the relaxed complex scheme (RCS), to design small molecule libraries for docking, and to perform statistical analyses on the virtual screening results. Methods include equidistant spacing, RMSD-based clustering, and QR factorization protocols for ensemble generation and ROC analysis for ensemble selection.
    No preview · Article · Jan 2015 · Methods in Molecular Biology
  • Jacob D. Durrant · Rommie E. Amaro
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    ABSTRACT: The emergence of drug-resistant bacteria threatens to revert humanity back to the preantibiotic era. Even now, multidrug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the pipeline. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug-discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics, leading to improved hit rates and faster transitions to preclinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field.
    No preview · Article · Jan 2015 · Chemical Biology & Drug Design
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    ABSTRACT: We describe the development of automated workflows that support computed-aided drug discovery (CADD) and molecular dynamics (MD) simulations and are included as part of the National Biomedical Computation Resource (NBCR). The main workflow components include: file management tasks, ligand force field parameterization, receptor-ligand molecular dynamics (MD) simulations, job submission, serial and parallel execution, and monitoring on relevant high-performance computing (HPC) resources, receptor structural clustering, virtual screening (VS), and statistical analyses of the VS results. The workflows aim to standardize simulation and analysis and promote best practices within the molecular simulation and CADD communities. Each component is developed as a stand-alone workflow, which should allow for easy integration into larger frameworks built suiting user needs, while remaining intuitive and easy to extend.
    Full-text · Article · Dec 2014 · Procedia Computer Science
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    ABSTRACT: Analysis of macromolecular/small-molecule binding pockets can provide important insights into molecular recognition and receptor dynamics. Since its release in 2011, the POVME (POcket Volume MEasurer) algorithm has been widely adopted as a simple-to-use tool for measuring and characterizing pocket volumes and shapes. We here present POVME 2.0, which is an order of magnitude faster, has improved accuracy, includes a graphical user interface, and can produce volumetric density maps for improved pocket analysis. To demonstrate the utility of the algorithm, we use it to analyze the binding pocket of RNA editing ligase 1 from the unicellular parasite Trypanosoma brucei, the etiological agent of African sleeping sickness. The POVME analysis characterizes the full dynamics of a potentially druggable transient binding pocket and so may guide future antitrypanosomal drug-discovery efforts. We are hopeful that this new version will be a useful tool for the computational- and medicinal-chemist community.
    Preview · Article · Nov 2014 · Journal of Chemical Theory and Computation
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    ABSTRACT: During β-adrenergic stimulation, cardiac troponin I (cTnI) is phosphorylated by protein kinase A (PKA) at sites S23/S24, located at the N-terminus of cTnI. This phosphorylation has been shown to decrease KCa and pCa50, and weaken the cTnC-cTnI (C-I) interaction. We recently reported that phosphorylation results in an increase in the rate of early, slow phase of relaxation (kREL,slow) and a decrease in its duration (tREL,slow), which speeds up the overall relaxation. However, as the N-terminus of cTnI (residues 1-40) has not been resolved in the whole cardiac troponin (cTn) structure, little is known about the molecular-level behavior within the whole cTn complex upon phosphorylation of the S23/S24 residues of cTnI that results in these changes in function. In this study, we built up the cTn complex structure (including residues cTnC 1-161, cTnI 1-172, and cTnT 236-285) with the N-terminus of cTnI. We performed molecular-dynamics (MD) simulations to elucidate the structural basis of PKA phosphorylation-induced changes in cTn structure and Ca(2+) binding. We found that introducing two phosphomimic mutations into sites S23/S24 had no significant effect on the coordinating residues of Ca(2+) binding site II. However, the overall fluctuation of cTn was increased and the C-I interaction was altered relative to the wild-type model. The most significant changes involved interactions with the N-terminus of cTnI. Interestingly, the phosphomimic mutations led to the formation of intrasubunit interactions between the N-terminus and the inhibitory peptide of cTnI. This may result in altered interactions with cTnC and could explain the increased rate and decreased duration of slow-phase relaxation seen in myofibrils.
    No preview · Article · Oct 2014 · Biophysical Journal
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    Full-text · Dataset · Sep 2014
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    ABSTRACT: Owing to recent developments in computational algorithms and architectures, it is now computationally tractable to explore biologically relevant, equilibrium dynamics of realistically-sized functional proteins using all-atom molecular dynamics simulations. Molecular dynamics simulations coupled with Markov state models is a nascent but rapidly growing technology that is enabling robust exploration of equilibrium dynamics. The objective of this work is to explore the challenges of coupling molecular dynamics simulations and Markov state models in the study of functional proteins. Using recent studies as a framework, we explore progress in sampling, model building, model selection, and coarse-grained analysis of models. Our goal is to highlight some of the current challenges in applying Markov state models to realistically-sized proteins and spur discussion on advances in the field.
    Full-text · Article · Jul 2014 · Journal of Chemical Theory and Computation
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    Jacob D Durrant · Rommie E Amaro
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    ABSTRACT: As ever larger and more complex biological systems are modeled in silico, approximating physiological lipid bilayers with simple planar models becomes increasingly unrealistic. In order to build accurate large-scale models of subcellular environments, models of lipid membranes with carefully considered, biologically relevant curvature will be essential. In the current work, we present a multi-scale utility called LipidWrapper capable of creating curved membrane models with geometries derived from various sources, both experimental and theoretical. To demonstrate its utility, we use LipidWrapper to examine an important mechanism of influenza virulence. A copy of the program can be downloaded free of charge under the terms of the open-source FreeBSD License from http://nbcr.ucsd.edu/lipidwrapper. LipidWrapper has been tested on all major computer operating systems.
    Preview · Article · Jul 2014 · PLoS Computational Biology

Publication Stats

1k Citations
316.78 Total Impact Points

Institutions

  • 2007-2015
    • University of California, San Diego
      • Department of Chemistry and Biochemistry
      San Diego, California, United States
  • 2009-2012
    • University of California, Irvine
      • • Department of Pharmaceutical Sciences
      • • Department of Computer Science
      Irvine, California, United States
  • 2001-2007
    • University of Illinois, Urbana-Champaign
      • • Department of Chemistry
      • • School of Chemical Sciences
      Urbana, IL, United States