Comparing short protein substructures by a method based on backbone torsion angles

Statistical and molecular dynamics (MD) simulation approach to investigate the role of intrinsically disordered regions of shikimate dehydrogenase in microorganisms surviving at different temperatures

Hyperthermophiles, a subset of prokaryotes that thrive in adverse temperatures, potentially utilize the protein molecular biosystem for maintaining thermostability in a wide range of temperatures. Recent studies revealed that these organisms have smaller proportions of intrinsically disordered proteins. In this study, we performed sequence and structural analysis to investigate the maintenance of protein conformation and their stability at different temperatures. The sequence analysis reveals the higher proportion of charged amino acids are responsible for preventing the helix formation and, hence, become disordered regions. For structural analysis, we chose shikimate dehydrogenase from four species, namely Listeria monocytogenes, Escherichia coli, Thermus thermophilus, and Methanopyrus kandleri, and evaluated the protein adaptation at 283 K, 300 K, and 395 K temperatures. From this investigation, we found more residues of shikimate dehydrogenase prefer an order-to-disorder transition at 395 K only for hyperthermophilic species. The solvent-accessible surface area (SASA) and hydrogen-bond analysis revealed that the tertiary conformation and the number of hydrogen bonds for hyperthermophilic shikimate dehydrogenase are highly preserved at 395 K, compared to 300 K. Our simulation results conjointly provide shikimate dehydrogenase of hyperthermophile which resists high temperatures through stronger protein tertiary conformations.

Conserved Binding Regions Provide the Clue for Peptide-Based Vaccine Development: A Chemical Perspective

Synthetic peptides have become invaluable biomedical research and medicinal chemistry tools for studying functional roles, i.e., binding or proteolytic activity, naturally-occurring regions’ immunogenicity in proteins and developing therapeutic agents and vaccines. Synthetic peptides can mimic protein sites; their structure and function can be easily modulated by specific amino acid replacement. They have major advantages, i.e., they are cheap, easily-produced and chemically stable, lack infectious and secondary adverse reactions and can induce immune responses via T- and B-cell epitopes. Our group has previously shown that using synthetic peptides and adopting a functional approach has led to identifying Plasmodium falciparumconserved regions binding to host cells. Conserved high activity binding peptides’ (cHABPs) physicochemical, structural and immunological characteristics have been taken into account for properly modifying and converting them into highly immunogenic, protection-inducing peptides (mHABPs) in the experimental Aotus monkey model. This article describes stereo–electron and topochemical characteristics regarding major histocompatibility complex (MHC)-mHABP-T-cell receptor (TCR) complex formation. Some mHABPs in this complex inducing long-lasting, protective immunity have been named immune protection-inducing protein structures (IMPIPS), forming the subunit components in chemically synthesized vaccines. This manuscript summarizes this particular field and adds our recent findings concerning intramolecular interactions (H-bonds or π-interactions) enabling proper IMPIPS structure as well as the peripheral flanking residues (PFR) to stabilize the MHCII-IMPIPS-TCR interaction, aimed at inducing long-lasting, protective immunological memory.

Protein backbone torsion angle-based structure comparison and secondary structure database web server

Structural information has been a major concern for biological and pharmaceutical studies for its intimate relationship to the function of a protein. Three-dimensional representation of the positions of protein atoms is utilized among many structural information repositories that have been published. The reliability of the torsional system, which represents the native processes of structural change in the structural analysis, was partially proven with previous structural alignment studies. Here, a web server providing structural information and analysis based on the backbone torsional representation of a protein structure is newly introduced. The web server offers functions of secondary structure database search, secondary structure calculation, and pair-wise protein structure comparison, based on a backbone torsion angle representation system. Application of the implementation in pair-wise structural alignment showed highly accurate results. The information derived from this web server might be further utilized in the field of ab initio protein structure modeling or protein homology-related analyses.

Multi-view methods for protein structure comparison using latent dirichlet allocation

Motivation: With rapidly expanding protein structure databases, efficiently retrieving structures similar to a given protein is an important problem. It involves two major issues: (i) effective protein structure representation that captures inherent relationship between fragments and facilitates efficient comparison between the structures and (ii) effective framework to address different retrieval requirements. Recently, researchers proposed vector space model of proteins using bag of fragments representation (FragBag), which corresponds to the basic information retrieval model.

Results: In this article, we propose an improved representation of protein structures using latent dirichlet allocation topic model. Another important requirement is to retrieve proteins, whether they are either close or remote homologs. In order to meet diverse objectives, we propose multi-viewpoint based framework that combines multiple representations and retrieval techniques. We compare the proposed representation and retrieval framework on the benchmark dataset developed by Kolodny and co-workers. The results indicate that the proposed techniques outperform state-of-the-art methods.

Availability:http://www.cse.iitm.ac.in/~ashishvt/research/protein-lda/.

Contact:ashishvt@cse.iitm.ac.in

Structural fragment clustering reveals novel structural and functional motifs in alpha-helical transmembrane proteins

Background

A large proportion of an organism's genome encodes for membrane proteins. Membrane proteins are important for many cellular processes, and several diseases can be linked to mutations in them. With the tremendous growth of sequence data, there is an increasing need to reliably identify membrane proteins from sequence, to functionally annotate them, and to correctly predict their topology.

Results

We introduce a technique called structural fragment clustering, which learns sequential motifs from 3D structural fragments. From over 500,000 fragments, we obtain 213 statistically significant, non-redundant, and novel motifs that are highly specific to α-helical transmembrane proteins. From these 213 motifs, 58 of them were assigned to function and checked in the scientific literature for a biological assessment. Seventy percent of the motifs are found in co-factor, ligand, and ion binding sites, 30% at protein interaction interfaces, and 12% bind specific lipids such as glycerol or cardiolipins. The vast majority of motifs (94%) appear across evolutionarily unrelated families, highlighting the modularity of functional design in membrane proteins. We describe three novel motifs in detail: (1) a dimer interface motif found in voltage-gated chloride channels, (2) a proton transfer motif found in heme-copper oxidases, and (3) a convergently evolved interface helix motif found in an aspartate symporter, a serine protease, and cytochrome b.

Conclusions

Our findings suggest that functional modules exist in membrane proteins, and that they occur in completely different evolutionary contexts and cover different binding sites. Structural fragment clustering allows us to link sequence motifs to function through clusters of structural fragments. The sequence motifs can be applied to identify and characterize membrane proteins in novel genomes.

MUSTANG: a multiple structural alignment algorithm

Multiple structural alignment is a fundamental problem in structural genomics. In this article, we define a reliable and robust algorithm, MUSTANG (MUltiple STructural AligNment AlGorithm), for the alignment of multiple protein structures. Given a set of protein structures, the program constructs a multiple alignment using the spatial information of the C(alpha) atoms in the set. Broadly based on the progressive pairwise heuristic, this algorithm gains accuracy through novel and effective refinement phases. MUSTANG reports the multiple sequence alignment and the corresponding superposition of structures. Alignments generated by MUSTANG are compared with several handcurated alignments in the literature as well as with the benchmark alignments of 1033 alignment families from the HOMSTRAD database. The performance of MUSTANG was compared with DALI at a pairwise level, and with other multiple structural alignment tools such as POSA, CE-MC, MALECON, and MultiProt. MUSTANG performs comparably to popular pairwise and multiple structural alignment tools for closely related proteins, and performs more reliably than other multiple structural alignment methods on hard data sets containing distantly related proteins or proteins that show conformational changes.

Protein structural alignments and functional genomics

Structural genomics-the systematic solution of structures of the proteins of an organism-will increasingly often produce molecules of unknown function with no close relative of known function. Prediction of protein function from structure has thereby become a challenging problem of computational molecular biology. The strong conservation of active site conformations in homologous proteins suggests a method for identifying them. This depends on the relationship between size and goodness-of-fit of aligned substructures in homologous proteins. For all pairs of proteins studied, the root-mean-square deviation (RMSD) as a function of the number of residues aligned varies exponentially for large common substructures and linearly for small common substructures. The exponent of the dependence at large common substructures is well correlated with the RMSD of the core as originally calculated by Chothia and Lesk (EMBO J 1986;5:823-826), affording the possibility of reconciling different structural alignment procedures. In the region of small common substructures, reduced aligned subsets define active sites and can be used to suggest the locations of active sites in homologous proteins.

Leap-dynamics: efficient sampling of conformational space of proteins and peptides in solution

A molecular simulation scheme, called Leap-dynamics, that provides efficient sampling of protein conformational space in solution is presented. The scheme is a combined approach using a fast sampling method, imposing conformational 'leaps' to force the system over energy barriers, and molecular dynamics (MD) for refinement. The presence of solvent is approximated by a potential of mean force depending on the solvent accessible surface area. The method has been successfully applied to N-acetyl-L-alanine-N-methylamide (alanine dipeptide), sampling experimentally observed conformations inaccessible to MD alone under the chosen conditions. The method predicts correctly the increased partial flexibility of the mutant Y35G compared to native bovine pancreatic trypsin inhibitor. In particular, the improvement over MD consists of the detection of conformational flexibility that corresponds closely to slow motions identified by nuclear magnetic resonance techniques.

Simplified representation of proteins

The conventional methods for characterizing the secondary structures of proteins based on hydrogen bonding patterns and phi,rho torsions are not fully specific in determining the spatial arrangements of various secondary structural elements. This fact motivates a search for an efficient description of the various secondary structures and their interactions. The successive identical repeating units of a polypeptide chain, namely the atoms of the peptide plane may be superposed using a method based on the mathematical quaternion. The superposition angle then characterizes different secondary structures. The distortions in protein alpha-helices such as kinks and bends are also precisely determined. The twist in beta-sheets is quantified and reverse turns are found to have characteristic variations. This new representation might pave the way for a better understanding of the final folding conformation of the polypeptide chain.

Geometrical analysis of structural changes in immunoglobulin domains' transition from native to molten state

Molecular dynamics simulation (300, 320, 340 K) performed on the Fab (Kol) fragment of immunoglobulin G revealed that the structural changes associated with relaxation of peptides after their release from the stabilized by the tertiary interaction native conformation may be considered characteristic of the transition from native to molten state. The configuration of peptide chains at temperatures close to melting, liberated from the constraints associated with tertiary packing, was found to deviate toward helical rather than extended forms. The direction of the shift is diagonal on the phi-psi map. The torsional angles tend to concentrate in the Cea7 region, and some leak to the alphaR area. The geometrical parameters designed to describe the configuration of the peptide chain in Fab fragment also confirmed that during melting the peptides generally moved toward helical form.

Systematic representation of protein folding patterns

A tabular representation of protein folding patterns is described, which comprises information about the order along the chain of helices and strands of sheet, identifies the elements of secondary structure that interact, and indicates their relative orientation. These tableaux are intelligible to both people and computers, and support the application of algorithms for identification of proteins with similar folding patterns. Their inclusion in a database of protein structures would support investigations of structural relationships at the topological level.

Proline cis-trans isomerization in staphylococcal nuclease: multi-substrate free energy perturbation calculations

Staphylococcal nuclease A exists in two folded forms that differ in the isomerization state of the Lys 116-Pro 117 peptide bond. The dominant form (90% occupancy) adopts a cis peptide bond, which is observed in the crystal structure. NMR studies show that the relatively small difference in free energy between the cis and trans forms (delta Gcis-->trans approximately 1.2 kcal/mol) results from large and nearly compensating differences in enthalpy and entropy (delta Hcis-->trans approximately delta TScis-->trans approximately 10 kcal/mol). There is evidence from X-ray crystal structures that the structural differences between the cis and the trans forms of nuclease are confined to the conformation of residues 112-117, a solvated protein loop. Here, we obtain a thermodynamic and structural description of the conformational equilibrium of this protein loop through an exhaustive conformational search that identified several substates followed by free energy simulations between the substrates. By partitioning the search into conformational substates, we overcame the multiple minima problem in this particular case and obtained precise and reproducible free energy values. The protein and water environment was implicitly modeled by appropriately chosen nonbonded terms between the explicitly treated loop and the rest of the protein. These simulations correctly predicted a small free energy difference between the cis and trans forms composed of larger, compensating differences in enthalpy and entropy. The structural predictions of these simulations were qualitatively consistent with known X-ray structures of nuclease variants and yield a model of the unknown minor trans conformation.

Protein structure prediction: recognition of primary, secondary, and tertiary structural features from amino acid sequence

This review attempts a critical stock-taking of the current state of the science aimed at predicting structural features of proteins from their amino acid sequences. At the primary structure level, methods are considered for detection of remotely related sequences and for recognizing amino acid patterns to predict posttranslational modifications and binding sites. The techniques involving secondary structural features include prediction of secondary structure, membrane-spanning regions, and secondary structural class. At the tertiary structural level, methods for threading a sequence into a mainchain fold, homology modeling and assigning sequences to protein families with similar folds are discussed. A literature analysis suggests that, to date, threading techniques are not able to show their superiority over sequence pattern recognition methods. Recent progress in the state of ab initio structure calculation is reviewed in detail. The analysis shows that many structural features can be predicted from the amino acid sequence much better than just a few years ago and with attendant utility in experimental research. Best prediction can be achieved for new protein sequences that can be assigned to well-studied protein families. For single sequences without homologues, the folding problem has not yet been solved.

Knowledge-based protein modeling

Knowledge, both from the three-dimensional structures of homologous proteins and from the general analysis of protein structure, is of value in modeling a protein of known sequence but unknown structure. While many models are still constructed at least in part by manual methods on graphics devices, automated procedures have come into greater use. These procedures include those that assemble fragments of structure from other known structures and those that derive coordinates for the model from the satisfaction of restraints placed on atomic positions.

Three-dimensional searching for recurrent structural motifs in data bases of protein structures

The problem of searching a data base of coordinates of proteins for substructures similar to a probe structure or motif is an important problem in computational molecular biology. It is the three-dimensional analog of the one-dimensional case of pattern matching in strings, procedures for which are widely used in molecular biology to search data bases of gene sequences. Typical applications of substructure searching are: (i) Determining whether structural features observed in one protein structure are unique or recurrent, and (ii) in predictions of protein structures, to bridge gaps in an incomplete structural model, by searching the data base for peptides that link the given starting and ending points. We describe our analysis of the problem and our experience in developing software.

Conformational backbone dynamics of the cyclic decapeptide antamanide. Application of a new multiconformational search algorithm based on NMR data

A general procedure for the analysis of biomolecular structures by NMR in the presence of rapid conformational dynamics has been applied to the study of the cyclic decapeptide antamanide. Two-dimensional experiments, relaxation measurements in the rotating frame, and homo- and heteronuclear coupling constant determinations have been used to characterize the dynamic properties of the molecule, in combination with a novel search algorithm for investigating multiconformational equilibria. Direct evidence for the presence of a conformational exchange process with an activation energy of approximately 20 kJ mol-1 and an exchange lifetime of approximately 25 microseconds at 320 K has been obtained from rotating frame relaxation measurements. This evidence is combined with the information derived from the multiconformational search algorithm MEDUSA to propose sets of structures that coexist in a dynamic exchange equilibrium.

Differences in the amino acid distributions of 3(10)-helices and alpha-helices

Local determinants of 3(10)-helix stabilization have been ascertained from the analysis of the crystal structure data base. We have clustered all 5-length substructures from 51 nonhomologous proteins into classes based on the conformational similarity of their backbone dihedral angles. Several clusters, derived from 3(10)-helices and multiple-turn conformations, had strong amino acid sequence patterns not evident among alpha-helices. Aspartate occurred over twice as frequently in the N-cap position of 3(10)-helices as in the N-cap position of alpha-helices. Unlike alpha-helices, 3(10)-helices had few C-termini ending in a left-handed alpha conformation; most 3(10) C-caps adopted an extended conformation. Differences in the distribution of hydrophobic residues among 3(10)- and alpha-helices were also apparent, producing amphipathic 3(10)-helices. Local interactions that stabilize 3(10)-helices can be inferred both from the strong amino acid preferences found for these short helices, as well as from the existence of substructures in which tertiary interactions replace consensus local interactions. Because the folding and unfolding of alpha-helices have been postulated to proceed through reverse-turn and 3(10)-helix intermediates, sequence differences between 3(10)- and alpha-helices can also lend insight into factors influencing alpha-helix initiation and propagation.

A common pentapeptide conformation occurs in viral acid proteases and other proteins

We found a pentapeptide conformation, termed a type I twist, which has a strikingly high propensity (56%) for aspartic acid in the first position. Type I twists include the active site loops from cellular and viral aspartic proteases, with the catalytic Asp in the first position. Fifteen other type I twists, from non-homologous proteins, were found among high-resolution structures in the Protein Data Bank using a comparison method based on main-chain torsion angles. We propose that the Asp affects electrostatic interactions and thus plays a major structural role in the formation of this recurring motif, in addition to its catalytic role in the aspartic proteases.