Lane W. Votapka

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.

Weighted Implementation of Suboptimal Paths (WISP):An Optimized Algorithm and Tool for Dynamical Network Analysis

Allostery can occur by way of subtle cooperation among protein residues (e.g., amino acids) even in the absence of large conformational shifts. Dynamical network analysis has been used to model this cooperation, helping to computationally explain how binding to an allosteric site can impact the behavior of a primary site many ångstroms away. Traditionally, computational efforts have focused on the most optimal path of correlated motions leading from the allosteric to the primary active site. We present a program called Weighted Implementation of Suboptimal Paths (WISP) capable of rapidly identifying additional suboptimal pathways that may also play important roles in the transmission of allosteric signals. Aside from providing signal redundancy, suboptimal paths traverse residues that, if disrupted through pharmacological or mutational means, could modulate the allosteric regulation of important drug targets. To demonstrate the utility of our program, we present a case study describing the allostery of HisH-HisF, an amidotransferase from T. maritima thermotiga. WISP and its VMD-based graphical user interface (GUI) can be downloaded from http://nbcr.ucsd.edu/wisp.

Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning.

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.

Multistructural hot spot characterization with FTProd

UNLABELLED Computational solvent fragment mapping is typically performed on a single structure of a protein to identify and characterize binding sites. However, the simultaneous analysis of several mutant structures or frames of a molecular dynamics simulation may provide more realistic detail about the behavior of the sites. Here we present a plug-in for Visual Molecular Dynamics that streamlines the comparison of the binding configurations of several FTMAP-generated structures. AVAILABILITY FTProd is a freely available and open-source plug-in that can be downloaded at http://amarolab.ucsd.edu/ftprod.

Bridging scales through multiscale modeling: a case study on protein kinase A

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.

SEEKR: Simulation Enabled Estimation of Kinetic Rates, A Computational Tool to Estimate Molecular Kinetics and Its Application to Trypsin–Benzamidine Binding

We present the Simulation Enabled Estimation of Kinetic Rates (SEEKR) package, a suite of open-source scripts and tools designed to enable researchers to perform multiscale computation of the kinetics of molecular binding, unbinding, and transport using a combination of molecular dynamics, Brownian dynamics, and milestoning theory. To demonstrate its utility, we compute the kon, koff, and ΔGbind for the protein trypsin with its noncovalent binder, benzamidine, and examine the kinetics and other results generated in the context of the new software, and compare our findings to previous studies performed on the same system. We compute a kon estimate of (2.1 ± 0.3) × 107 M-1 s-1, a koff estimate of 83 ± 14 s-1, and a ΔGbind of -7.4 ± 0.1 kcal·mol-1, all of which compare closely to the experimentally measured values of 2.9 × 107 M-1 s-1, 600 ± 300 s-1, and -6.71 ± 0.05 kcal·mol-1, respectively.

Two Relations to Estimate Membrane Permeability Using Milestoning

Prediction of passive permeation rates of solutes across lipid bilayers is important to drug design, toxicology, and other biological processes such as signaling. The inhomogeneous solubility-diffusion (ISD) equation is traditionally used to relate the position-dependent potential of mean force and diffusivity to the permeability coefficient. The ISD equation is derived via the Smoluchowski equation and assumes overdamped system dynamics. It has been suggested that the complex membrane environment may exhibit more complicated damping conditions. Here we derive a variant of the inhomogeneous solubility diffusion equation as a function of the mean first passage time (MFPT) and show how milestoning, a method that can estimate kinetic quantities of interest, can be used to estimate the MFPT of membrane crossing and, by extension, the permeability coefficient. We further describe a second scheme, agnostic to the damping condition, to estimate the permeability coefficient from milestoning results or other methods that compute a probability of membrane crossing. The derived relationships are tested using a one-dimensional Langevin dynamics toy system confirming that the presented theoretical methods can be used to estimate permeabilities given simulation and milestoning results.

38 Multiscale estimation of binding kinetics using molecular dynamics, brownian dynamics, and milestoning

maps. T7 promoters are known to be classified into two groups (class II and class III) by their location in the genome, time of their expression and functional behaviour. For comparative study 2D electrostatic maps of each class promoters were averaged and the “consensus” maps were analysed by their spatial match with the PBC electrostatic pattern of RNAP. There was observed a good correlation in spatial organisation of positively charged crests of RNAP and negatively charged specific elements of the promoter DNA. However it is interesting that different set of electrostatic interactions were found to be involved in complex formation of RNAP with T7 promoters belonging to different classes. Differential character in the topology of electrostatic T7 RNA polymerase – promoter DNA interactions can be provided due to the presence of three different positively charged sites in the enzyme binding to different parts of the promoter DNA. The difference in the electrostatic arrangement of the primary complex formed by the different T7 promoter classes may affect the pathway and the rate of formation of the final active complex thus suggesting a reasonable explanation for the difference in “strength” and functional behaviour of the promoters belonging to the different classes.

Variable ligand- and receptor-binding hot spots in key strains of influenza neuraminidase

Influenza A continues to be a major public health concern due to its ability to cause epidemic and pandemic disease outbreaks in humans. Computational investigations of structural dynamics of the major influenza glycoproteins, especially the neuraminidase (NA) enzyme, are able to provide key insights beyond what is currently accessible with standard experimental techniques. In particular, all-atom molecular dynamics simulations reveal the varying degrees of flexibility for such enzymes. Here we present an analysis of the relative flexibility of the ligand- and receptor-binding area of three key strains of influenza A: highly pathogenic H5N1, the 2009 pandemic H1N1, and a human N2 strain. Through computational solvent mapping, we investigate the various ligand- and receptor-binding “hot spots” that exist on the surface of NA which interacts with both sialic acid receptors on the host cells and antiviral drugs. This analysis suggests that the variable cavities found in the different strains and their corresponding capacities to bind ligand functional groups may play an important role in the ability of NA to form competent reaction encounter complexes with other species of interest, including antiviral drugs, sialic acid receptors on the host cell surface, and the hemagglutinin protein. Such considerations may be especially useful for the prediction of how such complexes form and with what binding capacity.