Disease complexity: A bird’s eye view

Over the last few decades, biologists understood gradually that a set of complex interactions between the numerous constituents of a cell, gives rise to different biological phenotypes. Diseases serve as interesting examples of a great number of heterogeneous, interacting entities of biological systems. Though the ultimate goal is to understand the causes and effects along with the mechanisms of regulation, the precise simulation to mimic the real biological phenomena had been quite tough. The present talk encompasses a discussion on the model networks of few infectious diseases focused around identifying the proteins indispensable for virulence followed by probing into the structure function relation of the proteins involved there in and their molecular evolution. The diseases are either caused by bacterial infection like typhoid caused by Samonella enterica, nosocomial infection by Acinetobacter baumannii and fish pathogenesis by Edwardsiella tarda. On an initial note, the indispensability issue has been taken off for virulent proteins from the 28 Pathogenicity Alien Islands (PAI) causing the hospital borne infection caused by Acinetobacter. Taking down to the practical level, a conglomerate of secretion systems and signaling proteins of Edwardsiella were used for identifying an important candidate suitable for fish vaccination. Finally, a methodology has been figured out theoretically to focus on the indispensable virulent proteins amongst a barrage of Salmonella Pathogenecity Island (SPI) proteins and proven by microarray data for Salmonella. The candidate for therapeutic drug targeting had also been modeled. An overview of phylogenetic network brought out some sources of evolution

Quorum sensing: An imperative longevity weapon in bacteria

Bacterial cells exhibit a complex pattern of co-operative behaviour as shown by their capacity to communicate amongst each other. Quorum sensing (QS) is a generic term used for bacterial cell-to-cell communication which secures survival of its species. Many QS bacteria produce and release autoinducers like acyl-homoserine lactone-signaling molecules to regulate cell population density. Different species of bacteria utilize different QS molecules to regulate its gene expression. A free-living marine bacterium, Vibrio harveyi, uses two QS system to control the density-dependent expression of bioluminescence (lux), commonly classified as sensor and autoinducer system. In Pseudomonas aeruginosa, QS not only controls virulence factor production but also biofilm formation. It is comprised two hierarchically organised systems, each consisting of an autoinducer synthetase (LasI/RhlI) and a corresponding regulator protein (LasR/RhlR). Biofilms produced by Pseudomonas, under control of QS, are ubiquitous in nature and contribute towards colonizations in patients of cystic fibrosis. Other organisms like Haemophilus influenzae and Streptococcus also utilize QS mechanism to control virulence in otitis and endocarditic decay. Overall, QS plays a major role in controlling bacterial economy. It is a simple, practical and effective mechanism of production and control. If the concentration of enzyme is critical, bacteria can sense it and perform a prompt activation or repression of certain target genes for controlling its environment. This review focuses on the QS mechanisms and their role in the survival of few important bacterial species

Paradigm shift in drug re-purposing from Phenalenone to Phenaleno-Furanone to combat multi-drug resistant Salmonella Enterica Serovar Typhi

Over recent years, typhoid fever has gained increasing attention with several cases reporting treatment failure due to multidrug resistant (MDR) strains of Salmonella enterica serovar Typhi. While new drug development strategies are being devised to combat the threat posed by these MDR pathogens, drug repurposing or repositioning has become a good alternative. The latter is considered mainly due to its capacity for saving sufficient time and effort for pre-clinical and optimization studies. Owing to the possibility of an unsuccessful repositioning, due to the mismatch in the optimization of the drug ligand for the changed biochemical properties of “old” and “new” targets, we have chosen a “targeted” approach of adopting a combined chemical moiety-based drug repurposing. Using small molecules selected from a combination of earlier approved drugs having phenalenone and furanone moieties, we have computationally delineated a step-wise approach to drug design against MDR Salmonella. We utilized our network analysisbased pre-identified, essential chaperone protein, SicA, which regulates the folding and quality of several secretory proteins including the Hsp70 chaperone, SigE. To this end, another crucial chaperone protein, Hsp70 DnaK, was also considered due to its importance for pathogen survival under the stress conditions typically encountered during antibiotic therapies. These were docked with the 19 marketed anti-typhoid drugs along with two phenalenone-furanone derivatives, 15 non-related drugs which showed 70% similarity to phenalenone and furanone derivatives and other analogous small molecules. Furthermore, molecular dynamics simulation studies were performed to check the stability of the protein-drug complexes. Our results showed the best binding interaction and stability, under the parameters of a virtual human body environment, with XR770, a phenaleno-furanone moiety based derivative. We therefore propose XR770, for repurposing for therapeutic intervention against emerging and significant drug resistance conferred by pathogenic Salmonella strains

Computational analysis of protein interaction networks for infectious diseases

Infectious diseases caused by pathogens, including viruses, bacteria and parasites, pose a serious threat to human health worldwide. Frequent changes in the pattern of infection mechanisms and the emergence of multidrug resistant strains among pathogens have weakened the current treatment regimen. This necessitates the development of new therapeutic interventions to prevent and control such diseases. To cater to the need, analysis of protein interaction networks (PINs) has gained importance as one of the promising strategies. The present review aims to discuss various computational approaches to analyse the PINs in context to infectious diseases. Topology and modularity analysis of the network with their biological relevance, and the scenario till date about host-pathogen and intra-pathogenic protein interaction studies were delineated. This would provide useful insights to the research community thereby enabling them to design novel biomedicine against such infectious diseases

Computational Identification of Indispensable Virulence Proteins of Salmonella Typhi CT18

Typhoid infections have become an alarming concern with the increase of multidrug resistant strains of Salmonella serovars. The new pathogenic Gram-negative strains are resistant to most antibiotics such as chloramphenicol, ampicillin, trimethoprim, ciprofloxacin and even co-trimoxazole and their derivatives thereby causing numerous outbreaks in the Indian subcontinent, Southeast Asian and African countries. Conventional and modern methods of typing had been adopted to differentiate outbreak strains. However, identifying the most indispensable proteins from the complete set of proteins of the whole genome of Salmonella sp., comprising the Salmonella pathogenicity islands (SPI) responsible for virulence, has remained an ever challenging task. We have adopted a network-based method to figure out, albeit theoretically, the most significant proteins which might be involved in the resistance to antibiotics of the Salmonella sp. An understanding of the above will provide insight into conditions that are encountered by this pathogen during the course of infection, which will further contribute in identifying new targets for antimicrobial agents

Precision medicine and future of cancer treatment

Over the last few decades, there has been a deluge in the production of large-scale biological data mainly due to the advances in high-throughput technology. This initiated a paradigm shift on the focus in medical research. Ability to investigate molecular changes over the whole genome provided a unique opportunity in the field of translational research. This also gave rise to the concept of precision medicine which provided a strong hope for the development of better diagnostic and therapeutic tools. This is especially relevant to cancer as its incidence is increasing throughout the world. The purpose of this article is to review tools and applications of precision medicine in cancer

Strategic Role Players of Important Antimicrobial-Resistant Pathogens

Over the years, tireless efforts of the concerned scientists have produced various new therapeutics and methods for the treatment of bacterial infections. However, despite the vast regimen of modern antibiotics being corroborated, the diseases caused by the Gram-positive and -negative pathogens has become untreatable, mainly due to the constantly evolving threat of antimicrobial resistance (AMR), thereby leading to huge morbidity and mortality. Moreover, shortage of efficient therapies, lack of successful prevention strategies and availability of only a few effective antibiotics urgently necessitated the development of novel therapeutics and alternative antimicrobial treatments. These developments have been based on the molecular mechanisms of resistance posed by the pathogens during their interactions with the host. Herein, we collate four essential bacterial components like chaperones, efflux pumps, two-component systems and biofilms which can present challenges for the most coveted control of infection. Essentially, we discuss the current knowledge status of these components to provide insight into the complex regulation of virulence and resistance for some medically important multidrug-resistant (MDR) pathogens. This will help the future scientists to clearly focus on some specific proteins to be targeted by against the available class of drugs and/or antibiotics with the broader perspective to develop novel antimicrobial agents

PNMA family: Protein interaction network and cell signalling pathways implicated in cancer and apoptosis

Paraneoplastic Ma Family (PNMA) comprises a growing number of family members which share relatively conserved protein sequences encoded by the human genome and is localized to several human chromosomes, including the X-chromosome. Based on sequence analysis, PNMA family members share sequence homology to the Gag protein of LTR retrotransposon, and several family members with aberrant protein expressions have been reported to be closely associated with the human Paraneoplastic Disorder (PND). In addition, gene mutations of specific members of PNMA family are known to be associated with human mental retardation or 3-M syndrome consisting of restrictive post-natal growth or dwarfism, and development of skeletal abnormalities. Other than sequence homology, the physiological function of many members in this family remains unclear. However, several members of this family have been characterized, including cell signalling events mediated by these proteins that are associated with apoptosis, and cancer in different cell types. Furthermore, while certain PNMA family members show restricted gene expression in the human brain and testis, other PNMA family members exhibit broader gene expression or preferential and selective protein interaction profiles, suggesting functional divergence within the family. Functional analysis of some members of this family have identified protein domains that are required for subcellular localization, protein-protein interactions, and cell signalling events which are the focus of this review paper

Influential Quorum Sensing Proteins of multidrug resistant Proteus mirabilis causing urinary tract infections

Catheter-associated urinary tract infections (CAUTI) has become an alarming hospital based disease with the increase of multidrug resistance (MDR) strains of Proteus mirabilis. High prevalence of long-term hospital based CAUTI for patients along with moderate percentage of morbidity due to ignorance, failure and MDR, necessitates an immediate intervention strategy to combat the deadly disease. Several reports and reviews focus on revealing the important genes and proteins essential to tackle CAUTI caused by P. mirabilis. Despite longitudinal studies and methodical strategies to circumvent the issues, effective means of unearthing the most influential proteins to target for therapeutic uses have been meagre. Here we have reported a strategic approach for identifying the most influential proteins from the complete set of proteins of the whole genome of P. mirabilis, besides comparing the interactomes comprising the autoinducer-2 (AI-2) biosynthetic pathway along with other proteins involved in biofilm formation and responsible for virulence. Essentially, we have adopted a computational network model based approach to construct a set of small protein interaction networks (SPIN) along with the whole genome (GPIN) to identify, albeit theoretically, the most significant proteins. These might actually be responsible for the phenomenon of quorum sensing (QS) and biofilm formation and thus, could be therapeutically targeted to fight out the 188 MDR threats to antibiotics of P. mirabilis. Our approach signifies the eigenvector centrality coupled with k-core analyses to be a better measure in addressing the pressing issues

A side-effect free method for identifying cancer drug targets

Identifying efective drug targets, with little or no side efects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side efect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identifcation of efective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying efective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as efective candidates for drug development