A topological data analytic approach for discovering biophysical signatures in protein dynamics

Identifying structural differences among proteins can be a non-trivial task. When contrasting ensembles of protein structures obtained from molecular dynamics simulations, biologically-relevant features can be easily overshadowed by spurious fluctuations. Here, we present SINATRA Pro, a computational pipeline designed to robustly identify topological differences between two sets of protein structures. Algorithmically, SINATRA Pro works by first taking in the 3D atomic coordinates for each protein snapshot and summarizing them according to their underlying topology. Statistically significant topological features are then projected back onto a user-selected representative protein structure, thus facilitating the visual identification of biophysical signatures of different protein ensembles. We assess the ability of SINATRA Pro to detect minute conformational changes in five independent protein systems of varying complexities. In all test cases, SINATRA Pro identifies known structural features that have been validated by previous experimental and computational studies, as well as novel features that are also likely to be biologically-relevant according to the literature. These results highlight SINATRA Pro as a promising method for facilitating the non-trivial task of pattern recognition in trajectories resulting from molecular dynamics simulations, with substantially increased resolution.     

Structural features that predict real-value fluctuations of globular proteins

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B‐factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Proteins 2012; © 2012 Wiley Periodicals, Inc.     

Incorporating replacement free energy of binding‐site waters in molecular docking

Binding‐site water molecules play a crucial role in protein‐ligand recognition, either being displaced upon ligand binding or forming water bridges to stabilize the complex. However, rigorously treating explicit binding‐site waters is challenging in molecular docking, which requires to fully sample ensembles of waters and to consider the free energy cost of replacing waters. Here, we describe a method to incorporate structural and energetic properties of binding‐site waters into molecular docking. We first developed a solvent property analysis (SPA) program to compute the replacement free energies of binding‐site water molecules by post‐processing molecular dynamics trajectories obtained from ligand‐free protein structure simulation in explicit water. Next, we implemented a distance‐dependent scoring term into DOCK scoring function to take account of the water replacement free energy cost upon ligand binding. We assessed this approach in protein targets containing important binding‐site waters, and we demonstrated that our approach is reliable in reproducing the crystal binding geometries of protein‐ligand‐water complexes, as well as moderately improving the ligand docking enrichment performance. In addition, SPA program (free available to academic users upon request) may be applied in identifying hot‐spot binding‐site residues and structure‐based lead optimization. Proteins 2014; 82:1765–1776. © 2014 Wiley Periodicals, Inc.     

Visualizing global properties of a molecular dynamics trajectory

Molecular dynamics (MD) trajectories are very large data sets that contain substantial information about the dynamic behavior of a protein. Condensing these data into a form that can provide intuitively useful understanding of the molecular behavior during the trajectory is a substantial challenge that has received relatively little attention. Here, we introduce the sigma‐r plot, a plot of the standard deviation of intermolecular distances as a function of that distance. This representation of global dynamics contains within a single, one‐dimensional plot, the average range of motion between pairs of atoms within a macromolecule. Comparison of sigma‐r plots calculated from 10 ns trajectories of proteins representing the four major SCOP fold classes indicates diversity of dynamic behaviors which are recognizably different among the four classes. Differences in domain structure and molecular weight also produce recognizable features in sigma‐r plots, reflective of differences in global dynamics. Plots generated from trajectories with progressively increasing simulation time reflect the increased sampling of the structural ensemble as a function of time. Single amino acid replacements can give rise to changes in global dynamics detectable through comparison of sigma‐r plots. Dynamic behavior of substructures can be monitored by careful choice of interatomic vectors included in the calculation. These examples provide demonstrations of the utility of the sigma‐r plot to provide a simple measure of the global dynamics of a macromolecule. Proteins 2016; 84:82–91. © 2015 Wiley Periodicals, Inc.     

DockTrina: Docking triangular protein trimers

In spite of the abundance of oligomeric proteins within a cell, the structural characterization of protein–protein interactions is still a challenging task. In particular, many of these interactions involve heteromeric complexes, which are relatively difficult to determine experimentally. Hence there is growing interest in using computational techniques to model such complexes. However, assembling large heteromeric complexes computationally is a highly combinatorial problem. Nonetheless the problem can be simplified greatly by considering interactions between protein trimers. After dimers and monomers, triangular trimers (i.e. trimers with pair‐wise contacts between all three pairs of proteins) are the most frequently observed quaternary structural motifs according to the three‐dimensional (3D) complex database. This article presents DockTrina, a novel protein docking method for modeling the 3D structures of nonsymmetrical triangular trimers. The method takes as input pair‐wise contact predictions from a rigid body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation test. Finally, it ranks the predictions using a scoring function which combines triples of pair‐wise contact terms and a geometric clash penalty term. The overall approach takes less than 2 min per complex on a modern desktop computer. The method is tested and validated using a benchmark set of 220 bound and seven unbound protein trimer structures. DockTrina will be made available at http://nano‐d.inrialpes.fr/software/docktrina . Proteins 2014; 82:34–44. © 2013 Wiley Periodicals, Inc.     

Validation of protein structure models using network similarity score

Accurate structural validation of proteins is of extreme importance in studies like protein structure prediction, analysis of molecular dynamic simulation trajectories and finding subtle changes in very similar structures. The benchmarks for today's structure validation are scoring methods like global distance test‐total structure (GDT‐TS), TM‐score and root mean square deviations (RMSD). However, there is a lack of methods that look at both the protein backbone and side‐chain structures at the global connectivity level and provide information about the differences in connectivity. To address this gap, a graph spectral based method (NSS—network similarity score) which has been recently developed to rigorously compare networks in diverse fields, is adopted to compare protein structures both at the backbone and at the side‐chain noncovalent connectivity levels. In this study, we validate the performance of NSS by investigating protein structures from X‐ray structures, modeling (including CASP models), and molecular dynamics simulations. Further, we systematically identify the local and the global regions of the structures contributing to the difference in NSS, through the components of the score, a feature unique to this spectral based scoring scheme. It is demonstrated that the method can quantify subtle differences in connectivity compared to a reference protein structure and can form a robust basis for protein structure comparison. Additionally, we have also introduced a network‐based method to analyze fluctuations in side chain interactions (edge‐weights) in an ensemble of structures, which can be an useful tool for the analysis of MD trajectories.     

NMR structures of polytopic integral membrane proteins

Abstract

Membrane proteins represent up to 30% of the proteins in all organisms, they are involved in many biological processes and are the molecular targets for around 50% of validated drugs. Despite this, membrane proteins represent less than 1% of all high-resolution protein structures due to various challenges associated with applying the main biophysical techniques used for protein structure determination. Recent years have seen an explosion in the number of high-resolution structures of membrane proteins determined by NMR spectroscopy, especially for those with multiple transmembrane-spanning segments. This is a review of the structures of polytopic integral membrane proteins determined by NMR spectroscopy up to the end of the year 2010, which includes both β-barrel and α-helical proteins from a number of different organisms and with a range in types of function. It also considers the challenges associated with performing structural studies by NMR spectroscopy on membrane proteins and how some of these have been overcome, along with its exciting potential for contributing new knowledge about the molecular mechanisms of membrane proteins, their roles in human disease, and for assisting drug design.     

Structure and dynamics of DRD4 bound to an agonist and an antagonist using in silico approaches

Human dopamine receptor D4 (DRD4), a member of G‐protein coupled receptor (GPCR) family, plays a central role in cell signaling and trafficking. Dysfunctional activity of DRD4 can lead to several psychiatric conditions and, therefore, represents target for many neurological disorders. However, lack of atomic structure impairs our understanding of the mechanism regulating its activity. Here, we report the modeled structure of DRD4 alone and in complex with dopamine and spiperone, its natural agonist and antagonist, respectively. To assess the conformational dynamics induced upon ligand binding, all‐atom explicit solvent molecular dynamics simulations in membrane environment were performed. Comprehensive analyses of simulations reveal that agonist binding triggers a series of conformational changes in the transmembrane region, including rearrangement of residues, characteristic of transmission and tyrosine toggle molecular switches. Further, the trajectories indicate that a loop region in the intracellular region––ICL3, is significantly dynamic in nature, mainly due to the side‐chain movements of conserved proline residues involved in SH3 binding domains. Interestingly, in dopamine‐bound receptor simulation, ICL3 represents an open conformation ideal for G protein binding. The structural and dynamical information presented here suggest a mode of activation of DRD4, upon ligand binding. Our study will help in further understanding of receptor activation, as acquiring structural information is crucial for the design of highly selective DRD4 ligands. Proteins 2014; 83:867–880. © 2014 Wiley Periodicals, Inc.     

Concerted motions in copper plastocyanin and azurin: an essential dynamics study

Essential dynamics analysis of molecular dynamics simulation trajectories (1.1 ns) of two copper containing electron transfer proteins, plastocyanin and azurin, has been performed. The protein essential modes have been analysed in order to identify large concerted motions which could be relevant for the electron transfer function exerted by these proteins. The analysis, conducted for temporal windows of different lengths along the protein trajectories, shows a rapid convergence and indicates that for both the proteins the predominant internal motions occur in a subspace of only a few degrees of freedom. Moreover, it is found that for both the proteins the likely binding sites (i.e. the hydrophobic and negative patches) with the reaction partners move in a concerted fashion with a few structural regions far from the active site. Such results are discussed in connection with the possible involvement of large concerted motions in the recognition and binding interaction with physiological electron transfer partners.     

Right‐ and left‐handed three‐helix proteins. II. Similarity and differences in mechanical unfolding of proteins

Here, we study mechanical properties of eight 3‐helix proteins (four right‐handed and four left‐handed ones), which are similar in size under stretching at a constant speed and at a constant force on the atomic level using molecular dynamics simulations. The analysis of 256 trajectories from molecular dynamics simulations with explicit water showed that the right‐handed three‐helix domains are more mechanically resistant than the left‐handed domains. Such results are observed at different extension velocities studied (192 trajectories obtained at the following conditions: v = 0.1, 0.05, and 0.01 Å ps^?1, T = 300 K) and under constant stretching force (64 trajectories, F = 800 pN, T = 300 K). We can explain this by the fact, at least in part, that the right‐handed domains have a larger number of contacts per residue and the radius of cross section than the left‐handed domains. Proteins 2014; 82:90–102. © 2013 Wiley Periodicals, Inc.     

FF12MC: A revised AMBER forcefield and new protein simulation protocol

Specialized to simulate proteins in molecular dynamics (MD) simulations with explicit solvation, FF12MC is a combination of a new protein simulation protocol employing uniformly reduced atomic masses by tenfold and a revised AMBER forcefield FF99 with (i) shortened C? H bonds, (ii) removal of torsions involving a nonperipheral sp³ atom, and (iii) reduced 1–4 interaction scaling factors of torsions ? and ψ. This article reports that in multiple, distinct, independent, unrestricted, unbiased, isobaric–isothermal, and classical MD simulations FF12MC can (i) simulate the experimentally observed flipping between left‐ and right‐handed configurations for C14–C38 of BPTI in solution, (ii) autonomously fold chignolin, CLN025, and Trp‐cage with folding times that agree with the experimental values, (iii) simulate subsequent unfolding and refolding of these miniproteins, and (iv) achieve a robust Z score of 1.33 for refining protein models TMR01, TMR04, and TMR07. By comparison, the latest general‐purpose AMBER forcefield FF14SB locks the C14–C38 bond to the right‐handed configuration in solution under the same protein simulation conditions. Statistical survival analysis shows that FF12MC folds chignolin and CLN025 in isobaric–isothermal MD simulations 2–4 times faster than FF14SB under the same protein simulation conditions. These results suggest that FF12MC may be used for protein simulations to study kinetics and thermodynamics of miniprotein folding as well as protein structure and dynamics. Proteins 2016; 84:1490–1516. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.     

Development of a conditional localization approach to control apicoplast protein trafficking in malaria parasites

Secretory proteins are of particular importance to apicomplexan parasites and comprise over 15% of the genomes of the human pathogens that cause diseases like malaria, toxoplasmosis and babesiosis as well as other diseases of agricultural significance. Here, we developed an approach that allows us to control the trafficking destination of secretory proteins in the human malaria parasite Plasmodium falciparum. Based on the unique structural requirements of apicoplast transit peptides, we designed three conditional localization domains (CLD1, 2 and 3) that can be used to control protein trafficking via the addition of a cell permeant ligand. Studies comparing the trafficking dynamics of each CLD show that CLD2 has the most optimal trafficking efficiency. To validate this system, we tested whether CLD2 could conditionally localize a biotin ligase called holocarboxylase synthetase 1 (HCS1) without interfering with the function of the enzyme. In a parasite line expressing CLD2‐HCS1, we were able to control protein biotinylation in the apicoplast in a ligand‐dependent manner, demonstrating the full functionality of the CLD tool. We have developed and validated a novel molecular tool that may be used in future studies to help elucidate the function of secretory proteins in malaria parasites.     

NMR structures of polytopic integral membrane proteins

Membrane proteins represent up to 30% of the proteins in all organisms, they are involved in many biological processes and are the molecular targets for around 50% of validated drugs. Despite this, membrane proteins represent less than 1% of all high-resolution protein structures due to various challenges associated with applying the main biophysical techniques used for protein structure determination. Recent years have seen an explosion in the number of high-resolution structures of membrane proteins determined by NMR spectroscopy, especially for those with multiple transmembrane-spanning segments. This is a review of the structures of polytopic integral membrane proteins determined by NMR spectroscopy up to the end of the year 2010, which includes both β-barrel and α-helical proteins from a number of different organisms and with a range in types of function. It also considers the challenges associated with performing structural studies by NMR spectroscopy on membrane proteins and how some of these have been overcome, along with its exciting potential for contributing new knowledge about the molecular mechanisms of membrane proteins, their roles in human disease, and for assisting drug design.     

A less‐biased analysis of metalloproteins reveals novel zinc coordination geometries

Zinc metalloproteins are involved in many biological processes and play crucial biochemical roles across all domains of life. Local structure around the zinc ion, especially the coordination geometry (CG), is dictated by the protein sequence and is often directly related to the function of the protein. Current methodologies in characterizing zinc metalloproteins' CG consider only previously reported CG models based mainly on nonbiological chemical context. Exceptions to these canonical CG models are either misclassified or discarded as “outliers.” Thus, we developed a less‐biased method that directly handles potential exceptions without pre‐assuming any CG model. Our study shows that numerous exceptions could actually be further classified and that new CG models are needed to characterize them. Also, these new CG models are cross‐validated by strong correlation between independent structural and functional annotation distance metrics, which is partially lost if these new CGs models are ignored. Furthermore, these new CG models exhibit functional propensities distinct from the canonical CG models. Proteins 2015; 83:1470–1487. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.     

Banding 2of NMR‐derived methyl order parameters: Implications for protein dynamics

Our understanding of protein folding, stability, and function has begun to more explicitly incorporate dynamical aspects. Nuclear magnetic resonance has emerged as a powerful experimental method for obtaining comprehensive site‐resolved insight into protein motion. It has been observed that methyl‐group motion tends to cluster into three “classes” when expressed in terms of the popular Lipari‐Szabo model‐free squared generalized order parameter. Here the origins of the three classes or bands in the distribution of order parameters are examined. As a first step, a Bayesian based approach, which makes no a priori assumption about the existence or number of bands, is developed to detect the banding of values derived either from NMR experiments or molecular dynamics simulations. The analysis is applied to seven proteins with extensive molecular dynamics simulations of these proteins in explicit water to examine the relationship between O² and fine details of the motion of methyl bearing side chains. All of the proteins studied display banding, with some subtle differences. We propose a very simple yet plausible physical mechanism for banding. Finally, our Bayesian method is used to analyze the measured distributions of methyl group motions in the catabolite activating protein and several of its mutants in various liganded states and discuss the functional implications of the observed banding to protein dynamics and function. Proteins 2014; 82:2106–2117. © 2014 Wiley Periodicals, Inc.     

Structural basis of diversity and homodimerization specificity of zinc-finger-associated domains in Drosophila

In arthropods, zinc finger-associated domains (ZADs) are found at the N-termini of many DNA-binding proteins with tandem arrays of Cys2-His2 zinc fingers (ZAD-C2H2 proteins). ZAD-C2H2 proteins undergo fast evolutionary lineage-specific expansion and functional diversification. Here, we show that all ZADs from Drosophila melanogaster form homodimers, but only certain ZADs with high homology can also heterodimerize. CG2712, for example, is unable to heterodimerize with its paralog, the previously characterized insulator protein Zw5, with which it shares 46% homology. We obtained a crystal structure of CG2712 protein''s ZAD domain that, in spite of a low sequence homology, has similar spatial organization with the only known ZAD structure (from Grauzone protein). Steric clashes prevented the formation of heterodimers between Grauzone and CG2712 ZADs. Using detailed structural analysis, site-directed mutagenesis, and molecular dynamics simulations, we demonstrated that rapid evolutionary acquisition of interaction specificity was mediated by the more energy-favorable formation of homodimers in comparison to heterodimers, and that this specificity was achieved by multiple amino acid substitutions resulting in the formation or breaking of stabilizing interactions. We speculate that specific homodimerization of ZAD-C2H2 proteins is important for their architectural role in genome organization.     

Constant electric field simulations of the membrane potential illustrated with simple systems

Advances in modern computational methods and technology make it possible to carry out extensive molecular dynamics simulations of complex membrane proteins based on detailed atomic models. The ultimate goal of such detailed simulations is to produce trajectories in which the behavior of the system is as realistic as possible. A critical aspect that requires consideration in the case of biological membrane systems is the existence of a net electric potential difference across the membrane. For meaningful computations, it is important to have well validated methodologies for incorporating the latter in molecular dynamics simulations. A widely used treatment of the membrane potential in molecular dynamics consists of applying an external uniform electric field E perpendicular to the membrane. The field acts on all charged particles throughout the simulated system, and the resulting applied membrane potential V is equal to the applied electric field times the length of the periodic cell in the direction perpendicular to the membrane. A series of test simulations based on simple membrane-slab models are carried out to clarify the consequences of the applied field. These illustrative tests demonstrate that the constant-field method is a simple and valid approach for accounting for the membrane potential in molecular dynamics studies of biomolecular systems. This article is part of a Special Issue entitled: Membrane protein structure and function.