MetaMQAP: a meta-server for the quality assessment of protein models

AI in drug discovery and its clinical relevance

The COVID-19 pandemic has emphasized the need for novel drug discovery process. However, the journey from conceptualizing a drug to its eventual implementation in clinical settings is a long, complex, and expensive process, with many potential points of failure. Over the past decade, a vast growth in medical information has coincided with advances in computational hardware (cloud computing, GPUs, and TPUs) and the rise of deep learning. Medical data generated from large molecular screening profiles, personal health or pathology records, and public health organizations could benefit from analysis by Artificial Intelligence (AI) approaches to speed up and prevent failures in the drug discovery pipeline. We present applications of AI at various stages of drug discovery pipelines, including the inherently computational approaches of de novo design and prediction of a drug's likely properties. Open-source databases and AI-based software tools that facilitate drug design are discussed along with their associated problems of molecule representation, data collection, complexity, labeling, and disparities among labels. How contemporary AI methods, such as graph neural networks, reinforcement learning, and generated models, along with structure-based methods, (i.e., molecular dynamics simulations and molecular docking) can contribute to drug discovery applications and analysis of drug responses is also explored. Finally, recent developments and investments in AI-based start-up companies for biotechnology, drug design and their current progress, hopes and promotions are discussed in this article.

Insights on Rigidity and Flexibility at the Global and Local Levels of Protein Structures and Their Roles in Homologous Psychrophilic, Mesophilic, and Thermophilic Proteins: A Computational Study

The rigidity and flexibility of homologous psychrophilic (P), mesophilic (M), and thermophilic (T) proteins have been investigated at the global and local levels in terms of "packing factors" and "atomic fluctuations" obtained from B-factors. For comparison of atomic fluctuations, correction of errors by considering errors in B-factors from all sources in a consolidated manner and conversion of the fluctuations to the same temperature have been suggested and validated. The results indicate no differences in the global values like the average packing factor among the three classes of protein homologues, but at local levels there are differences. A comparison of homologous protein triplets show that the average atomic fluctuations at a given temperature mainly obey the order P > M > T. Packing factors and the atomic fluctuations are anti-correlated, suggesting that altering the rigidity of the active site might be a potential strategy to make tailor-made psychrophilic or thermophilic proteins from their mesophilic homologues. The computer codes developed and used in this work are available at the link https://github.com/Munna-Sarkar/proteins-rigidity-flexibility.git.

Combined Protein and Alkaloid Research of Chelidonium majus Latex Reveals CmMLP1 Accompanied by Alkaloids with Cytotoxic Potential to Human Cervical Carcinoma Cells

Chelidonium majus L. is a latex-bearing plant used in traditional folk medicine to treat human papillomavirus (HPV)-caused warts, papillae, and condylomas. Its latex and extracts are rich in many low-molecular compounds and proteins, but there is little or no information on their potential interaction. We describe the isolation and identification of a novel major latex protein (CmMLP1) composed of 147 amino acids and present a model of its structure containing a conserved hydrophobic cavity with high affinity to berberine, 8-hydroxycheleritrine, and dihydroberberine. CmMLP1 and the accompanying three alkaloids were present in the eluted chromatographic fractions of latex. They decreased in vitro viability of human cervical cancer cells (HPV-negative and HPV-positive). We combined, for the first time, research on macromolecular and low-molecular-weight compounds of latex-bearing plants in contrast to other studies that investigated proteins and alkaloids separately. The observed interaction between latex protein and alkaloids may influence our knowledge on plant defense. The proposed toolbox may help in further understanding of plant disease resistance and in pharmacological research.

Characterization and expression of a novel thaumatin-like protein (CcTLP1) from papaveraceous plant Corydalis cava

Thaumatin-like proteins (TLPs, osmotins) form a protein family which shares a significant sequence homology to the sweet-tasting thaumatin from the plant Thaumatococcus daniellii. TLPs are not sweet-tasting and are involved in response to biotic stresses and developmental processes. Recently it has been shown using a proteomic approach that the tuber extract from Corydalis cava (Papaveraceae) contains a TLP protein. The aim of this work was to characterize the structure and expression of TLP from C. cava tubers. The results obtained using a PCR approach with degenerate primers demonstrated a coding sequence of a novel protein, named CcTLP1. It consists of 225 aa, has a predicted molecular weight of 24.2 kDa (NCBI GenBank accession no. KJ513303) and has 16 strictly conserved cysteine residues, which form 8 disulfide bridges and stabilize the 3D structure. CcTLP1 may be classified into class IX of plant TLPs. The highest CcTLP1 expression levels were shown by qPCR in the stem of the plant compared to other organs and in the medium-size plants compared to other growth phases. The results confirm that CcTLP1 is expressed during plant growth and development until flowering, with a possible defensive function against different stress conditions.

Voronoia 4-ever

We present an updated version of the Voronoia service that enables fully automated analysis of the atomic packing density of macromolecules. Voronoia combines previous efforts to analyse 3D protein and RNA structures into a single service, combined with state-of-the-art online visualization. Voronoia uses the Voronoi cell method to calculate the free space between neighbouring atoms to estimate van der Waals interactions. Compared to other methods that derive van der Waals interactions by calculating solvent-free surfaces, it explicitly considers volume or packing defects. Large internal voids refer either to water molecules or ions unresolved by X-ray crystallography or cryo-EM, cryptic ligand binding pockets, or parts of a structural model that require further refinement. Voronoia is, therefore mainly used for functional analyses of 3D structures and quality assessments of structural models. Voronoia 4-ever updates the database of precomputed packing densities of PDB entries, allows uploading multiple structures, adds new filter options and facilitates direct access to the results through intuitive display with the NGL viewer. Voronoia is available at: htttp://proteinformatics.org/voronoia.

Homology modeling in the time of collective and artificial intelligence

Homology modeling is a method for building protein 3D structures using protein primary sequence and utilizing prior knowledge gained from structural similarities with other proteins. The homology modeling process is done in sequential steps where sequence/structure alignment is optimized, then a backbone is built and later, side-chains are added. Once the low-homology loops are modeled, the whole 3D structure is optimized and validated. In the past three decades, a few collective and collaborative initiatives allowed for continuous progress in both homology and ab initio modeling. Critical Assessment of protein Structure Prediction (CASP) is a worldwide community experiment that has historically recorded the progress in this field. Folding@Home and Rosetta@Home are examples of crowd-sourcing initiatives where the community is sharing computational resources, whereas RosettaCommons is an example of an initiative where a community is sharing a codebase for the development of computational algorithms. Foldit is another initiative where participants compete with each other in a protein folding video game to predict 3D structure. In the past few years, contact maps deep machine learning was introduced to the 3D structure prediction process, adding more information and increasing the accuracy of models significantly. In this review, we will take the reader in a journey of exploration from the beginnings to the most recent turnabouts, which have revolutionized the field of homology modeling. Moreover, we discuss the new trends emerging in this rapidly growing field.

An information gain-based approach for evaluating protein structure models

For three decades now, knowledge-based scoring functions that operate through the "potential of mean force" (PMF) approach have continuously proven useful for studying protein structures. Although these statistical potentials are not to be confused with their physics-based counterparts of the same name-i.e. PMFs obtained by molecular dynamics simulations-their particular success in assessing the native-like character of protein structure predictions has lead authors to consider the computed scores as approximations of the free energy. However, this physical justification is a matter of controversy since the beginning. Alternative interpretations based on Bayes' theorem have been proposed, but the misleading formalism that invokes the inverse Boltzmann law remains recurrent in the literature. In this article, we present a conceptually new method for ranking protein structure models by quality, which is (i) independent of any physics-based explanation and (ii) relevant to statistics and to a general definition of information gain. The theoretical development described in this study provides new insights into how statistical PMFs work, in comparison with our approach. To prove the concept, we have built interatomic distance-dependent scoring functions, based on the former and new equations, and compared their performance on an independent benchmark of 60,000 protein structures. The results demonstrate that our new formalism outperforms statistical PMFs in evaluating the quality of protein structural decoys. Therefore, this original type of score offers a possibility to improve the success of statistical PMFs in the various fields of structural biology where they are applied. The open-source code is available for download at https://gitlab.rpbs.univ-paris-diderot.fr/src/ig-score.

Ten quick tips for homology modeling of high-resolution protein 3D structures

The purpose of this quick guide is to help new modelers who have little or no background in comparative modeling yet are keen to produce high-resolution protein 3D structures for their study by following systematic good modeling practices, using affordable personal computers or online computational resources. Through the available experimental 3D-structure repositories, the modeler should be able to access and use the atomic coordinates for building homology models. We also aim to provide the modeler with a rationale behind making a simple list of atomic coordinates suitable for computational analysis abiding to principles of physics (e.g., molecular mechanics). Keeping that objective in mind, these quick tips cover the process of homology modeling and some postmodeling computations such as molecular docking and molecular dynamics (MD). A brief section was left for modeling nonprotein molecules, and a short case study of homology modeling is discussed.

Genome-wide functional analyses of plant coiled-coil NLR-type pathogen receptors reveal essential roles of their N-terminal domain in oligomerization, networking, and immunity

The ability to induce a defense response after pathogen attack is a critical feature of the immune system of any organism. Nucleotide-binding leucine-rich repeat receptors (NLRs) are key players in this process and perceive the occurrence of nonself-activities or foreign molecules. In plants, coevolution with a variety of pests and pathogens has resulted in repertoires of several hundred diverse NLRs in single individuals and many more in populations as a whole. However, the mechanism by which defense signaling is triggered by these NLRs in plants is poorly understood. Here, we show that upon pathogen perception, NLRs use their N-terminal domains to transactivate other receptors. Their N-terminal domains homo- and heterodimerize, suggesting that plant NLRs oligomerize upon activation, similar to the vertebrate NLRs; however, consistent with their large number in plants, the complexes are highly heterometric. Also, in contrast to metazoan NLRs, the N-terminus, rather than their centrally located nucleotide-binding (NB) domain, can mediate initial partner selection. The highly redundant network of NLR interactions in plants is proposed to provide resilience to perturbation by pathogens.

Structure-function studies of the asparaginyl-tRNA synthetase from Fasciola gigantica: understanding the role of catalytic and non-catalytic domains

The asparaginyl-tRNA synthetase (NRS) catalyzes the attachment of asparagine to its cognate tRNA during translation. NRS first catalyzes the binding of Asn and ATP to form the NRS-asparaginyl adenylate complex, followed by the esterification of Asn to its tRNA. We investigated the role of constituent domains in regulating the structure and activity of Fasciola gigantica NRS (FgNRS). We cloned the full-length FgNRS, along with its various truncated forms, expressed, and purified the corresponding proteins. Size exclusion chromatography indicated a role of the anticodon-binding domain (ABD) of FgNRS in protein dimerization. The N-terminal domain (NTD) was not essential for cognate tRNA binding, and the hinge region between the ABD and the C-terminal domain (CTD) was crucial for regulating the enzymatic activity. Molecular docking and fluorescence quenching experiments elucidated the binding affinities of the substrates to various domains. The molecular dynamics simulation of the modeled protein showed the presence of an unstructured region between the NTD and ABD that exhibited a large number of conformations over time, and further analysis indicated this region to be intrinsically disordered. The present study provides information on the structural and functional regulation, protein-substrate(s) interactions and dynamics, and the role of non-catalytic domains in regulating the activity of FgNRS.

Rapid evolution of the Helicobacter pylori AlpA adhesin in a high gastric cancer risk region from Colombia

To be able to survive, Helicobacter pylori must adhere to the gastric epithelial cells of its human host. For this purpose, the bacterium employs an array of adhesins, for example, AlpA. The adhesin AlpA has been proposed as a major adhesin because of its critical role in human stomach colonization. Therefore, understanding how AlpA evolved could be important for the development of new diagnostic strategies. However, the genetic variation and microevolutionary patterns of alpA have not been described in Colombia. The study aim was to describe the variation patterns and microevolutionary process of alpA in Colombian clinical isolates of H. pylori. The existing polymorphisms, which are deviations from the neutral model of molecular evolution, and the genetic differentiation of the alpA gene from Colombian clinical isolates of H. pylori were determined. The analysis shows that gene conversion and purifying selection have shaped the evolution of three different variants of alpA in Colombia.

Activation mode of the eukaryotic m2G10 tRNA methyltransferase Trm11 by its partner protein Trm112

Post-transcriptional and post-translational modifications of factors involved in translation are very important for the control and accuracy of protein biosynthesis. Among these factors, tRNAs harbor the largest variety of grafted chemical structures, which participate in tRNA stability or mRNA decoding. Here, we focused on Trm112 protein, which associates with four different eukaryotic methyltransferases modifying tRNAs (Trm9 and Trm11) but also 18S-rRNA (Bud23) and translation termination factor eRF1 (Mtq2). In particular, we have investigated the role of Trm112 in the Trm11–Trm112 complex, which forms 2-methylguanosine at position 10 on several tRNAs and thereby is assumed to stabilize tRNA structure. We show that Trm112 is important for Trm11 enzymatic activity by influencing S-adenosyl-L-methionine binding and by contributing to tRNA binding. Using hydrogen-deuterium eXchange coupled to mass spectrometry, we obtained experimental evidences that the Trm11–Trm112 interaction relies on the same molecular bases as those described for other Trm112–methyltransferases complexes. Hence, all Trm112-dependent methyltransferases compete to interact with this partner.

PLAA Mutations Cause a Lethal Infantile Epileptic Encephalopathy by Disrupting Ubiquitin-Mediated Endolysosomal Degradation of Synaptic Proteins

During neurotransmission, synaptic vesicles undergo multiple rounds of exo-endocytosis, involving recycling and/or degradation of synaptic proteins. While ubiquitin signaling at synapses is essential for neural function, it has been assumed that synaptic proteostasis requires the ubiquitin-proteasome system (UPS). We demonstrate here that turnover of synaptic membrane proteins via the endolysosomal pathway is essential for synaptic function. In both human and mouse, hypomorphic mutations in the ubiquitin adaptor protein PLAA cause an infantile-lethal neurodysfunction syndrome with seizures. Resulting from perturbed endolysosomal degradation, Plaa mutant neurons accumulate K63-polyubiquitylated proteins and synaptic membrane proteins, disrupting synaptic vesicle recycling and neurotransmission. Through characterization of this neurological intracellular trafficking disorder, we establish the importance of ubiquitin-mediated endolysosomal trafficking at the synapse.

Insight into the 3D structure and substrate specificity of previously uncharacterized GNAT superfamily acetyltransferases from pathogenic bacteria

Members of the Gcn5-related N-acetyltransferase (GNAT) superfamily catalyze the acetylation of a wide range of small molecule and protein substrates. Due to their abundance in all kingdoms of life and diversity of their functions, they are implicated in many aspects of eukaryotic and prokaryotic physiology. Although numerous GNATs have been identified thus far, many remain structurally and functionally uncharacterized. The elucidation of their structures and functions is critical for broadening our knowledge of this diverse and important superfamily. In this work, we present the structural and kinetic analyses of two previously uncharacterized bacterial acetyltransferases - SACOL1063 from Staphylococcus aureus strain COL and CD1211 from Clostridium difficile strain 630. Our structures of SACOL1063 show substantial flexibility of a loop that is likely responsible for substrate recognition and binding compared to structures of other homologs. In the CoA complex structure, we found two CoA molecules bound in both the canonical AcCoA/CoA-binding site and the acceptor-substrate-binding site. Our work also provides initial clues regarding the substrate specificity of these two enzymes; however, their native function(s) remain unknown. We found both proteins act as N- rather than O-acetyltransferases and preferentially acetylate l-threonine. The combination of structural and kinetic analyses of these two previously uncharacterized GNATs provides fundamental knowledge and a framework on which future studies can be built to elucidate their native functions.

Dimeric peroxiredoxins are druggable targets in human Burkitt lymphoma

Burkitt lymphoma is a fast-growing tumor derived from germinal center B cells. It is mainly treated with aggressive chemotherapy, therefore novel therapeutic approaches are needed due to treatment toxicity and developing resistance. Disturbance of red-ox homeostasis has recently emerged as an efficient antitumor strategy. Peroxiredoxins (PRDXs) are thioredoxin-family antioxidant enzymes that scavenge cellular peroxides and contribute to red-ox homeostasis. PRDXs are robustly expressed in various malignancies and critically involved in cell proliferation, differentiation and apoptosis. To elucidate potential role of PRDXs in lymphoma, we studied their expression level in B cell-derived primary lymphoma cells as well as in cell lines. We found that PRDX1 and PRDX2 are upregulated in tumor B cells as compared with normal counterparts. Concomitant knockdown of PRDX1 and PRDX2 significantly attenuated the growth rate of lymphoma cells. Furthermore, in human Burkitt lymphoma cell lines, we isolated dimeric 2-cysteine peroxiredoxins as targets for SK053, a novel thiol-specific small-molecule peptidomimetic with antitumor activity. We observed that treatment of lymphoma cells with SK053 triggers formation of covalent PRDX dimers, accumulation of intracellular reactive oxygen species, phosphorylation of ERK1/2 and AKT and leads to cell cycle arrest and apoptosis. Based on site-directed mutagenesis and modeling studies, we propose a mechanism of SK053-mediated PRDX crosslinking, involving double thioalkylation of active site cysteine residues. Altogether, our results suggest that peroxiredoxins are novel therapeutic targets in Burkitt lymphoma and provide the basis for new approaches to the treatment of this disease.

Modeling of the catalytic core of Arabidopsis thaliana Dicer-like 4 protein and its complex with double-stranded RNA

Plant Dicer-like proteins (DCLs) belong to the Ribonuclease III (RNase III) enzyme family. They are involved in the regulation of gene expression and antiviral defense through RNA interference pathways. A model plant, Arabidopsis thaliana encodes four DCL proteins (AtDCL1-4) that produce different classes of small regulatory RNAs. Our studies focus on AtDCL4 that processes double-stranded RNAs (dsRNAs) into 21 nucleotide trans-acting small interfering RNAs. So far, little is known about the structures of plant DCLs and the complexes they form with dsRNA. In this work, we present models of the catalytic core of AtDCL4 and AtDCL4-dsRNA complex constructed by computational methods. We built a homology model of the catalytic core of AtDCL4 comprising Platform, PAZ, Connector helix and two RNase III domains. To assemble the AtDCL4-dsRNA complex two modeling approaches were used. In the first method, to establish conformations that allow building a consistent model of the complex, we used Normal Mode Analysis for both dsRNA and AtDCL4. The second strategy involved template-based approach for positioning of the PAZ domain and manual arrangement of the Connector helix. Our results suggest that the spatial orientation of the Connector helix, Platform and PAZ relative to the RNase III domains is crucial for measuring dsRNA of defined length. The modeled complexes provide information about interactions that may contribute to the relative orientations of these domains and to dsRNA binding. All these information can be helpful for understanding the mechanism of AtDCL4-mediated dsRNA recognition and binding, to produce small RNA of specific size.

Left-handed polyproline-II helix revisited: proteins causing proteopathies

Left-handed polyproline-II type helix is a regular conformation of polypeptide chain not only of fibrous, but also of folded and natively unfolded proteins and peptides. It is the only class of regular secondary structure substantially represented in non-fibrous proteins and peptides on a par with right-handed alpha-helix and beta-structure. In this study, we have shown that polyproline-II helix is abundant in several peptides and proteins involved in proteopathies, the amyloid-beta peptides, protein tau and prion protein. Polyproline-II helices form two interaction sites in the amyloid-beta peptides, which are pivotal for pathogenesis of Alzheimer's disease (AD). It also with high probability is the structure of the majority of tau phosphorylation sites, important for tau hyperphosphorylation and formation of neurofibrillary tangles, a hallmark of AD. Polyproline-II helices form large parts of the structure of the folded domain of prion protein. They can undergo conversion to beta-structure as a result of relatively small change of one torsional angle of polypeptide chain. We hypothesize that in prions and amyloids, in general polyproline-II helices can serve as structural elements of the normal structure as well as dormant nuclei of structure conversion, and thus play important role in structure changes leading to the formation of fibrils.

Structural alignment of protein descriptors - a combinatorial model

Background

Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction.

Results

In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency.

Conclusions

All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub (https://github.com/mantczak/descs-standalone).

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1237-9) contains supplementary material, which is available to authorized users.

Maintenance of electrostatic stabilization in altered tubulin lateral contacts may facilitate formation of helical filaments in foraminifera

Microtubules in foraminiferan protists (forams) can convert into helical filament structures, in which longitudinal intraprotofilament interactions between tubulin heterodimers are thought to be lost, while lateral contacts across protofilaments are still maintained. The coarse geometric features of helical filaments are known through low-resolution negative stain electron microscopy (EM). In this study, geometric restraints derived from these experimental data were used to generate an average atomic-scale helical filament model, which anticipated a modest reorientation in the lateral tubulin heterodimer interface. Restrained molecular dynamics (MD) simulations of the nearest neighbor interactions combined with a Genalized Born implicit solvent model were used to assess the lateral, longitudinal, and seam contacts in 13-3 microtubules and the reoriented lateral contacts in the helical filament model. This electrostatic analysis suggests that the change in the lateral interface in the helical filament does not greatly diminish the lateral electrostatic interaction. After longitudinal dissociation, the 13-3 seam interaction is much weaker than the reoriented lateral interface in the helical filament model, providing a plausible atomic-detail explanation for seam-to-lateral contact transition that enables the transition to a helical filament structure.

Sorting protein decoys by machine-learning-to-rank

Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, and these methods could be roughly divided into three categories: the single-model methods, clustering-based methods and quasi single-model methods. In this study, we develop a single-model method MQAPRank based on the learning-to-rank algorithm firstly, and then implement a quasi single-model method Quasi-MQAPRank. The proposed methods are benchmarked on the 3DRobot and CASP11 dataset. The five-fold cross-validation on the 3DRobot dataset shows the proposed single model method outperforms other methods whose outputs are taken as features of the proposed method, and the quasi single-model method can further enhance the performance. On the CASP11 dataset, the proposed methods also perform well compared with other leading methods in corresponding categories. In particular, the Quasi-MQAPRank method achieves a considerable performance on the CASP11 Best150 dataset.

Identification of Biomarkers for Resistance to Fusarium oxysporum f. sp. cubense Infection and in Silico Studies in Musa paradisiaca Cultivar Puttabale through Proteomic Approach

Panama wilt caused by Fusarium oxysporum f. sp. cubense (Foc) is one of the major disease constraints of banana production. Previously, we reported the disease resistance Musa paradisiaca cv. puttabale clones developed from Ethylmethanesulfonate and Foc culture filtrate against Foc inoculation. Here, the same resistant clones and susceptible clones were used for the study of protein accumulation against Foc inoculation by two-dimensional gel electrophoresis (2-DE), their expression pattern and an in silico approach. The present investigation revealed mass-spectrometry identified 16 proteins that were over accumulated and 5 proteins that were under accumulated as compared to the control. The polyphosphoinositide binding protein ssh2p (PBPssh2p) and Indoleacetic acid-induced-like (IAA) protein showed significant up-regulation and down-regulation. The docking of the pathogenesis-related protein (PR) with the fungal protein endopolygalacturonase (PG) exemplify the three ionic interactions and seven hydrophobic residues that tends to good interaction at the active site of PG with free energy of assembly dissociation (1.5 kcal/mol). The protein-ligand docking of the Peptide methionine sulfoxide reductase chloroplastic-like protein (PMSRc) with the ligand β-1,3 glucan showed minimum binding energy (−6.48 kcal/mol) and docking energy (−8.2 kcal/mol) with an interaction of nine amino-acid residues. These explorations accelerate the research in designing the host pathogen interaction studies for the better management of diseases.

Cell Wall Anchoring of the Campylobacter Antigens to Lactococcus lactis

Campylobacter jejuni is the most frequent cause of human food-borne gastroenteritis and chicken meat is the main source of infection. Recent studies showed that broiler chicken immunization against Campylobacter should be the most efficient way to lower the number of human infections by this pathogen. Induction of the mucosal immune system after oral antigen administration should provide protective immunity to chickens. In this work we tested the usefulness of Lactococcus lactis, the most extensively studied lactic acid bacterium, as a delivery vector for Campylobacter antigens. First we constructed hybrid protein - CjaA antigen presenting CjaD peptide epitopes on its surface. We showed that specific rabbit anti-rCjaAD serum reacted strongly with both CjaA and CjaD produced by a wild type C. jejuni strain. Next, rCjaAD and CjaA were fused to the C-terminus of the L. lactis YndF containing the LPTXG motif. The genes expressing these proteins were transcribed under control of the L. lactis Usp45 promoter and their products contain the Usp45 signal sequences. This strategy ensures a cell surface location of both analyzed proteins, which was confirmed by immunofluorescence assay. In order to evaluate the impact of antigen location on vaccine prototype efficacy, a L. lactis strain producing cytoplasm-located rCjaAD was also generated. Animal experiments showed a decrease of Campylobacter cecal load in vaccinated birds as compared with the control group and showed that the L. lactis harboring the surface-exposed rCjaAD antigen afforded greater protection than the L. lactis producing cytoplasm-located rCjaAD. To the best of our knowledge, this is the first attempt to employ Lactic Acid Bacteria (LAB) strains as a mucosal delivery vehicle for chicken immunization. Although the observed reduction of chicken colonization by Campylobacter resulting from vaccination was rather moderate, the experiments showed that LAB strains can be considered as an alternative vector to deliver heterologous antigens to the bird immune system. Additionally, the analysis of the structure and immunogenicity of the generated rCjaAD hybrid protein showed that the CjaA antigen can be considered as a starting point to construct multiepitope anti-Campylobacter vaccines.

Classification of ADAMTS binding sites: The first step toward selective ADAMTS7 inhibitors

Genome-wide association studies identified ADAMTS7 as a risk locus for coronary artery disease. In carotid arteries of rats, neointima formation after balloon-mediated injury goes along with enhanced Adamts7 expression. Vice versa, Adamts7-deficient mice display reduced neointima formation following vascular injury. Although a causal link between ADAMTS7 and coronary artery disease remains to be proven, inhibition of ADAMTS7 represents a potential new target for intervention in this disease. ADAMTS7, a member of the 'a disintegrin and metalloproteinase with thrombospondin motifs' (ADAMTS) family of proteins, contains a catalytic zinc ion in the binding site of its metalloproteinase domain. The structure of ADAMTS7 and its inhibitors are unknown. In this study, we used in silico methods, including homology modeling and pharmacophore modeling, to analyze the ADAMTS7 metalloproteinase domain, particularly its binding site. The results revealed structural and sequence differences relative to the binding sites of the other ADAMTS proteins; these non-conserved regions represent potential binding regions for selective ADAMTS7 inhibitors. The main contribution of this study is the proposal of a pharmacophore for ADAMTS7. The characterization of the ADAMTS7 binding site and definition of a pharmacophore are the first step toward developing a new therapeutic target for coronary artery disease.

The architecture of the Schizosaccharomyces pombe CCR4-NOT complex

CCR4-NOT is a large protein complex present both in cytoplasm and the nucleus of eukaryotic cells. Although it is involved in a variety of distinct processes related to expression of genetic information such as poly(A) tail shortening, transcription regulation, nuclear export and protein degradation, there is only fragmentary information available on some of its nine subunits. Here we show a comprehensive structural characterization of the native CCR4-NOT complex from Schizosaccharomyces pombe. Our cryo-EM 3D reconstruction of the complex, combined with techniques such as immunomicroscopy, RNA-nanogold labelling, docking of the available high-resolution structures and models of different subunits and domains, allow us to propose its full molecular architecture. We locate all functionally defined domains endowed with deadenylating and ubiquitinating activities, the nucleus-specific RNA-interacting subunit Mmi1, as well as surfaces responsible for protein–protein interactions. This information provides insight into cooperation of the different CCR4-NOT complex functions.

CCR4-NOT is a protein complex involved in a variety of important genetic processes. Here, the authors report the mid-resolution structure of this complex, and model the positions and contacts between the subunits, providing structural support for the previously reported functions of the complex.

Insight into the Meligethes aeneus voltage-sensitive sodium channel structure and an attempt to select the best pyrethroid ligands

BACKGROUND

The voltage-sensitive sodium channel (VSSC) is a target for the pharmacological action of pyrethroids which are used in controlling pests, including those of agricultural importance. Among these is the pollen beetle (Meligethes aeneus F.) - the most serious pest of Brassica napus. Owing to the heavy use of pyrethroids, a widespread build-up of resistance has occurred. The main cause of pyrethroid insensitivity in M. aeneus is considered to be an increased oxidative metabolism; however, the additional mechanism of resistance associated with mutations in the VSSC might contribute to this phenomenon.

RESULTS

We generated a VSSC 3D model to study the docking affinities of pyrethroids to their target site within the channel. Our goal was to identify the pyrethroids for which docking affinity scores were high and not affected by potential mutations in the VSSC. We found that the docking scores of cypermethrin are hardly influenced by the appearance of point mutations. Additionally, tau-fluvalinate, deltamethrin and bifenthrin are VSSC ligands with high affinity scores.

CONCLUSIONS

Our docking models suggest that point mutations in the VSSC binding pocket might affect the stability of ligand interactions and change the pattern of ligand docking locations, which might have a potential effect on VSSC gating properties.

Bioinformatic characterization of type-specific sequence and structural features in auxiliary activity family 9 proteins

BACKGROUND

Due to the impending depletion of fossil fuels, it has become important to identify alternative energy sources. The biofuel industry has proven to be a promising alternative. However, owing to the complex nature of plant biomass, hence the degradation, biofuel production remains a challenge. The copper-dependent Auxiliary Activity family 9 (AA9) proteins have been found to act synergistically with other cellulose-degrading enzymes resulting in an increased rate of cellulose breakdown. AA9 proteins are lytic polysaccharide monooxygenase (LPMO) enzymes, otherwise known as polysaccharide monooxygenases (PMOs). They are further classified as Type 1, 2 or 3 PMOs, depending on the different cleavage products formed. As AA9 proteins are known to exhibit low sequence conservation, the analysis of unique features of AA9 domains of these enzymes should provide insights for the better understanding of how different AA9 PMO types function.

RESULTS

Bioinformatics approaches were used to identify features specific to the catalytic AA9 domains of each type of AA9 PMO. Sequence analysis showed the N terminus to be highly variable with type-specific inserts evident in this region. Phylogenetic analysis was performed to cluster AA9 domains based on their types. Motif analysis enabled the identification of sub-groups within each AA9 PMO type with the majority of these motifs occurring within the highly variable N terminus of AA9 domains. AA9 domain structures were manually docked to crystalline cellulose and used to analyze both the type-specific inserts and motifs at a structural level. The results indicated that these regions influence the AA9 domain active site topology and may contribute to the regioselectivity displayed by different AA9 PMO types. Physicochemical property analysis was performed and detected significant differences in aromaticity, isoelectric point and instability index between certain AA9 PMO types.

CONCLUSIONS

In this study, a type-specific characterisation of AA9 domains was performed using various bioinformatics approaches. These highly variable proteins were found to have a greater degree of conservation within their respective types. Type-specific features were identified for AA9 domains, which could be observed at a sequence, structural and physicochemical level. This provides a basis under which to identify and group new AA9 LPMOs in future.

Large-scale model quality assessment for improving protein tertiary structure prediction

Motivation: Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well.

Results: Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM’s outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling.

Availability and implementation: The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/.

Contact: chengji@missouri.edu

Structural analysis of human 2'-O-ribose methyltransferases involved in mRNA cap structure formation

The 5′ cap of human messenger RNA contains 2′-O-methylation of the first and often second transcribed nucleotide that is important for its processing, translation and stability. Human enzymes that methylate these nucleotides, termed CMTr1 and CMTr2, respectively, have recently been identified. However, the structures of these enzymes and their mechanisms of action remain unknown. In the present study, we solve the crystal structures of the active CMTr1 catalytic domain in complex with a methyl group donor and a capped oligoribonucleotide, thereby revealing the mechanism of specific recognition of capped RNA. This mechanism differs significantly from viral enzymes, thus providing a framework for their specific targeting. Based on the crystal structure of CMTr1, a comparative model of the CMTr2 catalytic domain is generated. This model, together with mutational analysis, leads to the identification of residues involved in RNA and methyl group donor binding.

Human mRNA transcripts possess a 5' cap structure that is modified by methylation. Here, Smietanski et al. present the structures of human methyltransferases responsible for this reaction, revealing key differences to their viral counterparts and thereby providing a framework for targeted drug design.

Phylogenomics and sequence-structure-function relationships in the GmrSD family of Type IV restriction enzymes

BACKGROUND

GmrSD is a modification-dependent restriction endonuclease that specifically targets and cleaves glucosylated hydroxymethylcytosine (glc-HMC) modified DNA. It is encoded either as two separate single-domain GmrS and GmrD proteins or as a single protein carrying both domains. Previous studies suggested that GmrS acts as endonuclease and NTPase whereas GmrD binds DNA.

METHODS

In this work we applied homology detection, sequence conservation analysis, fold recognition and homology modeling methods to study sequence-structure-function relationships in the GmrSD restriction endonucleases family. We also analyzed the phylogeny and genomic context of the family members.

RESULTS

Results of our comparative genomics study show that GmrS exhibits similarity to proteins from the ParB/Srx fold which can have both NTPase and nuclease activity. In contrast to the previous studies though, we attribute the nuclease activity also to GmrD as we found it to contain the HNH endonuclease motif. We revealed residues potentially important for structure and function in both domains. Moreover, we found that GmrSD systems exist predominantly as a fused, double-domain form rather than as a heterodimer and that their homologs are often encoded in regions enriched in defense and gene mobility-related elements. Finally, phylogenetic reconstructions of GmrS and GmrD domains revealed that they coevolved and only few GmrSD systems appear to be assembled from distantly related GmrS and GmrD components.

CONCLUSIONS

Our study provides insight into sequence-structure-function relationships in the yet poorly characterized family of Type IV restriction enzymes. Comparative genomics allowed to propose possible role of GmrD domain in the function of the GmrSD enzyme and possible active sites of both GmrS and GmrD domains. Presented results can guide further experimental characterization of these enzymes.

Random mutagenesis of the nucleotide-binding domain of NRC1 (NB-LRR Required for Hypersensitive Response-Associated Cell Death-1), a downstream signalling nucleotide-binding, leucine-rich repeat (NB-LRR) protein, identifies gain-of-function mutations in the nucleotide-binding pocket

Plant nucleotide-binding, leucine-rich repeat (NB-LRR) proteins confer immunity to pathogens possessing the corresponding avirulence proteins. Activation of NB-LRR proteins is often associated with induction of the hypersensitive response (HR), a form of programmed cell death. NRC1 (NB-LRR Required for HR-Associated Cell Death-1) is a tomato (Solanum lycopersicum) NB-LRR protein that participates in the signalling cascade leading to resistance to the pathogens Cladosporium fulvum and Verticillium dahliae. To identify mutations in NRC1 that cause increased signalling activity, we generated a random library of NRC1 variants mutated in their nucleotide-binding domain and screened them for the ability to induce an elicitor-independent HR in Nicotiana tabacum. Screening of 1920 clones retrieved 11 gain-of-function mutants, with 10 of them caused by a single amino acid substitution. All substitutions are located in or very close to highly conserved motifs within the nucleotide-binding domain, suggesting modulation of the signalling activity of NRC1. Three-dimensional modelling of the nucleotide-binding domain of NRC1 revealed that the targeted residues are centred around the bound nucleotide. Our mutational approach has generated a wide set of novel gain-of-function mutations in NRC1 and provides insight into how the activity of this NB-LRR is regulated.

Genome-wide prediction of prokaryotic two-component system networks using a sequence-based meta-predictor

BACKGROUND

Two component systems (TCS) are signalling complexes manifested by a histidine kinase (receptor) and a response regulator (effector). They are the most abundant signalling pathways in prokaryotes and control a wide range of biological processes. The pairing of these two components is highly specific, often requiring costly and time-consuming experimental characterisation. Therefore, there is considerable interest in developing accurate prediction tools to lessen the burden of experimental work and cope with the ever-increasing amount of genomic information.

RESULTS

We present a novel meta-predictor, MetaPred2CS, which is based on a support vector machine. MetaPred2CS integrates six sequence-based prediction methods: in-silico two-hybrid, mirror-tree, gene fusion, phylogenetic profiling, gene neighbourhood, and gene operon. To benchmark MetaPred2CS, we also compiled a novel high-quality training dataset of experimentally deduced TCS protein pairs for k-fold cross validation, to act as a gold standard for TCS partnership predictions. Combining individual predictions using MetaPred2CS improved performance when compared to the individual methods and in comparison with a current state-of-the-art meta-predictor.

CONCLUSION

We have developed MetaPred2CS, a support vector machine-based metapredictor for prokaryotic TCS protein pairings. Central to the success of MetaPred2CS is a strategy of integrating individual predictors that improves the overall prediction accuracy, with the in-silico two-hybrid method contributing most to performance. MetaPred2CS outperformed other available systems in our benchmark tests, and is available online at http://metapred2cs.ibers.aber.ac.uk, along with our gold standard dataset of TCS interaction pairs.

Structure and intrinsic disorder of the proteins of the Trypanosoma brucei editosome

Mitochondrial pre-mRNAs in trypanosomatids undergo RNA editing to be converted into translatable mRNAs. The reaction is characterized by the insertion and deletion of uridine residues and is catalyzed by a macromolecular protein complex called the editosome. Despite intensive research, structural information for the majority of editosome proteins is still missing and no high resolution structure for the editosome exists. Here we present a comprehensive structural bioinformatics analysis of all proteins of the Trypanosoma brucei editosome. We specifically focus on the interplay between intrinsic order and disorder. According to computational predictions, editosome proteins involved in the basal reaction steps of the processing cycle are mostly ordered. By contrast, thirty percent of the amino acid content of the editosome is intrinsically disordered, which includes most prominently proteins with OB-fold domains. Based on the data we suggest a functional model, in which the structurally disordered domains of the complex are correlated with the RNA binding and RNA unfolding activity of the T. brucei editosome.

Atypical femoral fracture in osteoporosis pseudoglioma syndrome associated with two novel compound heterozygous mutations in LRP5

Osteoporosis pseudoglioma syndrome (OPPG) is a rare autosomal recessive condition of congenital blindness and severe childhood osteoporosis with skeletal fragility, caused by loss-of-function mutations in the low-density lipoprotein receptor-related protein 5 (LRP5) gene. We report the first case of atypical (subtrochanteric) femoral fracture (AFF) in OPPG, occurring in a 38-year-old man within the context of relatively low bone turnover and trabecular osteoporosis on bone histology. We identify two novel LRP5 mutations: R752W is associated with low bone mineral density (BMD), as demonstrated by the heterozygous carriage identified in his 57-year-old mother; however, the combination of this R752W mutation with another novel W79R mutation, causes a severe case of compound heterozygous OPPG. We undertake 3D homology modeling of the four extracellular YWTD β-propeller/EGF-like domains (E1-E4) of LRP5, and show that both novel mutations destabilize the β-propeller domains that are critical for protein and ligand binding to regulate Wnt signaling and osteoblast function. Although AFFs have been reported in other rare bone diseases, this is the first in a genetic condition of primary osteoblast dysfunction. The relatively low bone turnover observed, and knowledge of LRP5 function, implicates impaired bone remodeling in the pathogenesis of AFF.

Identification of STAT1 and STAT3 specific inhibitors using comparative virtual screening and docking validation

Signal transducers and activators of transcription (STATs) facilitate action of cytokines, growth factors and pathogens. STAT activation is mediated by a highly conserved SH2 domain, which interacts with phosphotyrosine motifs for specific STAT-receptor contacts and STAT dimerization. The active dimers induce gene transcription in the nucleus by binding to a specific DNA-response element in the promoter of target genes. Abnormal activation of STAT signaling pathways is implicated in many human diseases, like cancer, inflammation and auto-immunity. Searches for STAT-targeting compounds, exploring the phosphotyrosine (pTyr)-SH2 interaction site, yielded many small molecules for STAT3 but sparsely for other STATs. However, many of these inhibitors seem not STAT3-specific, thereby questioning the present modeling and selection strategies of SH2 domain-based STAT inhibitors. We generated new 3D structure models for all human (h)STATs and developed a comparative in silico docking strategy to obtain further insight into STAT-SH2 cross-binding specificity of a selection of previously identified STAT3 inhibitors. Indeed, by primarily targeting the highly conserved pTyr-SH2 binding pocket the majority of these compounds exhibited similar binding affinity and tendency scores for all STATs. By comparative screening of a natural product library we provided initial proof for the possibility to identify STAT1 as well as STAT3-specific inhibitors, introducing the ‘STAT-comparative binding affinity value’ and ‘ligand binding pose variation’ as selection criteria. In silico screening of a multi-million clean leads (CL) compound library for binding of all STATs, likewise identified potential specific inhibitors for STAT1 and STAT3 after docking validation. Based on comparative virtual screening and docking validation, we developed a novel STAT inhibitor screening tool that allows identification of specific STAT1 and STAT3 inhibitory compounds. This could increase our understanding of the functional role of these STATs in different diseases and benefit the clinical need for more drugable STAT inhibitors with high specificity, potency and excellent bioavailability.

Mechanistic insights of SrtA–LPXTG blockers targeting the transpeptidase mechanism in Streptococcus mutans

The SrtA–LPXTG interaction plays a key role in transpeptidation reaction, cell wall and biofilm formations. This study explains the blocking of LEU interactions with SrtA will results as SrtA inhibitors through MD simulation and energy calculations methods.

Quality assessment of modeled protein structure using physicochemical properties

Physicochemical properties of proteins always guide to determine the quality of the protein structure, therefore it has been rigorously used to distinguish native or native-like structure from other predicted structures. In this work, we explore nine machine learning methods with six physicochemical properties to predict the Root Mean Square Deviation (RMSD), Template Modeling (TM-score), and Global Distance Test (GDT_TS-score) of modeled protein structure in the absence of its true native state. Physicochemical properties namely total surface area, euclidean distance (ED), total empirical energy, secondary structure penalty (SS), sequence length (SL), and pair number (PN) are used. There are a total of 95,091 modeled structures of 4896 native targets. A real coded Self-adaptive Differential Evolution algorithm (SaDE) is used to determine the feature importance. The K-fold cross validation is used to measure the robustness of the best predictive method. Through the intensive experiments, it is found that Random Forest method outperforms over other machine learning methods. This work makes the prediction faster and inexpensive. The performance result shows the prediction of RMSD, TM-score, and GDT_TS-score on Root Mean Square Error (RMSE) as 1.20, 0.06, and 0.06 respectively; correlation scores are 0.96, 0.92, and 0.91 respectively; R(2) are 0.92, 0.85, and 0.84 respectively; and accuracy are 78.82% (with ± 0.1 err), 86.56% (with ± 0.1 err), and 87.37% (with ± 0.1 err) respectively on the testing data set. The data set used in the study is available as supplement at http://bit.ly/RF-PCP-DataSets.

Structural characterization of the putative ABC-type 2 transporter from Thermotoga maritima MSB8

This study describes the structure of the putative ABC-type 2 transporter TM0543 from Thermotoga maritima MSB8 determined at a resolution of 2.3 Å. In comparative sequence-clustering analysis, TM0543 displays similarity to NatAB-like proteins, which are components of the ABC-type Na(+) efflux pump permease. However, the overall structure fold of the predicted nucleotide-binding domain reveals that it is different from any known structure of ABC-type efflux transporters solved to date. The structure of the putative TM0543 domain also exhibits different dimer architecture and topology of its presumed ATP binding pocket, which may indicate that it does not bind nucleotide at all. Structural analysis of calcium ion binding sites found at the interface between TM0543 dimer subunits suggests that protein may be involved in ion-transporting activity. A detailed analysis of the protein sequence and structure is presented and discussed.

A survey of pyrethroid-resistant populations of Meligethes aeneus F. in Poland indicates the incidence of numerous substitutions in the pyrethroid target site of voltage-sensitive sodium channels in individual beetles

The pollen beetle (Meligethes aeneus F.) is the most devastating pest of oilseed rape (Brassica napus) and is controlled by pyrethroid insecticides. However, resistance to pyrethroids in Europe is becoming widespread and predominant. Pyrethroids target the voltage-sensitive sodium channel (VSSC), and mutations in VSSC may be responsible for pyrethroid insensitivity. Here, we analysed individual beetles that were resistant to esfenvalerate, a pyrethroid, from 14 populations that were collected from oilseed rape fields in Poland. We screened the VSSC domains that were presumed to directly interact with pyrethroids. We identified 18 heterozygous nucleic acid substitutions, amongst which six caused an amino acid change: N912S, G926S, I936V, R957G, F1538L and E1553G. Our analysis of the three-dimensional structure of these domains in VSSC revealed that some of these changes may slightly influence the protein structure and hence the docking efficiency of esfenvalerate. Therefore, these mutations may impact the susceptibility of the sodium channel to the action of this insecticide.

Functional and bioinformatics analysis of two Campylobacter jejuni homologs of the thiol-disulfide oxidoreductase, DsbA

Background

Bacterial Dsb enzymes are involved in the oxidative folding of many proteins, through the formation of disulfide bonds between their cysteine residues. The Dsb protein network has been well characterized in cells of the model microorganism Escherichia coli. To gain insight into the functioning of the Dsb system in epsilon-Proteobacteria, where it plays an important role in the colonization process, we studied two homologs of the main Escherichia coli Dsb oxidase (EcDsbA) that are present in the cells of the enteric pathogen Campylobacter jejuni, the most frequently reported bacterial cause of human enteritis in the world.

Methods and Results

Phylogenetic analysis suggests the horizontal transfer of the epsilon-Proteobacterial DsbAs from a common ancestor to gamma-Proteobacteria, which then gave rise to the DsbL lineage. Phenotype and enzymatic assays suggest that the two C. jejuni DsbAs play different roles in bacterial cells and have divergent substrate spectra. CjDsbA1 is essential for the motility and autoagglutination phenotypes, while CjDsbA2 has no impact on those processes. CjDsbA1 plays a critical role in the oxidative folding that ensures the activity of alkaline phosphatase CjPhoX, whereas CjDsbA2 is crucial for the activity of arylsulfotransferase CjAstA, encoded within the dsbA2-dsbB-astA operon.

Conclusions

Our results show that CjDsbA1 is the primary thiol-oxidoreductase affecting life processes associated with bacterial spread and host colonization, as well as ensuring the oxidative folding of particular protein substrates. In contrast, CjDsbA2 activity does not affect the same processes and so far its oxidative folding activity has been demonstrated for one substrate, arylsulfotransferase CjAstA. The results suggest the cooperation between CjDsbA2 and CjDsbB. In the case of the CjDsbA1, this cooperation is not exclusive and there is probably another protein to be identified in C. jejuni cells that acts to re-oxidize CjDsbA1. Altogether the data presented here constitute the considerable insight to the Epsilonproteobacterial Dsb systems, which have been poorly understood so far.

Structural comparison, substrate specificity, and inhibitor binding of AGPase small subunit from monocot and dicot: present insight and future potential

ADP-glucose pyrophosphorylase (AGPase) is the first rate limiting enzyme of starch biosynthesis pathway and has been exploited as the target for greater starch yield in several plants. The structure-function analysis and substrate binding specificity of AGPase have provided enormous potential for understanding the role of specific amino acid or motifs responsible for allosteric regulation and catalytic mechanisms, which facilitate the engineering of AGPases. We report the three-dimensional structure, substrate, and inhibitor binding specificity of AGPase small subunit from different monocot and dicot crop plants. Both monocot and dicot subunits were found to exploit similar interactions with the substrate and inhibitor molecule as in the case of their closest homologue potato tuber AGPase small subunit. Comparative sequence and structural analysis followed by molecular docking and electrostatic surface potential analysis reveal that rearrangements of secondary structure elements, substrate, and inhibitor binding residues are strongly conserved and follow common folding pattern and orientation within monocot and dicot displaying a similar mode of allosteric regulation and catalytic mechanism. The results from this study along with site-directed mutagenesis complemented by molecular dynamics simulation will shed more light on increasing the starch content of crop plants to ensure the food security worldwide.

In silico modeling of human α2C-adrenoreceptor interaction with filamin-2

Vascular smooth muscle α2C-adrenoceptors (α2C-ARs) mediate vasoconstriction of small blood vessels, especially arterioles. Studies of endogenous receptors in human arteriolar smooth muscle cells (referred to as microVSM) and transiently transfected receptors in heterologous HEK293 cells show that the α2C-ARs are perinuclear receptors that translocate to the cell surface under cellular stress and elicit a biological response. Recent studies in microVSM unraveled a crucial role of Rap1A-Rho-ROCK-F-actin pathways in receptor translocation, and identified protein-protein interaction of α2C-ARs with the actin binding protein filamin-2 as an essential step in the process. To better understand the molecular nature and specificity of this interaction, in this study, we constructed comparative models of human α2C-AR and human filamin-2 proteins. Finally, we performed in silico protein-protein docking to provide a structural platform for the investigation of human α2C-AR and filamin-2 interactions. We found that electrostatic interactions seem to play a key role in this complex formation which manifests in interactions between the C-terminal arginines of α2C-ARs (particularly R454 and R456) and negatively charged residues from filamin-2 region between residues 1979 and 2206. Phylogenetic and sequence analysis showed that these interactions have evolved in warm-blooded animals.

Three-dimensional modeling and diversity analysis reveals distinct AVR recognition sites and evolutionary pathways in wild and domesticated wheat Pm3 R genes

The Pm3 gene confers resistance against wheat powdery mildew. Studies of Pm3 diversity have shown that Pm3 alleles isolated from southern populations of wild emmer wheat located in Lebanon, Jordan, Israel, and Syria are more diverse and more distant from bread wheat alleles than alleles from the northern wild wheat populations located in Turkey, Iran, and Iraq. Therefore, southern populations from Israel were studied extensively to reveal novel Pm3 alleles that are absent from the cultivated gene pool. Candidate Pm3 genes were isolated via a polymerase chain reaction cloning approach. Known and newly identified Pm3 genes were subjected to variation analysis and polymorphic amino acid residues were superimposed on a three-dimensional (3D) model of PM3. The region of highest interspecies diversity between Triticum aestivum and T. dicoccoides lies in leucine-rich repeats (LRR) 19 to 24, whereas most intraspecies diversity in T. aestivum is located in LRR 25 to 28. Interestingly, these two regions are separated by one large LRR whose propensity for flexibility facilitates the conformation of the PM3 LRR domain into two differently structured models. The combination of evolutionary and protein 3D structure analysis revealed that Pm3 genes in wild and domesticated wheat show different evolutionary histories which might have been triggered through different interactions with the powdery mildew pathogen.

The crystal structure of pyrimidine/thiamin biosynthesis precursor-like domain-containing protein CAE31940 from proteobacterium Bordetella bronchiseptica RB50, and evolutionary insight into the NMT1/THI5 family

We report a 2.0 Å structure of the CAE31940 protein, a proteobacterial NMT1/THI5-like domain-containing protein. We also discuss the primary and tertiary structure similarity with its homologs. The highly conserved FGGXMP motif was identified in CAE31940, which corresponds to the GCCCX motif located in the vicinity of the active center characteristic for THi5-like proteins found in yeast. This suggests that the FGGXMP motif may be a unique hallmark of proteobacterial NMT1/THI5-like proteins.