Dynamics alignment: comparison of protein dynamics in the SCOP database

A novel methodology for comparison of protein dynamics is presented. Protein dynamics is calculated using the Gaussian network model and the modes of motion are globally aligned using the dynamic programming algorithm of Needleman and Wunsch, commonly used for sequence alignment. The alignment is fast and can be used to analyze large sets of proteins. The methodology is applied to the four major classes of the SCOP database: "all alpha proteins," "all beta proteins," "alpha and beta proteins," and "alpha/beta proteins". We show that different domains may have similar global dynamics. In addition, we report that the dynamics of "all alpha proteins" domains are less specific to structural variations within a given fold or superfamily compared with the other classes. We report that domain pairs with the most similar and the least similar global dynamics tend to be of similar length. The significance of the methodology is that it suggests a new and efficient way of mapping between the global structural features of protein families/subfamilies and their encoded dynamics.     

Improvements in GROMACS plugin for PyMOL including implicit solvent simulations and displaying results of PCA analysis

In order to get the dynamic molecule model from the static one, the molecular dynamics (MD) simulation needs to be performed. Some software sets such as GROMACS are used for that purpose. Unfortunately they lack GUI. The Dynamics PyMOL plugin allows researcher to perform MD simulations directly from the PyMOL software by GUI-based interface of GROMACS tools. This paper describes many improvements introduced into the Dynamics PyMOL plugin 2.0 including: an integration with ProDy library, possibility to use the implicit solvents, an ability to interpret the MD simulations, and implementation of some more GROMACS functionality.     

Activation and Speciation Mechanisms in Class A GPCRs

Accurate development of allosteric modulators of GPCRs require a thorough assessment of their sequence, structure, and dynamics, toward gaining insights into their mechanisms of actions shared by family members, as well as dynamic features that distinguish subfamilies. Building on recent progress in the characterization of the signature dynamics of proteins, we analyzed here a dataset of 160 Class A GPCRs to determine their sequence similarities, structural landscape, and dynamic features across different species (human, bovine, mouse, squid, and rat), different activation states (active/inactive), and different subfamilies. The two dominant directions of variability across experimentally resolved structures, identified by principal component analysis of the dataset, shed light to cooperative mechanisms of activation, subfamily differentiation, and speciation of Class A GPCRs. The analysis reveals the functional significance of the conformational flexibilities of specific structural elements, including: the dominant role of the intracellular loop 3 (ICL3) together with the cytoplasmic ends of the adjoining helices TM5 and TM6 in enabling allosteric activation; the role of particular structural motifs at the extracellular loop 2 (ECL2) connecting TM4 and TM5 in binding ligands specific to different subfamilies; or even the differentiation of the N-terminal conformation across different species. Detailed analyses of the modes of motions accessible to the members of the dataset and their variations across members demonstrate how the active and inactive states of GPCRs obey distinct conformational dynamics. The collective fluctuations of the GPCRs are robustly defined in the active state, while the inactive conformers exhibit broad variance among members.     

Conformational analysis of nucleic acids revisited: Curves+

We describe Curves+, a new nucleic acid conformational analysis program which is applicable to a wide range of nucleic acid structures, including those with up to four strands and with either canonical or modified bases and backbones. The program is algorithmically simpler and computationally much faster than the earlier Curves approach, although it still provides both helical and backbone parameters, including a curvilinear axis and parameters relating the position of the bases to this axis. It additionally provides a full analysis of groove widths and depths. Curves+ can also be used to analyse molecular dynamics trajectories. With the help of the accompanying program Canal, it is possible to produce a variety of graphical output including parameter variations along a given structure and time series or histograms of parameter variations during dynamics.     

Human LC3 and GABARAP subfamily members achieve functional specificity via specific structural modulations

ABSTRACT

Autophagy is a conserved adaptive cellular pathway essential to maintain a variety of physiological functions. Core components of this machinery are the six human Atg8 orthologs that initiate formation of appropriate protein complexes. While these proteins are routinely used as indicators of autophagic flux, it is presently not possible to discern their individual biological functions due to our inability to predict specific binding partners. In our attempts towards determining downstream effector functions, we developed a computational pipeline to define structural determinants of human Atg8 family members that dictate functional diversity. We found a clear evolutionary separation between human LC3 and GABARAP subfamilies and also defined a novel sequence motif responsible for their specificity. By analyzing known protein structures, we observed that functional modules or microclusters reveal a pattern of intramolecular network, including distinct hydrogen bonding of key residues (F52/Y49; a subset of HP2) that may directly modulate their interaction preferences. Multiple molecular dynamics simulations were performed to characterize how these proteins interact with a common protein binding partner, PLEKHM1. Our analysis showed remarkable differences in binding modes via intrinsic protein dynamics, with PLEKHM1-bound GABARAP complexes showing less fluctuations and higher number of contacts. We further mapped 373 genomic variations and demonstrated that distinct cancer-related mutations are likely to lead to significant structural changes. Our findings present a quantitative framework to establish factors underlying exquisite specificity of human Atg8 proteins, and thus facilitate the design of precise modulators.

Abbreviations: Atg: autophagy-related; ECs: evolutionary constraints; GABARAP: GABA type A receptor-associated protein; HsAtg8: human Atg8; HP: hydrophobic pocket; KBTBD6: kelch repeat and BTB domain containing 6; LIR: LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MD: molecular dynamics; HIV-1 Nef: human immunodeficiency virus type 1 negative regulatory factor; PLEKHM1: pleckstrin homology and RUN domain containing M1; RMSD: root mean square deviation; SQSTM1/p62: sequestosome 1; WDFY3/ALFY: WD repeat and FYVE domain containing 3     

Distinct dynamics and interaction patterns in H‐ and K‐Ras oncogenic P‐loop mutants

Despite years of study, the structural or dynamical basis for the differential reactivity and oncogenicity of Ras isoforms and mutants remains unclear. In this study, we investigated the effects of amino acid variations on the structure and dynamics of wild type and oncogenic mutants G12D, G12V, and G13D of H‐ and K‐Ras proteins. Based on data from µs‐scale molecular dynamics simulations, we show that the overall structure of the proteins remains similar but there are important differences in dynamics and interaction networks. We identified differences in residue interaction patterns around the canonical switch and distal loop regions, and persistent sodium ion binding near the GTP particularly in the G13D mutants. Our results also suggest that different Ras variants have distinct local structural features and interactions with the GTP, variations that have the potential to affect GTP release and hydrolysis. Furthermore, we found that H‐Ras proteins and particularly the G12V and G13D variants are significantly more flexible than their K‐Ras counterparts. Finally, while most of the simulated proteins sampled the effector‐interacting state 2 conformational state, G12V and G13D H‐Ras adopted an open switch state 1 conformation that is defective in effector interaction. These differences have implications for Ras GTPase activity, effector or exchange factor binding, dimerization and membrane interaction. Proteins 2017; 85:1618–1632. © 2017 Wiley Periodicals, Inc.     

Temperature dependence of the NMR generalized order parameter

The study of protein conformational dynamics is motivated in large part by a desire to understand the forces present at different sites throughout the molecular structure. The generalized order parameter determined by NMR spectroscopy has played a central role in the study of protein dynamics on the picosecond-nanosecond time scale. A modeling procedure is presented for analysis of the temperature dependence of the generalized order parameter that extends a previous analysis (Massi and Palmer, J Am Chem Soc 2003;125:11158-11159). As part of this procedure, the potential of mean force is characterized for the N-H bond vectors of the protein backbone. This procedure accounts for the observed temperature dependence of the generalized order parameter in a representative data set from the B1 domain of Streptococcal protein G (Seewald, Pichumani, Stowell, Tibbals, Regan, and Stone, Protein Sci 2000;9:1177-1193). The results indicate a general trend, in which the force constants associated with the potential of mean force decrease with increasing temperature. The analysis also provides evidence for variations in the potential of mean force for different secondary structural elements.     

Propagation of dynamic changes in barnase upon binding of barstar: an NMR and computational study

NMR spectroscopy and computer simulations were used to examine changes in chemical shifts and in dynamics of the ribonuclease barnase that result upon binding to its natural inhibitor barstar. Although the spatial structures of free and bound barnase are very similar, binding results in changes of the dynamics of both fast side-chains, as revealed by (2)H relaxation measurements, and NMR chemical shifts in an extended beta-sheet that is located far from the binding interface. Both side-chain dynamics and chemical shifts are sensitive to variations in the ensemble populations of the inter-converting molecular states, which can escape direct structural observation. Molecular dynamics simulations of free barnase and barnase in complex with barstar, as well as a normal mode analysis of barnase using a Gaussian network model, reveal relatively rigid domains that are separated by the extended beta-sheet mentioned above. The observed changes in NMR parameters upon ligation can thus be rationalized in terms of changes in inter-domain dynamics and in populations of exchanging states, without measurable structural changes. This provides an alternative model for the propagation of a molecular response to ligand binding across a protein that is based exclusively on changes in dynamics.     

Advances in all atom sampling methods for modeling protein-ligand binding affinities

Conformational dynamics plays a fundamental role in the regulation of molecular recognition processes. Conformational heterogeneity and entropy variations upon binding, although not always evident from the analysis of structural data, can substantially affect affinity and specificity. Computer modeling is able to provide some of the most direct insights into these aspects of molecular recognition. We review recent physics-based computational studies that employ advanced conformational sampling algorithms and effective potentials to model the three main classes of degrees of freedom relevant to the binding process: ligand positioning relative to the receptor, ligand and receptor internal reorganization, and hydration. Collectively these studies show that all of these elements are important for proper modeling of protein-ligand interactions.     

Multiple Gaussian network modes alignment reveals dynamically variable regions: The hemoglobin case

Gaussian network model (GNM) modes of motion are calculated to a dataset of h emoglobin (Hb) structures and modes with dynamics similarity to the T state are multiply aligned. The sole criterion for the alignment is the mode shape itself and not sequence or structural similarity. Standard deviation (SD) of the GNM value score along the alignment is calculated, regions with high SD are defined as dynamically variable. The analysis shows that the α1β1/α2β2 interface is a dynamically variable region but not the α1β2/α2β1 and the α1α2/β1β2 interfaces. The results are in accordance with the T → R2 transition of Hb. We suggest that dynamically variable regions are regions that are likely to undergo structural change in the protein upon binding, conformational transition, or any other relevant chemical event. The represented technique of multiple dynamics ‐ based alignment of modes is novel and may offer a new insight in proteins ' dynamics to function relation. Proteins 2014; 82:2097–2105. © 2014 Wiley Periodicals, Inc.     

Probing the pH sensitivity of R-phycoerythrin: Investigations of active conformational and functional variation

Crystal structures of phycobiliproteins have provided valuable information regarding the conformations and amino acid organizations of peptides and chromophores, and enable us to investigate their structural and functional relationships with respect to environmental variations. In this work, we explored the pH-induced conformational and functional dynamics of R-phycoerythrin (R-PE) by means of absorption, fluorescence and circular dichroism spectra, together with analysis of its crystal structure. R-PE presents stronger functional stability in the pH range of 3.5-10 compared to the structural stability. Beyond this range, pronounced functional and structural changes occur. Crystal structure analysis shows that the tertiary structure of R-PE is fixed by several key anchoring points of the protein. With this specific association, the fundamental structure of R-PE is stabilized to present physiological spectroscopic properties, while local variations in protein peptides are also allowed in response to environmental disturbances. The functional stability and relative structural sensitivity of R-PE allow environmental adaptation.     

How Structure Shapes Dynamics: Knowledge Development in Wikipedia - A Network Multilevel Modeling Approach

Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base.     

Structural requirements for cooperativity in ileal bile acid-binding proteins

Ileal bile acid-binding proteins (I-BABP), belonging to the family of intracellular lipid-binding proteins, control bile acid trafficking in enterocytes and participate in regulating the homeostasis of these cholesterol-derived metabolites. I-BABP orthologues share the same structural fold and are able to host up to two ligands in their large internal cavities. However variations in the primary sequences determine differences in binding properties such as the degree of binding cooperativity. To investigate the molecular requirements for cooperativity we adopted a gain-of-function approach, exploring the possibility to turn the noncooperative chicken I-BABP (cI-BABP) into a cooperative mutant protein. To this aim we first solved the solution structure of cI-BABP in complex with two molecules of the physiological ligand glycochenodeoxycholate. A comparative structural analysis with closely related members of the same protein family provided the basis to design a double mutant (H99Q/A101S cI-BABP) capable of establishing a cooperative binding mechanism. Molecular dynamics simulation studies of the wild type and mutant complexes and essential dynamics analysis of the trajectories supported the role of the identified amino acid residues as hot spot mediators of communication between binding sites. The emerging picture is consistent with a binding mechanism that can be described as an extended conformational selection model.     

Structural characteristics of BAR domain superfamily to sculpt the membrane

Membrane dynamics is an essential process for cell locomotion, cytokinesis, vesicular transport and organelle morphogenesis. Formation of tubes or buds from a nearly flat membrane is a widely spread feature of the membrane shape changes. The BAR (Bin/Amphiphysin/Rvs-homology) domain dimers exhibit long extended curved shapes and appear to be outstandingly suitable modules for this purpose. So far, crystal structures of 18 independent BAR domains including inverse-BAR domains and FCH-BAR domains have been reported. These atomic models show a vast variation of dimer shapes on a common and simple basic framework. Comparison of the structural variations with respect to differences in membrane sculpting properties provide useful clues about the mechanisms for modifying the framework into a particular dimer that generates and/or senses a distinct curvature set of the membrane.     

High Density LD-Based Structural Variations Analysis in Cattle Genome

Genomic structural variations represent an important source of genetic variation in mammal genomes, thus, they are commonly related to phenotypic expressions. In this work, ∼770,000 single nucleotide polymorphism genotypes from 506 animals from 19 cattle breeds were analyzed. A simple LD-based structural variation was defined, and a genome-wide analysis was performed. After applying some quality control filters, for each breed and each chromosome we calculated the linkage disequilibrium (r ²) of short range (≤100 Kb). We sorted SNP pairs by distance and obtained a set of LD means (called the expected means) using bins of 5 Kb. We identified 15,246 segments of at least 1 Kb, among the 19 breeds, consisting of sets of at least 3 adjacent SNPs so that, for each SNP, r ² within its neighbors in a 100 Kb range, to the right side of that SNP, were all bigger than, or all smaller than, the corresponding expected mean, and their P-value were significant after a Benjamini-Hochberg multiple testing correction. In addition, to account just for homogeneously distributed regions we considered only SNPs having at least 15 SNP neighbors within 100 Kb. We defined such segments as structural variations. By grouping all variations across all animals in the sample we defined 9,146 regions, involving a total of 53,137 SNPs; representing the 6.40% (160.98 Mb) from the bovine genome. The identified structural variations covered 3,109 genes. Clustering analysis showed the relatedness of breeds given the geographic region in which they are evolving. In summary, we present an analysis of structural variations based on the deviation of the expected short range LD between SNPs in the bovine genome. With an intuitive and simple definition based only on SNPs data it was possible to discern closeness of breeds due to grouping by geographic region in which they are evolving.     

Dynamics of the Hck-SH3 domain: comparison of experiment with multiple molecular dynamics simulations

Molecular dynamics calculations provide a method by which the dynamic properties of molecules can be explored over timescales and at a level of detail that cannot be obtained experimentally from NMR or X-ray analyses. Recent work (Philippopoulos M, Mandel AM, Palmer AG III, Lim C, 1997, Proteins 28:481-493) has indicated that the accuracy of these simulations is high, as measured by the correspondence of parameters extracted from these calculations to those determined through experimental means. Here, we investigate the dynamic behavior of the Src homology 3 (SH3) domain of hematopoietic cell kinase (Hck) via 5N backbone relaxation NMR studies and a set of four independent 4 ns solvated molecular dynamics calculations. We also find that molecular dynamics simulations accurately reproduce fast motion dynamics as estimated from generalized order parameter (S2) analysis for regions of the protein that have experimentally well-defined coordinates (i.e., stable secondary structural elements). However, for regions where the coordinates are not well defined, as indicated by high local root-mean-square deviations among NMR-determined structural family members or high B-factors/low electron density in X-ray crystallography determined structures, the parameters calculated from a short to moderate length (less than 5-10 ns) molecular dynamics trajectory are dependent on the particular coordinates chosen as a starting point for the simulation.     

Computer-based screening of functional conformers of proteins

A long-standing goal in biology is to establish the link between function, structure, and dynamics of proteins. Considering that protein function at the molecular level is understood by the ability of proteins to bind to other molecules, the limited structural data of proteins in association with other bio-molecules represents a major hurdle to understanding protein function at the structural level. Recent reports show that protein function can be linked to protein structure and dynamics through network centrality analysis, suggesting that the structures of proteins bound to natural ligands may be inferred computationally. In the present work, a new method is described to discriminate protein conformations relevant to the specific recognition of a ligand. The method relies on a scoring system that matches critical residues with central residues in different structures of a given protein. Central residues are the most traversed residues with the same frequency in networks derived from protein structures. We tested our method in a set of 24 different proteins and more than 260,000 structures of these in the absence of a ligand or bound to it. To illustrate the usefulness of our method in the study of the structure/dynamics/function relationship of proteins, we analyzed mutants of the yeast TATA-binding protein with impaired DNA binding. Our results indicate that critical residues for an interaction are preferentially found as central residues of protein structures in complex with a ligand. Thus, our scoring system effectively distinguishes protein conformations relevant to the function of interest.     

Hydrophobic Core Variations Provide a Structural Framework for Tyrosine Kinase Evolution and Functional Specialization

Protein tyrosine kinases (PTKs) are a group of closely related enzymes that have evolutionarily diverged from serine/threonine kinases (STKs) to regulate pathways associated with multi-cellularity. Evolutionary divergence of PTKs from STKs has occurred through accumulation of mutations in the active site as well as in the commonly conserved hydrophobic core. While the functional significance of active site variations is well understood, relatively little is known about how hydrophobic core variations contribute to PTK evolutionary divergence. Here, using a combination of statistical sequence comparisons, molecular dynamics simulations, mutational analysis and in vitro thermostability and kinase assays, we investigate the structural and functional significance of key PTK-specific variations in the kinase core. We find that the nature of residues and interactions in the hydrophobic core of PTKs is strikingly different from other protein kinases, and PTK-specific variations in the core contribute to functional divergence by altering the stability and dynamics of the kinase domain. In particular, a functionally critical STK-conserved histidine that stabilizes the regulatory spine in STKs is selectively mutated to an alanine, serine or glutamate in PTKs, and this loss-of-function mutation is accommodated, in part, through compensatory PTK-specific interactions in the core. In particular, a PTK-conserved phenylalanine in the I-helix appears to structurally and functionally compensate for the loss of STK-histidine by interacting with the regulatory spine, which has far-reaching effects on enzyme activity, inhibitor sensing, and stability. We propose that hydrophobic core variations provide a selective advantage during PTK evolution by increasing the conformational flexibility, and therefore the allosteric potential of the kinase domain. Our studies also suggest that Tyrosine Kinase Like kinases such as RAF are intermediates in PTK evolutionary divergence inasmuch as they share features of both PTKs and STKs in the core. Finally, our studies provide an evolutionary framework for identifying and characterizing disease and drug resistance mutations in the kinase core.