Extracting Curvature Preferences of Lipids Assembled in Flat Bilayers Shows Possible Kinetic Windows for Genesis of Bilayer Asymmetry and Domain Formation in Biological Membranes

Studies on the assembly of pure lipid components allow mechanistic insights toward understanding the structural and functional aspects of biological membranes. Molecular dynamic (MD) simulations on membrane systems provide molecular details on membrane dynamics that are difficult to obtain experimentally. A large number of MD studies have remained somewhat disconnected from a key concept of amphipathic assembly resulting in membrane structures—shape parameters of lipid molecules in those structures in aqueous environments. This is because most of the MD studies have been done on flat lipid membranes. With the above in view, we analyzed MD simulations of 26 pure lipid patches as a function of (1) lipid type(s) and (2) time of MD simulations along with 35–40 ns trajectories of five pure lipids. We report, for the first time, extraction of curvature preferences of lipids from MD simulations done on flat bilayers. Our results may lead to mechanistic insights into the possible origins of bilayer asymmetries and domain formation in biological membranes.     

Structural dynamics of neuropeptide hPYY

We have employed a combination of experiment and simulation to characterize the ensemble of structures sampled by human Peptide YY (hPYY), an important member of the neuropeptide Y family. Experimental structural characterization carried out with far UV circular dichroism spectroscopy and Fourier Transform-Infrared measurements confirmed that the major feature of the secondary structure of hPYY is the α-helix, encompassing about half the peptide residues, with smaller contributions from turn and β-sheet like structures. The peptide undergoes thermal denaturation characterized by a melting temperature of 48°C with an enthalpy change of -24.5 kcal/mol and entropy change of -76.2 cal/(mol K). In our computational studies, based on a 4-μsec MD trajectory generated with the AMBER03 potential, we found excellent agreement of the predicted features with experimental data, including a stable C-terminal helix, a central turn and conservation of about 80% of measured long-range NOE contacts. The main structural fluctuations involved partial helix unwinding and large-scale motions of the N-terminal. Our joint experimental/computational approach leads to several insights into the biological function of PYY. We conclude that the C-terminal helix is crucial for the structural integrity of PYY. The structures and motions found in the simulations suggest microscopic explanations for observed changes in biological activity of the peptide upon mutation and truncation. We also performed microsecond-length MD and replica-exchange simulations of hPYY with the OPLS-AA force field, for which computed structures did not agree well with experimental data, predicting significant loss of helicity and NOE contacts.     

qFit 3: Protein and ligand multiconformer modeling for X‐ray crystallographic and single‐particle cryo‐EM density maps

New X‐ray crystallography and cryo‐electron microscopy (cryo‐EM) approaches yield vast amounts of structural data from dynamic proteins and their complexes. Modeling the full conformational ensemble can provide important biological insights, but identifying and modeling an internally consistent set of alternate conformations remains a formidable challenge. qFit efficiently automates this process by generating a parsimonious multiconformer model. We refactored qFit from a distributed application into software that runs efficiently on a small server, desktop, or laptop. We describe the new qFit 3 software and provide some examples. qFit 3 is open‐source under the MIT license, and is available at https://github.com/ExcitedStates/qfit-3.0 .     

Structural analysis of intrinsically disordered proteins by small-angle X-ray scattering

Small-angle scattering of X-rays (SAXS) is an established method to study the overall structure and structural transitions of biological macromolecules in solution. For folded proteins, the technique provides three-dimensional low resolution structures ab initio or it can be used to drive rigid-body modeling. SAXS is also a powerful tool for the quantitative analysis of flexible systems, including intrinsically disordered proteins (IDPs), and is highly complementary to the high resolution methods of X-ray crystallography and NMR. Here we present the basic principles of SAXS and review the main approaches to the characterization of IDPs and flexible multidomain proteins using SAXS. Together with the standard approaches based on the analysis of overall parameters, a recently developed Ensemble Optimization Method (EOM) is now available. The latter method allows for the co-existence of multiple protein conformations in solution compatible with the scattering data. Analysis of the selected ensembles provides quantitative information about flexibility and also offers insights into structural features. Examples of the use of SAXS and combined approaches with NMR, X-ray crystallography, and computational methods to characterize completely or partially disordered proteins are presented.     

Event detection and sub‐state discovery from biomolecular simulations using higher‐order statistics: Application to enzyme adenylate kinase

Biomolecular simulations at millisecond and longer time‐scales can provide vital insights into functional mechanisms. Because post‐simulation analyses of such large trajectory datasets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi‐anharmonic analysis (QAA) (Ramanathan et al., PLoS One 2011;6:e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub‐states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth‐order statistics for characterizing atomic fluctuations. In this article, we extend QAA for analyzing long time‐scale simulations online. In particular, we present HOST4MD—a higher‐order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub‐states, and (3) identifies conformational transitions that enable the protein to access those sub‐states. We demonstrate HOST4MD on microsecond timescale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three subdomains (LID, CORE, and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate that HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time‐scale simulations. Proteins 2012. © 2012 Wiley Periodicals, Inc.     

VoroMQA: Assessment of protein structure quality using interatomic contact areas

In the absence of experimentally determined protein structure many biological questions can be addressed using computational structural models. However, the utility of protein structural models depends on their quality. Therefore, the estimation of the quality of predicted structures is an important problem. One of the approaches to this problem is the use of knowledge‐based statistical potentials. Such methods typically rely on the statistics of distances and angles of residue‐residue or atom‐atom interactions collected from experimentally determined structures. Here, we present VoroMQA (Voronoi tessellation‐based Model Quality Assessment), a new method for the estimation of protein structure quality. Our method combines the idea of statistical potentials with the use of interatomic contact areas instead of distances. Contact areas, derived using Voronoi tessellation of protein structure, are used to describe and seamlessly integrate both explicit interactions between protein atoms and implicit interactions of protein atoms with solvent. VoroMQA produces scores at atomic, residue, and global levels, all in the fixed range from 0 to 1. The method was tested on the CASP data and compared to several other single‐model quality assessment methods. VoroMQA showed strong performance in the recognition of the native structure and in the structural model selection tests, thus demonstrating the efficacy of interatomic contact areas in estimating protein structure quality. The software implementation of VoroMQA is freely available as a standalone application and as a web server at http://bioinformatics.lt/software/voromqa . Proteins 2017; 85:1131–1145. © 2017 Wiley Periodicals, Inc.     

DALI and the persistence of protein shape

DALI is a popular resource for comparing protein structures. The software is based on distance‐matrix alignment. The associated web server provides tools to navigate, integrate and organize some data pushed out by genomics and structural genomics. The server has been running continuously for the past 25 years. Structural biologists routinely use DALI to compare a new structure against previously known protein structures. If significant similarities are discovered, it may indicate a distant homology, that is, that the structures are of shared origin. This may be significant in determining the molecular mechanisms, as these may remain very similar from a distant predecessor to the present day, for example, from the last common ancestor of humans and bacteria. Meta‐analysis of independent reference‐based evaluations of alignment accuracy and fold discrimination shows DALI at top rank in six out of 12 studies. The web server and standalone software are available from http://ekhidna2.biocenter.helsinki.fi/dali .     

Transfer RNA recognition by aminoacyl-tRNA synthetases

The aminoacyl-tRNA synthetases are an ancient group of enzymes that catalyze the covalent attachment of an amino acid to its cognate transfer RNA. The question of specificity, that is, how each synthetase selects the correct individual or isoacceptor set of tRNAs for each amino acid, has been referred to as the second genetic code. A wealth of structural, biochemical, and genetic data on this subject has accumulated over the past 40 years. Although there are now crystal structures of sixteen of the twenty synthetases from various species, there are only a few high resolution structures of synthetases complexed with cognate tRNAs. Here we review briefly the structural information available for synthetases, and focus on the structural features of tRNA that may be used for recognition. Finally, we explore in detail the insights into specific recognition gained from classical and atomic group mutagenesis experiments performed with tRNAs, tRNA fragments, and small RNAs mimicking portions of tRNAs.     

Variations in clique and community patterns in protein structures during allosteric communication: investigation of dynamically equilibrated structures of methionyl tRNA synthetase complexes

The allosteric concept has played a key role in understanding the biological functions of proteins. The rigidity or plasticity and the conformational population are the two important ideas invoked in explaining the allosteric effect. Although molecular insights have been gained from a large number of structures, a precise assessment of the ligand-induced conformational changes in proteins at different levels, ranging from gross topology to intricate details, remains a challenge. In this study, we have explored the conformational changes in the complexes of methionyl tRNA synthetase (MetRS) through novel network parameters such as cliques and communities, which identify the rigid regions in the protein structure networks (PSNs) constructed from the noncovalent interactions of amino acid side chains. MetRS belongs to the aminoacyl tRNA synthetase (aaRS) family that plays a crucial role in the translation of genetic code. These enzymes are modular with distinct domains from which extensive genetic, kinetic, and structural data are available, highlighting the role of interdomain communication. The network parameters evaluated here on the conformational ensembles of MetRS complexes, generated from molecular dynamics simulations, have enabled us to understand the interdomain communication in detail. Additionally, the characterization of conformational changes in terms of cliques and communities has also become possible, which had eluded conventional analyses. Furthermore, we find that most of the residues participating in cliques and communities are strikingly different from those that take part in long-range communication. The cliques and communities evaluated here for the first time on PSNs have beautifully captured the local geometries in detail within the framework of global topology. Here the allosteric effect is revealed at the residue level via identification of the important residues specific for structural rigidity and functional flexibility in MetRS. This ought to enhance our understanding of the functioning of aaRS in general.     

Stereochemical mechanisms of tRNA methyltransferases

Methylation of tRNA on the four canonical bases adds structural complexity to the molecule, and improves decoding specificity and efficiency. While many tRNA methylases are known, detailed insight into the catalytic mechanism is only available in a few cases. Of interest among all tRNA methylases is the structural basis for nucleotide selection, by which the specificity is limited to a single site, or broadened to multiple sites. General themes in catalysis include the basis for rate acceleration at highly diverse nucleophilic centers for methyl transfer, using S-adenosylmethionine as a cofactor. Studies of tRNA methylases have also yielded insights into molecular evolution, particularly in the case of enzymes that recognize distinct structures to perform identical reactions at the same target nucleotide.     

Network properties of protein-decoy structures

Convergence of the vast sequence space of proteins into a highly restricted fold/conformational space suggests a simple yet unique underlying mechanism of protein folding that has been the subject of much debate in the last several decades. One of the major challenges related to the understanding of protein folding or in silico protein structure prediction is the discrimination of non-native structures/decoys from the native structure. Applications of knowledge-based potentials to attain this goal have been extensively reported in the literature. Also, scoring functions based on accessible surface area and amino acid neighbourhood considerations were used in discriminating the decoys from native structures. In this article, we have explored the potential of protein structure network (PSN) parameters to validate the native proteins against a large number of decoy structures generated by diverse methods. We are guided by two principles: (a) the PSNs capture the local properties from a global perspective and (b) inclusion of non-covalent interactions, at all-atom level, including the side-chain atoms, in the network construction accommodates the sequence dependent features. Several network parameters such as the size of the largest cluster, community size, clustering coefficient are evaluated and scored on the basis of the rank of the native structures and the Z-scores. The network analysis of decoy structures highlights the importance of the global properties contributing to the uniqueness of native structures. The analysis also exhibits that the network parameters can be used as metrics to identify the native structures and filter out non-native structures/decoys in a large number of data-sets; thus also has a potential to be used in the protein ‘structure prediction’ problem.     

ModuleSearch: finding functional modules in a protein–protein interaction network

Many biological processes are performed by a group of proteins rather than by individual proteins. Proteins involved in the same biological process often form a densely connected sub-graph in a protein–protein interaction network. Therefore, finding a dense sub-graph provides useful information to predict the function or protein complex of uncharacterised proteins in the sub-graph. We developed a heuristic algorithm that finds functional modules in a protein–protein interaction network and visualises the modules. The algorithm has been implemented in a platform-independent, standalone program called ModuleSearch. In an interaction network of yeast proteins, ModuleSearch found 366 overlapping modules. Of the modules, 71% have a function shared by more than half the proteins in the module and 58% have a function shared by all proteins in the module. Comparison of ModuleSearch with other programs shows that ModuleSearch finds more sub-graphs than most other programs, yet a higher proportion of the sub-graphs correspond to known functional modules. ModuleSearch and sample data are freely available to academics at http://bclab.inha.ac.kr/ModuleSearch.     

Probing subtle conformational changes induced by phosphorylation and point mutations in the TIR domains of TLR2 and TLR3

Extensive research performed on Toll‐like receptor (TLR) signaling has identified residues in the Toll/interleukin‐1 receptor (TIR) domains that are essential for its proper functioning. Among these residues, those in BB loop are particularly significant as single amino acid mutations in this region can cause drastic changes in downstream signaling. However, while the effect of these mutations on the function is well studied (like the P681H mutation in TLR2, the A795P mutation in TLR3, and the P714H mutation in TLR4), their influence on the dynamics and inter‐residue networks is not well understood. The effects of local perturbations induced by these mutations could propagate throughout the TIR domain, influencing interactions with other TIR domain‐containing proteins. The identification of these subtle changes in inter‐residue interactions can provide new insights and structural rationale for how single‐point mutations cause drastic changes in TIR–TIR interactions. We employed molecular dynamics simulations and protein structure network (PSN) analyses to investigate the structural transitions with special emphasis on TLR2 and TLR3. Our results reveal that phosphorylation of the Tyr 759 residue in the TIR domain of TLR3 introduces rigidity to its BB loop. Subtle differences in the intra BB loop hydrogen bonding network between TLR3 and TLR2 are also observed. The PSN analyses indicate that the TIR domain is highly connected and pinpoints key differences in the inter‐residue interactions between the wild‐type and mutant TIR domains, suggesting that TIR domain structure is prone to allosteric effects, consistent with the current view of the influence of allostery on TLR signaling.     

A molecular dynamics simulation study of an aminoglycoside/A-site RNA complex: conformational and hydration patterns

Aminoglycoside antibiotics interfere with the translation mechanism by binding to the tRNA decoding site of the 16S ribosomal RNA. Crystallographic structures of aminoglycosides bound to A-site systems clarified many static aspects of RNA-ligand interactions. To gain some insight on the dynamic aspects of recognition phenomena, we conducted molecular dynamics simulations of the aminoglycoside paromomycin bound to a eubacterial ribosomal decoding A-site oligonucleotide. Results from 25 ns of simulation time revealed that: (i) the neamine part of the antibiotic represents the main anchor for binding, (ii) additional sugar rings provide limited and fragile contacts, (iii) long-resident water molecules present at the drug/RNA interface are involved in the recognition phenomena. The combination of MD simulations together with systematic structural information offers striking insights into the molecular recognition processes underlying RNA/aminoglycoside binding. Important methodological considerations related to the use of medium resolution starting structures and associated sampling problems are thoroughly discussed.     

Molecular basis of the recognition of arachidonic acid by cytochrome P450 2E1 along major access tunnel

Cytochrome P450 2E1 is widely known for its ability to oxidize both low molecular weight xenobiotics and endogenous fatty acids (e.g., arachidonic acid (AA)). In this study, we investigated the structural features of the AA‐bound CYP2E1 complex utilizing molecular dynamics (MD) and found that the distinct binding modes for both AA and fatty acid analog are conserved. Moreover, multiple random acceleration MD simulations and steered MD simulations uncovered the most possible tunnel for fatty acids. The main attractions are derived from three key residues, His107, Ala108, and His109, whose side chains reorient to keep ligands bound via hydrogen bonds during the initial unbinding process. More importantly, based on the calculated binding free energy results, we hypothesize that the hydrogen bonds between the receptor and the ligand are the most important contributors involved in the binding affinity. Thus, it is inferred that the hydrogen bonds between these three residues and the ligand may help offer insights into the structural basis of the different ligand egress mechanisms for fatty acids and small weight compounds. Our investigation provides detailed atomistic insights into the structural features of human CYP2E1–fatty acid complex structures. Furthermore, the ligand‐binding characteristics obtained in the present study are helpful for both experimental and computational studies of CYPs and may allow future researchers to achieve desirable changes in enzymatic activities. © 2014 Wiley Periodicals, Inc. Biopolymers 103: 53–66, 2015.     

Structure networks of E. coli glutaminyl-tRNA synthetase: effects of ligand binding

It is well known that proteins undergo backbone as well as side chain conformational changes upon ligand binding, which is not necessarily confined to the active site. Both the local and the global conformational changes brought out by ligand-binding have been extensively studied earlier. However, the global changes have been reported mainly at the protein backbone level. Here we present a method that explicitly takes into account the side chain interactions, yet providing a global view of the ligand-induced conformational changes. This is achieved through the analysis of Protein Structure Networks (PSN), constructed from the noncovalent side chain interactions in the protein. Here, E. coli Glutaminyl-tRNA synthetase (GlnRS) in the ligand-free and different ligand-bound states is used as a case study to assess the effect of binding of tRNA, ATP, and the amino acid Gln to GlnRS. The PSNs are constructed on the basis of the strength of noncovalent interactions existing between the side chains of amino acids. The parameters like the size of the largest cluster, edge to node ratio, and the total number of hubs are used to quantitatively assess the structure network changes. These network parameters have effectively captured the ligand-induced structural changes at a global structure network level. Hubs, the highly connected amino acids, are also identified from these networks. Specifically, we are able to characterize different types of hubs based on the comparison of structure networks of the GlnRS system. The differences in the structure networks in both the presence and the absence of the ligands are reflected in these hubs. For instance, the characterization of hubs that are present in both the ligand-free and all the ligand-bound GlnRS (the invariant hubs) might implicate their role in structural integrity. On the other hand, identification of hubs unique to a particular ligand-bound structure (the exclusive hubs) not only highlights the structural differences mediated by ligand-binding at the structure network level, but also highlights significance of these amino acids hubs in binding to the ligand and catalyzing the biochemical function. Further, the hubs identified from this study could be ideal targets for mutational studies to ascertain the ligand-induced structure-function relationships in E. coli GlnRS. The formalism used in this study is simple and can be applied to other protein-ligands in general to understand the allosteric changes mediated by the binding of ligands.     

REMO: A new protocol to refine full atomic protein models from C‐alpha traces by optimizing hydrogen‐bonding networks

Protein structure prediction approaches usually perform modeling simulations based on reduced representation of protein structures. For biological utilizations, it is an important step to construct full atomic models from the reduced structure decoys. Most of the current full atomic model reconstruction procedures have defects which either could not completely remove the steric clashes among backbone atoms or generate final atomic models with worse topology similarity relative to the native structures than the reduced models. In this work, we develop a new protocol, called REMO, to generate full atomic protein models by optimizing the hydrogen‐bonding network with basic fragments matched from a newly constructed backbone isomer library of solved protein structures. The algorithm is benchmarked on 230 nonhomologous proteins with reduced structure decoys generated by I‐TASSER simulations. The results show that REMO has a significant ability to remove steric clashes, and meanwhile retains good topology of the reduced model. The hydrogen‐bonding network of the final models is dramatically improved during the procedure. The REMO algorithm has been exploited in the recent CASP8 experiment which demonstrated significant improvements of the I‐TASSER models in both atomic‐level structural refinement and hydrogen‐bonding network construction. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Asymmetric structure and domain binding interfaces of human tyrosyl‐tRNA synthetase studied by molecular dynamics simulations

Human tyrosyl‐tRNA synthetase (HsTyrRS) is composed of two structural modules: N‐terminal catalytic core and an EMAP II‐like C‐terminal domain. The structures of these modules are known, but no crystal structure of the full‐length HsTyrRS is currently available. An all‐atom model of the full‐length HsTyrRS was developed in this work. The structure, dynamics, and domain binding interfaces of HsTyrRS were investigated by extensive molecular dynamics (MD) simulations. Our data suggest that HsTyrRS in solution consists of a number of compact asymmetric conformations, which differ significantly by their rigidity, internal mobility, orientation of C‐terminal modules, and the strength of interdomain binding. Interfaces of domain binding obtained in MD simulations are in perfect agreement with our previous coarse‐grained hierarchical rotations technique simulations. Formation of the hydrogen bonds between R93 residue of the ELR cytokine motif and the residues A340 and E479 in the C‐module was observed. This observation supports the idea that the lack of cytokine activity in the full‐length HsTyrRS is explained by interactions between N‐modules and C‐modules, which block the ELR motif. Copyright © 2013 John Wiley & Sons, Ltd.