Robert V. Swift

Mechanism of 150-cavity formation in influenza neuraminidase

The recently discovered 150-cavity in the active site of group-1 influenza A neuraminidase (NA) proteins provides a target for rational structure-based drug development to counter the increasing frequency of antiviral resistance in influenza. Surprisingly, the 2009 H1N1 pandemic virus (09N1) neuramidase was crystalized without the 150-cavity characteristic of group-1 NAs. Here we demonstrate, through a total sum of 1.6 μs of biophysical simulations, that 09N1 NA exists in solution preferentially with an open 150-cavity. Comparison with simulations using avian N1, human N2 and 09N1 with a I149V mutation and an extensive bioinformatics analysis suggests that the conservation of a key salt bridge is crucial in the stabilization of the 150-cavity across both subtypes. This result provides an atomic-level structural understanding of the recent finding that antiviral compounds designed to take advantage of contacts in the 150-cavity can inactivate both 2009 H1N1 pandemic and avian H5N1 viruses.

Back to the Future: Can Physical Models of Passive Membrane Permeability Help Reduce Drug Candidate Attrition and Move Us Beyond QSPR?

It is widely recognized that adsorption, distribution, metabolism, excretion, and toxicology liabilities kill the majority of drug candidates that progress to clinical trials. The development of computational models to predict small molecule membrane permeability is therefore of considerable scientific and public health interest. Empirical qualitative structure permeability relationship models of permeability have been a mainstay in industrial applications, but lack a deep understanding of the underlying biologic physics. Others and we have shown that implicit solvent models to predict passive permeability for small molecules exhibit mediocre predictive performance when validated across experimental test sets. Given the vast increase in computer power, more efficient parallelization schemes, and extension of current atomistic simulation codes to general use graphical processing units, the development and application of physical models based on all‐atom simulations may now be feasible. Preliminary results from rigorous free energy calculations using all‐atom simulations indicate that performance relative to implicit solvent models may be improved, but many outstanding questions remain. Here, we review the current state‐of‐the‐art physical models for passive membrane permeability prediction and present a prospective look at promising new directions for all‐atom approaches.

Novel Naphthalene-Based Inhibitors of Trypanosoma brucei RNA Editing Ligase 1

Background Neglected tropical diseases, including diseases caused by trypanosomatid parasites such as Trypanosoma brucei, cost tens of millions of disability-adjusted life-years annually. As the current treatments for African trypanosomiasis and other similar infections are limited, new therapeutics are urgently needed. RNA Editing Ligase 1 (REL1), a protein unique to trypanosomes and other kinetoplastids, was identified recently as a potential drug target. Methodology/Principal Findings Motivated by the urgent need for novel trypanocidal therapeutics, we use an ensemble-based virtual-screening approach to discover new naphthalene-based TbREL1 inhibitors. The predicted binding modes of the active compounds are evaluated within the context of the flexible receptor model and combined with computational fragment mapping to determine the most likely binding mechanisms. Ultimately, four new low-micromolar inhibitors are presented. Three of the four compounds may bind to a newly revealed cleft that represents a putative druggable site not evident in any crystal structure. Conclusions/Significance Pending additional optimization, the compounds presented here may serve as precursors for future novel therapies useful in the fight against several trypanosomatid pathogens, including human African trypanosomiasis, a devastating disease that afflicts the vulnerable patient populations of sub-Saharan Africa.

Simulation-Based Approaches for Determining Membrane Permeability of Small Compounds.

Predicting the rate of nonfacilitated permeation of solutes across lipid bilayers is important to drug design, toxicology, and signaling. These rates can be estimated using molecular dynamics simulations combined with the inhomogeneous solubility-diffusion model, which requires calculation of the potential of mean force and position-dependent diffusivity of the solute along the transmembrane axis. In this paper, we assess the efficiency and accuracy of several methods for the calculation of the permeability of a model DMPC bilayer to urea, benzoic acid, and codeine. We compare umbrella sampling, replica exchange umbrella sampling, adaptive biasing force, and multiple-walker adaptive biasing force for the calculation of the transmembrane PMF. No definitive advantage for any of these methods in their ability to predict the membrane permeability coefficient Pm was found, provided that a sufficiently long equilibration is performed. For diffusivities, a Bayesian inference method was compared to a generalized Langevin method, both being sensitive to chosen parameters and the slow relaxation of membrane defects. Agreement within 1.5 log units of the computed Pm with experiment is found for all permeants and methods. Remaining discrepancies can likely be attributed to limitations of the force field as well as slowly relaxing collective movements within the lipid environment. Numerical calculations based on model profiles show that Pm can be reliably estimated from only a few data points, leading to recommendations for calculating Pm from simulations.

Using multistate free energy techniques to improve the efficiency of replica exchange accelerated molecular dynamics

Replica exchange accelerated molecular dynamics (REXAMD) is a method that enhances conformational sampling while retaining at least one replica on the original potential, thus avoiding the statistical problems of exponential reweighting. In this article, we study three methods that can combine the data from the accelerated replicas to enhance the estimate of properties on the original potential: weighted histogram analysis method (WHAM), pairwise multistate Bennett acceptance ratio (PBAR), and multistate Bennett acceptance ratio (MBAR). We show that the method that makes the most efficient use of equilibrium data from REXAMD simulations is the MBAR method. This observation holds for both alchemical free energy and structural observable prediction. The combination of REXAMD and MBAR should allow for more efficient scaling of the REXAMD method to larger biopolymer systems.

Substrate Induced Population Shifts and Stochastic Gating in the PBCV-1 mRNA Capping Enzyme

The 317 residue PBCV-1 mRNA capping enzyme catalyzes the second enzymatic reaction in the formation of an N-7-methyl-GMP cap on the 5′-end of the nascent mRNA. It is composed of two globular domains bound by a short flexible peptide linker, which have been shown to undergo opening and closing events. The small size and experimentally demonstrated domain mobility make the PBCV-1 capping enzyme an ideally suited model system to explore domain mobility in context of substrate binding. Here, we specifically address the following four questions: (1) How does substrate binding affect relative domain mobility: is the system better described by an induced fit or population shift mechanism? (2) What are the gross characteristics of a conformation capable of binding substrate? (3) Does “domain gating” of the active site affect the rate of substrate binding? (4) Does the magnitude of receptor conformational fluctuations confer substrate specificity by sterically occluding molecules of a particular size or geometry? We answer these questions using a combination of theory, Brownian dynamics, and molecular dynamics. Our results show that binding efficiency is a function of conformation but that isomerization between efficient and inefficient binding conformations does not impact the substrate association rate. Additionally, we show that conformational flexibility alone is insufficient to explain single stranded mRNA specificity. While our results are specific to the PBCV-1 mRNA capping enzyme, they provide a useful context within which the substrate binding behavior of similarly structured enzymes or proteins may be considered.

Rational prediction with molecular dynamics for hit identification.

Although the motions of proteins are fundamental for their function, for pragmatic reasons, the consideration of protein elasticity has traditionally been neglected in drug discovery and design. This review details protein motion, its relevance to biomolecular interactions and how it can be sampled using molecular dynamics simulations. Within this context, two major areas of research in structure-based prediction that can benefit from considering protein flexibility, binding site detection and molecular docking, are discussed. Basic classification metrics and statistical analysis techniques, which can facilitate performance analysis, are also reviewed. With hardware and software advances, molecular dynamics in combination with traditional structure-based prediction methods can potentially reduce the time and costs involved in the hit identification pipeline.

Functional and Structural Insights Revealed by Molecular Dynamics Simulations of an Essential RNA Editing Ligase in Trypanosoma brucei

RNA editing ligase 1 (TbREL1) is required for the survival of both the insect and bloodstream forms of Trypanosoma brucei, the parasite responsible for the devastating tropical disease African sleeping sickness. The type of RNA editing that TbREL1 is involved in is unique to the trypanosomes, and no close human homolog is known to exist. In addition, the high-resolution crystal structure revealed several unique features of the active site, making this enzyme a promising target for structure-based drug design. In this work, two 20 ns atomistic molecular dynamics (MD) simulations are employed to investigate the dynamics of TbREL1, both with and without the ATP substrate present. The flexibility of the active site, dynamics of conserved residues and crystallized water molecules, and the interactions between TbREL1 and the ATP substrate are investigated and discussed in the context of TbREL1s function. Differences in local and global motion upon ATP binding suggest that two peripheral loops, unique to the trypanosomes, may be involved in interdomain signaling events. Notably, a significant structural rearrangement of the enzymes active site occurs during the apo simulations, opening an additional cavity adjacent to the ATP binding site that could be exploited in the development of effective inhibitors directed against this protozoan parasite. Finally, ensemble averaged electrostatics calculations over the MD simulations reveal a novel putative RNA binding site, a discovery that has previously eluded scientists. Ultimately, we use the insights gained through the MD simulations to make several predictions and recommendations, which we anticipate will help direct future experimental studies and structure-based drug discovery efforts against this vital enzyme.

Biochemical, Structural and Molecular Dynamics Analyses of the Potential Virulence Factor RipA from Yersinia pestis

Human diseases are attributed in part to the ability of pathogens to evade the eukaryotic immune systems. A subset of these pathogens has developed mechanisms to survive in human macrophages. Yersinia pestis, the causative agent of the bubonic plague, is a predominately extracellular pathogen with the ability to survive and replicate intracellularly. A previous study has shown that a novel rip (required for intracellular proliferation) operon (ripA, ripB and ripC) is essential for replication and survival of Y. pestis in postactivated macrophages, by playing a role in lowering macrophage-produced nitric oxide (NO) levels. A bioinformatics analysis indicates that the rip operon is conserved among a distally related subset of macrophage-residing pathogens, including Burkholderia and Salmonella species, and suggests that this previously uncharacterized pathway is also required for intracellular survival of these pathogens. The focus of this study is ripA, which encodes for a protein highly homologous to 4-hydroxybutyrate-CoA transferase; however, biochemical analysis suggests that RipA functions as a butyryl-CoA transferase. The 1.9 Å X-ray crystal structure reveals that RipA belongs to the class of Family I CoA transferases and exhibits a unique tetrameric state. Molecular dynamics simulations are consistent with RipA tetramer formation and suggest a possible gating mechanism for CoA binding mediated by Val227. Together, our structural characterization and molecular dynamic simulations offer insights into acyl-CoA specificity within the active site binding pocket, and support biochemical results that RipA is a butyryl-CoA transferase. We hypothesize that the end product of the rip operon is butyrate, a known anti-inflammatory, which has been shown to lower NO levels in macrophages. Thus, the results of this molecular study of Y. pestis RipA provide a structural platform for rational inhibitor design, which may lead to a greater understanding of the role of RipA in this unique virulence pathway.

Modeling the pharmacodynamics of passive membrane permeability

Small molecule permeability through cellular membranes is critical to a better understanding of pharmacodynamics and the drug discovery endeavor. Such permeability may be estimated as a function of the free energy change of barrier crossing by invoking the barrier domain model, which posits that permeation is limited by passage through a single “barrier domain” and assumes diffusivity differences among compounds of similar structure are negligible. Inspired by the work of Rezai and co-workers (JACS 128:14073–14080, 2006), we estimate this free energy change as the difference in implicit solvation free energies in chloroform and water, but extend their model to include solute conformational affects. Using a set of eleven structurally diverse FDA approved compounds and a set of thirteen congeneric molecules, we show that the solvation free energies are dominated by the global minima, which allows solute conformational distributions to be effectively neglected. For the set of tested compounds, the best correlation with experiment is obtained when the implicit chloroform global minimum is used to evaluate the solvation free energy difference.