Michael S. Lee

An efficient hybrid explicit/implicit solvent method for biomolecular simulations†

We present a new hybrid explicit/implicit solvent method for dynamics simulations of macromolecular systems. The method models explicitly the hydration of the solute by either a layer or sphere of water molecules, and the generalized Born (GB) theory is used to treat the bulk continuum solvent outside the explicit simulation volume. To reduce the computational cost, we implemented a multigrid method for evaluating the pairwise electrostatic and GB terms. It is shown that for typical ion and protein simulations our method achieves similar equilibrium and dynamical observables as the conventional particle mesh Ewald (PME) method. Simulation timings are reported, which indicate that the hybrid method is much faster than PME, primarily due to a significant reduction in the number of explicit water molecules required to model hydration effects.

In Silico Derived Small Molecules Bind the Filovirus VP35 Protein and Inhibit Its Polymerase Cofactor Activity

The Ebola virus (EBOV) genome only encodes a single viral polypeptide with enzymatic activity, the viral large (L) RNA-dependent RNA polymerase protein. However, currently, there is limited information about the L protein, which has hampered the development of antivirals. Therefore, antifiloviral therapeutic efforts must include additional targets such as protein-protein interfaces. Viral protein 35 (VP35) is multifunctional and plays important roles in viral pathogenesis, including viral mRNA synthesis and replication of the negative-sense RNA viral genome. Previous studies revealed that mutation of key basic residues within the VP35 interferon inhibitory domain (IID) results in significant EBOV attenuation, both in vitro and in vivo. In the current study, we use an experimental pipeline that includes structure-based in silico screening and biochemical and structural characterization, along with medicinal chemistry, to identify and characterize small molecules that target a binding pocket within VP35. NMR mapping experiments and high-resolution x-ray crystal structures show that select small molecules bind to a region of VP35 IID that is important for replication complex formation through interactions with the viral nucleoprotein (NP). We also tested select compounds for their ability to inhibit VP35 IID-NP interactions in vitro as well as VP35 function in a minigenome assay and EBOV replication. These results confirm the ability of compounds identified in this study to inhibit VP35-NP interactions in vitro and to impair viral replication in cell-based assays. These studies provide an initial framework to guide development of antifiloviral compounds against filoviral VP35 proteins.

Small Molecule Probes Targeting the Viral PPxY-Host Nedd4 Interface Block Egress of a Broad Range of RNA Viruses

ABSTRACT Budding of filoviruses, arenaviruses, and rhabdoviruses is facilitated by subversion of host proteins, such as Nedd4 E3 ubiquitin ligase, by viral PPxY late (L) budding domains expressed within the matrix proteins of these RNA viruses. As L domains are important for budding and are highly conserved in a wide array of RNA viruses, they represent potential broad-spectrum targets for the development of antiviral drugs. To identify potential competitive blockers, we used the known Nedd4 WW domain-PPxY interaction interface as the basis of an in silico screen. Using PPxY-dependent budding of Marburg (MARV) VP40 virus-like particles (VLPs) as our model system, we identified small-molecule hit 1 that inhibited Nedd4-PPxY interaction and PPxY-dependent budding. This lead candidate was subsequently improved with additional structure-activity relationship (SAR) analog testing which enhanced antibudding activity into the nanomolar range. Current lead compounds 4 and 5 exhibit on-target effects by specifically blocking the MARV VP40 PPxY-host Nedd4 interaction and subsequent PPxY-dependent egress of MARV VP40 VLPs. In addition, lead compounds 4 and 5 exhibited antibudding activity against Ebola and Lassa fever VLPs, as well as vesicular stomatitis and rabies viruses (VSV and RABV, respectively). These data provide target validation and suggest that inhibition of the PPxY-Nedd4 interaction can serve as the basis for the development of a novel class of broad-spectrum, host-oriented antivirals targeting viruses that depend on a functional PPxY L domain for efficient egress. IMPORTANCE There is an urgent and unmet need for the development of safe and effective therapeutics against biodefense and high-priority pathogens, including filoviruses (Ebola and Marburg) and arenaviruses (e.g., Lassa and Junin) which cause severe hemorrhagic fever syndromes with high mortality rates. We along with others have established that efficient budding of filoviruses, arenaviruses, and other viruses is critically dependent on the subversion of host proteins. As disruption of virus budding would prevent virus dissemination, identification of small-molecule compounds that block these critical viral-host interactions should effectively block disease progression and transmission. Our findings provide validation for targeting these virus-host interactions as we have identified lead inhibitors with broad-spectrum antiviral activity. In addition, such inhibitors might prove useful for newly emerging RNA viruses for which no therapeutics would be available.

Comparison of two adaptive temperature-based replica exchange methods applied to a sharp phase transition of protein unfolding-folding

Temperature-based replica exchange (T-ReX) enhances sampling of molecular dynamics simulations by autonomously heating and cooling simulation clients via a Metropolis exchange criterion. A pathological case for T-ReX can occur when a change in state (e.g., folding to unfolding of a protein) has a large energetic difference over a short temperature interval leading to insufficient exchanges amongst replica clients near the transition temperature. One solution is to allow the temperature set to dynamically adapt in the temperature space, thereby enriching the population of clients near the transition temperature. In this work, we evaluated two approaches for adapting the temperature set: a method that equalizes exchange rates over all neighbor temperature pairs and a method that attempts to induce clients to visit all temperatures (dubbed current maximization) by positioning many clients at or near the transition temperature. As a test case, we simulated the 57-residue SH3 domain of alpha-spectrin. Exchange rate equalization yielded the same unfolding-folding transition temperature as fixed-temperature ReX with much smoother convergence of this value. Surprisingly, the current maximization method yielded a significantly lower transition temperature, in close agreement with experimental observation, likely due to more extensive sampling of the transition state.

Comparison between self-guided Langevin dynamics and molecular dynamics simulations for structure refinement of protein loop conformations†

This article presents a comparative analysis of two replica‐exchange simulation methods for the structure refinement of protein loop conformations, starting from low‐resolution predictions. The methods are self‐guided Langevin dynamics (SGLD) and molecular dynamics (MD) with a Nosé–Hoover thermostat. We investigated a small dataset of 8‐ and 12‐residue loops, with the shorter loops placed initially from a coarse‐grained lattice model and the longer loops from an enumeration assembly method (the Loopy program). The CHARMM22 + CMAP force field with a generalized Born implicit solvent model (molecular‐surface parameterized GBSW2) was used to explore conformational space. We also assessed two empirical scoring methods to detect nativelike conformations from decoys: the all‐atom distance‐scaled ideal‐gas reference state (DFIRE‐AA) statistical potential and the Rosetta energy function. Among the eight‐residue loop targets, SGLD out performed MD in all cases, with a median of 0.48 Å reduction in global root‐mean‐square deviation (RMSD) of the loop backbone coordinates from the native structure. Among the more challenging 12‐residue loop targets, SGLD improved the prediction accuracy over MD by a median of 1.31 Å, representing a substantial improvement. The overall median RMSD for SGLD simulations of 12‐residue loops was 0.91 Å, yielding refinement of a median 2.70 Å from initial loop placement. Results from DFIRE‐AA and the Rosetta model applied to rescoring conformations failed to improve the overall detection calculated from the CHARMM force field. We illustrate the advantage of SGLD over the MD simulation model by presenting potential‐energy landscapes for several loop predictions. Our results demonstrate that SGLD significantly outperforms traditional MD in the generation and populating of nativelike loop conformations and that the CHARMM force field performs comparably to other empirical force fields in identifying these conformations from the resulting ensembles. Published 2011 Wiley Periodicals, Inc. J Comput Chem, 2011

A Host-Oriented Inhibitor of Junin Argentine Hemorrhagic Fever Virus Egress

ABSTRACT There are currently no U.S. Food and Drug Administration (FDA)-approved vaccines or therapeutics to prevent or treat Argentine hemorrhagic fever (AHF). The causative agent of AHF is Junin virus (JUNV); a New World arenavirus classified as a National Institute of Allergy and Infectious Disease/Centers for Disease Control and Prevention category A priority pathogen. The PTAP late (L) domain motif within JUNV Z protein facilitates virion egress and transmission by recruiting host Tsg101 and other ESCRT complex proteins to promote scission of the virus particle from the plasma membrane. Here, we describe a novel compound (compound 0013) that blocks the JUNV Z-Tsg101 interaction and inhibits budding of virus-like particles (VLPs) driven by ectopic expression of the Z protein and live-attenuated JUNV Candid-1 strain in cell culture. Since inhibition of the PTAP-Tsg101 interaction inhibits JUNV egress, compound 0013 serves as a prototype therapeutic that could reduce virus dissemination and disease progression in infected individuals. Moreover, since PTAP l-domain-mediated Tsg101 recruitment is utilized by other RNA virus pathogens (e.g., Ebola virus and HIV-1), PTAP inhibitors such as compound 0013 have the potential to function as potent broad-spectrum, host-oriented antiviral drugs. IMPORTANCE There are currently no FDA-approved vaccines or therapeutics to prevent or treat Argentine hemorrhagic fever (AHF). The causative agent of AHF is Junin virus (JUNV); a New World arenavirus classified as an NIAID/CDC category A priority pathogen. Here, we describe a prototype therapeutic that blocks budding of JUNV and has the potential to function as a broad-spectrum antiviral drug.

Structure refinement of protein model decoys requires accurate side‐chain placement

In this study, the application of temperature‐based replica‐exchange (T‐ReX) simulations for structure refinement of decoys taken from the I‐TASSER dataset was examined. A set of eight nonredundant proteins was investigated using self‐guided Langevin dynamics (SGLD) with a generalized Born implicit solvent model to sample conformational space. For two of the protein test cases, a comparison of the SGLD/T‐ReX method with that of a hybrid explicit/implicit solvent molecular dynamics T‐ReX simulation model is provided. Additionally, the effect of side‐chain placement among the starting decoy structures, using alternative rotamer conformations taken from the SCWRL4 modeling program, was investigated. The simulation results showed that, despite having near‐native backbone conformations among the starting decoys, the determinant of their refinement is side‐chain packing to a level that satisfies a minimum threshold of native contacts to allow efficient excursions toward the downhill refinement regime on the energy landscape. By repacking using SCWRL4 and by applying the RWplus statistical potential for structure identification, the SGLD/T‐ReX simulations achieved refinement to an average of 38% increase in the number of native contacts relative to the original I‐TASSER decoy sets and a 25% reduction in values of Cα root‐mean‐square deviation. The hybrid model succeeded in obtaining a sharper funnel to low‐energy states for a modeled target than the implicit solvent SGLD model; yet, structure identification remained roughly the same. Without meeting a threshold of near‐native packing of side chains, the T‐ReX simulations degrade the accuracy of the decoys, and subsequently, refinement becomes tantamount to the protein folding problem. Proteins 2013. 2012 Published by Wiley Periodicals, Inc.

PSPP: a protein structure prediction pipeline for computing clusters.

Background Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a users own high-performance computing cluster. Methodology/Principal Findings The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP) fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML) formats. So far, the pipeline has been used to study viral and bacterial proteomes. Conclusions The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform resource-intensive ab initio structure prediction.

Fold prediction of VP24 protein of Ebola and Marburg viruses using de novo fragment assembly

Virus particle 24 (VP24) is the smallest protein of the Ebola and Marburg virus genomes. Recent experiments show that Ebola VP24 blocks binding of tyrosine-phosphorylated STAT-1 homodimer (PY-STAT1) to the NPI-1 subfamily of importin alpha, thereby preventing nuclear accumulation of this interferon-promoting transcription factor which, in turn, reduces the innate immune response of the host target. Lacking an experimental structure for VP24, we applied de novo protein structure prediction using the fragment assembly-based Rosetta method to classify its fold topology and better understand its biological function. Filtering and ranking of models were performed with the DFIRE all-atom statistical potential and the CHARMM22 force field with a generalized Born solvent model. From 40,000 Rosetta-generated structures and selective comparisons with the SCOP database, a structural match to two of our top 10-ranking models was the Armadillo repeat fold topology. Specific members of this fold family include importin alpha, importin beta, and exportin. We propose that, unlike the nuclear import of host cargo, VP24 lacks a classical nuclear localization signal (NLS) and targets importin alpha in a similar manner to the observed heterodimeric complex with exportin, thereby interfering with the auto-inhibitory NLS on importin alpha and blocking peripheral docking sites for PY-STAT1 assembly.

Free-Energy Profiles of Membrane Insertion of the M2 Transmembrane Peptide from Influenza A Virus

The insertion of the M2 transmembrane peptide from influenza A virus into a membrane has been studied with molecular-dynamics simulations. This system is modeled by an atomically detailed peptide interacting with a continuum representation of a membrane bilayer in aqueous solution. We performed replica-exchange molecular-dynamics simulations with umbrella-sampling techniques to characterize the probability distribution and conformation preference of the peptide in the solution, at the membrane interface, and in the membrane. The minimum in the calculated free-energy surface of peptide insertion corresponds to a fully inserted, helical peptide spanning the membrane. The free-energy profile also shows that there is a significant barrier for the peptide to enter into this minimum in a nonhelical conformation. The sequence of the peptide is such that hydrophilic amino acid residues at the ends of the otherwise primarily hydrophobic peptide create a trapped, U-shaped conformation with the hydrophilic residues associated with the aqueous phase and the hydrophobic residues embedded in the membrane. Analysis of the free energy shows that the barrier to insertion is largely enthalpic in nature, whereas the membrane-spanning global minimum is favored by entropy.