Even in the current age of advanced medicine, the prognosis of malignant peritoneal mesothelioma (MPM) remains abysmal. Molecular mechanisms responsible for the initiation and progression of MPM are still largely not understood. Adopting an integrated bioinformatics approach, this study aims to identify the key genes and pathways responsible for MPM. Genes that are differentially expressed in MPM in comparison with the peritoneum of healthy controls have been identified by analyzing a microarray gene expression dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of these differentially expressed genes (DEG) were conducted to gain a better insight. A protein-protein interaction (PPI) network of the proteins encoded by the DEGs was constructed using STRING and hub genes were detected analyzing this network. Next, the transcription factors and miRNAs that have possible regulatory roles on the hub genes were detected. Finally, survival analyses based on the hub genes were conducted using the GEPIA2 web server. Six hundred six genes were found to be differentially expressed in MPM; 133 are upregulated and 473 are downregulated. Analyzing the STRING generated PPI network, six dense modules and 12 hub genes were identified. Fifteen transcription factors and 10 miRNAs were identified to have the most extensive regulatory functions on the DEGs. Through bioinformatics analyses, this work provides an insight into the potential genes and pathways involved in MPM.

T-box transcription factor 5 gene (TBX5) encodes the transcription factor TBX5, which plays a crucial role in the development of heart and upper limbs. Damaging single nucleotide variants in this gene alter the protein structure, disturb the functions of TBX5, and ultimately cause Holt-Oram Syndrome (HOS). By analyzing the available single nucleotide polymorphism information in the dbSNP database, this study was designed to identify the most deleterious TBX5 SNPs through in silico approaches and predict their structural and functional consequences.

Multiple antibiotic-resistant strains of Klebsiella pneumoniae can cause life-threatening infections. Bacterial enoyl-acyl carrier protein (ACP) reductases (ENRs) are considered critical targets for developing antibiotics. Our current study aims to identify inhibitors of K. pneumoniae ENRs (FabI and FabV). Due to the unavailability of experimental structures, protein models of FabI and FabV were predicted and validated in this study. Virtual screening of the 1930 FDA-approved drug database was conducted against the active site of the FabI protein with the help of the LEA3D server, and carfilzomib was chosen among the screened drugs for further docking studies. Carfilzomib, a proteasome inhibitor used in the treatment of multiple myeloma, was among the best-suited compounds obtained from the virtual screening and was found to be bactericidal in the in vitro experiment. Carfilzomib was docked against the active sites of the FabI and FabV proteins, and the ENR of Mycobacterium tuberculosis, InhA. Carfilzomib showed a high binding affinity with all three proteins. Molecular dynamics (MD) simulations were conducted following the docking studies. MD simulations revealed that carfilzomib binds strongly to the active sites of the above mentioned ENRs. Our study found that carfilzomib is a potential inhibitor of the ENRs of K. pneumoniae and M. tuberculosis. This is a possible mechanism of its bactericidal property against M. tuberculosis observed in vitro in addition to its predicted actions on zinc-dependent metalloprotease-1 and peptide deformylase, two other drug target enzymes of M. tuberculosis. Our study suggests that this drug could be used as a lead compound to develop antibiotics that can selectively act against ENRs of bacteria, without interfering with the activities of human proteasome. Communicated by Ramaswamy H. Sarma

Antibiotic resistance is a global concern. Two members of the bacterial genus Elizabethkingia, namely, E. anophelis and E. meningoseptica have raised much concern in recent years because of their resistance to multiple commonly used antibiotics. Identification of multidrug resistant and pan-drug resistant bacteria has propelled the search for new antibiotics that can act on unconventional targets. Researches are going on to find out the possibility of using bacterial ribonucleotide reductases as a novel target for antibiotic development. Through in silico evaluations, this study aims for characterization and functional annotation of ribonucleotide reductase enzymes of E. anophelis and E. meningoseptica. Binding affinities with these enzymes of the compounds that have shown promising results in inhibiting Pseudomonas aeruginosa growth by acting on its ribonucleotide reductase were also assessed by molecular docking and dynamics simulations. Insights from this study will help in battling these infections in the near future. Communicated by Ramaswamy H. Sarma

T-box transcription factor 5 ( TBX5 ) gene encodes the transcription factor TBX5, which plays a crucial role in developing the heart and upper limbs. Damaging single nucleotide variants in this gene alters the protein structure, disturbs the functions of TBX5, and ultimately causes Holt-Oram Syndrome (HOS). By analyzing available single nucleotide polymorphism information in the dbSNP database, this study was designed to identify the most deleterious TBX5 SNPs through silico approaches and predict their structural and functional consequences. Fifty-eight missense substitutions were found damaging by sequences homology-based tools like SIFT and PROVEAN and structure homology-based tools like PolyPhen-2. These SNPs were further scrutinized by various disease association meta-predictor tools. Additionally, the conservation profile of amino acid residues, their surface accessibility, stability, and structural integrity of the native protein upon mutations was assessed. From these analyses, finally 5 SNPs were detected as the most damaging ones [rs1565941579 (P85S), rs1269970792 (W121R), rs772248871 (V153D), rs769113870 (E208D), and rs1318021626 (I222N)]. Analyses of stop-loss, nonsense, UTR, and splice site SNPs were also conducted. Through integrative bioinformatics analyses, this study has identified SNPs that are deleterious to the TBX5 protein structure and have the potential to cause HOS. Further wet-lab experiments can validate these findings.