Infectious diseases are the leading causes of death worldwide. Hence, there is a need to develop new antimicrobial agents. Traditional method of drug discovery is time consuming and yields a few drug targets with little intracellular information for guiding target selection. Thus, focus in drug development has been shifted to computational comparative genomics for identifying novel drug targets. Leptospirosis is a worldwide zoonosis of global concern caused by Leptospira interrogans. Availability of L. interrogans serovars and human genome sequences facilitated to search for novel drug targets using bioinformatics tools. The genome sequence of L. interrogans serovar Copenhageni has 5,124 genes while that of serovar Lai has 4,727 genes. Through subtractive genomic approach 218 genes in serovar Copenhageni and 158 genes in serovar Lai have been identified as putative drug targets. Comparative genomic approach had revealed that 88 drug targets were common to both the serovars. Pathway analysis using the Kyoto Encyclopaedia of Genes and Genomes revealed that 66 targets are enzymes and 22 are non-enzymes. Sixty two common drug targets were predicted to be localized in cytoplasm and 16 were surface proteins. The identified potential drug targets form a platform for further investigation in discovery of novel therapeutic compounds against Leptospira.

Vascular wilt of tomato caused by Fusarium oxysporum f.sp. lycopersici (FOL) is one of the most devastating diseases, that delimits the tomato production worldwide. Fungal short-chain dehydrogenases/reductases (SDRs) are NADP(H) dependent oxidoreductases, having shared motifs and common functional mechanism, have been demonstrated as biochemical targets for commercial fungicides. The 1,3,6,8 tetra hydroxynaphthalene reductase (T4HNR) protein, a member of SDRs family, catalyzes the naphthol reduction reaction in fungal melanin biosynthesis. We retrieved an orthologous member of T4HNR, (complexed with NADP(H) and pyroquilon from Magnaporthe grisea) in the FOL (namely; FOXG_04696) based on homology search, percent identity and sequence similarity (93% query cover; 49% identity). The hypothetical protein FOXG_04696 (T4HNR like) had conserved T-G-X-X-X-G-X-G motif (cofactor binding site) at N-terminus, similar to M. grisea (1JA9) and Y-X-X-X-K motif, as a part of the active site, bearing homologies with two fungal keto reductases T4HNR (M. grisea) and 17-β-hydroxysteroid dehydrogenase from Curvularia lunata (teleomorph: Cochliobolus lunatus PDB ID: 3IS3). The catalytic tetrad of T4HNR was replaced with ASN115, SER141, TYR154, and LYS158 in the FOXG_04696. The structural alignment and superposition of FOXG_04696 over the template proteins (3IS3 and 1JA9) revealed minimum RMSD deviations of the C alpha atomic coordinates, and therefore, had structural conservation. The best protein model (FOXG_04696) was docked with 37 fungicides, to evaluate their binding affinities. The Glide XP and YASARA docked complexes showed discrepancies in results, for scoring and ranking the binding affinities of fungicides. The docked complexes were further refined and rescored from their docked poses through 50 ns long MD simulations, and binding free energies (ΔGbind) calculations, using MM/GBSA analysis, revealed Oxathiapiprolin and Famoxadone as better fungicides among the selected one. However, Famoxadone had better interaction of the docked residues, with best protein ligand contacts, minimum RMSD (high accuracy of the docking pose) and RMSF (structural integrity and conformational flexibility of docking) at the specified docking site. The Famoxadone was found to be acceptable based on in silico toxicity and in vitro growth inhibition assessment. We conclude that the FOXG_04696, could be employed as a novel candidate protein, for structure-based design, and screening of target fungicides against the FOL pathogen.

The life-threatening infections caused by Leptospira serovars demand the need for designing anti-leptospirosis drugs. The present study encompasses exploring inhibitors against phosphoheptose isomerase (GmhA) of Leptospira, which is vital for lipopolysaccharide (LPS) biosynthesis and is identified as a common drug target through the subtractive genomic approach. GmhA model was built in Modeller 9v7. Structural refinement and energy minimization of the predicted model was carried out using Maestro 9.0. The refined model reliability was assessed through Procheck, ProSA, ProQ and Profile 3D. The substrate-based virtual high-throughput screening (VHTS) in Ligand.Info Meta-Database tool generated an in-house library of 354 substrate structural analogs. Furthermore, structure-based VHTS from the in-house library with different conformations of each ligand provided 14 novel competitive inhibitors. The model together with insight gained from the VHTS would be a promising starting point for developing anti-leptospirosis competitive inhibitors targeting LPS biosynthesis pathway.

The life-threatening infections caused by Leptospira serovars remain a global challenge since long time. Prevention of infection by controlling environmental factors being difficult to practice in developing countries, there is a need for designing potent anti-leptospirosis drugs. ATP-dependent MurD involved in biosynthesis of peptidoglycan was identified as common drug target among pathogenic Leptospira serovars through subtractive genomic approach. Peptidoglycan biosynthesis pathway being unique to bacteria and absent in host represents promising target for antimicrobial drug discovery. Thus, MurD 3D models were generated using crystal structures of 1EEH and 2JFF as templates in Modeller9v7. Structural refinement and energy minimization of the model was carried out in Maestro 9.0 applying OPLS-AA 2001 force field and was evaluated through Procheck, ProSA, PROQ, and Profile 3D. The active site residues were confirmed from the models in complex with substrate and inhibitor. Four published MurD inhibitors (two phosphinics, one sulfonamide, and one benzene 1,3-dicarbixylic acid derivative) were queried against more than one million entries of Ligand.Info Meta-Database to generate in-house library of 1,496 MurD inhibitor analogs. Our approach of virtual screening of the best-ranked compounds with pharmacokinetics property prediction has provided 17 novel MurD inhibitors for developing anti-leptospirosis drug targeting peptidoglycan biosynthesis pathway.

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