Functional Annotation Of Hypothetical Proteins Research Articles

Structural and Functional Annotation of Hypothetical Proteins from the Microsporidia Species Vittaforma corneae ATCC 50505 Using in silico Approaches.

Microsporidia are spore-forming eukaryotes that are related to fungi but have unique traits that set them apart. They have compact genomes as a result of evolutionary gene loss associated with their complete dependency on hosts for survival. Despite having a relatively small number of genes, a disproportionately high percentage of the genes in microsporidia genomes code for proteins whose functions remain unknown (hypothetical proteins-HPs). Computational annotation of HPs has become a more efficient and cost-effective alternative to experimental investigation. This research developed a robust bioinformatics annotation pipeline of HPs from Vittaforma corneae, a clinically important microsporidian that causes ocular infections in immunocompromised individuals. Here, we describe various steps to retrieve sequences and homologs and to carry out physicochemical characterization, protein family classification, identification of motifs and domains, protein-protein interaction network analysis, and homology modelling using a variety of online resources. Classification of protein families produced consistent findings across platforms, demonstrating the accuracy of annotation utilizing in silico methods. A total of 162 out of 2034 HPs were fully annotated, with the bulk of them categorized as binding proteins, enzymes, or regulatory proteins. The protein functions of several HPs from Vittaforma corneae were accurately inferred. This improved our understanding of microsporidian HPs despite challenges related to the obligate nature of microsporidia, the absence of fully characterized genes, and the lack of homologous genes in other systems.

In silico functional annotation of hypothetical proteins from the Bacillus paralicheniformis strain Bac84 reveals proteins with biotechnological potentials and adaptational functions to extreme environments.

Members of the Bacillus genus are industrial cell factories due to their capacity to secrete significant quantities of biomolecules with industrial applications. The Bacillus paralicheniformis strain Bac84 was isolated from the Red Sea and it shares a close evolutionary relationship with Bacillus licheniformis. However, a significant number of proteins in its genome are annotated as functionally uncharacterized hypothetical proteins. Investigating these proteins' functions may help us better understand how bacteria survive extreme environmental conditions and to find novel targets for biotechnological applications. Therefore, the purpose of our research was to functionally annotate the hypothetical proteins from the genome of B. paralicheniformis strain Bac84. We employed a structured in-silico approach incorporating numerous bioinformatics tools and databases for functional annotation, physicochemical characterization, subcellular localization, protein-protein interactions, and three-dimensional structure determination. Sequences of 414 hypothetical proteins were evaluated and we were able to successfully attribute a function to 37 hypothetical proteins. Moreover, we performed receiver operating characteristic analysis to assess the performance of various tools used in this present study. We identified 12 proteins having significant adaptational roles to unfavorable environments such as sporulation, formation of biofilm, motility, regulation of transcription, etc. Additionally, 8 proteins were predicted with biotechnological potentials such as coenzyme A biosynthesis, phenylalanine biosynthesis, rare-sugars biosynthesis, antibiotic biosynthesis, bioremediation, and others. Evaluation of the performance of the tools showed an accuracy of 98% which represented the rationality of the tools used. This work shows that this annotation strategy will make the functional characterization of unknown proteins easier and can find the target for further investigation. The knowledge of these hypothetical proteins' potential functions aids B. paralicheniformis strain Bac84 in effectively creating a new biotechnological target. In addition, the results may also facilitate a better understanding of the survival mechanisms in harsh environmental conditions.

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.

Identification and functional annotation of hypothetical proteins of uropathogenic Escherichia coli strain CFT073 towards designing antimicrobial drug targets

Urinary tract infections are a serious health concern worldwide, especially in developing countries. Escherichia coli strain CFT073 is a highly virulent pathogenic bacterial strain. CFT073 proteome contains 4897 proteins, out of which 992 have been classified as hypothetical proteins. Identification and characterization of hypothetical proteins can aid in the selection of targets for drug design. In this study, we studied the hypothetical proteins from the UPEC strain CFT073 using various computational tools. By NCBI-CDD, 376 protein sequences showed conserved domains. Based on the functional motifs in their primary sequences, we classified these 376 hypothetical proteins into 7 functional categories. Further KEGG database was used to find the roles of these hypothetical proteins in several pathways. Protein interaction network analysis of hypothetical proteins identified 53 proteins as highly interacting metabolic proteins. Virulence factor analysis of the proteins identified 8 proteins as virulent. We conducted a non-homology search for the identified proteins of UPEC in the available human proteome. We observed that 35 proteins are non-homologous to humans and hence could be selected for drug designing targets. Qualitative characterization of the selected 35 non-homologous hypothetical proteins including essentiality analysis and evaluation of druggability by similarity search against drug bank database was performed. Out of these 35 proteins, three-dimensional structures of six proteins (NP_752562.1, NP_756345.1, NP_754893.1, NP_756600.2, NP_755264.1 and NP_752994.1) could be successfully modelled. These new annotations can help to better understand disease mechanisms at the molecular level, as well as provide new targets for drug development against the UPEC strain CFT073. Communicated by Ramaswamy H. Sarma

Functional annotation of hypothetical proteins involved in multiple stress response in Oryza sativa

Plants being sessile in nature face multiple stresses during its growth and development. Understanding the dynamic tolerance mechanism of plants to changing environment is the need of the hour and developing climate smart crops is still a nightmare. Functional characterization of relevant genes is a prerequisite when identifying candidates for crop improvement, in this study we identified 66 multiple stress responsive genes in rice that could serve as potential candidates for breeding for stress tolerance. The 15 hypothetical genes rendering multiple stress tolerance were functionally annotated using a rich set of tools ranging from sequence similarity search to fold recognition methods. It is predicted that the query protein might be a copper chaperone for superoxide dismutase. A novel approach to annotate hypothetical proteins with different remote homology search and structure-based threading approaches was designed. In addition to identified multiple stress responsive proteins in rice (Oryza sativa L.), our study also provides a robust toolkit to annotate other hypothetical proteins in plants.

Functional Annotation of Hypothetical Proteins Derived from Suppressive Subtraction Hybridization (SSH) Analysis Shows NPR1 (Non-Pathogenesis Related)-Like Activity

Fusarium wilt is considered the most devastating banana disease incited by Fusarium oxysporum f. sp. cubense (FOC). The present study addresses suppressive subtraction hybridization (SSH) analysis for differential gene expression in banana plant, mediated through FOC and its interaction with biocontrol agent Trichoderma asperellum (prr2). SSH analysis yielded a total of 300 clones. The resultant clones were sequenced and processed to obtain 22 contigs and 87 singleton sequences. BLAST2GO (Basic Local Alignment Search Tool 2 Gene Ontology) analysis was performed to assign known protein function. Initial functional annotation showed that contig 21 possesses p38-like endoribonuclease activity and duality in subcellular localization. To gain insights into its additional roles and precise functions, a sequential docking protocol was done to affirm its role in the defense pathway. Atomic contact energies revealed binding affinities in the order of miRNA > phytoalexins > polyubiquitin, emphasizing their role in the Musa defense pathway. Contig 21 and polyubiquitin showed an atomic contact energy value of −479.60 kJ/mol, and even higher atomic contact energies were observed for miRNA (−804.86, −482.28, −494.75 kJ/mol), demonstrating its high RNA-binding properties. Phytoalexin contig 21-interacting interfacial residues were identified as rigid (10)/non-rigid (2) based on Bi, N values, and B-factor per residue. Hence, based on these results, contig 21 was characterized as a NPR1 (non-pathogenesis-related protein) homolog that is involved in plant defense and systemic induced resistance.

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.

Correction: Identification of Functional Candidates amongst Hypothetical Proteins of Treponema pallidum ssp. pallidum.

[This corrects the article DOI: 10.1371/journal.pone.0124177.].

Functional association prediction by community profiling.

Recent years have witnessed unprecedented accumulation of DNA sequences and therefore protein sequences (predicted from DNA sequences), due to the advances of sequencing technology. One of the major sources of the hypothetical proteins is the metagenomics research. Current annotation of metagenomes (collections of short metagenomic sequences or assemblies) relies on similarity searches against known gene/protein families, based on which functional profiles of microbial communities can be built. This practice, however, leaves out the hypothetical proteins, which may outnumber the known proteins for many microbial communities. On the other hand, we may ask: what can we gain from the large number of metagenomes made available by the metagenomic studies, for the annotation of metagenomic sequences as well as functional annotation of hypothetical proteins in general? Here we propose a community profiling approach for predicting functional associations between proteins: two proteins are predicted to be associated if they share similar presence and absence profiles (called community profiles) across microbial communities. Community profiling is conceptually similar to the phylogenetic profiling approach to functional prediction, however with fundamental differences. We tested different profile construction methods, the selection of reference metagenomes, and correlation metrics, among others, to optimize the performance of this new approach. We demonstrated that the community profiling approach alone slightly outperforms the phylogenetic profiling approach for associating proteins in species that are well represented by sequenced genomes, and combining phylogenetic and community profiling further improves (though only marginally) the prediction of functional association. Further we showed that community profiling method significantly outperforms phylogenetic profiling, revealing more functional associations, when applied to a more recently sequenced bacterial genome.

Prediction driven functional annotation of hypothetical proteins in the major facilitator superfamily of S. aureus NCTC 8325.

Antibiotic resistance Staphylococcus aureus strains cause several life threatening infections. New drug treatment options are needed, but are slow to develop because 50% of the S. aureus genome is hypothetical. The goal of this is to aid in the annotation of the S. aureus NCTC 8325 genome by identifying hypothetical proteins related to the Major Facilitator Superfamily (MFS). The MFS is a broad protein group with members involved in drug efflux mechanisms causing resistance. To do this, sequences for three MFS proteins with x-ray crystal structures in E. coli were PSI-BLASTed against the S. aureus NCTC 8325 genome to identify homologs. Eleven identified hypothetical protein homologs underwent BLASTP against the non-redundant NCBI database to fit homologs specific to each hypothetical protein. ExPASy characterized the physiochemical features, CDD-BLAST and Pfam identified domains, and the SOSUI server defined transmembrane helices of each hypothetical protein. Based on size (300 – 700 amino acids), number of transmembrane helices (>7), CD06174 and MFS domains in CDD-BLAST and Pfam, respectively, and close relation to well-defined homologs, SAOUHSC_00058, SAOUHSC_00078, SAOUHSC_00952, SAOUHSC_02435, SAOUHSC_02752, and ABD31642.1 are members of the MFS. Further multiple-alignment and phylogeny analyses show SAOUHSC_00058 to be a quinolone resistance protein (NorB), SAOUHSC_00058 a siderophore biosynthesis protein (SbnD), SAOUHSC_00952 a glycolipid permease (LtaA), SAOUHSC_02435 a macrolide MFS transporter, SAOUHSC_02752 a chloramphenicol resistance (DHA1), and ABD31642.1 is a Bcr/CflA family drug resistance efflux transporter. These findings provide better annotation for the existing genome, and identify proteins related to antibiotic resistance in S. aureus NCTC 8325.

Identification of Novel Abiotic Stress Proteins in Triticum aestivum Through Functional Annotation of Hypothetical Proteins.

Cereal grain bread wheat (T. aestivum) is an important source of food and belongs to Poaceae family. Hypothetical proteins (HPs), i.e., proteins with unknown functions, share a substantial portion of wheat proteomes and play important roles in growth and physiology of plant system. Several functional annotations studies utilizing the protein sequences for characterization of role of individual protein in physiology of plant systems were being reported in recent past. In this study, an integrated pipeline of software/servers has been used for the identification and functional annotation of 124 unique HPs of T. aestivum considering available data in NCBI till date. All HPs were broadly annotated, out of which functions of 77 HPs were successfully assigned with high confidence level. Precisely functional annotation of remaining 47 HPs is also characterized with low confidence. Several latest versions of protein family databases, pathways information, genomics context methods and in silico tools were utilized to identify and assign function for individual HPs. Annotation result of several HPs mainly belongs to cellular protein, metabolic enzymes, binding proteins, transmembrane proteins, transcription factors and photosystem regulator proteins. Subsequently, functional analysis has revealed the role of few HPs in abiotic stress, which were further verified by phylogenetic analysis. The functionally associated proteins with each of above-mentioned abiotic stress-related proteins were identified through protein-protein interaction network analysis. The outcome of this study may be helpful for formulating general set pipeline/protocols for a better understanding of the role of HPs in physiological development of various plant systems.

Identification of functional candidates amongst hypothetical proteins of Treponema pallidum ssp. pallidum.

Syphilis is a globally occurring venereal disease, and its infection is propagated through sexual contact. The causative agent of syphilis, Treponema pallidum ssp. pallidum, a Gram-negative sphirochaete, is an obligate human parasite. Genome of T. pallidum ssp. pallidum SS14 strain (RefSeq NC_010741.1) encodes 1,027 proteins, of which 444 proteins are known as hypothetical proteins (HPs), i.e., proteins of unknown functions. Here, we performed functional annotation of HPs of T. pallidum ssp. pallidum using various database, domain architecture predictors, protein function annotators and clustering tools. We have analyzed the sequences of 444 HPs of T. pallidum ssp. pallidum and subsequently predicted the function of 207 HPs with a high level of confidence. However, functions of 237 HPs are predicted with less accuracy. We found various enzymes, transporters, binding proteins in the annotated group of HPs that may be possible molecular targets, facilitating for the survival of pathogen. Our comprehensive analysis helps to understand the mechanism of pathogenesis to provide many novel potential therapeutic interventions.

Structure-based functional annotation of hypothetical proteins from Candida dubliniensis: a quest for potential drug targets.

Candida dubliniensis is an emerging pathogenic yeast in humans and infections are usually restricted to mucosal parts of the body. However, its presence in specimens of immunocompromised individuals, especially in HIV-positive patients, is of major medical concern. There is a large fraction of genomes of C. dubliniensis in the database which are uncharacterized for their biochemical, biophysical, and/or cellular functions, and are identified as hypothetical proteins (HPs). Function annotation of Candida genome is, therefore, essentially required to facilitate the understanding of mechanisms of pathogenesis and biochemical pathways important for selecting novel therapeutic target. Here, we carried out an extensive analysis to explain the functional properties of genome, using available protein structure and function analysis tools. We successfully modeled the structures of eight HPs for which a template with moderate sequence similarity was available in the protein data bank. All modeled structures were analyzed and we found that these proteins may act as transporter, kinase, transferase, ketosteroid, isomerase, hydrolase, oxidoreductase, and binding targets for DNA and RNA. Since these unique HPs of Candida showed no homologs in humans, these proteins are expected to be a potential target for future antifungal therapy.Electronic supplementary materialThe online version of this article (doi:10.1007/s13205-014-0256-3) contains supplementary material, which is available to authorized users.

Piecing together the structure–function puzzle: Experiences in structure‐based functional annotation of hypothetical proteins

The combination of genomic sequencing with structural genomics has provided a wealth of new structures for previously uncharacterized ORFs, more commonly referred to as hypothetical proteins. This rapid growth has been the direct result of high-throughput, automated approaches in both the identification of new ORFs and the determination of high-resolution 3-D protein structures. A significant bottleneck is reached, however, at the stage of functional annotation in that the assignment of function is not readily automatable. It is often the case that the initial structural analysis at best indicates a functional family for a given hypothetical protein, but further identification of a relevant ligand or substrate is impeded by the diversity of function in a particular structural classification of proteins family, a highly selective and specific ligand-binding site, or the identification of a novel protein fold. Our approach to the functional annotation of hypothetical proteins relies on the combination of structural information with additional bioinformatics evidence garnered from operon prediction, loose functional information of additional operon members, conservation of catalytic residues, as well as cocrystallization trials and virtual ligand screening. The synthesis of all available information for each protein has permitted the functional annotation of several hypothetical proteins from Escherichia coli and each assignment has been confirmed through generally accepted biochemical methods.

Functional annotation of hypothetical proteins - A review.

The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins.