Structures Of Homologous Proteins Research Articles

63 - Redox-Regulation of Ca2+-Independent Phospholipase A2γ: From Computational Predictions to Experimental Procedures

Redox reactions of cysteine residues lead to a range of reversible post-translational modifications of proteins, regulating their functions. Ca2+-independent phospholipase A2γ (iPLA2γ) belongs to a family of enzymes which catalyze the hydrolysis of membrane glycerophospholipids to liberate free fatty acids and lysophospholipids, contributing to cellular signaling, membrane homeostasis and energy metabolism. The activity of iPLA2γ is regulated by a redox-sensitive process, suggesting a thiol-based modification. Using recent computational methods, we searched the primary sequence of human iPLA2γ for potential cysteine residues that could be involved in a thiol-based redox regulation of the protein. Two cysteines, Cys233 and Cys329, were pointed out as highly probable S-sulfenylation target sites. In addition, we used protein structure homology modeling to create a three-dimensional structure of iPLA2γ to visualize the topology of the predicted cysteine residues. The primary sequence was aligned to search for suitable templates and the model was optimized by energy minimization using the GROMOS96 parameter set and checked for errors in the 3D protein structure. The final 3D structure with visualized cysteine residues was designed using molecular graphic system PyMOL. Using isolated recombinant human iPLA2γ, both Cys233Ser and Cys329Ser targeted mutations revealed altered regulation of the catalytic activity by H2O2. These results are consistent with the participation of iPLA2γ in cellular redox homeostasis and serve as preliminary tools leading to a direct identification of cysteine oxidative modifications of the enzyme. Supported by grant GA15-02051S to M.J. from the Grant Agency of the Czech Republic.

Structure alignment of membrane proteins: Accuracy of available tools and a consensus strategy.

Protein structure alignment methods are used for the detection of evolutionary and functionally related positions in proteins. A wide array of different methods are available, but the choice of the best method is often not apparent to the user. Several studies have assessed the alignment accuracy and consistency of structure alignment methods, but none of these explicitly considered membrane proteins, which are important targets for drug development and have distinct structural features. Here, we compared 13 widely used pairwise structural alignment methods on a test set of homologous membrane protein structures (called HOMEP3). Each pair of structures was aligned and the corresponding sequence alignment was used to construct homology models. The model accuracy compared to the known structures was assessed using scoring functions not incorporated in the tested structural alignment methods. The analysis shows that fragment-based approaches such as FR-TM-align are the most useful for aligning structures of membrane proteins. Moreover, fragment-based approaches are more suitable for comparison of protein structures that have undergone large conformational changes. Nevertheless, no method was clearly superior to all other methods. Additionally, all methods lack a measure to rate the reliability of a position within a structure alignment. To solve both of these problems, we propose a consensus-type approach, combining alignments from four different methods, namely FR-TM-align, DaliLite, MATT, and FATCAT. Agreement between the methods is used to assign confidence values to each position of the alignment. Overall, we conclude that there remains scope for the improvement of structural alignment methods for membrane proteins.

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles.

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation —with Protein Blocks—, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the ‘Hard’ category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.

Structural Studies of GABAA Receptor Binding Sites: Which Experimental Structure Tells us What?

Atomic resolution structures of cys-loop receptors, including one of a γ-aminobutyric acid type A receptor (GABAA receptor) subtype, allow amazing insights into the structural features and conformational changes that these pentameric ligand-gated ion channels (pLGICs) display. Here we present a comprehensive analysis of more than 30 cys-loop receptor structures of homologous proteins that revealed several allosteric binding sites not previously described in GABAA receptors. These novel binding sites were examined in GABAA receptor homology models and assessed as putative candidate sites for allosteric ligands. Four so far undescribed putative ligand binding sites were proposed for follow up studies based on their presence in the GABAA receptor homology models. A comprehensive analysis of conserved structural features in GABAA and glycine receptors (GlyRs), the glutamate gated ion channel, the bacterial homologs Erwinia chrysanthemi (ELIC) and Gloeobacter violaceus GLIC, and the serotonin type 3 (5-HT3) receptor was performed. The conserved features were integrated into a master alignment that led to improved homology models. The large fragment of the intracellular domain that is present in the structure of the 5-HT3 receptor was utilized to generate GABAA receptor models with a corresponding intracellular domain fragment. Results of mutational and photoaffinity ligand studies in GABAA receptors were analyzed in the light of the model structures. This led to an assignment of candidate ligands to two proposed novel pockets, candidate binding sites for furosemide and neurosteroids in the trans-membrane domain were identified. The homology models can serve as hypotheses generators, and some previously controversial structural interpretations of biochemical data can be resolved in the light of the presented multi-template approach to comparative modeling. Crystal and cryo-EM microscopic structures of the closest homologs that were solved in different conformational states provided important insights into structural rearrangements of binding sites during conformational transitions. The impact of structural variation and conformational motion on the shape of the investigated binding sites was analyzed. Rules for best template and alignment choice were obtained and can generally be applied to modeling of cys-loop receptors. Overall, we provide an updated structure based view of ligand binding sites present in GABAA receptors.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction.

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information.Method: We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence–structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration.Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM–HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods.Availability and implementation: Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx.Contact: xin.gao@kaust.edu.saSupplementary information: Supplementary data are available at Bioinformatics online.

Improving Polymerase Activity with Unnatural Substrates by Sampling Mutations in Homologous Protein Architectures.

The ability to synthesize and propagate genetic information encoded in the framework of xeno-nucleic acid (XNA) polymers would inform a wide range of topics from the origins of life to synthetic biology. While directed evolution has produced examples of engineered polymerases that can accept XNA substrates, these enzymes function with reduced activity relative to their natural counterparts. Here, we describe a biochemical strategy that enables the discovery of engineered polymerases with improved activity for a given unnatural polymerase function. Our approach involves identifying specificity determining residues (SDRs) that control polymerase activity, screening mutations at SDR positions in a model polymerase scaffold, and assaying key gain-of-function mutations in orthologous protein architectures. By transferring beneficial mutations between homologous protein structures, we show that new polymerases can be identified that function with superior activity relative to their starting donor scaffold. This concept, which we call scaffold sampling, was used to generate engineered DNA polymerases that can faithfully synthesize RNA and TNA (threose nucleic acid), respectively, on a DNA template with high primer-extension efficiency and low template sequence bias. We suggest that the ability to combine phenotypes from different donor and recipient scaffolds provides a new paradigm in polymerase engineering where natural structural diversity can be used to refine the catalytic activity of synthetic enzymes.

Phylogenetic analysis and protein structure modelling identifies distinct Ca(2+)/Cation antiporters and conservation of gene family structure within Arabidopsis and rice species.

BackgroundThe Ca2+/Cation Antiporter (CaCA) superfamily is an ancient and widespread family of ion-coupled cation transporters found in nearly all kingdoms of life. In animals, K+-dependent and K+-indendent Na+/Ca2+ exchangers (NCKX and NCX) are important CaCA members. Recently it was proposed that all rice and Arabidopsis CaCA proteins should be classified as NCX proteins. Here we performed phylogenetic analysis of CaCA genes and protein structure homology modelling to further characterise members of this transporter superfamily.FindingsPhylogenetic analysis of rice and Arabidopsis CaCAs in comparison with selected CaCA members from non-plant species demonstrated that these genes form clearly distinct families, with the H+/Cation exchanger (CAX) and cation/Ca2+ exchanger (CCX) families dominant in higher plants but the NCKX and NCX families absent. NCX-related Mg2+/H+ exchanger (MHX) and CAX-related Na+/Ca2+ exchanger-like (NCL) proteins are instead present. Analysis of genomes of ten closely-related rice species and four Arabidopsis-related species found that CaCA gene family structures are highly conserved within related plants, apart from minor variation. Protein structures were modelled for OsCAX1a and OsMHX1. Despite exhibiting broad structural conservation, there are clear structural differences observed between the different CaCA types.ConclusionsMembers of the CaCA superfamily form clearly distinct families with different phylogenetic, structural and functional characteristics, and therefore should not be simply classified as NCX proteins, which should remain as a separate gene family.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-016-0075-8) contains supplementary material, which is available to authorized users.

Identification and prediction of the consequences of nonsynonymous SNPs in glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene of zebrafish Danio rerio

The recent progress in DNA sequencing and computational algorithms dramatically heightened the value of single nucleotide polymorphism (SNP) databases. The experimental studies of mutation for the particular gene of interest are laborious and time-consuming. In this study, we used several computational algorithms to investigate the structural and functional consequences of SNPs on the glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene of zebrafish (Danio rerio). The GAPDH gene is involved in multiple cellular activities, in addition to its association with classical glycolytic pathway. It has most commonly been used as the housekeeping gene for differential gene expression profiling, including western blots. The computational analysis, which used sequence-based tools such as SIFT, PANTHER, PROVEAN, and I-Mutant2.0, predicted deleterious nonsynonymous SNPs (nsSNPs) at p.W194R in the GAPDH gene. The SWISS Model tool generated a homology-modeled 3D structure of GAPDH by applying homologous protein structures retrieved from the RCSB PDB databank (PDB ID: 1U8F_O, 1ZNQ_O, 1J0X_O, 3GPD_R, and 1SZJ_G). The sequence identities of the above selected models were 86%, 86%, 86%, 83%, and 75%, respectively. The Procheck quality assessment in the Ramachandran plot showed that the incorporated mutation (p.W194R) led to a shifting of amino acid residues from the most favored regions towards the disallowed region, as compared to the native counterpart. The lowered ERRAT and PROSA Z scores in the mutant confirmed the overall deteriorating quality of mutant GAPDH. We also predicted an effect of mutation on increased H-bonding patterns due to mutant residue. The molecular docking analysis, while binding GAPDH to its ligand (NAD+), also revealed elevated global energy in the mutant. Altogether, this study demonstrated the impact of nsSNPs on the protein structure and function. The results of work provide an insight/roadmap for future investigations with regard to the pathological consequences of nsSNPs using in vivo methods.

A Nucleolar PUF RNA-binding Protein with Specificity for a Unique RNA Sequence

PUF proteins are a conserved group of sequence specific RNA-binding proteins that bind to RNA in a modular fashion. The RNA-binding domain of PUF proteins typically consists of eight clustered Puf repeats. Plant genomes code for large families of PUF proteins that show significant variability in their predicted Puf repeat number, organization, and amino acid sequence. Here we sought to determine whether the observed variability in the RNA-binding domains of four plant PUFs results in a preference for nonclassical PUF RNA target sequences. We report the identification of a novel RNA binding sequence for a nucleolar Arabidopsis PUF protein that contains an atypical RNA-binding domain. The Arabidopsis PUM23 (APUM23) binding sequence was 10 nucleotides in length, contained a centrally located UUGA core element, and had a preferred cytosine at nucleotide position 8. These RNA sequence characteristics differ from those of other PUF proteins, because all natural PUFs studied to date bind to RNAs that contain a conserved UGU sequence at their 5' end and lack specificity for cytosine. Gel mobility shift assays validated the identity of the APUM23 binding sequence and supported the location of 3 of the 10 predicted Puf repeats in APUM23, including the cytosine-binding repeat. The preferred 10-nucleotide sequence bound by APUM23 is present within the 18S rRNA sequence, supporting the known role of APUM23 in 18S rRNA maturation. This work also reveals that APUM23, an ortholog of yeast Nop9, could provide an advanced structural backbone for Puf repeat engineering and target-specific regulation of cellular RNAs.

Accurate Ab Initio and Template-Based Prediction of Short Intrinsically-Disordered Regions by Bidirectional Recurrent Neural Networks Trained on Large-Scale Datasets.

Intrinsically-disordered regions lack a well-defined 3D structure, but play key roles in determining the function of many proteins. Although predictors of disorder have been shown to achieve relatively high rates of correct classification of these segments, improvements over the the years have been slow, and accurate methods are needed that are capable of accommodating the ever-increasing amount of structurally-determined protein sequences to try to boost predictive performances. In this paper, we propose a predictor for short disordered regions based on bidirectional recurrent neural networks and tested by rigorous five-fold cross-validation on a large, non-redundant dataset collected from MobiDB, a new comprehensive source of protein disorder annotations. The system exploits sequence and structural information in the forms of frequency profiles, predicted secondary structure and solvent accessibility and direct disorder annotations from homologous protein structures (templates) deposited in the Protein Data Bank. The contributions of sequence, structure and homology information result in large improvements in predictive accuracy. Additionally, the large scale of the training set leads to low false positive rates, making our systems a robust and efficient way to address high-throughput disorder prediction.

PoLi: A Virtual Screening Pipeline Based on Template Pocket and Ligand Similarity.

Often in pharmaceutical research the goal is to identify small molecules that can interact with and appropriately modify the biological behavior of a new protein target. Unfortunately, most proteins lack both known structures and small molecule binders, prerequisites of many virtual screening, VS, approaches. For such proteins, ligand homology modeling, LHM, that copies ligands from homologous and perhaps evolutionarily distant template proteins, has been shown to be a powerful VS approach to identify possible binding ligands. However, if we want to target a specific pocket for which there is no homologous holo template protein structure, then LHM will not work. To address this issue, in a new pocket-based approach, PoLi, we generalize LHM by exploiting the fact that the number of distinct small molecule ligand-binding pockets in proteins is small. PoLi identifies similar ligand-binding pockets in a holo template protein library, selectively copies relevant parts of template ligands, and uses them for VS. In practice, PoLi is a hybrid structure and ligand-based VS algorithm that integrates 2D fingerprint-based and 3D shape-based similarity metrics for improved virtual screening performance. On standard DUD and DUD-E benchmark databases, using modeled receptor structures, PoLi achieves an average enrichment factor of 13.4 and 9.6, respectively, in the top 1% of the screened library. In contrast, traditional docking-based VS using AutoDock Vina and homology-based VS using FINDSITE(filt) have an average enrichment of 1.6 (3.0) and 9.0 (7.9) on the DUD (DUD-E) sets, respectively. Experimental validation of PoLi predictions on dihydrofolate reductase, DHFR, using differential scanning fluorimetry, DSF, identifies multiple ligands with diverse molecular scaffolds, thus demonstrating the advantage of PoLi over current state-of-the-art VS methods.

Hypothetical protein CT398 (CdsZ) interacts with σ(54) (RpoN)-holoenzyme and the type III secretion export apparatus in Chlamydia trachomatis.

A significant challenge to bacteriology is the relatively large proportion of proteins that lack sufficient sequence similarity to support functional annotation (i.e. hypothetical proteins). The aim of this study was to apply protein structural homology to gain insights into a candidate protein of unknown function (CT398) within the medically important, obligate intracellular bacterium Chlamydia trachomatis. C. trachomatis is a major human pathogen responsible for numerous infections throughout the world that can lead to blindness and infertility. A 2.12 Å crystal structure of hypothetical protein CT398 was determined that was comprised of N-terminal coiled-coil and C-terminal Zn-ribbon domains. The structure of CT398 displayed a high degree of structural similarity to FlgZ (Flagellar-associated zinc-ribbon domain protein) from Helicobacter pylori. This observation directed analyses of candidate protein partners of CT398, revealing interactions with two paralogous type III secretion system (T3SS) ATPase-regulators (CdsL and FliH) and the alternative sigma factor RpoN (σ(54) ). Furthermore, genetic introduction of a conditional expression, affinity-tagged construct into C. trachomatis enabled the purification of a CT398-RpoN-holoenzyme complex, suggesting a potential role for CT398 in modulating transcriptional activity during infection. The interactions reported here, in tandem with previous FlgZ studies in H. pylori, indicate that CT398 functions as a regulator of several key areas of chlamydial biology throughout the developmental cycle. Accordingly, we propose that CT398 be named CdsZ (Contact-dependent secretion-associated zinc-ribbon domain protein).

Structure alignment of membrane proteins: Accuracy of available tools and a consensus strategy.

Protein structure alignment methods are used for the detection of evolutionary and functionally related positions in proteins. A wide array of different methods are available, but the choice of the best method is often not apparent to the user. Several studies have assessed the alignment accuracy and consistency of structure alignment methods, but none of these explicitly considered membrane proteins, which are important targets for drug development and have distinct structural features. Here, we compared 13 widely used pairwise structural alignment methods on a test set of homologous membrane protein structures (called HOMEP3). Each pair of structures was aligned and the corresponding sequence alignment was used to construct homology models. The model accuracy compared to the known structures was assessed using scoring functions not incorporated in the tested structural alignment methods. The analysis shows that fragment-based approaches such as FR-TM-align are the most useful for aligning structures of membrane proteins. Moreover, fragment-based approaches are more suitable for comparison of protein structures that have undergone large conformational changes. Nevertheless, no method was clearly superior to all other methods. Additionally, all methods lack a measure to rate the reliability of a position within a structure alignment. To solve both of these problems, we propose a consensus-type approach, combining alignments from four different methods, namely FR-TM-align, DaliLite, MATT, and FATCAT. Agreement between the methods is used to assign confidence values to each position of the alignment. Overall, we conclude that there remains scope for the improvement of structural alignment methods for membrane proteins.

Multiple Drug Transport Pathways through Human P-Glycoprotein.

P-Glycoprotein (P-gp) is a plasma membrane efflux pump that is commonly associated with therapy resistances in cancers and infectious diseases. P-gp can lower the intracellular concentrations of many drugs to subtherapeutic levels by translocating them out of the cell. Because of the broad range of substrates transported by P-gp, overexpression of P-gp causes multidrug resistance. We reported previously on dynamic transitions of P-gp as it moved through conformations based on crystal structures of homologous ABCB1 proteins using in silico targeted molecular dynamics techniques. We expanded these studies here by docking transport substrates to drug binding sites of P-gp in conformations open to the cytoplasm, followed by cycling the pump through conformations that opened to the extracellular space. We observed reproducible transport of two substrates, daunorubicin and verapamil, by an average of 11-12 Å through the plane of the membrane as P-gp progressed through a catalytic cycle. Methylpyrophosphate, a ligand that should not be transported by P-gp, did not show this movement through P-gp. Drug binding to either of two subsites on P-gp appeared to determine the initial pathway used for drug movement through the membrane. The specific side-chain interactions with drugs within each pathway seemed to be, at least in part, stochastic. The docking and transport properties of a P-gp inhibitor, tariquidar, were also studied. A mechanism of inhibition by tariquidar that involves stabilization of an outward open conformation with tariquidar bound in intracellular loops or at the drug binding domain of P-gp is presented.

Homology Modeling of the Oxytocin G-Protein Coupling Receptor

Oxytocin (OT) is a neurohypophysial hormone, which acts both on the peripheral tissues (hormonal), and as a neurotransmitter in the brain. It plays an important role in the control of uterine contractions during labor, secretion of milk and many social and behavioral functions. OT accomplishes its functions via interaction with specific oxytocin receptors, which belong to the rhodopsin-type (class I) group of G-protein coupled receptors (GPCR). High levels of oxytocin during pregnancy are the main cause for preterm birth. Oxytocin receptor antagonists are widely employed for prevention in such cases [1]. Design of these antagonists requires a proper model of the hormone – receptor interaction. However, the 3D structure of the OT receptor is not known. The aim of this investigation is to construct a three-dimensional model of the oxytocin receptor. Protein structure homology modelling is an efficient technique for generating 3D models of proteins in the absence of experimental data. We employed the software package Modeller to generate a family of oxytocin GPCR structures. The assessment of the structures was based on test MD simulations of their interactions with the natural ligand oxytocin.

Structures of citrate synthase and malate dehydrogenase of Mycobacterium tuberculosis.

The tricarboxylic acid (TCA) cycle is a central metabolic pathway of all aerobic organisms and is responsible for the synthesis of many important precursors and molecules. TCA cycle plays a key role in the metabolism of Mycobacterium tuberculosis and is involved in the adaptation process of the bacteria to the host immune response. We present here the first crystal structures of M. tuberculosis malate dehydrogenase and citrate synthase, two consecutive enzymes of the TCA, at 2.6 Å and 1.5 Å resolution, respectively. General analogies and local differences with the previously reported homologous protein structures are described.

Role of Lipids in Folding, Misfolding and Function of Integral Membrane Proteins.

The lipid bilayer that constitutes cell membranes imposes environmental constraints on the structure, folding and function of integral membrane proteins. The cell membrane is an enormously heterogeneous and dynamic system in its chemical composition and associated physical forces. The lipid compositions of cell membranes not only vary over the tree of life but also differ by subcellular compartments within the same organism. Even in the same subcellular compartment, the membrane composition shows strong temporal and spatial dependence on the environmental or biological cues. Hence, one may expect that the membrane protein conformations and their equilibria strongly depend on the physicochemical variables of the lipid bilayer. Contrary to this expectation, the structures of homologous membrane proteins belonging to the same family but from evolutionary distant organisms exhibit a striking similarity. Furthermore, the atomic structures of the same protein in different lipid environments are also very similar. This suggests that certain stable folds optimized for a specific function have been selected by evolution. On the other hand, there is growing evidence that, despite the overall stability of the protein folds, functions of certain membrane proteins require a particular lipid composition in the bulk bilayer or binding of specific lipid species. Here I discuss the specific and nonspecific modulation of folding, misfolding and function of membrane proteins by lipids and introduce several diseases that are caused by misfolding of membrane proteins.

Leishmania braziliensis replication protein A subunit 1: molecular modelling, protein expression and analysis of its affinity for both DNA and RNA.

BackgroundReplication factor A (RPA) is a single-strand DNA binding protein involved in DNA replication, recombination and repair processes. It is composed by the subunits RPA-1, RPA-2 and RPA-3; the major DNA-binding activity resides in the subunit 1 of the heterotrimeric RPA complex. In yeast and higher eukaryotes, besides the three basic structural DNA-binding domains, the RPA-1 subunit contains an N-terminal region involved in protein-protein interactions with a fourth DNA-binding domain. Remarkably, the N-terminal extension is absent in the RPA-1 of the pathogenic protozoan Leishmania (Leishmania) amazonensis; however, the protein maintains its ability to bind ssDNA. In a recent work, we identify Leishmania (Viannia) braziliensis RPA-1 by its specific binding to the untranslated regions of the HSP70 mRNAs, suggesting that this protein might be also an RNA-binding protein.MethodsBoth rLbRPA-1 purified by His-tag affinity chromatography as well as the in vitro transcribed L. braziliensis 3′ HSP70-II UTR were used to perform pull down assays to asses nucleic acid binding properties. Also, homology modeling was carried out to construct the LbRPA-1 tridimensional structure to search relevant amino acid residues to bind nucleic acids.ResultsIn this work, after obtaining the recombinant L. braziliensis RPA-1 protein under native conditions, competitive and non-competitive pull-down assays confirmed the single-stranded DNA binding activity of this protein and demonstrated its interaction with the 3′ UTR from the HSP70-II mRNA. As expected, this protein exhibits a high affinity for ssDNA, but we have found that RPA-1 interacts also with RNA. Additionally, we carried out a structural analysis of L. braziliensis RPA-1 protein using the X-ray diffraction structure of Ustilago maydis homologous protein as a template. Our results indicate that, in spite of the evolutionary divergence between both organisms, the structure of these two RPA-1 proteins seems to be highly conserved.ConclusionThe LbRPA-1 protein is a ssDNA binding protein, but also it shows affinity in vitro for the HSP70 mRNA; this finding supports a possible in vivo role in the HSP70 mRNA metabolism. On the other hand, the three dimensional model of Leishmania RPA-1 serves as a starting point for both functional analysis and its exploration as a chemotherapeutic target to combat leishmaniasis.

Improved packing of protein side chains with parallel ant colonies

IntroductionThe accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains.MethodsWe present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library.ResultsWe focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of and 77.11% of angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains.ConclusionsThis parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms.

How do the protonation states of E296 and D312 in OmpF and D299 and D315 in homologous OmpC affect protein structure and dynamics? Simulation studies

In this study, the structural and dynamic properties of two major porins (OmpF and OmpC) in Escherichia coli are investigated using molecular dynamics (MD) simulations. Both porins have the extracellular loop L3 folded halfway through the pore to form a constriction area. The solute influx and efflux are controlled by the L3 movement. E296 and D312 in OmpF and homologous D299 and D315 in OmpC located on the barrel wall are found to play a key role in L3 gating activity. All possible charged states of both E296(D299) and D312(315) are applied in this study to observe changes in overall structure and especially L3 movement. The results show that different protonation states of both residues cause the large-scale deviations in structure and pore cavity especially in OmpF. Fully charged E296(D299) and D312(315) increase the protein flexibility significantly. Deprotonating at least one of E296(D299) and D312(315) helps to fasten L3 to the barrel wall and maintain pore size. Lacking of interactions with D312(315) can lead to the pore closure in OmpF. Comparing with OmpC, not only is OmpF less stable, but it is also more sensitive to the charge states of both E296(D299) and D312(315).