Structure-based functional inference of hypothetical proteins from Mycoplasma hyopneumoniae

In-Silico Functional Annotation of Plasmodium falciparum Hypothetical Proteins to Identify Novel Drug Targets

Plasmodium falciparum is one of the plasmodium species responsible for the majority of life-threatening malaria cases. The current antimalarial therapies are becoming less effective due to growing drug resistance, leading to the urgent requirement for alternative and more effective antimalarial drugs or vaccines. To facilitate the novel drug discovery or vaccine development efforts, recent advances in sequencing technologies provide valuable information about the whole genome of the parasite, yet a lot more needs to be deciphered due to its incomplete proteome annotation. Surprisingly, out of the 5,389 proteins currently annotated in the Plasmodium falciparum 3D7 strain, 1,626 proteins (∼30% data) are annotated as hypothetical proteins. In parasite genomic studies, the challenge to annotate hypothetical proteins is often ignored, which may obscure the crucial information related to the pathogenicity of the parasite. In this study, we attempt to characterize hypothetical proteins of the parasite to identify novel drug targets using a computational pipeline. The study reveals that out of the overall pool of the hypothetical proteins, 266 proteins have conserved functional signatures. Furthermore, the pathway analysis of these proteins revealed that 23 proteins have an essential role in various biochemical, signalling and metabolic pathways. Additionally, all the proteins (266) were subjected to computational structure analysis. We could successfully model 11 proteins. We validated and checked the structural stability of the models by performing molecular dynamics simulation. Interestingly, eight proteins show stable conformations, and seven proteins are specific for Plasmodium falciparum, based on homology analysis. Lastly, mapping the seven shortlisted hypothetical proteins on the Plasmodium falciparum protein-protein interaction network revealed 3,299 nodes and 2,750,692 edges. Our study revealed interesting functional details of seven hypothetical proteins of the parasite, which help learn more about the less-studied molecules and their interactions, providing valuable clues to unravel the role of these proteins via future experimental validation.

Functional characterization of the putative FAD synthase from Mycoplasma hyopneumoniae

In bacteria, the biosynthesis of the cofactor flavin adenine dinucleotide (FAD), important in many physiological responses, is catalyzed by the bifunctional enzyme FAD synthase (FADSyn) which converts riboflavin into FAD by both kinase and adenylylation activity. The in silico 3D structure of a putative FADSyn from Mycoplasma hyopneumoniae (MhpFADSyn), the etiological agent of enzootic pneumonia was already reported, nevertheless, the in vitro functional characterization was not yet demonstrated. Our phylogenetic analysis revealed that MhpFADSyn is close related to the bifunctional FADSyn from Corynebacterium ammoniagenes. However, only the domain related to adenylylation was assigned by InterPro database. The activity of MhpFADSyn was evaluated through in vitro enzymatic assays using cell extracts from IPTG-inducible heterologous expression of MhpFADSyn in Escherichia coli. The flavoproteins were analyzed by HPLC and results showed that IPTG-induced cell lysate resulted in the formation of twofold increased amounts of FAD if compared to non IPTG-induced cells. Consumption of riboflavin substrate was also threefold greater in IPTG-induced lysate compared to non IPTG-induced cell extract. Thus, the recombinant MhpFADSyn protein could be associated to FAD biosynthesis. These findings contribute to expand the range of potential drug targets in diseases control and unveil metabolic pathways that could be attribute to mycoplasmas.

Functional Prediction and Assignment of Methanobrevibacter ruminantium M1 Operome Using a Combined Bioinformatics Approach

Methanobrevibacter ruminantium M1 (MRU) is a rod-shaped rumen methanogen with the ability to use H₂ and CO₂, and formate as substrates for methane formation in the ruminants. Enteric methane emitted from this organism can also be influential to the loss of dietary energy in ruminants and humans. To date, there is no successful technology to reduce methane due to a lack of knowledge on its molecular machinery and 73% conserved hypothetical proteins (HPs; operome) whose functions are still not ascertained perceptively. To address this issue, we have predicted and assigned a precise function to HPs and categorize them as metabolic enzymes, binding proteins, and transport proteins using a combined bioinformatics approach. The results of our study show that 257 (34%) HPs have well-defined functions and contributed essential roles in its growth physiology and host adaptation. The genome-neighborhood analysis identified 6 operon-like clusters such as hsp, TRAM, dsr, cbs and cas, which are responsible for protein folding, sudden heat-shock, host defense, and protection against the toxicities in the rumen. The functions predicted from MRU operome comprised of 96 metabolic enzymes with 17 metabolic subsystems, 31 transcriptional regulators, 23 transport, and 11 binding proteins. Functional annotation of its operome is thus more imperative to unravel the molecular and cellular machinery at the systems-level. The functional assignment of its operome would advance strategies to develop new anti-methanogenic targets to mitigate methane production. Hence, our approach provides new insight into the understanding of its growth physiology and lifestyle in the ruminants and also to reduce anthropogenic greenhouse gas emissions worldwide.

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.

Designing of an epitope-based peptide vaccine against walking pneumonia: an immunoinformatics approach

Mycoplasma pneumoniae is a substantial respiratory pathogen that develops not only pneumonia but also other respiratory diseases, which mimic viral respiratory syndromes. Nevertheless, vaccine development for this pathogen delays behind as immunity correlated with protection is now predominantly unknown. In the present study, an immunoinformatics pipeline is utilized for epitope-based peptide vaccine design, which can trigger a critical immune response against M. pneumoniae. A total of 105 T-cell epitopes from 12 membrane associated proteins and 7 T-cell epitopes from 5 cytadherence proteins of M. pneumoniae were obtained and validated. Thus, 18 peptides with 9-mer core sequence were identified as best T-cell epitopes by considering the number of residues with > 75% in favored region. Further, the crucial screening studies predicted three peptides with good binding affinity towards HLA molecules as best T-cell and B-cell epitopes. Based on this result, visualization, and dynamic simulation for the three epitopes (WIHGLILLF, VILLFLLLF, and LLAWMLVLF) were assessed. The predicted epitopes needs to be further validated for their adept use as vaccine. Collectively, the study opens up a new horizon with extensive therapeutic application against M. pneumoniae and its associated diseases.

Crystal structure of the MSMEG_4306 gene product from Mycobacterium smegmatis

The MSMEG_4306 gene from Mycobacterium smegmatis encodes a protein of unknown function with 242 amino-acid residues that contains a conserved zinc-ribbon domain at its C-terminus. Here, the crystal structure of MSMEG_4306 determined by the single-wavelength anomalous dispersion method using just one zinc ion co-purified with the protein is reported. The crystal structure of MSMEG_4306 shows a coiled-coil helix domain in the N-terminal region and a zinc-ribbon domain in the C-terminal region. A structural similarity search against the Protein Data Bank using MSMEG_4306 as a query revealed two similar structures, namely CT398 from Chlamydia trachomatis and HP0958 from Helicobacter pylori, although they share only ∼15% sequence identity with MSMEG_4306. Based on comparative analysis, it is predicted that MSMEG_4306 may be involved in secretion systems, possibly by interacting with multiple proteins or nucleic acids.

In silico approaches for the identification of virulence candidates amongst hypothetical proteins of Mycoplasma pneumoniae 309

Mycoplasma pneumoniae type 2a strain 309 is a simplest known bacterium and is the primary cause of community acquired pneumonia in the children. It mainly causes severe atypical pneumonia as well as several other non-pulmonary manifestations such as neurological, hepatic, hemolytic anemia, cardiac diseases and polyarthritis. The size of M. pneumoniae genome (Accession number: NC_016807.1) is relatively smaller as compared to other bacteria and contains 707 functional proteins, in which 204 are classified as hypothetical proteins (HPs) because of the unavailability of experimentally validated functions. The functions of the HPs were predicted by integrating a variety of protein classification systems, motif discovery tools as well as methods that are based on characteristic features obtained from the protein sequence and metabolic pathways. The probable functions of 83HPs were predicted successfully. The accuracy of the diverse tools used in the adopted pipeline was evaluated on the basis of statistical techniques of Receiver Operating Characteristic (ROC), which indicated the reliability of the functional predictions. Furthermore, the virulent HPs present in the set of 83 functionally annotated proteins were predicted by using the Bioinformatics tools and the conformational behaviours of the proteins with highest virulence scores were studied by using the molecular dynamics (MD) simulations. This study will facilitate in the better understanding of various drug resistance and pathogenesis mechanisms present in the M. pneumoniae and can be utilized in designing of better therapeutic agents.

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.