Improved prediction of protein side-chain conformations with SCWRL4

IGF1R variants associated with isolated single suture craniosynostosis

The genetic contribution to the pathogenesis of isolated single suture craniosynostosis is poorly understood. The role of mutations in genes known to be associated with syndromic synostosis appears to be limited. We present our findings of a candidate gene resequencing approach to identify rare variants associated with the most common forms of isolated craniosynostosis. Resequencing of the coding regions, splice junction sites, and 5' and 3' untranslated regions of 27 candidate genes in 186 cases of isolated non-syndromic single suture synostosis revealed three novel and two rare sequence variants (R406H, R595H, N857S, P190S, M446V) in insulin-like growth factor I receptor (IGF1R) that are enriched relative to control samples. Mapping the resultant amino acid changes to the modeled homodimer protein structure suggests a structural basis for segregation between these and other disease-associated mutations found in IGF1R. These data suggest that IGF1R mutations may contribute to the risk and in some cases cause single suture craniosynostosis.

Automated minimization of steric clashes in protein structures

Molecular modeling of proteins including homology modeling, structure determination, and knowledge-based protein design requires tools to evaluate and refine three-dimensional protein structures. Steric clash is one of the artifacts prevalent in low-resolution structures and homology models. Steric clashes arise due to the unnatural overlap of any two nonbonding atoms in a protein structure. Usually, removal of severe steric clashes in some structures is challenging since many existing refinement programs do not accept structures with severe steric clashes. Here, we present a quantitative approach of identifying steric clashes in proteins by defining clashes based on the Van der Waals repulsion energy of the clashing atoms. We also define a metric for quantitative estimation of the severity of clashes in proteins by performing statistical analysis of clashes in high-resolution protein structures. We describe a rapid, automated, and robust protocol, Chiron, which efficiently resolves severe clashes in low-resolution structures and homology models with minimal perturbation in the protein backbone. Benchmark studies highlight the efficiency and robustness of Chiron compared with other widely used methods. We provide Chiron as an automated web server to evaluate and resolve clashes in protein structures that can be further used for more accurate protein design.

Modeling single nucleotide polymorphisms in the human AKR1C1 and AKR1C2 genes: implications for functional and genotyping analyses

Enzymes encoded by the AKR1C1 and AKR1C2 genes are responsible for the metabolism of progesterone and 5α-dihydrotestosterone (DHT), respectively. The effect of amino acid substitutions, resulting from single nucleotide polymorphisms (SNPs) in the AKR1C2 gene, on the enzyme kinetics of the AKR1C2 gene product were determined experimentally by Takashi et al. In this paper, we used homology modeling to predict and analyze the structure of AKR1C1 and AKR1C2 genetic variants. The experimental reduction in enzyme activity in the AKR1C2 variants F46Y and L172Q, as determined by Takahashi et al., is predicted to be due to increased instability in cofactor binding, caused by disruptions to the hydrogen bonds between NADP and AKR1C2, resulting from the insertion of polar residues into largely non-polar environments near the site of cofactor binding. Other AKR1C2 variants were shown to involve either conservative substitutions or changes taking place on the surface of the molecule and distant from the active site, confirming the experimental finding of Takahashi et al. that these variants do not result in any statistically significant reduction in enzyme activity. The AKR1C1 R258C variant is predicted to have no effect on enzyme activity for similar reasons. Thus, we provide further insight into the molecular mechanism of the enzyme kinetics of these proteins. Our data also highlight previously reported difficulties with online databases.

Systematic classification and analysis of themes in protein-DNA recognition

Protein-DNA recognition plays a central role in the regulation of gene expression. With the rapidly increasing number of protein-DNA complex structures available at atomic resolution in recent years, a systematic, complete, and intuitive framework to clarify the intrinsic relationship between the global binding modes of these complexes is needed. In this work, we modified, extended, and applied previously defined RNA-recognition themes to describe protein-DNA recognition and used a protocol that incorporates automatic methods into manual inspection to plant a comprehensive classification tree for currently available high-quality protein-DNA structures. Further, a nonredundant (representative) data set consisting of 200 thematically diverse complexes was extracted from the leaves of the classification tree by using a locally sensitive interface comparison algorithm. On the basis of the representative data set, various physical and chemical properties associated with protein-DNA interactions were analyzed using empirical or semiempirical methods. We also examined the individual energetic components involved in protein-DNA interactions and highlighted the importance of conformational entropy, which has been almost completely ignored in previous studies of protein-DNA binding energy.

PCRPi-DB: a database of computationally annotated hot spots in protein interfaces

Protein–protein interactions are central to almost any cellular process. Although typically protein interfaces are large, it is well established that only a relatively small region, the so-called ‘hot spot’, contributes the most to the total binding energy. There is a clear interest in identifying hot spots because of its application in drug discovery and protein design. Presaging Critical Residues in Protein Interfaces Database (PCRPi-DB) is a public repository that archives computationally annotated hot spots in protein complexes for which the 3D structure is known. Hot spots have been annotated using a new and highly accurate computational method developed in the lab. PCRPi-DB is freely available to the scientific community at http://www.bioinsilico.org/PCRPIDB. Besides browsing and querying the contents of the database, extensive documentation and links to relevant on-line resources and contents are available to users. PCRPi-DB is updated on a weekly basis.

Disease risk of missense mutations using structural inference from predicted function

Advancements in sequencing techniques place personalized genomic medicine upon the horizon, bringing along the responsibility of clinicians to understand the likelihood for a mutation to cause disease, and of scientists to separate etiology from nonpathologic variability. Pathogenicity is discernable from patterns of interactions between a missense mutation, the surrounding protein structure, and intermolecular interactions. Physicochemical stability calculations are not accessible without structures, as is the case for the vast majority of human proteins, so diagnostic accuracy remains in infancy. To model the effects of missense mutations on functional stability without structure, we combine novel protein sequence analysis algorithms to discern spatial distributions of sequence, evolutionary, and physicochemical conservation, through a new approach to optimize component selection. Novel components include a combinatory substitution matrix and two heuristic algorithms that detect positions which confer structural support to interaction interfaces. The method reaches 0.91 AUC in ten-fold cross-validation to predict alteration of function for 6,392 in vitro mutations. For clinical utility we trained the method on 7,022 disease associated missense mutations within the Online Mendelian inheritance in man amongst a larger randomized set. In a blinded prospective test to delineate mutations unique to 186 patients with craniosynostosis from those in the 95 highly variant Coriell controls and 1000 age matched controls, we achieved roughly 1/3 sensitivity and perfect specificity. The component algorithms retained during machine learning constitute novel protein sequence analysis techniques to describe environments supporting neutrality or pathology of mutations. This approach to pathogenetics enables new insight into the mechanistic relationship of missense mutations to disease phenotypes in our patients.

Species specificity of the complement inhibitor compstatin investigated by all-atom molecular dynamics simulations

The development of compounds to regulate the activation of the complement system in non-primate species is of profound interest because it can provide models for human diseases. The peptide compstatin inhibits protein C3 in primate mammals and is a potential therapeutic agent against unregulated activation of complement in humans but is inactive against nonprimate species. Here, we elucidate this species specificity of compstatin by molecular dynamics simulations of complexes between the most potent natural compstatin analog and human or rat C3. The results are compared against an experimental conformation of the human complex, determined recently by X-ray diffraction at 2.4-A resolution. The human complex simulations provide information on the relative contributions to stability of specific C3 and compstatin residues. In the rat simulations, the protein undergoes reproducible conformational changes, which eliminate or weaken specific interactions and reduce the complex stability. The simulation insights can be used to design improved compstatin-based inhibitors for human C3 and active inhibitors against lower mammals.

Consistent refinement of submitted models at CASP using a knowledge-based potential

Protein structure refinement is an important but unsolved problem; it must be solved if we are to predict biological function that is very sensitive to structural details. Specifically, critical assessment of techniques for protein structure prediction (CASP) shows that the accuracy of predictions in the comparative modeling category is often worse than that of the template on which the homology model is based. Here we describe a refinement protocol that is able to consistently refine submitted predictions for all categories at CASP7. The protocol uses direct energy minimization of the knowledge-based potential of mean force that is based on the interaction statistics of 167 atom types (Summa and Levitt, Proc Natl Acad Sci USA 2007; 104:3177-3182). Our protocol is thus computationally very efficient; it only takes a few minutes of CPU time to run typical protein models (300 residues). We observe an average structural improvement of 1% in GDT_TS, for predictions that have low and medium homology to known PDB structures (Global Distance Test score or GDT_TS between 50 and 80%). We also observe a marked improvement in the stereochemistry of the models. The level of improvement varies amongst the various participants at CASP, but we see large improvements (>10% increase in GDT_TS) even for models predicted by the best performing groups at CASP7. In addition, our protocol consistently improved the best predicted models in the refinement category at CASP7 and CASP8. These improvements in structure and stereochemistry prove the usefulness of our computationally inexpensive, powerful and automatic refinement protocol.

A novel evaluation of residue and protein volumes by means of Laguerre tessellation

Amino acids control the protein folding process and maintain its functional fold. This study underlines the interest of the Laguerre tessellation to determine relevant amino acid volumes in proteins. Previous studies used a limited number of proteins and only buried residues. The present computations improve the method and results on three main points: (i) a large, high-quality updated and refined data bank of proteins is used; (ii) all residues are taken into account, including those at the protein surface, thanks to (iii) the addition of a realistic solvent. The new values of the average and standard deviation of amino acid volumes show significant corrections with respect to previous studies. Another issue of the method is the polyhedral protein/water interface area (PIA) which quantifies the exposure of atoms or residues to the solvent. We propose this PIA as a new, parameter-free, alternative for measuring accessibility. The comparison with NACCESS is satisfactory; however, the methods disagree in pointing out buried residues: where NACCESS evaluates to zero, the exposure given by PIA ranges from 0 to 20%. Variations of average residue volumes have been analyzed under several conditions, e.g., how they depend on protein size and on secondary structure environments. As it is based on strong mathematical grounds and on numerous high-quality protein structures, our work gives a reliable methodology and up-to-date values of amino acid volumes and surface accessibility.

Staphylococcus aureus NrdH redoxin is a reductant of the class Ib ribonucleotide reductase

Staphylococci contain a class Ib NrdEF ribonucleotide reductase (RNR) that is responsible, under aerobic conditions, for the synthesis of deoxyribonucleotide precursors for DNA synthesis and repair. The genes encoding that RNR are contained in an operon consisting of three genes, nrdIEF, whereas many other class Ib RNR operons contain a fourth gene, nrdH, that determines a thiol redoxin protein, NrdH. We identified a 77-amino-acid open reading frame in Staphylococcus aureus that resembles NrdH proteins. However, S. aureus NrdH differs significantly from the canonical NrdH both in its redox-active site, C-P-P-C instead of C-M/V-Q-C, and in the absence of the C-terminal [WF]SGFRP[DE] structural motif. We show that S. aureus NrdH is a thiol redox protein. It is not essential for aerobic or anaerobic growth and appears to have a marginal role in protection against oxidative stress. In vitro, S. aureus NrdH was found to be an efficient reductant of disulfide bonds in low-molecular-weight substrates and proteins using dithiothreitol as the source of reducing power and an effective reductant for the homologous class Ib RNR employing thioredoxin reductase and NADPH as the source of the reducing power. Its ability to reduce NrdEF is comparable to that of thioredoxin-thioredoxin reductase. Hence, S. aureus contains two alternative thiol redox proteins, NrdH and thioredoxin, with both proteins being able to function in vitro with thioredoxin reductase as the immediate hydrogen donors for the class Ib RNR. It remains to be clarified under which in vivo physiological conditions the two systems are used.

Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions

Background

Accurate evaluation and modelling of residue-residue interactions within and between proteins is a key aspect of computational structure prediction including homology modelling, protein-protein docking, refinement of low-resolution structures, and computational protein design.

Results

Here we introduce a method for accurate protein structure modelling and evaluation based on a novel 4-distance description of residue-residue interaction geometry. Statistical 4-distance preferences were extracted from high-resolution protein structures and were used as a basis for a knowledge-based potential, called Hunter. We demonstrate that 4-distance description of side chain interactions can be used reliably to discriminate the native structure from a set of decoys. Hunter ranked the native structure as the top one in 217 out of 220 high-resolution decoy sets, in 25 out of 28 "Decoys 'R' Us" decoy sets and in 24 out of 27 high-resolution CASP7/8 decoy sets. The same concept was applied to side chain modelling in protein structures. On a set of very high-resolution protein structures the average RMSD was 1.47 Å for all residues and 0.73 Å for buried residues, which is in the range of attainable accuracy for a model. Finally, we show that Hunter performs as good or better than other top methods in homology modelling based on results from the CASP7 experiment. The supporting web site http://bioinfo.weizmann.ac.il/hunter/ was developed to enable the use of Hunter and for visualization and interactive exploration of 4-distance distributions.

Conclusions

Our results suggest that Hunter can be used as a tool for evaluation and for accurate modelling of residue-residue interactions in protein structures. The same methodology is applicable to other areas involving high-resolution modelling of biomolecules.

Structural and biochemical characterization of a nitrilase from the thermophilic bacterium, Geobacillus pallidus RAPc8

Geobacillus pallidus RAPc8 (NRRL: B-59396) is a moderately thermophilic gram-positive bacterium, originally isolated from Australian lake sediment. The G. pallidus RAPc8 gene encoding an inducible nitrilase was located and cloned using degenerate primers coding for well-conserved nitrilase sequences, coupled with inverse PCR. The nitrilase open reading frame was cloned into an expression plasmid and the expressed recombinant enzyme purified and characterized. The protein had a monomer molecular weight of 35,790 Da, and the purified functional enzyme had an apparent molecular weight of approximately 600 kDa by size exclusion chromatography. Similar to several plant nitrilases and some bacterial nitrilases, the recombinant G. pallidus RAPc8 enzyme produced both acid and amide products from nitrile substrates. The ratios of acid to amide produced from the substrates we tested are significantly different to those reported for other enzymes, and this has implications for our understanding of the mechanism of the nitrilases which may assist with rational design of these enzymes. Electron microscopy and image classification showed complexes having crescent-like, "c-shaped", circular and "figure-8" shapes. Protein models suggested that the various complexes were composed of 6, 8, 10 and 20 subunits, respectively.

Testing computational prediction of missense mutation phenotypes: functional characterization of 204 mutations of human cystathionine beta synthase

Predicting the phenotypes of missense mutations uncovered by large-scale sequencing projects is an important goal in computational biology. High-confidence predictions can be an aid in focusing experimental and association studies on those mutations most likely to be associated with causative relationships between mutation and disease. As an aid in developing these methods further, we have derived a set of random mutations of the enzymatic domains of human cystathionine beta synthase. This enzyme is a dimeric protein that catalyzes the condensation of serine and homocysteine to produce cystathionine. Yeast missing this enzyme cannot grow on medium lacking a source of cysteine, while transfection of functional human CBS into yeast strains missing endogenous enzyme can successfully complement for the missing gene. We used PCR mutagenesis with error-prone Taq polymerase to produce 948 colonies and compared cell growth in the presence or absence of a cysteine source as a measure of CBS function. We were able to infer the phenotypes of 204 single-site mutants, 79 of them deleterious and 125 neutral. This set was used to test the accuracy of six publicly available prediction methods for phenotype prediction of missense mutations: SIFT, PolyPhen, PMut, SNPs3D, PhD-SNP, and nsSNPAnalyzer. The top methods are PolyPhen, SIFT, and nsSNPAnalyzer, which have similar performance. Using kernel discriminant functions, we found that the difference in position-specific scoring matrix values is more predictive than the wild-type PSSM score alone, and that the relative surface area in the biologically relevant complex is more predictive than that of the monomeric proteins.

Beyond rotamers: a generative, probabilistic model of side chains in proteins

Background

Accurately covering the conformational space of amino acid side chains is essential for important applications such as protein design, docking and high resolution structure prediction. Today, the most common way to capture this conformational space is through rotamer libraries - discrete collections of side chain conformations derived from experimentally determined protein structures. The discretization can be exploited to efficiently search the conformational space. However, discretizing this naturally continuous space comes at the cost of losing detailed information that is crucial for certain applications. For example, rigorously combining rotamers with physical force fields is associated with numerous problems.

Results

In this work we present BASILISK: a generative, probabilistic model of the conformational space of side chains that makes it possible to sample in continuous space. In addition, sampling can be conditional upon the protein's detailed backbone conformation, again in continuous space - without involving discretization.

Conclusions

A careful analysis of the model and a comparison with various rotamer libraries indicates that the model forms an excellent, fully continuous model of side chain conformational space. We also illustrate how the model can be used for rigorous, unbiased sampling with a physical force field, and how it improves side chain prediction when used as a pseudo-energy term. In conclusion, BASILISK is an important step forward on the way to a rigorous probabilistic description of protein structure in continuous space and in atomic detail.

The RCK2 domain uses a coordination site present in Kir channels to confer sodium sensitivity to Slo2.2 channels

Slo2 Na(+)-activated potassium channels are widely expressed in neurons and other cells, such as kidney, heart, and skeletal muscle. Although their important physiological roles continue to be appreciated, molecular determinants responsible for sensing intracellular Na(+) remain unknown. Here we report identification of an Na(+) regulatory site, similar to an Na(+) coordination motif described in Kir channels, localized in the RCK2 domain of Slo2.2 channels. Molecular simulations of the homology-modeled Slo2.2 RCK2 domain provided structural insights into the organization of this Na(+) coordination site. Furthermore, free energy calculations reproduced the experimentally derived monovalent cation selectivity. Our results suggest that Slo2.2 and Kir channels share a similar mechanism to coordinate Na(+). The localization of an Na(+) sensor within the RCK2 domain of Slo2.2 further supports the role of RCK (regulators of conductance of K(+)) domains of Slo channels in coupling ion sensing to channel gating.

Development of a rotamer library for use in beta-peptide foldamer computational design

Foldamers present a particularly difficult challenge for accurate computational design compared to the case for conventional peptide and protein design due to the lack of a large body of structural data to allow parametrization of rotamer libraries and energies. We therefore explored the use of molecular mechanics for constructing rotamer libraries for non-natural foldamer backbones. We first evaluated the accuracy of molecular mechanics (MM) for the prediction of rotamer probability distributions in the crystal structures of proteins is explored. The van der Waals radius, dielectric constant and effective Boltzmann temperature were systematically varied to maximize agreement with experimental data. Boltzmann-weighted probabilities from these molecular mechanics energies compare well with database-derived probabilities for both an idealized alpha-helix (R = 0.95) as well as beta-strand conformations (R = 0.92). Based on these parameters, de novo rotamer probabilities for secondary structures of peptides built from beta-amino acids were determined. To limit computational complexity, it is useful to establish a residue-specific criterion for excluding rare, high-energy rotamers from the library. This is accomplished by including only those rotamers with probability greater than a given threshold (e.g., 10%) of the random value, defined as 1/n where n is the number of potential rotamers for each residue type.

Fine grained sampling of residue characteristics using molecular dynamics simulation

In a fine-grained computational analysis of protein structure, we investigated the relationships between a residue's backbone conformations and its side-chain packing as well as conformations. To produce continuous distributions in high resolution, we ran molecular dynamics simulations over a set of protein folds (dynameome). In effect, the dynameome dataset samples not only the states well represented in the PDB but also the known states that are not well represented in the structural database. In our analysis, we characterized the mutual influence among the backbone phi,psi angles with the first side-chain torsion angles (chi(1)) and the volumes occupied by the side-chains. The dependencies of these relationships on side-chain environment and amino acids are further explored. We found that residue volumes exhibit dependency on backbone 2 degrees structure conformation: side-chains pack more densely in extended beta-sheet than in alpha-helical structures. As expected, residue volumes on the protein surface were larger than those in the interior. The first side-chain torsion angles are found to be dependent on the backbone conformations in agreement with previous studies, but the dynameome dataset provides higher resolution of rotamer preferences based on the backbone conformation. All three gauche(-), gauche(+), and trans rotamers show different patterns of phi,psi dependency, and variations in chi(1) value are skewed from their canonical values to relieve the steric strains. By demonstrating the utility of dynameomic modeling on the native state ensemble, this study reveals details of the interplay among backbone conformations, residue volumes and side-chain conformations.

Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble

BACKGROUND

Modelling the ligand binding site of a protein is an important component of understanding protein-ligand interactions and is being actively studied. Even if the side chains are restricted to rotamers, a set of commonly-observed low-energy conformations, the exhaustive combinatorial search of ligand binding site conformers is known as NP-hard. Here we propose a new method, ROTAIMAGE, for modelling the plausible conformers for the ligand binding site given a fixed backbone structure.

RESULTS

ROTAIMAGE includes a procedure of selecting ligand binding site residues, exhaustively searching rotameric conformers, clustering them by dissimilarities in pocket shape, and suggesting a representative conformer per cluster. Prior to the clustering, the list of conformers generated by exhaustive search can be reduced by pruning the conformers that have near identical pocket shapes, which is done using simple bit operations. We tested our approach by modelling the active-site inhibitor binding pockets of matrix metalloproteinase-1 and -13. For both cases, analyzing the conformers based on their pocket shapes substantially reduced the 'computational complexity' (10 to 190 fold). The subsequent clustering revealed that the pocket shapes of both proteins could be grouped into approximately 10 distinct clusters. At this level of clustering, the conformational space spanned by the known crystal structures was well covered. Heatmap analysis identified a few bit blocks that combinatorially dictated the clustering pattern. Using this analytical approach, we demonstrated that each of the bit blocks was associated with a specific pocket residue. Identification of residues that influenced the shape of the pocket is an interesting feature unique to the ROTAIMAGE algorithm.

CONCLUSIONS

ROTAIMAGE is a novel algorithm that was efficient in exploring the conformational space of the ligand binding site. Its ability to identify 'key' pocket residues also provides further insight into conformational flexibility with specific implications for protein-ligand interactions.

PRIMO/PRIMONA: a coarse-grained model for proteins and nucleic acids that preserves near-atomistic accuracy

The new coarse graining model PRIMO/PRIMONA for proteins and nucleic acids is proposed. This model combines one to several heavy atoms into coarse-grained sites that are chosen to allow an analytical, high-resolution reconstruction of all-atom models based on molecular bonding geometry constraints. The accuracy of proposed reconstruction method in terms of structure and energetics is tested and compared with other popular reconstruction methods for a variety of protein and nucleic acid test sets.

Structural basis of membrane targeting by the Dock180 family of Rho family guanine exchange factors (Rho-GEFs)

The Dock180 family of atypical Rho family guanine nucleotide exchange factors (Rho-GEFs) regulate a variety of processes involving cellular or subcellular polarization, including cell migration and phagocytosis. Each contains a Dock homology region-1 (DHR-1) domain that is required to localize its GEF activity to a specific membrane compartment where levels of phosphatidylinositol (3,4,5)-trisphosphate (PtdIns(3,4,5)P(3)) are up-regulated by the local activity of PtdIns 3-kinase. Here we define the structural and energetic bases of phosphoinositide specificity by the DHR-1 domain of Dock1 (a GEF for Rac1), and show that DHR-1 utilizes a C2 domain scaffold and surface loops to create a basic pocket on its upper surface for recognition of the PtdIns(3,4,5)P(3) head group. The pocket has many of the characteristics of those observed in pleckstrin homology domains. We show that point mutations in the pocket that abolish phospholipid binding in vitro ablate the ability of Dock1 to induce cell polarization, and propose a model that brings together recent mechanistic and structural studies to rationalize the central role of DHR-1 in dynamic membrane targeting of the Rho-GEF activity of Dock180.

Quality assessment of protein model-structures using evolutionary conservation

Motivation: Programs that evaluate the quality of a protein structural model are important both for validating the structure determination procedure and for guiding the model-building process. Such programs are based on properties of native structures that are generally not expected for faulty models. One such property, which is rarely used for automatic structure quality assessment, is the tendency for conserved residues to be located at the structural core and for variable residues to be located at the surface.

Results: We present ConQuass, a novel quality assessment program based on the consistency between the model structure and the protein's conservation pattern. We show that it can identify problematic structural models, and that the scores it assigns to the server models in CASP8 correlate with the similarity of the models to the native structure. We also show that when the conservation information is reliable, the method's performance is comparable and complementary to that of the other single-structure quality assessment methods that participated in CASP8 and that do not use additional structural information from homologs.

Availability: A perl implementation of the method, as well as the various perl and R scripts used for the analysis are available at http://bental.tau.ac.il/ConQuass/.

Contact:nirb@tauex.tau.ac.il

Supplementary information:Supplementary data are available at Bioinformatics online.

DOC2B, C2 domains, and calcium: A tale of intricate interactions

Ca(+2)-dependent exocytosis involves vesicle docking, priming, fusion, and recycling. This process is performed and regulated by a vast number of synaptic proteins and depends on proper protein-protein and protein-lipid interactions. Double C2 domain (DOC2) is a protein family of three isoforms found while screening DNA libraries with a C2 probe. DOC2 has three domains: the Munc13-interacting domain and tandem C2s (designated C2A and C2B) connected by a short polar linker. The C2 domain binds phospholipids in a Ca(2+)-dependent manner. This review focuses on the ubiquitously expressed isoform DOC2B. Sequence alignment of the tandem C2 protein family in mouse revealed high homology (81%) between rabphilin-3A and DOC2B proteins. We created a structural model of DOC2B's C2A based on the crystal structure of rabphilin-3A with and without calcium and found that the calcium-binding loops of DOC2B move upon calcium binding, enabling efficient plasma membrane penetration of its C2A. Here, we discuss the potential relation between the DOC2B bioinformatical model and its function and suggest a possible working model for its interaction with other proteins of the exocytotic machinery, including Munc13, Munc18, and syntaxin.

An integrated methodology for mining promiscuous proteins: a case study of an integrative bioinformatics approach for hepatitis C virus non-structural 5A protein

A methodology for elucidation of structural, functional, and mechanistic knowledge on promiscuous proteins is proposed that constitutes a workflow of integrated bioinformatics analysis. Sequence alignments with closely related homologues can reveal conserved regions which are functionally important. Scanning protein motif databases, along with secondary and surface accessibility predictions integrated with post-translational modification sites (PTMs) prediction reveal functional and protein-binding motifs. Integrating this information about the protein with the GO, SCOP, and CATH annotations of the templates can help to formulate a 3D model with reasonable accuracy even in the case of distant sequence homology. A novel integrative model of the non-structural protein 5A of Hepatitis C virus: a hub promiscuous protein with roles in virus replication and host interactions is proposed. The 3D structure for domain II was predicted based on, the Homo sapiens Replication factor-A protein-1 (RPA1), as a template using consensus meta-servers results. Domain III is an intrinsically unstructured domain with a fold from the retroviral matrix protein, which conducts diverse protein interactions and is involved in viral replication and protein interactions. It also has a single-stranded DNA-binding protein motif (SSDP) signature for pyrimidine binding during viral replication. Two protein-binding motifs with high sequence conservation and disordered regions are proposed; the first corresponds to an Interleukin-8B receptor signature (IL-8R-B), while the second has a lymphotoxin beta receptor (LTβR) high local similarity. A mechanism is proposed to their contribution to NS5A Interferon signaling pathway interception. Lastly, the overlapping between LTβR and SSDP is considered as a sign for NS5A date hubs.

Comparative protein structure modeling using Modeller

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.