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Chlamydophila pneumoniae, a Gram-negative bacterium belongs to the family Chlamydiaceae, is known to cause community-acquired pneumonia and bronchitis. There is a need for genomic analyses of C. pneumoniae as its chronic infections result in reactive airway disease, lung cancer and asthma. Recent advancement in the sequencing techniques led to the generation of large genomic data. In order to utilize these data, sequence-based function predictions were used for annotating the uncharacterized genes. The genome of C. pneumoniae encodes 1052 proteins, which include a group of 366 functionally uncharacterized proteins, known as "hypothetical proteins" (HPs). Functions of these HPs were predicted by utilizing an integrated approach that combines varieties of bioinformatics tools. The functions of 142 proteins were successfully predicted and categorized into different classes of enzymes, transport proteins, binding proteins and virulence factors. Among these functionally annotated HPs, we were able to identify 12 virulent HPs. Furthermore, the HP with the highest virulence score was subjected to molecular dynamics (MD) simulations to better understand their dynamical behavior in explicit water conditions. These analyses could be utilized for an in-depth understanding of virulence mechanism. The functional knowledge of these proteins could be useful in drug design and discovery process of infections caused by C. pneumoniae.

The development in sequencing technologies over the past few decades have increased the pace of decoding genetic and functional information present in the genomes of pathogenic microorganisms. The knowledge obtained through sequencing projects facilitated the identification of genes that codes for virulence factors. A major portion of genomes of pathogenic of bacteria contains genes which are classified as "hypothetical or uncharacterized". Due to unavailability of precise information about the functionality of these genes, the pathogenic mechanisms utilized by varieties of microorganisms are not fully understood. This respective class of proteins draws a significant interest of pharmaceutical research as they have potential to provide new clues regarding the development of novel therapeutics particularly against the multidrug resistant strains of bacteria. The in silico identification of putative drug and vaccine targets in the set of uncharacterized proteins through comparative and subtractive genome analyses facilitates the increase usability and efficiency of the present drugs. The functional annotation of these characterized target proteins can uncover varieties of biochemical pathways important for the survival and pathogenesis of bacteria. This review focuses on the current protocols available for identification and functional annotations of these uncharacterized potential therapeutic targets.

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., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

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.

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.