Detection of functionally important regions in "hypothetical proteins" of known structure

An immuno-informatics approach for annotation of hypothetical proteins and multi-epitope vaccine designed against the Mpox virus

A worrying new outbreak of Monkeypox (Mpox) in humans is caused by the Mpox virus (MpoxV). The pathogen has roughly 28 hypothetical proteins of unknown structure, function, and pathogenicity. Using reliable bioinformatics tools, we attempted to analyze the MpoxV genome, identify the role of hypothetical proteins (HPs), and design a potential candidate vaccine. Out of 28, we identified seven hypothetical proteins using multi-server validation with high confidence for the occurrence of conserved domains. Their physical, chemical, and functional characterizations, including molecular weight, theoretical isoelectric point, 3D structures, GRAVY value, subcellular localization, functional motifs, antigenicity, and virulence factors, were performed. We predicted possible cytotoxic T cell (CTL), helper T cell (HTL) and linear and conformational B cell epitopes, which were combined in a 219 amino acid multiepitope vaccine with human β defensin as a linker. This multi-epitopic vaccine was structurally modelled and docked with toll-like receptor-3 (TLR-3). The dynamical stability of the vaccine-TLR-3 docked complexes exhibited stable interactions based on RMSD and RMSF tests. Additionally, the modelled vaccine was cloned in-silico in an E. coli host to check the appropriate expression of the final vaccine built. Our results might conform to an immunogenic and safe vaccine, which would require further experimental validation.Communicated by Ramaswamy H. Sarma.

Biochemical and structural characterization reveals Rv3400 codes for β-phosphoglucomutase in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) adapt to various host environments and utilize a variety of sugars and lipids as carbon sources. Among these sugars, maltose and trehalose, also play crucial role in bacterial physiology and virulence. However, some key enzymes involved in trehalose and maltose metabolism in Mtb are not yet known. Here we structurally and functionally characterized a conserved hypothetical gene Rv3400. We determined the crystal structure of Rv3400 at 1.7 Å resolution. The crystal structure revealed that Rv3400 adopts Rossmann fold and shares high structural similarity with haloacid dehalogenase family of proteins. Our comparative structural analysis suggested that Rv3400 could perform either phosphatase or pyrophosphatase or β-phosphoglucomutase (β-PGM) activity. Using biochemical studies, we further confirmed that Rv3400 performs β-PGM activity and hence, Rv3400 encodes for β-PGM in Mtb. Our data also confirm that Mtb β-PGM is a metal dependent enzyme having broad specificity for divalent metal ions. β-PGM converts β-D-glucose-1-phosphate to β-D-glucose-6-phosphate which is required for the generation of ATP and NADPH through glycolysis and pentose phosphate pathway, respectively. Using site directed mutagenesis followed by biochemical studies, we show that two Asp residues in the highly conserved DxD motif, D29 and D31, are crucial for enzyme activity. While D29A, D31A, D29E, D31E and D29N mutants lost complete activity, D31N mutant retained about 30% activity. This study further helps in understanding the role of β-PGM in the physiology of Mtb.

Functional annotation of Candida albicans hypothetical proteins: a bioinformatics approach

Candida albicans is a member of the ascomycetes class of fungi and it is an opportunistic pathogen species responsible for a wide range of fungal infections in humans. Bioinformatics and sequencing analysis of Candida proteomics has disclosed that around 69% proteome is still uncharacterized which needs to be annotated with functions. The NCBI-Genome has termed them as hypothetical proteins (HPs) in the whole proteome of Candida. Interpretation of this substantial portion of the proteome can reveal novel pharmacological targets for markers, drug development, and other therapeutics and so on. In this article, we have assigned functional annotation to these hypothetical proteins using bioinformatics methodologies. The advanced and robust computational models have been used to assign the preliminary functions to these putative HPs with high level of confidence. The findings of this study unveil some novel pharmacological targets for drug therapy and vaccines and it would help to identify novel molecular mechanisms underlying the fungal pathogenesis.

In silico analysis of a novel hypothetical protein (YP_498675.1) from Staphylococcus aureus unravels the protein of tryptophan synthase beta superfamily (Try-synth-beta_ II)

BACKGROUND

Staphylococcus aureus is a gram-positive spherical bacteria and the most common cause of nosocomial infections in the world. Given its clinical significance, the genome sequence of S. aureus has been elucidated to enhance our comprehension of its lifestyle and pathogenicity. The research aimed to summarize a potential hypothetical protein that may play an important role in S. aureus virulence and pathogenicity, covering its anticipated structure, probable biological functions, and importance in this context.

RESULTS

A hypothetical protein, YP_498675.1 with 281 amino acid residues of S. aureus, was chosen for analysis and modeling by several bioinformatics tools and databases in this work. According to primary and secondary structure analyses, YP_498675.1 is a stable hydrophilic protein with a significant proportion of α-helices. Subcellular localization predictions by CELLO, PSORTb, and SOSUI server indicate that it is a cytoplasmic protein. NCBI-CDD, Pfam, and InterProScan functional genomics research revealed that the hypothetical protein may include the pyridoxal phosphate (PLP)-dependent 2, 3-diaminopropionate biosynthesis protein SbnA domain. In the homology modeling method, the HHpred server was employed to create its 3D structure using the template structure of a Staphyloferrin B precursor biosynthetic enzyme SbnA bound to PLP (PDB ID: 5D84_A), an X-ray diffraction model having 100% sequence identity with the hypothetical protein. After energy minimization, several quality assessments and validation factors determined that the generated protein model was reliable and of reasonable quality.

CONCLUSION

The present study has characterized and functionally annotated the hypothetical protein YP_498675.1 of S. aureus. Further experimental validation would aid in determining the actual function of YP_498675.1 as well as confirm the protein's value as a therapeutic target.

In Silico Functional Characterization of a Hypothetical Protein From Pasteurella Multocida Reveals a Novel S-Adenosylmethionine-Dependent Methyltransferase Activity

Genomes may now be sequenced in a matter of weeks, leading to an influx of "hypothetical" proteins (HP) whose activities remain a mystery in GenBank. The information included inside these genes has quickly grown in prominence. Thus, we selected to look closely at the structure and function of an HP (AFF25514.1; 246 residues) from Pasteurella multocida (PM) subsp. multocida str. HN06. Possible insights into bacterial adaptation to new environments and metabolic changes might be gained by studying the functions of this protein. The PM HN06 2293 gene encodes an alkaline cytoplasmic protein with a molecular weight of 28352.60 Da, an isoelectric point (pI) of 9.18, and an overall average hydropathicity of around -0.565. One of its functional domains, tRNA (adenine (37)-N6)-methyltransferase TrmO, is a S-adenosylmethionine (SAM)-dependent methyltransferase (MTase), suggesting that it belongs to the Class VIII SAM-dependent MTase family. The tertiary structures represented by HHpred and I-TASSER models were found to be flawless. We predicted the model's active site using the Computed Atlas of Surface Topography of Proteins (CASTp) and FTSite servers, and then displayed it in 3 dimensional (3D) using PyMOL and BIOVIA Discovery Studio. Based on molecular docking (MD) results, we know that HP interacts with SAM and S-adenosylhomocysteine (SAH), 2 crucial metabolites in the tRNA methylation process, with binding affinities of 7.4 and 7.5 kcal/mol, respectively. Molecular dynamic simulations (MDS) of the docked complex, which included only modest structural adjustments, corroborated the strong binding affinity of SAM and SAH to the HP. Evidence for HP's possible role as an SAM-dependent MTase was therefore given by the findings of Multiple sequence alignment (MSA), MD, and molecular dynamic modeling. These in silico data suggest that the investigated HP might be used as a useful adjunct in the investigation of Pasteurella infections and the development of drugs to treat zoonotic pasteurellosis.

Functional annotation of uncharacterized proteins from Fusobacterium nucleatum: identification of virulence factors

Fusobacterium nucleatum is a gram-negative bacteria associated with diverse infections like appendicitis and colorectal cancer. It mainly attacks the epithelial cells in the oral cavity and throat of the infected individual. It has a single circular genome of 2.7 Mb. Many proteins in F. nucleatum genome are listed as "Uncharacterized." Annotation of these proteins is crucial for obtaining new facts about the pathogen and deciphering the gene regulation, functions, and pathways along with discovery of novel target proteins. In the light of new genomic information, an armoury of bioinformatic tools were used for predicting the physicochemical parameters, domain and motif search, pattern search, and localization of the uncharacterized proteins. The programs such as receiver operating characteristics determine the efficacy of the databases that have been employed for prediction of different parameters at 83.6%. Functions were successfully assigned to 46 uncharacterized proteins which included enzymes, transporter proteins, membrane proteins, binding proteins, etc. Apart from the function prediction, the proteins were also subjected to string analysis to reveal the interacting partners. The annotated proteins were also put through homology-based structure prediction and modeling using Swiss PDB and Phyre2 servers. Two probable virulent factors were also identified which could be investigated further for potential drug-related studies. The assigning of functions to uncharacterized proteins has shown that some of these proteins are important for cell survival inside the host and can act as effective drug targets.

xProtCAS: A Toolkit for Extracting Conserved Accessible Surfaces from Protein Structures

The identification of protein surfaces required for interaction with other biomolecules broadens our understanding of protein function, their regulation by post-translational modification, and the deleterious effect of disease mutations. Protein interaction interfaces are often identifiable as patches of conserved residues on a protein's surface. However, finding conserved accessible surfaces on folded regions requires an understanding of the protein structure to discriminate between functional and structural constraints on residue conservation. With the emergence of deep learning methods for protein structure prediction, high-quality structural models are now available for any protein. In this study, we introduce tools to identify conserved surfaces on AlphaFold2 structural models. We define autonomous structural modules from the structural models and convert these modules to a graph encoding residue topology, accessibility, and conservation. Conserved surfaces are then extracted using a novel eigenvector centrality-based approach. We apply the tool to the human proteome identifying hundreds of uncharacterised yet highly conserved surfaces, many of which contain clinically significant mutations. The xProtCAS tool is available as open-source Python software and an interactive web server.

In silico annotation of a hypothetical protein from Listeria monocytogenes EGD-e unfolds a toxin protein of the type II secretion system

The gram-positive bacterium Listeria monocytogenes is an important foodborne intracellular pathogen that is widespread in the environment. The functions of hypothetical proteins (HP) from various pathogenic bacteria have been successfully annotated using a variety of bioinformatics strategies. In this study, a HP Imo0888 (NP_464414.1) from the Listeria monocytogenes EGD-e strain was annotated using several bioinformatics tools. Various techniques, including CELLO, PSORTb, and SOSUIGramN, identified the candidate protein as cytoplasmic. Domain and motif analysis revealed that the target protein is a PemK/MazF-like toxin protein of the type II toxin-antitoxin system (TA) which was consistent with BLASTp analysis. Through secondary structure analysis, we found the random coil to be the most frequent. The Alpha Fold 2 Protein Structure Prediction Database was used to determine the three-dimensional (3D) structure of the HP using the template structure of a type II TA PemK/MazF family toxin protein (DB ID_AFDB: A0A4B9HQB9) with 99.1% sequence identity. Various quality evaluation tools, such as PROCHECK, ERRAT, Verify 3D, and QMEAN were used to validate the 3D structure. Following the YASARA energy minimization method, the target protein's 3D structure became more stable. The active site of the developed 3D structure was determined by the CASTp server. Most pathogens that harbor TA systems create a crucial risk to human health. Our aim to annotate the HP Imo088 found in Listeria could offer a chance to understand bacterial pathogenicity and identify a number of potential targets for drug development.

Functional Annotation of Hypothetical Proteins From the Enterobacter cloacae B13 Strain and Its Association With Pathogenicity

Enterobacter cloacae B13 strain is a rod-shaped gram-negative bacterium that belongs to the Enterobacteriaceae family. It can cause respiratory and urinary tract infections, and is responsible for several outbreaks in hospitals. E. cloacae has become an important pathogen and an emerging global threat because of its opportunistic and multidrug resistant ability. However, little knowledge is present about a large portion of its proteins and functions. Therefore, functional annotation of the hypothetical proteins (HPs) can provide an improved understanding of this organism and its virulence activity. The workflow in the study included several bioinformatic tools which were utilized to characterize functions, family and domains, subcellular localization, physiochemical properties, and protein-protein interactions. The E. cloacae B13 strain has overall 604 HPs, among which 78 were functionally annotated with high confidence. Several proteins were identified as enzymes, regulatory, binding, and transmembrane proteins with essential functions. Furthermore, 23 HPs were predicted to be virulent factors. These virulent proteins are linked to pathogenesis with their contribution to biofilm formation, quorum sensing, 2-component signal transduction or secretion. Better knowledge about the HPs’ characteristics and functions will provide a greater overview of the proteome. Moreover, it will help against E. cloacae in neonatal intensive care unit (NICU) outbreaks and nosocomial infections.

Hypothetical protein predicted to be tumor suppressor: a protein functional analysis

Litorilituus sediminis is a Gram-negative, aerobic, novel bacterium under the family of Colwelliaceae, has a stunning hypothetical protein containing domain called von Hippel-Lindau that has significant tumor suppressor activity. Therefore, this study was designed to elucidate the structure and function of the biologically important hypothetical protein EMK97_00595 (QBG34344.1) using several bioinformatics tools. The functional annotation exposed that the hypothetical protein is an extracellular secretory soluble signal peptide and contains the von Hippel-Lindau (VHL; VHL beta) domain that has a significant role in tumor suppression. This domain is conserved throughout evolution, as its homologs are available in various types of the organism like mammals, insects, and nematode. The gene product of VHL has a critical regulatory activity in the ubiquitous oxygen-sensing pathway. This domain has a significant role in inhibiting cell proliferation, angiogenesis progression, kidney cancer, breast cancer, and colon cancer. At last, the current study depicts that the annotated hypothetical protein is linked with tumor suppressor activity which might be of great interest to future research in the higher organism.

In-silico characterization and structure-based functional annotation of a hypothetical protein from Campylobacter jejuni involved in propionate catabolism

Campylobacter jejuni is one of the most prevalent organisms associated with foodborne illness across the globe causing campylobacteriosis and gastritis. Many proteins of C. jejuni are still unidentified. The purpose of this study was to determine the structure and function of a non-annotated hypothetical protein (HP) from C. jejuni. A number of properties like physiochemical characteristics, 3D structure, and functional annotation of the HP (accession No. CAG2129885.1) were predicted using various bioinformatics tools followed by further validation and quality assessment. Moreover, the protein-protein interactions and active site were obtained from the STRING and CASTp server, respectively. The hypothesized protein possesses various characteristics including an acidic pH, thermal stability, water solubility, and cytoplasmic distribution. While alpha-helix and random coil structures are the most prominent structural components of this protein, most of it is formed of helices and coils. Along with expected quality, the 3D model has been found to be novel. This study has identified the potential role of the HP in 2-methylcitric acid cycle and propionate catabolism. Furthermore, protein-protein interactions revealed several significant functional partners. The in-silico characterization of this protein will assist to understand its molecular mechanism of action better. The methodology of this study would also serve as the basis for additional research into proteomic and genomic data for functional potential identification.

Comparative proteomic analysis to annotate the structural and functional association of the hypothetical proteins of S. maltophilia k279a and predict potential T and B cell targets for vaccination

Stenotrophomonas maltophilia is a multidrug-resistant bacterium with no precise clinical treatment. This bacterium can be a vital cause for death and different organ failures in immune-compromised, immune-competent, and long-time hospitalized patients. Extensive quorum sensing capability has become a challenge to develop new drugs against this pathogen. Moreover, the organism possesses about 789 proteins which function, structure, and pathogenesis remain obscured. In this piece of work, we tried to enlighten the aforementioned sectors using highly reliable bioinformatics tools validated by the scientific community. At first, the whole proteome sequence of the organism was retrieved and stored. Then we separated the hypothetical proteins and searched for the conserved domain with a high confidence level and multi-server validation, which resulted in 24 such proteins. Furthermore, all of their physical and chemical characterizations were performed, such as theoretical isoelectric point, molecular weight, GRAVY value, and many more. Besides, the subcellular localization, protein-protein interactions, functional motifs, 3D structures, antigenicity, and virulence factors were also evaluated. As an extension of this work, 'RTFAMSSER' and 'PAAPQPSAS' were predicted as potential T and B cell epitopes, respectively. We hope our findings will help in better understating the pathogenesis and smoothen the way to the cure.

In Silico Characterization of a Hypothetical Protein from Shigella dysenteriae ATCC 12039 Reveals a Pathogenesis-Related Protein of the Type-VI Secretion System

Shigellosis caused by Shigella dysenteriae is a major public health concern worldwide, particularly in developing countries. The bacterial genome is known, but there are many hypothetical proteins whose functions are yet to be discovered. A hypothetical protein (accession no. WP_128879999.1, 161 residues) of S. dysenteriae ATCC 12039 strain was selected in this study for comprehensive structural and functional analysis. Subcellular localization and different physicochemical properties of this hypothetical protein were estimated indicating it as a stable, soluble, and extracellular protein. Functional annotation tools, such as NCBI-CD Search, Pfam, and InterProScan, predicted our target protein to be an amidase effector protein 4 (Tae4) of type-VI secretion system (T6SS). Multiple sequence alignment of the homologous sequences coincided with previous findings. Random coil was found to be predominant in secondary structure. Three-dimensional (3D) structure of the protein was obtained using homology modeling method by SWISS-MODEL server using a template protein (PDB ID: 4J30) of 80.12% sequence identity. The 3D structure became more stable after YASARA energy minimization and was validated by several quality assessment tools like PROCHECK, QMEAN, Verify3D, and ERRAT. Superimposition of the target with the template protein by UCSF Chimera generated RMSD value of 0.115 Å, suggesting a reliable 3D structure. The active site of the modeled structure was predicted and visualized by CASTp server and PyMOL. Interestingly, similar binding affinity and key interacting residues were found for the target protein and a Salmonella enterica Tae4 protein with the ligand L-Ala D-Glu-mDAP by molecular docking analysis. Protein-protein docking was also performed between the target protein and hemolysin coregulated protein 1 of T6SS. Finally, the protein was found to be a unique protein of S. dysenteriae nonhomologous to human by comparative genomics approach indicating a potential therapeutic target. Most pathogens harboring T6SS in their system pose a significant threat to the human health. Many T6SSs and their effectors are associated with interbacterial competition, pathogenesis, and virulency; however, relationships between these effectors and pathogenicity of S. dysenteriae are yet to be determined. The study findings provide a lucrative platform for future antibacterial treatment.

Questing functions and structures of hypothetical proteins from Campylobacter jejuni: a computer-aided approach

Campylobacter jejuni (C. jejuni) is considered to be one of the most frequent causes of bacterial gastroenteritis globally, especially in young children. The genome of C. jejuni contains many proteins with unknown functions termed as hypothetical proteins (HPs). These proteins might have essential biological role to show the full spectrum of this bacterium. Hence, our study aimed to determine the functions of HPs, pertaining to the genome of C. jejuni. An in-silico work flow integrating various tools were performed for functional assignment, three-dimensional structure determination, domain architecture predictors, subcellular localization, physicochemical characterization, and protein-protein interactions (PPIs). Sequences of 267 HPs of C. jejuni were analyzed and successfully attributed the function of 49 HPs with higher confidence. Here, we found proteins with enzymatic activity, transporters, binding and regulatory proteins as well as proteins with biotechnological interest. Assessment of the performance of various tools used in this analysis revealed an accuracy of 95% using receiver operating characteristic (ROC) curve analysis. Functional and structural predictions and the results from ROC analyses provided the validity of in-silico tools used in the present study. The approach used for this analysis leads us to assign the function of unknown proteins and relate them with the functions that have already been described in previous literature.

Hypothetical Proteins as Predecessors of Long Non-coding RNAs

Hypothetical Proteins [HP] are the transcripts predicted to be expressed in an organism, but no evidence of it exists in gene banks. On the other hand, long non-coding RNAs [lncRNAs] are the transcripts that might be present in the 5’ UTR or intergenic regions of the genes whose lengths are above 200 bases. With the known unknown [KU] regions in the genomes rapidly existing in gene banks, there is a need to understand the role of open reading frames in the context of annotation. In this commentary, we emphasize that HPs could indeed be the predecessors of lncRNAs.

Functional Annotation and Curation of Hypothetical Proteins Present in A Newly Emerged Serotype 1c of Shigella flexneri: Emphasis on Selecting Targets for Virulence and Vaccine Design Studies

Shigella flexneri is the principal cause of bacillary dysentery, contributing significantly to the global burden of diarrheal disease. The appearance and increase in the multi-drug resistance among Shigella strains, necessitates further genetic studies and development of improved/new drugs against the pathogen. The presence of an abundance of hypothetical proteins in the genome and how little is known about them, make them interesting genetic targets. The present study aims to carry out characterization of the hypothetical proteins present in the genome of a newly emerged serotype of S. flexneri (strain Y394), toward their novel regulatory functions using various bioinformatics databases/tools. Analysis of the genome sequence rendered 4170 proteins, out of which 721 proteins were annotated as hypothetical proteins (HPs) with no known function. The amino acid sequences of these HPs were evaluated using a combination of latest bioinformatics tools based on homology search against functionally identified proteins. Functional domains were considered as the basis to infer the biological functions of HPs in this case and the annotation helped in assigning various classes to the proteins such as signal transducers, lipoproteins, enzymes, membrane proteins, transporters, virulence, and binding proteins. This study contributes to a better understanding of growth, survival, and disease mechanism at molecular level and provides potential new targets for designing drugs against Shigella infection.

Identifying miltefosine-resistant key genes in protein-protein interactions network and experimental verification in Iranian Leishmania major

Drug resistance is a complex phenomenon during leishmaniasis chemotherapy. In this study, the genes and pathways involved in miltefosine (MIL)-resistant Leishmania were identified using microarray data and in silico approaches. GSE30685 and GSE45496 were obtained from GEO database and analyzed with GEO2R tool to identify genes involved in MIL-resistant Leishmania. 177 differentially expressed genes (DEGs) were selected from these GSEs, which about half of them were uncharacterized/hypothetical proteins. The interactions between DEGs were investigated using STRING database and protein-protein interaction (PPI) networks. Five hub nodes were found in the PPI network. The gene ontology (GO) analysis of the resulting network revealed that DNA replication (GO:0006260) and ATP hydrolysis coupled proton transport (GO:0015991) were the most enriched GO term. Iranian MIL-resistant Leishmania major (L. major) parasites were generated by exposure of wild-type isolates to the increasing concentrations of MIL over a period of 5 months. Proof of mRNA expression levels of the obtained hub genes was assessed in Iranian wild-type and acquired resistant L. major parasites by real-time PCR. A significant higher expression level of LDBPK_150170 (encoding protein phosphatase 2C, PP2C), was only observed in Iranian L. major parasites resistance to MIL. Moreover, the RT-PCR results showed that the expression of metacyclic marker (small hydrophilic endoplasmic reticulum-associated protein, SHERP) and MIL-resistant marker (Leishmania MIL-transporter, LMT) was significantly increased and decreased, respectively, in Iranian MIL-resistant L. major parasites. Taken together, these data suggested that PP2C as well as SHERP and LMT genes may be prospective targets for the treatment of MIL-resistant Leishmania.

Cognizance of Molecular Methods for the Generation of Mutagenic Phage Display Antibody Libraries for Affinity Maturation

Antibodies leverage on their unique architecture to bind with an array of antigens. The strength of interaction has a direct relation to the affinity of the antibodies towards the antigen. In vivo affinity maturation is performed through multiple rounds of somatic hypermutation and selection in the germinal centre. This unique process involves intricate sequence rearrangements at the gene level via molecular mechanisms. The emergence of in vitro display technologies, mainly phage display and recombinant DNA technology, has helped revolutionize the way antibody improvements are being carried out in the laboratory. The adaptation of molecular approaches in vitro to replicate the in vivo processes has allowed for improvements in the way recombinant antibodies are designed and tuned. Combinatorial libraries, consisting of a myriad of possible antibodies, are capable of replicating the diversity of the natural human antibody repertoire. The isolation of target-specific antibodies with specific affinity characteristics can also be accomplished through modification of stringent protocols. Despite the ability to screen and select for high-affinity binders, some 'fine tuning' may be required to enhance antibody binding in terms of its affinity. This review will provide a brief account of phage display technology used for antibody generation followed by a summary of different combinatorial library characteristics. The review will focus on available strategies, which include molecular approaches, next generation sequencing, and in silico approaches used for antibody affinity maturation in both therapeutic and diagnostic applications.

A model to predict the function of hypothetical proteins through a nine-point classification scoring schema

BACKGROUND

Hypothetical proteins [HP] are those that are predicted to be expressed in an organism, but no evidence of their existence is known. In the recent past, annotation and curation efforts have helped overcome the challenge in understanding their diverse functions. Techniques to decipher sequence-structure-function relationship, especially in terms of functional modelling of the HPs have been developed by researchers, but using the features as classifiers for HPs has not been attempted. With the rise in number of annotation strategies, next-generation sequencing methods have provided further understanding the functions of HPs.

RESULTS

In our previous work, we developed a six-point classification scoring schema with annotation pertaining to protein family scores, orthology, protein interaction/association studies, bidirectional best BLAST hits, sorting signals, known databases and visualizers which were used to validate protein interactions. In this study, we introduced three more classifiers to our annotation system, viz. pseudogenes linked to HPs, homology modelling and non-coding RNAs associated to HPs. We discuss the challenges and performance of these classifiers using machine learning heuristics with an improved accuracy from Perceptron (81.08 to 97.67), Naive Bayes (54.05 to 96.67), Decision tree J48 (67.57 to 97.00), and SMO_npolyk (59.46 to 96.67).

CONCLUSION

With the introduction of three new classification features, the performance of the nine-point classification scoring schema has an improved accuracy to functionally annotate the HPs.

Functional Prediction of Hypothetical Proteins from Shigella flexneri and Validation of the Predicted Models by Using ROC Curve Analysis

Shigella spp. constitutes some of the key pathogens responsible for the global burden of diarrhoeal disease. With over 164 million reported cases per annum, shigellosis accounts for 1.1 million deaths each year. Majority of these cases occur among the children of the developing nations and the emergence of multi-drug resistance Shigella strains in clinical isolates demands the development of better/new drugs against this pathogen. The genome of Shigella flexneri was extensively analyzed and found 4,362 proteins among which the functions of 674 proteins, termed as hypothetical proteins (HPs) had not been previously elucidated. Amino acid sequences of all these 674 HPs were studied and the functions of a total of 39 HPs have been assigned with high level of confidence. Here we have utilized a combination of the latest versions of databases to assign the precise function of HPs for which no experimental information is available. These HPs were found to belong to various classes of proteins such as enzymes, binding proteins, signal transducers, lipoprotein, transporters, virulence and other proteins. Evaluation of the performance of the various computational tools conducted using receiver operating characteristic curve analysis and a resoundingly high average accuracy of 93.6% were obtained. Our comprehensive analysis will help to gain greater understanding for the development of many novel potential therapeutic interventions to defeat Shigella infection.

Functional annotation of hypothetical proteins from the Exiguobacterium antarcticum strain B7 reveals proteins involved in adaptation to extreme environments, including high arsenic resistance

Exiguobacterium antarcticum strain B7 is a psychrophilic Gram-positive bacterium that possesses enzymes that can be used for several biotechnological applications. However, many proteins from its genome are considered hypothetical proteins (HPs). These functionally unknown proteins may indicate important functions regarding the biological role of this bacterium, and the use of bioinformatics tools can assist in the biological understanding of this organism through functional annotation analysis. Thus, our study aimed to assign functions to proteins previously described as HPs, present in the genome of E. antarcticum B7. We used an extensive in silico workflow combining several bioinformatics tools for function annotation, sub-cellular localization and physicochemical characterization, three-dimensional structure determination, and protein-protein interactions. This genome contains 2772 genes, of which 765 CDS were annotated as HPs. The amino acid sequences of all HPs were submitted to our workflow and we successfully attributed function to 132 HPs. We identified 11 proteins that play important roles in the mechanisms of adaptation to adverse environments, such as flagellar biosynthesis, biofilm formation, carotenoids biosynthesis, and others. In addition, three predicted HPs are possibly related to arsenic tolerance. Through an in vitro assay, we verified that E. antarcticum B7 can grow at high concentrations of this metal. The approach used was important to precisely assign function to proteins from diverse classes and to infer relationships with proteins with functions already described in the literature. This approach aims to produce a better understanding of the mechanism by which this bacterium adapts to extreme environments and to the finding of targets with biotechnological interest.

Novel approach for structural identification of protein family: glyoxalase I

Glyoxalase is one of two enzymes of the glyoxalase detoxification system against methylglyoxal and other aldehydes, the metabolites derived from glycolysis. The glyoxalase system is found almost in all living organisms: bacteria, protozoa, plants, and animals, including humans, and is related to the class of 'life essential proteins'. The enzyme belongs to the expanded Glyoxalase/Bleomycin resistance protein/Dioxygenase superfamily. At present the GenBank contains about 700 of amino acid sequences of this enzyme type, and the Protein Data Bank includes dozens of spatial structures. We have offered a novel approach for structural identification of glyoxalase I protein family, which is based on the selecting of basic representative proteins with known structures. On this basis, six new subfamilies of these enzymes have been derived. Most populated subfamilies A1 and A2 were based on representative human Homo sapiens and bacterial Escherichia coli enzymes. We have found that the principle feature, which defines the subfamilies' structural differences, is conditioned by arrangement of N- and C-domains inside the protein monomer. Finely, we have deduced the structural classification for the glyoxalase I and assigned about 460 protein sequences distributed among six new subfamilies. Structural similarities and specific differences of all the subfamilies have been presented. This approach can be used for structural identification of thousands of the so-called hypothetical proteins with the known PDB structures allowing to identify many of already existing atomic coordinate entrees.

Functional, structural and epitopic prediction of hypothetical proteins of Mycobacterium tuberculosis H37Rv: An in silico approach for prioritizing the targets

The global control of tuberculosis (TB) remains a great challenge from the standpoint of diagnosis, detection of drug resistance, and treatment. Major serodiagnostic limitations include low sensitivity and high cost in detecting TB. On the other hand, treatment measures are often hindered by low efficacies of commonly used drugs and resistance developed by the bacteria. Hence, there is a need to look into newer diagnostic and therapeutic targets. The proteome information available suggests that among the 3906 proteins in Mycobacterium tuberculosis H37Rv, about quarter remain classified as hypothetical uncharacterized set. This study involves a combination of a number of bioinformatics tools to analyze those hypothetical proteins (HPs). An entire set of 999 proteins was primarily screened for protein sequences having conserved domains with high confidence using a combination of the latest versions of protein family databases. Subsequently, 98 of such potential target proteins were extensively analyzed by means of physicochemical characteristics, protein-protein interaction, sub-cellular localization, structural similarity and functional classification. Next, we predicted antigenic proteins from the entire set and identified B and T cell epitopes of these proteins in M. tuberculosis H37Rv. We predicted the function of these HPs belong to various classes of proteins such as enzymes, transporters, receptors, structural proteins, transcription regulators and other proteins. However, the structural similarity prediction of the annotated proteins substantiated the functional classification of those proteins. Consequently, based on higher antigenicity score and sub-cellular localization, we choose two (NP_216420.1, NP_216903.1) of the antigenic proteins to exemplify B and T cell epitope prediction approach. Finally we found 15 epitopes those located partially or fully in the linear epitope region. We found 21 conformational epitopes by using Ellipro server as well. In silico methodology used in this study and the data thus generated for HPs of M. tuberculosis H37Rv may facilitate swift experimental identification of potential serodiagnostic and therapeutic targets for treatment and control.

ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules

The degree of evolutionary conservation of an amino acid in a protein or a nucleic acid in DNA/RNA reflects a balance between its natural tendency to mutate and the overall need to retain the structural integrity and function of the macromolecule. The ConSurf web server (http://consurf.tau.ac.il), established over 15 years ago, analyses the evolutionary pattern of the amino/nucleic acids of the macromolecule to reveal regions that are important for structure and/or function. Starting from a query sequence or structure, the server automatically collects homologues, infers their multiple sequence alignment and reconstructs a phylogenetic tree that reflects their evolutionary relations. These data are then used, within a probabilistic framework, to estimate the evolutionary rates of each sequence position. Here we introduce several new features into ConSurf, including automatic selection of the best evolutionary model used to infer the rates, the ability to homology-model query proteins, prediction of the secondary structure of query RNA molecules from sequence, the ability to view the biological assembly of a query (in addition to the single chain), mapping of the conservation grades onto 2D RNA models and an advanced view of the phylogenetic tree that enables interactively rerunning ConSurf with the taxa of a sub-tree.

DynaFace: Discrimination between Obligatory and Non-obligatory Protein-Protein Interactions Based on the Complex's Dynamics

Protein-protein interfaces have been evolutionarily-designed to enable transduction between the interacting proteins. Thus, we hypothesize that analysis of the dynamics of the complex can reveal details about the nature of the interaction, and in particular whether it is obligatory, i.e., persists throughout the entire lifetime of the proteins, or not. Indeed, normal mode analysis, using the Gaussian network model, shows that for the most part obligatory and non-obligatory complexes differ in their decomposition into dynamic domains, i.e., the mobile elements of the protein complex. The dynamic domains of obligatory complexes often mix segments from the interacting chains, and the hinges between them do not overlap with the interface between the chains. In contrast, in non-obligatory complexes the interface often hinges between dynamic domains, held together through few anchor residues on one side of the interface that interact with their counterpart grooves in the other end. In automatic analysis, 117 of 139 obligatory (84.2%) and 203 of 246 non-obligatory (82.5%) complexes are correctly classified by our method: DynaFace. We further use DynaFace to predict obligatory and non-obligatory interactions among a set of 300 putative protein complexes. DynaFace is available at: http://safir.prc.boun.edu.tr/dynaface.

Towards New Drug Targets? Function Prediction of Putative Proteins of Neisseria meningitidis MC58 and Their Virulence Characterization

Neisseria meningitidis is a Gram-negative aerobic diplococcus, responsible for a variety of meningococcal diseases. The genome of N. meningitidis MC58 is comprised of 2114 genes that are translated into 1953 proteins. The 698 genes (∼35%) encode hypothetical proteins (HPs), because no experimental evidence of their biological functions are available. Analyses of these proteins are important to understand their functions in the metabolic networks and may lead to the discovery of novel drug targets against the infections caused by N. meningitidis. This study aimed at the identification and categorization of each HP present in the genome of N. meningitidis MC58 using computational tools. Functions of 363 proteins were predicted with high accuracy among the annotated set of HPs investigated. The reliably predicted 363 HPs were further grouped into 41 different classes of proteins, based on their possible roles in cellular processes such as metabolism, transport, and replication. Our studies revealed that 22 HPs may be involved in the pathogenesis caused by this microorganism. The top two HPs with highest virulence scores were subjected to molecular dynamics (MD) simulations to better understand their conformational behavior in a water environment. We also compared the MD simulation results with other virulent proteins present in N. meningitidis. This study broadens our understanding of the mechanistic pathways of pathogenesis, drug resistance, tolerance, and adaptability for host immune responses to N. meningitidis.

Structure-based functional annotation of putative conserved proteins having lyase activity from Haemophilus influenzae

Haemophilus influenzae is a small pleomorphic Gram-negative bacteria which causes several chronic diseases, including bacteremia, meningitis, cellulitis, epiglottitis, septic arthritis, pneumonia, and empyema. Here we extensively analyzed the sequenced genome of H. influenzae strain Rd KW20 using protein family databases, protein structure prediction, pathways and genome context methods to assign a precise function to proteins whose functions are unknown. These proteins are termed as hypothetical proteins (HPs), for which no experimental information is available. Function prediction of these proteins would surely be supportive to precisely understand the biochemical pathways and mechanism of pathogenesis of Haemophilus influenzae. During the extensive analysis of H. influenzae genome, we found the presence of eight HPs showing lyase activity. Subsequently, we modeled and analyzed three-dimensional structure of all these HPs to determine their functions more precisely. We found these HPs possess cystathionine-β-synthase, cyclase, carboxymuconolactone decarboxylase, pseudouridine synthase A and C, D-tagatose-1,6-bisphosphate aldolase and aminodeoxychorismate lyase-like features, indicating their corresponding functions in the H. influenzae. Lyases are actively involved in the regulation of biosynthesis of various hormones, metabolic pathways, signal transduction, and DNA repair. Lyases are also considered as a key player for various biological processes. These enzymes are critically essential for the survival and pathogenesis of H. influenzae and, therefore, these enzymes may be considered as a potential target for structure-based rational drug design. Our structure–function relationship analysis will be useful to search and design potential lead molecules based on the structure of these lyases, for drug design and discovery.

The structure of SAV1646 from Staphylococcus aureus belonging to a new `ribosome-associated' subfamily of bacterial proteins

The crystal structure of the SAV1646 protein from the pathogenic microorganism Staphylococcus aureus has been determined at 1.7 Å resolution. The 106-amino-acid protein forms a two-layer sandwich with α/β topology. The protein molecules associate as dimers in the crystal and in solution, with the monomers related by a pseudo-twofold rotation axis. A sequence-homology search identified the protein as a member of a new subfamily of yet uncharacterized bacterial `ribosome-associated' proteins with at least 13 members to date. A detailed analysis of the crystal protein structure along with the genomic structure of the operon containing the sav1646 gene allowed a tentative functional model of this protein to be proposed. The SAV1646 dimer is assumed to form a complex with ribosomal proteins L21 and L27 which could help to complete the assembly of the large subunit of the ribosome.

Redox proteomics changes in the fungal pathogen Trichosporon asahii on arsenic exposure: identification of protein responses to metal-induced oxidative stress in an environmentally-sampled isolate

Trichosporon asahii is a yeast pathogen implicated in opportunistic infections. Cultures of an isolate collected from industrial wastewater were exposed for 2 days to 100 mg/L sodium arsenite (NaAsO₂) and cadmium (CdCl₂). Both metals reduced glutathione transferase (GST) activity but had no effect on superoxide dismutase or catalase. NaAsO₂ exposure increased glutathione reductase activity while CdCl₂ had no effect. Protein thiols were labeled with 5-iodoacetamido fluorescein followed by one dimensional electrophoresis which revealed extensive protein thiol oxidation in response to CdCl₂ treatment but thiol reduction in response to NaAsO₂. Two dimensional electrophoresis analyses showed that the intensity of some protein spots was enhanced on treatment as judged by SameSpots image analysis software. In addition, some spots showed decreased IAF fluorescence suggesting thiol oxidation. Selected spots were excised and tryptic digested for identification by MALDI-TOF/TOF MS. Twenty unique T. asahii proteins were identified of which the following proteins were up-regulated in response to NaAsO₂: 3-isopropylmalate dehydrogenase, phospholipase B, alanine-glyoxylate aminotransferase, ATP synthase alpha chain, 20S proteasome beta-type subunit Pre3p and the hypothetical proteins A1Q1_08001, A1Q2_03020, A1Q1_06950, A1Q1_06913. In addition, the following showed decreased thiol-associated fluorescence consistent with thiol oxidation; aconitase; aldehyde reductase I; phosphoglycerate kinase; translation elongation factor 2; heat shock protein 70 and hypothetical protein A1Q2_04745. Some proteins showed both increase in abundance coupled with decrease in IAF fluorescence; 3-hydroxyisobutyryl- CoA hydrolase; homoserine dehydrogenase Hom6 and hypothetical proteins A1Q2_03020 and A1Q1_00754. Targets implicated in redox response included 10 unique metabolic enzymes, heat shock proteins, a component of the 20S proteasome and translation elongation factor 2. These data suggest extensive proteomic alterations in response to metal-induced oxidative stress in T. asahii. Amino acid metabolism, protein folding and degradation are principally affected.

Analysis of spatial and temporal protein expression in the cerebral cortex after ischemia-reperfusion injury

Background and Purpose

Hypoxia, or ischemia, is a common cause of neurological deficits in the elderly. This study elucidated the mechanisms underlying ischemia-induced brain injury that results in neurological sequelae.

Methods

Cerebral ischemia was induced in male Sprague-Dawley rats by transient ligation of the left carotid artery followed by 60 min of hypoxia. A two-dimensional differential proteome analysis was performed using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry to compare changes in protein expression on the lesioned side of the cortex relative to that on the contralateral side at 0, 6, and 24 h after ischemia.

Results

The expressions of the following five proteins were up-regulated in the ipsilateral cortex at 24 h after ischemia-reperfusion injury compared to the contralateral (i.e., control) side: aconitase 2, neurotensin-related peptide, hypothetical protein XP-212759, 60-kDa heat-shock protein, and aldolase A. The expression of one protein, dynamin-1, was up-regulated only at the 6-h time point. The level of 78-kDa glucose-regulated protein precursor on the lesioned side of the cerebral cortex was found to be high initially, but then down-regulated by 24 h after the induction of ischemia-reperfusion injury. The expressions of several metabolic enzymes and translational factors were also perturbed soon after brain ischemia.

Conclusions

These findings provide insights into the mechanisms underlying the neurodegenerative events that occur following cerebral ischemia.

SDS, a structural disruption score for assessment of missense variant deleteriousness

We have developed a novel structure-based evaluation for missense variants that explicitly models protein structure and amino acid properties to predict the likelihood that a variant disrupts protein function. A structural disruption score (SDS) is introduced as a measure to depict the likelihood that a case variant is functional. The score is constructed using characteristics that distinguish between causal and neutral variants within a group of proteins. The SDS score is correlated with standard sequence-based deleteriousness, but shows promise for improving discrimination between neutral and causal variants at less conserved sites. The prediction was performed on 3-dimentional structures of 57 gene products whose homozygous SNPs were identified as case-exclusive variants in an exome sequencing study of epilepsy disorders. We contrasted the candidate epilepsy variants with scores for likely benign variants found in the EVS database, and for positive control variants in the same genes that are suspected to promote a range of diseases. To derive a characteristic profile of damaging SNPs, we transformed continuous scores into categorical variables based on the score distribution of each measurement, collected from all possible SNPs in this protein set, where extreme measures were assumed to be deleterious. A second epilepsy dataset was used to replicate the findings. Causal variants tend to receive higher sequence-based deleterious scores, induce larger physico-chemical changes between amino acid pairs, locate in protein domains, buried sites or on conserved protein surface clusters, and cause protein destabilization, relative to negative controls. These measures were agglomerated for each variant. A list of nine high-priority putative functional variants for epilepsy was generated. Our newly developed SDS protocol facilitates SNP prioritization for experimental validation.

Functional annotation of conserved hypothetical proteins from Haemophilus influenzae Rd KW20

Haemophilus influenzae is a Gram negative bacterium that belongs to the family Pasteurellaceae, causes bacteremia, pneumonia and acute bacterial meningitis in infants. The emergence of multi-drug resistance H. influenzae strain in clinical isolates demands the development of better/new drugs against this pathogen. Our study combines a number of bioinformatics tools for function predictions of previously not assigned proteins in the genome of H. influenzae. This genome was extensively analyzed and found 1,657 functional proteins in which function of 429 proteins are unknown, termed as hypothetical proteins (HPs). Amino acid sequences of all 429 HPs were extensively annotated and we successfully assigned the function to 296 HPs with high confidence. We also characterized the function of 124 HPs precisely, but with less confidence. We believed that sequence of a protein can be used as a framework to explain known functional properties. Here we have combined the latest versions of protein family databases, protein motifs, intrinsic features from the amino acid sequence, pathway and genome context methods to assign a precise function to hypothetical proteins for which no experimental information is available. We found these HPs belong to various classes of proteins such as enzymes, transporters, carriers, receptors, signal transducers, binding proteins, virulence and other proteins. The outcome of this work will be helpful for a better understanding of the mechanism of pathogenesis and in finding novel therapeutic targets for H. influenzae.

An association-adjusted consensus deleterious scheme to classify homozygous Mis-sense mutations for personal genome interpretation

BACKGROUND

Personal genome analysis is now being considered for evaluation of disease risk in healthy individuals, utilizing both rare and common variants. Multiple scores have been developed to predict the deleteriousness of amino acid substitutions, using information on the allele frequencies, level of evolutionary conservation, and averaged structural evidence. However, agreement among these scores is limited and they likely over-estimate the fraction of the genome that is deleterious.

METHOD

This study proposes an integrative approach to identify a subset of homozygous non-synonymous single nucleotide polymorphisms (nsSNPs). An 8-level classification scheme is constructed from the presence/absence of deleterious predictions combined with evidence of association with disease or complex traits. Detailed literature searches and structural validations are then performed for a subset of homozygous 826 mis-sense mutations in 575 proteins found in the genomes of 12 healthy adults.

RESULTS

Implementation of the Association-Adjusted Consensus Deleterious Scheme (AACDS) classifies 11% of all predicted highly deleterious homozygous variants as most likely to influence disease risk. The number of such variants per genome ranges from 0 to 8 with no significant difference between African and Caucasian Americans. Detailed analysis of mutations affecting the APOE, MTMR2, THSB1, CHIA, αMyHC, and AMY2A proteins shows how the protein structure is likely to be disrupted, even though the associated phenotypes have not been documented in the corresponding individuals.

CONCLUSIONS

The classification system for homozygous nsSNPs provides an opportunity to systematically rank nsSNPs based on suggestive evidence from annotations and sequence-based predictions. The ranking scheme, in-depth literature searches, and structural validations of highly prioritized mis-sense mutations compliment traditional sequence-based approaches and should have particular utility for the development of individualized health profiles. An online tool reporting the AACDS score for any variant is provided at the authors' website.

A structural model of the copper ATPase ATP7B to facilitate analysis of Wilson disease-causing mutations and studies of the transport mechanism

The copper-transporting ATPase ATP7B has an essential role in human physiology, particularly for the liver and brain function. Inactivation of ATP7B is associated with a severe hepato-neurologic disorder, Wilson disease (WD). Hundreds of WD related mutations have been identified in ATP7B to date. The low frequency and the compound-heterozygous nature of causative mutations complicate the analysis of individual mutants and the establishment of genotype-phenotype correlations. To facilitate studies of disease-causing mutations and mechanistic understanding of WD, we have homology-modelled the ATP7B core (residues 643-1377) using the recent structure of the bacterial copper-ATPase LCopA as a template. The model, supported by evolutionary conservation and hydrophobicity analysis, as well as existing and new mutagenesis data, allows molecular interpretations of experimentally characterized clinical mutations. We also illustrate that structure and conservation can be used to grade potential deleterious effects for many WD mutations, which were clinically detected but have not yet been experimentally characterized. Finally, we compare the structural features of ATP7B and LCopA and discuss specific features of the eukaryotic copper pump.

Structural analysis of hypothetical proteins from Helicobacter pylori: an approach to estimate functions of unknown or hypothetical proteins

Helicobacter pylori (H. pylori) have a unique ability to survive in extreme acidic environments and to colonize the gastric mucosa. It can cause diverse gastric diseases such as peptic ulcers, chronic gastritis, mucosa-associated lymphoid tissue (MALT) lymphoma, gastric cancer, etc. Based on genomic research of H. pylori, over 1600 genes have been functionally identified so far. However, H. pylori possess some genes that are uncharacterized since: (i) the gene sequences are quite new; (ii) the function of genes have not been characterized in any other bacterial systems; and (iii) sometimes, the protein that is classified into a known protein based on the sequence homology shows some functional ambiguity, which raises questions about the function of the protein produced in H. pylori. Thus, there are still a lot of genes to be biologically or biochemically characterized to understand the whole picture of gene functions in the bacteria. In this regard, knowledge on the 3D structure of a protein, especially unknown or hypothetical protein, is frequently useful to elucidate the structure-function relationship of the uncharacterized gene product. That is, a structural comparison with known proteins provides valuable information to help predict the cellular functions of hypothetical proteins. Here, we show the 3D structures of some hypothetical proteins determined by NMR spectroscopy and X-ray crystallography as a part of the structural genomics of H. pylori. In addition, we show some successful approaches of elucidating the function of unknown proteins based on their structural information.

Functional region prediction with a set of appropriate homologous sequences--an index for sequence selection by integrating structure and sequence information with spatial statistics

Background

The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions.

Results

We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods.

Conclusions

Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems.

Detecting patches of protein sites of influenza A viruses under positive selection

Influenza A viruses are single-stranded RNA viruses capable of evolving rapidly to adapt to environmental conditions. Examples include the establishment of a virus in a novel host or an adaptation to increasing immunity within the host population due to prior infection or vaccination against a circulating strain. Knowledge of the viral protein regions under positive selection is therefore crucial for surveillance. We have developed a method for detecting positively selected patches of sites on the surface of viral proteins, which we assume to be relevant for adaptive evolution. We measure positive selection based on dN/dS ratios of genetic changes inferred by considering the phylogenetic structure of the data and suggest a graph-cut algorithm to identify such regions. Our algorithm searches for dense and spatially distinct clusters of sites under positive selection on the protein surface. For the hemagglutinin protein of human influenza A viruses of the subtypes H3N2 and H1N1, our predicted sites significantly overlap with known antigenic and receptor-binding sites. From the structure and sequence data of the 2009 swine-origin influenza A/H1N1 hemagglutinin and PB2 protein, we identified regions that provide evidence of evolution under positive selection since introduction of the virus into the human population. The changes in PB2 overlap with sites reported to be associated with mammalian adaptation of the influenza A virus. Application of our technique to the protein structures of viruses of yet unknown adaptive behavior could identify further candidate regions that are important for host–virus interaction.

Molecular characterization of an h-type thioredoxin gene from grape

Thioredoxins (Trxs), as small ubiquitous proteins, participate in dithiol-disulfide exchange reactions. In contrast to other organisms, plants have a complex family of Trxs, which contains seven different Trx types: f, h, m, o, x, y, and z. The h-type Trx consists of multiple forms that are involved in different processes. A full-length cDNA coding for a Trx h, designated VvTrx h2, was isolated and cloned from grape (Vitis vinifera L. cv. White Seedless) berry tissue by RT-PCR technique. Nucleotide sequence analysis revealed 561 nucleotides in length encoded for a protein of 114 amino acid residues. The deduced polypeptide sequence harbors a typical catalytic site, WCGPC and its calculated molecular mass and its predicted isoelectric point are 12.79 and 5.06 kDa, respectively. The threedimensional modeling and docking studies allow for the proposal that VvTrx h2 could be reduced by a NADP-thioredoxin reductase rather than glutaredoxin, as shown for its ortholog from Arabidopsis. The deduced amino acid sequence showed a high degree of similarity to Trx h isoforms from other sources. Phylogenetic studies indicated that VvTrx h2 gene is related to h-type Trx subgroup I. Semi-quantitative RT-PCR analysis revealed that the VvTrx h2 gene was expressed in all plant tissues at different developmental stages.

Isolation, identification and sequence analysis of a thioredoxin h gene, a member of subgroup III of h-type Trxs from grape (Vitis vinifera L. cv. Askari)

Thioredoxins (Trxs) are small ubiquitous proteins which play a regulatory role in a variety of cellular processes. In contrast to other organisms, plants have a great number of Trx types, consisting of six well-defined groups: f, m, x, and y in chloroplasts, o in mitochondria, and h mainly in cytosol. A full-length cDNA, designated VvCxxS2, encoding Trx h polypeptide was isolated and cloned from grape (Vitis vinifera L. cv. Askari) berries organ by reverse transcription polymerase chain reaction (RT-PCR). The cDNA was 381 bp nucleotides in length with a deduced amino acid of 126 residues, possessing a WCIPS active site, which belongs to the subgroup III of h-type Trxs based on phylogenetic analysis. The calculated molecular mass and the predicted isoelectric point of the deduced polypeptide are 14.25 kDa and 4.68, respectively. Nucleotide sequence analysis of genomic DNA fragment of VvCxxS2 gene revealed that this gene possesses two introns at positions identical to the previously sequenced Trx h genes. A modeling analysis indicated that VvCxxS2 shares a common structure with other Trxs, and is preferably reduced by Grx rather than NADPH-dependent thioredoxin reductase (NTR). The deduced protein sequence showed a high similarity to Trx h from other plants, in particular from castor bean (Ricinus communis), Betula pendula and sweet orange (Citrus sinensis). Semiquantitative RT-PCR experiments indicated that the transcripts of VvCxxS2 gene are present in all plant organs and different developmental stages. In addition, the higher expression of the VvCxxS2 gene was observed in berry organ as compared to the other organs.

Crystal structure of alkyl hydroperoxidase D like protein PA0269 from Pseudomonas aeruginosa: homology of the AhpD-like structural family

BACKGROUND

Alkyl hydroperoxidase activity provides an important antioxidant defense for bacterial cells. The catalytic mechanism requires two peroxidases, AhpC and AhpD, where AhpD plays the role of an essential adaptor protein.

RESULTS

The crystal structure of a putative AhpD from Pseudomonas aeruginosa has been determined at 1.9 Å. The protein has an all-helical fold with a chain topology similar to a known AhpD from Mycobacterium tuberculosis despite a low overall sequence identity of 9%. A conserved two α-helical motif responsible for function is present in both. However, in the P. aeruginosa protein, helices H3, H4 of this motif are located at the N-terminal part of the chain, while in M. tuberculosis AhpD, the corresponding helices H8, H9 are situated at the C-terminus. Residues 24-62 of the putative catalytic region of P. aeruginosa have a higher sequence identity of 33% where the functional activity is supplied by a proton relay system of five residues, Glu36, Cys48, Tyr50, Cys51, and His55, and one structural water molecule. A comparison of five other related hypothetical proteins from various species, assigned to the alkyl hydroperoxidase D-like protein family, shows they contain the same conserved structural motif and catalytic sequence Cys-X-X-Cys. We have shown that AhpD from P. aeruginosa exhibits a weak ability to reduce H(2)O(2) as tested using a ferrous oxidation-xylenol orange (FOX) assay, and this activity is blocked by thiol alkylating reagents.

CONCLUSION

Thus, this hypothetical protein was assigned to the AhpD-like protein family with peroxidase-related activity. The functional relationship of specific oligomeric structures of AhpD-like structural family is discussed.

Sequence and structure continuity of evolutionary importance improves protein functional site discovery and annotation

Protein functional sites control most biological processes and are important targets for drug design and protein engineering. To characterize them, the evolutionary trace (ET) ranks the relative importance of residues according to their evolutionary variations. Generally, top-ranked residues cluster spatially to define evolutionary hotspots that predict functional sites in structures. Here, various functions that measure the physical continuity of ET ranks among neighboring residues in the structure, or in the sequence, are shown to inform sequence selection and to improve functional site resolution. This is shown first, in 110 proteins, for which the overlap between top-ranked residues and actual functional sites rose by 8% in significance. Then, on a structural proteomic scale, optimized ET led to better 3D structure-function motifs (3D templates) and, in turn, to enzyme function prediction by the Evolutionary Trace Annotation (ETA) method with better sensitivity of (40% to 53%) and positive predictive value (93% to 94%). This suggests that the similarity of evolutionary importance among neighboring residues in the sequence and in the structure is a universal feature of protein evolution. In practice, this yields a tool for optimizing sequence selections for comparative analysis and, via ET, for better predictions of functional site and function. This should prove useful for the efficient mutational redesign of protein function and for pharmaceutical targeting.

DNABINDPROT: fluctuation-based predictor of DNA-binding residues within a network of interacting residues

DNABINDPROT is designed to predict DNA-binding residues, based on the fluctuations of residues in high-frequency modes by the Gaussian network model. The residue pairs that display high mean-square distance fluctuations are analyzed with respect to DNA binding, which are then filtered with their evolutionary conservation profiles and ranked according to their DNA-binding propensities. If the analyses are based on the exact outcome of fluctuations in the highest mode, using a conservation threshold of 5, the results have a sensitivity, specificity, precision and accuracy of 9.3%, 90.5%, 18.1% and 78.6%, respectively, on a dataset of 36 unbound–bound protein structure pairs. These values increase up to 24.3%, 93.4%, 45.3% and 83.3% for the respective cases, when the neighboring two residues are considered. The relatively low sensitivity appears with the identified residues being selective and susceptible more for the binding core residues rather than all DNA-binding residues. The predicted residues that are not tagged as DNA-binding residues are those whose fluctuations are coupled with DNA-binding sites. They are in close proximity as well as plausible for other functional residues, such as ligand and protein–protein interaction sites. DNABINDPROT is free and open to all users without login requirement available at: http://www.prc.boun.edu.tr/appserv/prc/dnabindprot/.

ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids

It is informative to detect highly conserved positions in proteins and nucleic acid sequence/structure since they are often indicative of structural and/or functional importance. ConSurf (http://consurf.tau.ac.il) and ConSeq (http://conseq.tau.ac.il) are two well-established web servers for calculating the evolutionary conservation of amino acid positions in proteins using an empirical Bayesian inference, starting from protein structure and sequence, respectively. Here, we present the new version of the ConSurf web server that combines the two independent servers, providing an easier and more intuitive step-by-step interface, while offering the user more flexibility during the process. In addition, the new version of ConSurf calculates the evolutionary rates for nucleic acid sequences. The new version is freely available at: http://consurf.tau.ac.il/.