In silico identification of common putative drug targets in Leptospira interrogans

Recent developments on UDP-N-acetylmuramoyl-L-alanine-D-gutamate ligase (Mur D) enzyme for antimicrobial drug development: An emphasis on in-silico approaches

Introduction

The rapid emergence of antibiotic resistance among various bacterial pathogens has been one of the major concerns of health organizations across the world. In this context, for the development of novel inhibitors against antibiotic-resistant bacterial pathogens, UDP-N-Acetylmuramoyl-L-Alanine-D-Glutamate Ligase (MurD) enzyme represents one of the most apposite targets.

Body

The present review focuses on updated advancements on MurD-targeted inhibitors in recent years along with genetic regulation, structural and functional characteristics of the MurD enzyme from various bacterial pathogens. A concise account of various crystal structures of MurD enzyme, submitted into Protein Data Bank is also discussed.

Discussion

MurD, an ATP dependent cytoplasmic enzyme is an important target for drug discovery. The genetic organization of MurD enzyme is well elucidated and many crystal structures of MurD enzyme are submitted into Protein Data bank. Various inhibitors against MurD enzyme have been developed so far with an increase in the use of in-silico methods in the recent past. But cell permeability barriers and conformational changes of MurD enzyme during catalytic reaction need to be addressed for effective drug development. So, a combination of in-silico methods along with experimental work is proposed to counter the catalytic machinery of MurD enzyme.

Multi-epitope chimeric vaccine designing and novel drug targets prioritization against multi-drug resistant Staphylococcus pseudintermedius

Biofilm synthesizing multi-drug resistant Staphylococcus pseudintermedius bacteria has been recognized as the human infectious agent. It has been detected in the diseases of skin, ear, and postoperative infections. Its infections are becoming a major health problem due to its multi-drug resistance capabilities. However, no commercial vaccine for the treatment of its infections is currently available in the market. Here we employed the subtractive proteomics and reverse vaccinology approach to determine the potential novel drug and vaccine targets against S. pseudintermedius infections in humans. After screening the core-proteome of the 39 complete genomes of S. pseudintermedius, 2 metabolic pathways dependent and 34 independent proteins were determined as novel potential drug targets. Two proteins were found and used as potential candidates for designing the chimeric vaccine constructs. Depending on the properties such as antigenicity, toxicity and solubility, multi-epitope based vaccines constructs were designed. For immunogenicity enhancement, different specific sequences like linkers, PADRE sequences and molecular adjuvants were added. Molecular docking and molecular dynamic simulation analyses were performed to evaluate the prioritized vaccine construct’s interactions with human immune cells HLA and TLR4. Finally, the cloning and expression ability of the vaccine construct was determined in the bacterial cloning system and human body immune response was predicted through immune simulation analysis. In conclusion, this study proposed the potential drug and vaccine targets and also designed a chimera vaccine to be tested and validated against infectious S. pseudintermedius species.

Identification of Putative Vaccine and Drug Targets against the Methicillin-Resistant Staphylococcus aureus by Reverse Vaccinology and Subtractive Genomics Approaches

Methicillin-resistant Staphylococcus aureus (MRSA) is an opportunistic pathogen and responsible for causing life-threatening infections. The emergence of hypervirulent and multidrug-resistant (MDR) S. aureus strains led to challenging issues in antibiotic therapy. Consequently, the morbidity and mortality rates caused by S. aureus infections have a substantial impact on health concerns. The current worldwide prevalence of MRSA infections highlights the need for long-lasting preventive measures and strategies. Unfortunately, effective measures are limited. In this study, we focus on the identification of vaccine candidates and drug target proteins against the 16 strains of MRSA using reverse vaccinology and subtractive genomics approaches. Using the reverse vaccinology approach, 4 putative antigenic proteins were identified; among these, PrsA and EssA proteins were found to be more promising vaccine candidates. We applied a molecular docking approach of selected 8 drug target proteins with the drug-like molecules, revealing that the ZINC4235426 as potential drug molecule with favorable interactions with the target active site residues of 5 drug target proteins viz., biotin protein ligase, HPr kinase/phosphorylase, thymidylate kinase, UDP-N-acetylmuramoyl-L-alanyl-D-glutamate-L-lysine ligase, and pantothenate synthetase. Thus, the identified proteins can be used for further rational drug or vaccine design to identify novel therapeutic agents for the treatment of multidrug-resistant staphylococcal infection.

Prediction of Novel Drug Targets and Vaccine Candidates against Human Lice (Insecta), Acari (Arachnida), and Their Associated Pathogens

The emergence of drug-resistant lice, acari, and their associated pathogens (APs) is associated with economic losses; thus, it is essential to find new appropriate therapeutic approaches. In the present study, a subtractive proteomics approach was used to predict suitable therapeutics against these vectors and their infectious agents. We found 9701 proteins in the lice (Pediculus humanus var. corporis) and acari (Ixodes scapularis, Leptotrombidium deliense), and 4822 proteins in the proteomes of their APs (Babesia microti, Borreliella mayonii, Borrelia miyamotoi, Borrelia recurrentis, Rickettsia prowazekii, Orientia tsutsugamushi str. Boryong) that were non-homologous to host proteins. Among these non-homologous proteins, 365 proteins of lice and acari, and 630 proteins of APs, were predicted as essential proteins. Twelve unique essential proteins were predicted to be involved in four unique metabolic pathways of lice and acari, and 103 unique proteins were found to be involved in 75 unique metabolic pathways of APs. The sub cellular localization analysis of 115 unique essential proteins of lice and acari and their APs revealed that 61 proteins were cytoplasmic, 42 as membrane-bound proteins and 12 proteins with multiple localization. The druggability analysis of the identified 73 cytoplasmic and multiple localization essential proteins revealed 22 druggable targets and 51 novel drug targets that participate in unique pathways of lice and acari and their APs. Further, the predicted 42 membrane bound proteins could be potential vaccine candidates. Screening of useful inhibitors against these novel targets may result in finding novel compounds efficient for the control of these parasites.

Genetic Determinants in Salmonella enterica Serotype Typhimurium Required for Overcoming In Vitro Stressors in the Mimicking Host Environment

Salmonella enterica serotype Typhimurium, a nontyphoidal Salmonella (NTS), results in a range of enteric diseases, representing a major disease burden worldwide. There is still a significant portion of Salmonella genes whose mechanistic basis to overcome host innate defense mechanisms largely remains unknown. Here, we have applied transposon insertion sequencing (Tn-seq) method to unveil the genetic factors required for the growth or survival of S. Typhimurium under various host stressors simulated in vitro. A highly saturating Tn5 library of S. Typhimurium 14028s was subjected to selection during growth in the presence of short-chain fatty acid (100 mM propionate), osmotic stress (3% NaCl), or oxidative stress (1 mM H2O2) or survival in extreme acidic pH (30 min in pH 3) or starvation (12 days in 1× phosphate-buffered saline [PBS]). We have identified a total of 339 conditionally essential genes (CEGs) required to overcome at least one of these conditions mimicking host insults. Interestingly, all eight genes encoding FoF1-ATP synthase subunit proteins were required for fitness in all five stresses. Intriguingly, a total of 88 genes in Salmonella pathogenicity islands (SPI), including SPI-1, SPI-2, SPI-3, SPI-5, SPI-6, and SPI-11, are also required for fitness under the in vitro conditions. Additionally, by comparative analysis of the genes identified in this study and the genes previously shown to be required for in vivo fitness, we identified novel genes (marBCT, envF, barA, hscA, rfaQ, rfbI, and the genes encoding putative proteins STM14_1138, STM14_3334, STM14_4825, and STM_5184) that have compelling potential for the development of vaccines and antibacterial drugs to curb Salmonella infection. IMPORTANCE Salmonella enterica serotype Typhimurium is a major human bacterial pathogen that enters the food chain through meat animals asymptomatically carrying this pathogen. Despite the rich genome sequence data, a significant portion of Salmonella genes remain to be characterized for their potential contributions to virulence. In this study, we used transposon insertion sequencing (Tn-seq) to elucidate the genetic factors required for growth or survival under various host stressors, including short-chain fatty acids, osmotic stress, oxidative stress, extreme acid, and starvation. Among the total of 339 conditionally essential genes (CEGs) that are required under at least one of these five stress conditions were 221 previously known virulence genes required for in vivo fitness during infection in at least one of four animal species, including mice, chickens, pigs, and cattle. This comprehensive map of virulence phenotype-genotype in S. Typhimurium provides a roadmap for further interrogation of the biological functions encoded by the genome of this important human pathogen to survive in hostile host environments.

In Silico Core Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against Streptococcus pyogenes

Streptococcus pyogenes is a significant pathogen that causes skin and upper respiratory tract infections and non-suppurative complications, such as acute rheumatic fever and post-strep glomerulonephritis. Multidrug resistance has emerged in S. pyogenes strains, making them more dangerous and pathogenic. Hence, it is necessary to identify and develop therapeutic methods that would present novel approaches to S. pyogenes infections. In the current study, a subtractive proteomics approach was employed to core proteomes of four strains of S. pyogenes using several bioinformatic software tools and servers. The core proteome consists of 1324 proteins, and 302 essential proteins were predicted from them. These essential proteins were analyzed using BLASTp against human proteome, and the number of potential targets was reduced to 145. Based on subcellular localization prediction, 46 proteins with cytoplasmic localization were chosen for metabolic pathway analysis. Only two cytoplasmic proteins, i.e., chromosomal replication initiator protein DnaA and two-component response regulator (TCR), were discovered to have the potential to be novel drug target candidates. Three-dimensional (3D) structure prediction of target proteins was carried out via the Swiss Model server. Molecular docking approach was employed to screen the library of 1000 phytochemicals against the interacting residues of the target proteins through the MOE software. Further, the docking studies were validated by running molecular dynamics simulation and highly popular binding free energy approaches of MM-GBSA and MM-PBSA. The findings revealed a promising candidate as a novel target against S. pyogenes infections.

Prioritization of potential drug targets and antigenic vaccine candidates against Klebsiella aerogenes using the computational subtractive proteome-driven approach

Klebsiella aerogenes is a multidrug-resistant Gram-negative bacterium that causes nosocomial infections. The organism showed resistance to most of the conventional antibiotics available. Because of the high resistance of the species, the treatment of K. aerogenes is difficult. These species are resistant to third-generation cephalosporins due to the production of chromosomal beta-lactams with cephalosporin activity. The lack of better treatment and the development of therapeutic resistance in hospitals hinders better/new broad-spectrum-based treatment against this pathogen. This study identifies potential drug targets/vaccine candidates through a computational subtractive proteome-driven approach. This method is used to predict proteins that are not homologous to humans and human symbiotic intestinal flora. The resultant proteome of K. aerogenes was further searched for proteins, which are essential, virulent, and determinants of antibiotic/drug resistance. Subsequently, their druggability properties were also studied. The data set was reduced based on its presence in the pathogen-specific metabolic pathways. The subtractive proteome analysis predicted 13 proteins as potential drug targets for K. aerogenes. Furthermore, these target proteins were annotated based on their spectrum of activity, cellular localization, and antigenicity properties, which ensured that they are potent candidates for broad-spectrum antibiotic and vaccine design. The results open up new opportunities for designing and manufacturing powerful antigenic vaccines against K. aerogenes and the detection and release of new and active drugs against K. aerogenes without altering the gut microbiome.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42485-021-00068-9.

Modeling Novel Putative Drugs and Vaccine Candidates against Tick-Borne Pathogens: A Subtractive Proteomics Approach

Ticks and tick-borne pathogens (TBPs) continuously causing substantial losses to the public and veterinary health sectors. The identification of putative drug targets and vaccine candidates is crucial to control TBPs. No information has been recorded on designing novel drug targets and vaccine candidates based on proteins. Subtractive proteomics is an in silico approach that utilizes extensive screening for the identification of novel drug targets or vaccine candidates based on the determination of potential target proteins available in a pathogen proteome that may be used effectively to control diseases caused by these infectious agents. The present study aimed to investigate novel drug targets and vaccine candidates by utilizing subtractive proteomics to scan the available proteomes of TBPs and predict essential and non-host homologous proteins required for the survival of these diseases causing agents. Subtractive proteome analysis revealed a list of fifteen essential, non-host homologous, and unique metabolic proteins in the complete proteome of selected pathogens. Among these therapeutic target proteins, three were excluded due to the presence in host gut metagenome, eleven were found to be highly potential drug targets, while only one was found as a potential vaccine candidate against TBPs. The present study may provide a foundation to design potential drug targets and vaccine candidates for the effective control of infections caused by TBPs.

Leptospiral protein LIC11334 display an immunogenic peptide KNSMP01

Leptospirosis is considered as a neglected tropical disease which is caused by pathogenic Leptospira spp. The precise mechanisms of leptospirosis pathogenesis are unclear and hence, the progress in development of treatment modalities has been dismal. The present study aimed to identify novel virulent factors of leptospires to understand the disease pathogenesis and to develop treatment modalities. Leptospira interrogans contains two chromosomes and encodes for ~3703 genes, but the functions of several open reading frames have not yet been explored. Among them, novel virulent associated leptospiral proteins (LIC11334, LIC11542, LIC11436, LIC11120 and LIC12539) were identified using VirulentPredict and the antigenicity of these targets was explored by VaxiJen server. Domain architecture of the pathogen specific proteins revealed that LIC11334 had potential to evoke significant immune response against leptospiral infection and LIC11436 contains four folds of immunoglobulin-like domain and plays a vital role in pathogenesis. Therefore, B-cell epitopes were predicted and the epitope of high virulence (and VaxiJen score from LIC11334) was chemically synthesized as peptide (KNSMP01) and labeled with Biotin (Biotin-SGSGEVENPDPKVAQEC). Binding affinity of KNSMP01 with MHC molecules was predicted and the molecule was discovered to have potential to elicit both humoral and cell mediated immune responses and found to interact with host components via hydrophobic interaction, hydrogen bonding and salt bridges. Rabbit antisera was raised against KNSMP01 and found to elicit antigenicity using Western, ELISA and dot blot assays. In silico and in vitro experiments show KNSMP01 to be a promising immunogen and may be a better vaccine candidate for leptospirosis.

In Silico Subtractive Proteomics Approach for Identification of Potential Drug Targets in Staphylococcus saprophyticus

Staphylococcus saprophyticus is a uropathogenic bacteria responsible for acute urinary tract infections (UTIs) mainly in young female patients. Patients suffering from urinary catheterization, pregnant patients, the elderly as well as those with nosocomial UTIs are at greater risk of the colonizing S. saprophyticus infection. The causative factors include benign prostatic hyperplasia, indwelling catheter, neurogenic bladder, pregnancy, and history of frequent UTIs. Recent findings have exhibited that S. saprophyticus is resistant to several antimicrobial agents. Moreover, there is a global concern regarding the increasing level of antimicrobial resistance, which leads to treatment failure and reduced effectiveness of broad-spectrum antimicrobials. Therefore, a novel approach is being utilized to combat resistant microbes since the past few years. Subtractive proteome analysis has been performed with the entire proteome of S. saprophyticus strain American Type Culture Collection (ATCC) 15305 using several bioinformatics servers and software. The proteins that were non-homologous to humans and bacteria were identified for metabolic pathway analysis. Only four cytoplasmic proteins were found possessing the potential of novel drug target candidates. The development of innovative therapeutic agents by targeting the inhibition of any essential proteins may disrupt the metabolic pathways specific to the pathogen, thus causing destruction as well as eradication of the pathogen from a particular host. The identified targets can facilitate in designing novel and potent drugs against S. saprophyticus strain ATCC 15305.

Novel and potent inhibitors for dihydropteroate synthase of Helicobacter pylori

An endless drug-resistant strains of Helicobacter pylori and multitudinous drug reactions are obstacles in the treatment of H. pylori infections, thereby ambitious novel proof-of-concept for inhibitor design was practiced in advancement of medication. Dihydropteroate synthase (DHPS) is an alluring target that plays a great role in folate synthesis pathway essential for amino acids biosynthesis was selected for designing novel drugs to prevent infections caused by pathogenic H. pylori. In the present study, a reliable tertiary structure of DHPS in complex with inhibitor 6MB was constructed by Modeler 9v19. DrugBank compounds of DHPS, published inhibitors, and co-crystal ligand (6MB) were docked against DHPS. The best docked compounds were screened against 28.5 million compounds resulted 1186 structural analogs. Virtual screening workflow and quantum polarized ligand dockings of these compounds against DHPS resulted three leads that showed better XP Gscores, ADME properties, and binding-free energies compared to 6MB, DrugBank compounds, and published inhibitors. The proposed leads were also validated by receiver operative characteristic (ROC) curve metrics in the presence of thousand decoys and the best docked existing compounds against DHPS. Long-range molecular dynamics (MD) simulations for 100 ns were executed after post-docking evaluations. Trajectory analysis showed the lead-DHPS docking complex's inter-molecular interactions were stable throughout the entire runtime of MD simulations than 6MB-DHPS complex and Eliglustat-DHPS complex. The study outcomes showed good competitive binding propensity and active-tunneling of leads over the existing inhibitors, thereby these leads could be ideal inhibitors against DHPS to target H. pylori.

In-silico Subtractive Proteomic Analysis Approach for Therapeutic Targets in MDR Salmonella enterica subsp. enterica serovar Typhi str. CT18

OBJECTIVE

In the present study, an attempt has been made for subtractive proteomic analysis approach for novel drug targets in Salmonella enterica subsp. enterica serover Typhi str.CT18 using computational tools.

METHODS

Paralogous, redundant and less than 100 amino acid protein sequences were removed by using CD-HIT. Further detection of bacterial proteins which are non-homologous to host and are essential for the survival of pathogens by using BLASTp against host proteome and DEG`s, respectively. Comparative Metabolic pathways analysis was performed to find unique and common metabolic pathways. The non-redundant, non-homologous and essential proteins were BLAST against approved drug targets for drug targets while Psortb and CELLO were used to predict subcellular localization.

RESULTS

There were 4473 protein sequences present in NCBI Database for Salmonella enterica subsp. enterica serover Typhi str. CT18 out of these 327 were essential proteins which were non-homologous to human. Among these essential proteins, 124 proteins were involved in 19 unique metabolic pathways. These proteins were further BLAST against approved drug targets in which 7 cytoplasmic proteins showed druggability and can be used as a therapeutic target.

CONCLUSION

Drug targets identification is the prime step towards drug discovery. We identified 7 cytoplasmic druggable proteins which are essential for the pathogen survival and non-homologous to human proteome. Further in vitro and in vivo validation is needed for the evaluation of these targets to combat against salmonellosis.

Network-Based Metabolism-Centered Screening of Potential Drug Targets in Klebsiella pneumoniae at Genome Scale

Klebsiella pneumoniae is an opportunistic bacterial pathogen leading to life-threatening nosocomial infections. Emergence of highly resistant strains poses a major challenge in the management of the infections by healthcare-associated K. pneumoniae isolates. Thus, despite intensive efforts, the current treatment strategies remain insufficient to eradicate such infections. Failure of the conventional infection-prevention and treatment efforts explicitly indicates the requirement of new therapeutic approaches. This prompted us to systematically analyze the K. pneumoniae metabolism to investigate drug targets. Genome-scale metabolic networks (GMNs) facilitating the systematic analysis of the metabolism are promising platforms. Thus, we used a GMN of K. pneumoniae MGH 78578 to determine putative targets through gene- and metabolite-centric approaches. To develop more realistic infection models, we performed the bacterial growth simulations within different host-mimicking media, using an improved biomass formation reaction. We selected more suitable targets based on several property-based prioritization procedures. KdsA was identified as the high-ranked putative target satisfying most of the target prioritization criteria specified under the gene-centric approach. Through a structure-based virtual screening protocol, we identified potential KdsA inhibitors. In addition, the metabolite-centric approach extended the drug target list based on synthetic lethality. This revealed the importance of combined metabolic analyses for a better understanding of the metabolism. To our knowledge, this is the first comprehensive effort on the investigation of the K. pneumoniae metabolism for drug target prediction through the constraint-based analysis of its GMN in conjunction with several bioinformatic approaches. This study can guide the researchers for the future drug designs by providing initial findings regarding crucial components of the Klebsiella metabolism.

Long-chain flavodoxin FldX1 improves Paraburkholderia xenovorans LB400 tolerance to oxidative stress caused by paraquat and H2O2

Flavodoxins are small electron transfer proteins containing flavin mononucleotide (FMN) as a prosthetic group, which play an important role during oxidative stress or iron limitation. The aims of this study were the identification and characterization of flavodoxins in the model aromatic-degrader Paraburkholderia xenovorans LB400 and the analyses of their protective effects during oxidative stress induced by paraquat and H2O2. Two genes (BxeA0278 and BxeB0391) encoding flavodoxins (hereafter referred to as fldX for flavodoxin from P. xenovorans), were identified at the LB400 major and minor chromosome. Genomic context of the flavodoxin-encoding genes showed genes encoding membrane proteins, transporters, and proteins involved in redox processes and biosynthesis of macromolecules. A secondary structure prediction of both LB400 flavodoxins showed the characteristic flavodoxin structure of five ß-sheets intercalated with five α-helices. FldX1 contains a loop intercalated in the fifth β-strand, which indicates that it belongs to the long-chain flavodoxins, whereas FldX2 is a short-chain flavodoxin. A phylogenetic analysis of 73 flavodoxins from 43 bacterial genera revealed eight clusters (I-VIII), while FldX1 and FldX2 grouped separately within a long-chain and a short-chain flavodoxin clades. FldX1 and FldX2 were overexpressed in P. xenovorans. Interestingly, the strain overexpressing the long-chain flavodoxin FldX1 (p2-fldX1) showed a faster growth in glucose than the control strain. The recombinant strain overexpressing the long-chain flavodoxin FldX1 (p2-fldx1) exposed to paraquat (20 mM) possessed lower susceptibility to growth inhibition on plates and higher survival in liquid medium than the control strain. The strains overexpressing the flavodoxins FldX1 and FldX2 showed higher survival during exposure to 1 mM paraquat (>95%) than the control strain (68%). Compared to the control strain, strains overexpressing FldX1 and FldX2 showed lower lipid peroxidation (>20%) after exposure to 1 mM paraquat and a lower protein carbonylation (~30%) after exposure to 1 mM H2O2 was observed. During exposure to paraquat, strain p2-fldx1 downregulated the katG4, hpf, trxB1 and ohr genes (> 2-fold), whereas strain p2-fldx2 upregulated the oxyR and ahpC1 genes (> 2-fold). In conclusion, the flavodoxins FldX1 and FldX2 of P. xenovorans LB400 conferred protection to cells exposed to the oxidizing agents paraquat and H2O2.

An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira

Leptospirosis is one of the leading zoonotic infections worldwide. As with other infectious diseases, report of antimicrobial resistance to existing therapeutic arsenal poses challenges in the management of disease. Hence, identification of novel drug targets for the pathogen deems essential. Present study used combined approach of comparative and subtractive genomics to identify putative drug targets. Crucial genes of 16 pathogenic Leptospira strains were filtered and subjected to homology search via target identification tool "TiD". Thereafter, comparative analysis was performed for non-homologous, essential genes to accomplish the broad-spectrum drug target. Consequently, 37 essential genes were found to be conserved in at least 10 strains of Leptospira. Further, prioritization of resultant set of genes revealed 18 were hubs in protein-protein interaction network. Sixteen putative targets among the hub genes were conserved in all strains of Leptospira. Out of sixteen, fourteen were enzymes while 8 were novel and 4 were involved in virulence mechanism. In addition, genome scale metabolic network reconstruction and choke point analysis revealed cobA (porphyrin and chlorophyll metabolism) and thiL (thiamine metabolism) as chokepoints in their respective metabolic pathways. The proposed hub genes could act as putative broad-spectrum drug targets for Leptospira species, however, these putative targets should be validated to ensure them as real one prior to utilizing them for target based lead discovery.

Proteome Mining for the Identification of Putative Drug Targets For Human Pathogen Clostridium Tetani

Background:

Clostridium tetani are rod-like, anaerobic types of pathogenic bacteria of the genus Clostridium. It is Gram-positive in nature and appears as a tennis racket or drumsticks on staining with the dye. Tetanus is a neuromuscular disease wherein the Clostridium tetani exotoxin produces muscle fits in the host. Tetanus is the second leading cause of worldwide deaths occurring from the family of immunization-preventable diseases.

Methods:

In this research, subtractive proteome analysis of C. tetani was performed to identify putative drug targets. The proteins were subjected to blast analysis against Homo sapiens to exclude homologous proteins. The database of Essential Genes was used to determine the essential proteins of the pathogen. These basic proteins were additionally analyzed to anticipate the corresponding metabolic pathways.

Results:

Cellular localization analysis was carried out to determine the possibility of the protein presence in the outer membrane. The study has recognized 29 essential genes and 20 unique pathways of 2314 proteins as potential drug targets. There are 29 essential proteins, out of which, 3 membrane proteins were also identified as putative drug targets.

Conclusion:

Virtual screening in contrast to these proteins can be valuable in the identification of novel clinical compounds for the C. tetani infections in Homo sapiens.

Computational identification and antifungal bioassay reveals phytosterols as potential inhibitor of Alternaria arborescens

Alternaria arborescens is a major pathogen for crops like tomato, tangerine and so on and its control is mostly dependent on the application of chemical agents. Plants as the sources of natural products are very attractive option for developing eco-friendly and natural antifungal agents. In this study, we modeled three-dimensional structure of chorismate synthase (CS) enzyme from A. arborescens. Docking studies of phytosterols, namely, γ-sitosterol and β-sitosterol, with CS showed them to be potential inhibitor of CS. To explore the stability and conformational flexibility of all the AaCS complex systems, molecular dynamics simulations were performed. None of the putative inhibitors as well as β- and γ-sitosterol showed interaction with the FMNH₂ binding pocket of the tomato CS (major host of A. arborescens) indicating their suitability as antifungal compounds inhibiting the shikimate pathway without causing any harm to the host. An in vivo antifungal bioassay showed a significant reduction in fungal growth in the presence of β-sitosterol (500 ppm) which resulted in ∼23% and ∼17% reduction in fungal fresh and dry weight, respectively, at 8 days after inoculation. This study provides experimental evidence establishing natural sterols like β-sitosterol can be useful in curbing A. arborescens damage in an eco-friendly manner.Communicated by Ramaswamy H. Sarma.

Computational screening of potential drug targets for pathogens causing bacterial pneumonia

Streptococcus pneumoniae is widely recognized as the main cause of bacterial pneumonia among all age groups. Other important gram-positive, gram-negative and atypical bacteria causing pneumonia majorly infect children and infants. Despite abundant occurrence of bacterial pneumonia, there is no specific antibiotic therapy available. On the other hand non-specific therapies are less effective and may influence bacterial resistance. Therefore, search for novel drug targets for pathogen is highly necessary. The current study suggested novel potential drug targets through the subtractive and comparative genomics approach. Putative drug targets were identified from highly virulent strain of Streptococcus pneumoniae using target identification (TiD) software and compared with other 12 pneumonia causing pathogens. The putative targets were prioritized through druggability analysis, virulence analysis, metabolic pathway enrichment followed by functional annotations and interactome network. Prioritization of 74 drug targets revealed that 42 of them were enzymes which included 29 new targets and seven chokepoint enzymes. Twenty (out of 74) potential targets are proposed as hub genes through interactome analysis and explored their significance in survival of the pathogen. Comparative analysis of 20 hub genes represents that 15 are enzymes and five are non-enzymes. Functional annotation of two chokepoint hub enzymes namely, peptidoglycan bridge formation alanyltransferase MurN (fibB) and PTS mannitol transporter subunit IIA (mltF) were significantly enriched in peptidoglycan biosynthesis and phosphotransferase system (PTS) respectively. Therefore these enzymes would be of prior interest for rational design of targeted therapy against bacterial pneumonia.

Pathway based therapeutic targets identification and development of an interactive database CampyNIBase of Campylobacter jejuni RM1221 through non-redundant protein dataset

The bacterial species Campylobacter jejuni RM1221 (CjR) is the primary cause of campylobacteriosis which poses a global threat for human health. Over the years the efficacy of antibiotic treatment is becoming more fruitless due to the development of multiple drug resistant strains. Therefore, identification of new drug targets is a valuable tool for the development of new treatments for affected patients and can be obtained by targeting essential protein(s) of CjR. We conducted this in silico study in order to identify therapeutic targets by subtractive CjR proteome analysis. The most important proteins of the CjR proteome, which includes chokepoint enzymes, plasmid, virulence and antibiotic resistant proteins were annotated and subjected to subtractive analyses to filter out the CjR essential proteins from duplicate or human homologous proteins. Through the subtractive and characterization analysis we have identified 38 eligible therapeutic targets including 1 potential vaccine target. Also, 12 potential targets were found in interactive network, 5 targets to be dealt with FDA approved drugs and one pathway as potential pathway based drug target. In addition, a comprehensive database 'CampyNIBase' has also been developed. Besides the results of this study, the database is enriched with other information such as 3D models of the identified targets, experimental structures and Expressed Sequence Tag (EST) sequences. This study, including the database might be exploited for future research and the identification of effective therapeutics against campylobacteriosis. URL: (http://nib.portal.gov.bd/site/page/4516e965-8935-4129-8c3f-df95e754c562#Banner).

Identification of potential drug targets and inhibitor of the pathogenic bacteria Shigella flexneri 2a through the subtractive genomic approach

Shigella flexneri 2a is one of the most pathogenic bacteria among the Shigella spp., which is responsible for dysentery and causes masses of deaths throughout the world per year. A proper identification of the potential drug targets and inhibitors is crucial for the treatment of the shigellosis due to their emerging multidrug resistance (MDR) patterns. In this study, a systematic subtractive approach was implemented for the identification of novel therapeutic targets of S. flexneri 2a (301) through genome-wide metabolic pathway analysis of the essential genes and proteins. Ligand-based virtual screening and ADMET analyses were also made for the identification of potential inhibitors as well. Initially, we found 70 essential unique proteins as novel targets. After subsequent prioritization, finally we got six unique targets as the potential therapeutic targets and their three-dimensional models were built thereafter. Aspartate-β-semialdehyde dehydrogenase (ASD), was the most potent target among them and used for docking analysis through ligand-based virtual screening. The compound 3 (PubChem CID: 11319750) suited well as the best inhibitor of the ASD through ADMET and enzyme inhibition capacity analysis. To end, we hope that our proposed therapeutic targets and its inhibitors might give some breakthrough to treat shigellosis efficiently in in vitro.

Comparative genomic analysis of Rickettsia rickettsii for identification of drug and vaccine targets: tolC as a proposed candidate for case study

BACKGROUND

Antibiotic resistance is increasing rapidly in pathogenic organisms, creating more complications for treatment of diseases. Rocky Mountain spotted fever (RMSF) is a neglected tropical disease in humans caused by Rickettsia rickettsii for which no effective therapeutic is available. Subtractive genomics methods facilitate the characterization of non-homologous essential proteins that could be targeted for the discovery of potential therapeutic compounds against R. rickettsii to combat RMSF. Present study followed an in-silico based methodology, involving scanning and filtering the complete proteome of Rickettsia rickettsii by using several prioritization parameters in the search of potential candidates for drug development. Further the putative targets were subjected to series of molecular dockings with ligands obtained from PDB ligand database to identify suitable potential inhibitors. The comparative genomic analysis revealed 606 non-homologous proteins and 233 essential non-homologous proteins of R. rickettsii. The metabolic pathway analysis predicted 120 proteins as putative drug targets, out of which 56 proteins were found to be associated with metabolic pathways unique to the bacteria and further subcellular localization analysis revealed that 9 proteins as potential drug targets which are secretion proteins, involved in peptidoglycan biosynthesis, folate biosynthesis and bacterial secretion system. As secretion proteins are more feasible as vaccine candidates, we have selected a most potential target i.e. tolC, an outer membrane efflux protein that belongs to type I secretion system and has major role in pathogen survival as well as MDR persistence. So for case study, we have modelled the three dimensional structure of tolC (tunnel protein). The model was further subjected to virtual screening and in-silico docking. The study identified three potential inhibitors having PDB Id 19V, 6Q8 and 39H. Further we have suggested that the above study would be most important while considering the selection of candidate targets and drug or vaccine designing against R. rickettsii.

LeptoDB: an integrated database of genomics and proteomics resource of Leptospira

Leptospirosis is a potentially fatal zoo-anthroponosis caused by pathogenic species of Leptospira belonging to the family of Leptospiraceae, with a worldwide distribution and effect, in terms of its burden and risk to human health. The 'LeptoDB' is a single window dedicated architecture (5 948 311 entries), modeled using heterogeneous data as a core resource for global Leptospira species. LeptoDB facilitates well-structured knowledge of genomics, proteomics and therapeutic aspects with more than 500 assemblies including 17 complete and 496 draft genomes encoding 1.7 million proteins for 23 Leptospira species with more than 250 serovars comprising pathogenic, intermediate and saprophytic strains. Also, it seeks to be a dynamic compendium for therapeutically essential components such as epitope, primers, CRISPR/Cas9 and putative drug targets. Integration of JBrowse provides elaborated locus centric description of sequence or contig. Jmol for structural visualization of protein structures, MUSCLE for interactive multiple sequence alignment annotation and analysis. The data on genomic islands will definitely provide an understanding of virulence and pathogenicity. Phylogenetics analysis integrated suggests the evolutionary division of strains. Easily accessible on a public web server, we anticipate wide use of this metadata on Leptospira for the development of potential therapeutics.Database URL: http://leptonet.org.in.

Study of intra-inter species protein-protein interactions for potential drug targets identification and subsequent drug design for Escherichia coli O104:H4 C277-11

Protein-protein interaction (PPI) and host-pathogen interactions (HPI) proteomic analysis has been successfully practiced for potential drug target identification in pathogenic infections. In this research, we attempted to identify new drug target based on PPI and HPI computation approaches and subsequently design new drug against devastating enterohemorrhagic Escherichia coli O104:H4 C277-11 (Broad), which causes life-threatening food borne disease outbreak in Germany and other countries in Europe in 2011. Our systematic in silico analysis on PPI and HPI of E. coli O104:H4 was able to identify bacterial D-galactose-binding periplasmic and UDP-N-acetylglucosamine 1-carboxyvinyltransferase as attractive candidates for new drug targets. Furthermore, computational three-dimensional structure modeling and subsequent molecular docking finally proposed [3-(5-Amino-7-Hydroxy-[1,2,3]Triazolo[4,5-D]Pyrimidin-2-Yl)-N-(3,5-Dichlorobenzyl)-Benzamide)] and (6-amino-2-[(1-naphthylmethyl)amino]-3,7-dihydro-8H-imidazo[4,5-g]quinazolin-8-one) as promising candidate drugs for further evaluation and development for E. coli O104:H4 mediated diseases. Identification of new drug target would be of great utility for humanity as the demand for designing new drugs to fight infections is increasing due to the developing resistance and side effects of current treatments. This research provided the basis for computer aided drug design which might be useful for new drug target identification and subsequent drug design for other infectious organisms.

Functional thioredoxin reductase from pathogenic and free-living Leptospira spp

Low molecular mass thiols and antioxidant enzymes have essential functions to detoxify reactive oxygen and nitrogen species maintaining cellular redox balance. The metabolic pathways for redox homeostasis in pathogenic (Leptospira interrogans) and free-living (Leptospira biflexa) leptospires species were not functionally characterized. We performed biochemical studies on recombinantly produced proteins to in depth analyze kinetic and structural properties of thioredoxin reductase (LinTrxR) and thioredoxin (LinTrx) from L. interrogans, and two TrxRs (LbiTrxR1 and LbiTrxR2) from L. biflexa. All the TrxRs were characterized as homodimeric flavoproteins, with LinTrxR and LbiTrxR1 catalyzing the NADPH dependent reduction of LinTrx and DTNB. The thioredoxin system from L. interrogans was able to use glutathione disulfide, lipoamide disulfide, cystine and bis-γ-glutamyl cysteine and homologous peroxiredoxin as substrates. Classic TrxR activity of LinTrxR2 had not been evidenced in vitro, but recombinant Escherichia coli cells overexpressing LbiTrxR2 showed high tolerance to oxidative stress. The enzymatic systems herein characterized could play a key role for the maintenance of redox homeostasis and the function of defense mechanisms against reactive oxidant species in Leptospira spp. Our results contribute to the general knowledge about redox biochemistry in these bacteria, positioning TrxR as a critical molecular target for the development of new anti-leptospiral drugs.

Inhibitor design against JNK1 through e-pharmacophore modeling docking and molecular dynamics simulations

c-Jun-NH2 terminal kinases (JNKs) come under a class of serine/threonine protein kinases and are encoded by three genes, namely JNK1, JNK2 and JNK3. Human JNK1 is a cytosolic kinase belonging to mitogen-activated protein kinase (MAPK) family, which plays a major role in intracrinal signal transduction cascade mechanism. Overexpressed human JNK1, a key kinase interacts with other kinases involved in the etiology of many cancers, such as skin cancer, liver cancer, breast cancer, brain tumors, leukemia, multiple myeloma and lymphoma. Thus, to unveil a novel human JNK1 antagonist, receptor-based pharmacophore modeling was performed with the available eighteen cocrystal structures of JNK1 in the protein data bank. Eighteen e-pharmacophores were generated from the 18 cocrystal structures. Four common e-pharmacophores were developed from the 18 e-pharmacophores, which were used as three-dimensional (3D) query for shape-based similarity screening against more than one million small molecules to generate a JNK1 ligand library. Rigid receptor docking (RRD) performed using GLIDE v6.3 for the 1683 compounds from in-house library and 18 cocrystal ligands with human JNK1 from lower stringency to higher stringency revealed 17 leads. Further to derive the best leads, dock complexes obtained from RRD were studied further with quantum-polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area (MM-GBSA). Four leads have showed lesser binding free energy and better binding affinity towards JNK1 compared to 18 cocrystal ligands. Additionally, JNK1-lead1 complex interaction stability was reasserted using 50 ns MD simulations run and also compared with the best resolute cocrystal structure using Desmond v3.8. Thus, the results obtained from RRD, QPLD, IFD and MD simulations indicated that lead1 might be used as a potent antagonist toward human JNK1 in cancer therapeutics.

E-pharmacophore-based virtual screening to identify GSK-3β inhibitors

Glycogen synthase kinase-3β (GSK-3β) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3β increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer's disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3β to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3β. The 50 ns MD simulations run confirmed the stable nature of GSK-3β-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3β.

Identification of potential drug targets by subtractive genome analysis of Escherichia coli O157:H7: an in silico approach

Bacterial enteric infections resulting in diarrhea, dysentery, or enteric fever constitute a huge public health problem, with more than a billion episodes of disease annually in developing and developed countries. In this study, the deadly agent of hemorrhagic diarrhea and hemolytic uremic syndrome, Escherichia coli O157:H7 was investigated with extensive computational approaches aimed at identifying novel and broad-spectrum antibiotic targets. A systematic in silico workflow consisting of comparative genomics, metabolic pathways analysis, and additional drug prioritizing parameters was used to identify novel drug targets that were essential for the pathogen’s survival but absent in its human host. Comparative genomic analysis of Kyoto Encyclopedia of Genes and Genomes annotated metabolic pathways identified 350 putative target proteins in E. coli O157:H7 which showed no similarity to human proteins. Further bio-informatic approaches including prediction of subcellular localization, calculation of molecular weight, and web-based investigation of 3D structural characteristics greatly aided in filtering the potential drug targets from 350 to 120. Ultimately, 44 non-homologous essential proteins of E. coli O157:H7 were prioritized and proved to have the eligibility to become novel broad-spectrum antibiotic targets and DNA polymerase III alpha (dnaE) was the top-ranked among these targets. Moreover, druggability of each of the identified drug targets was evaluated by the DrugBank database. In addition, 3D structure of the dnaE was modeled and explored further for in silico docking with ligands having potential druggability. Finally, we confirmed that the compounds N-coeleneterazine and N-(1,4-dihydro-5H-tetrazol-5-ylidene)-9-oxo-9H-xanthene-2-sulfon-amide were the most suitable ligands of dnaE and hence proposed as the potential inhibitors of this target protein. The results of this study could facilitate the discovery and release of new and effective drugs against E. coli O157:H7 and other deadly human bacterial pathogens.

Expeditious screening of candidate proteins for microbial vaccines

Advancements in high-throughput "omics" technologies have revolutionized the way vaccine candidates are identified. Now every surface expressed protein that an organism produces can be identified in silico and possibly made available for the rapid development of recombinant/subunit vaccines. However, evaluating the antigenicity of a large number of candidate proteins is an immense challenge, typically requiring cloning of several hundred candidates followed by immunogenicity screening. Here we report the development of a rapid, high-throughput method for screening candidate proteins for vaccines. This method involves utilizing a coupled, cell-free transcription-translation system to screen tagged proteins that are captured at the C-termini using appropriate ligand coated wells in 96 well ELISA plates. The template DNA for the cell-free expression is generated by two sequential PCRs and includes gene coding sequences, promoter, terminator, other necessary cis-acting elements and appropriate tag sequences. The process generates expressible candidate proteins containing two different peptide tags at the N- and the C-termini of the protein molecules. Proteins are screened in parallel for their quantity and immunoreactivity with N-terminal tag antibodies and antisera raised against the pathogen of interest, respectively. Normalization against the total detectable bound protein in the control wells allows for the identification of highly immunoreactive candidates. For this study we selected 30 representatives of >300 potential candidate proteins from Mannheimia haemolytica, a bacterial agent of pneumonia in feedlot cattle for expression with N-terminal Strep-II and C-terminal His(x6)-tag and evaluated their relative immunoreactivities using Strep-tactin-HRP and rabbit antisera generated against M. haemolytica. Using this system we were able to swiftly and quantitatively analyze and rank the suitability of proteins to identify potentially viable vaccine candidates, with the majority of the high ranking candidates being associated with virulence and pathogenicity. The system is adaptable to any bacterial target and presents an alternative to conventional laborious cloning, expression and screening procedures.

Genome-wide Analysis of Mycoplasma hominis for the Identification of Putative Therapeutic Targets

Ever increasing propensity of antibiotic resistance among pathogenic bacteria raises the demand for the development of novel therapeutic agents to control this grave problem. Advances in the field of bioinformatics, genomics, and proteomics have greatly facilitated the discovery of alternative drugs by swift identification of new drug targets. In the present study, we employed comparative genomics and metabolic pathway analysis with an aim of identifying therapeutic targets in Mycoplasma hominis. Our study has revealed 40 annotated metabolic pathways, including five unique pathways of M. hominis. Our study also identified 179 essential proteins, including 59 proteins having no similarity with human proteins. Further filtering by molecular weight, subcellular localization, functional analysis, and protein network interaction, we identified 57 putative candidates for which new drugs can be developed. Druggability analysis for each of the identified targets has prioritized 16 proteins as suitable for potential drug development.

Potential mechanism of action of meso-dihydroguaiaretic acid on Mycobacterium tuberculosis H37Rv

The isolation and characterization of the lignan meso-dihydroguaiaretic acid (MDGA) from Larrea tridentata and its activity against Mycobacterial tuberculosis has been demonstrated, but no information regarding its mechanism of action has been documented. Therefore, in this study we carry out the gene expression from total RNA obtained from M. tuberculosis H37Rv treated with MDGA using microarray technology, which was validated by quantitative real time polymerase chain reaction. Results showed that the alpha subunit of coenzyme A transferase of M. tuberculosis H37Rv is present in both geraniol and 1-and 2-methylnaphthalene degradation pathways, which are targeted by MDGA. This assumption was supported by molecular docking which showed stable interaction between MDGA with the active site of the enzyme. We propose that inhibition of coenzyme A transferase of M. tuberculosis H37Rv results in the accumulation of geraniol and 1-and 2-methylnaphtalene inside bacteria, causing membrane destabilization and death of the pathogen. The natural product MDGA is thus an attractive template to develop new anti-tuberculosis drugs, because its target is different from those of known anti-tubercular agents.

Unraveling novel broad-spectrum antibacterial targets in food and waterborne pathogens using comparative genomics and protein interaction network analysis

Food and waterborne diseases are a growing concern in terms of human morbidity and mortality worldwide, even in the 21st century, emphasizing the need for new therapeutic interventions for these diseases. The current study aims at prioritizing broad-spectrum antibacterial targets, present in multiple food and waterborne bacterial pathogens, through a comparative genomics strategy coupled with a protein interaction network analysis. The pathways unique and common to all the pathogens under study (viz., methane metabolism, d-alanine metabolism, peptidoglycan biosynthesis, bacterial secretion system, two-component system, C5-branched dibasic acid metabolism), identified by comparative metabolic pathway analysis, were considered for the analysis. The proteins/enzymes involved in these pathways were prioritized following host non-homology analysis, essentiality analysis, gut flora non-homology analysis and protein interaction network analysis. The analyses revealed a set of promising broad-spectrum antibacterial targets, present in multiple food and waterborne pathogens, which are essential for bacterial survival, non-homologous to host and gut flora, and functionally important in the metabolic network. The identified broad-spectrum candidates, namely, integral membrane protein/virulence factor (MviN), preprotein translocase subunits SecB and SecG, carbon storage regulator (CsrA), and nitrogen regulatory protein P-II 1 (GlnB), contributed by the peptidoglycan pathway, bacterial secretion systems and two-component systems, were also found to be present in a wide range of other disease-causing bacteria. Cytoplasmic proteins SecG, CsrA and GlnB were considered as drug targets, while membrane proteins MviN and SecB were classified as vaccine targets. The identified broad-spectrum targets can aid in the design and development of antibacterial agents not only against food and waterborne pathogens but also against other pathogens.

Genome subtraction for the identification of potential antimicrobial targets in Xanthomonas oryzae pv. oryzae PXO99A pathogenic to rice

In pathogenic bacteria, identification of essential proteins which are non-homologous to the host plants represents potential antimicrobial targets. We applied subtractive genomics approach for the identification of novel antimicrobial targets in Xanthomonas oryzae pv. oryzae PXO99A, the causative agent of bacterial blight in rice. Comparative analysis was performed through BLAST available with the NCBI. The analysis revealed that 27 essential protein sequences out of 4,988 sequences of X. oryzae pv. oryzae PXO99A are non-homologous to Oryza sativa. Subsequent analysis of 27 essential proteins revealed their involvement in different metabolic activities such as transport activity, DNA binding, structural constituent of ribosome, cell division, translation, and plasma membrane. These 27 proteins were analyzed for virulence and novelty and out of 27, three essential non-homologous proteins were found to be the novel antimicrobial targets.

CEG: a database of essential gene clusters

Background

Essential genes are indispensable for the survival of living entities. They are the cornerstones of synthetic biology, and are potential candidate targets for antimicrobial and vaccine design.

Description

Here we describe the Cluster of Essential Genes (CEG) database, which contains clusters of orthologous essential genes. Based on the size of a cluster, users can easily decide whether an essential gene is conserved in multiple bacterial species or is species-specific. It contains the similarity value of every essential gene cluster against human proteins or genes. The CEG_Match tool is based on the CEG database, and was developed for prediction of essential genes according to function. The database is available at http://cefg.uestc.edu.cn/ceg.

Conclusions

Properties contained in the CEG database, such as cluster size, and the similarity of essential gene clusters against human proteins or genes, are very important for evolutionary research and drug design. An advantage of CEG is that it clusters essential genes based on function, and therefore decreases false positive results when predicting essential genes in comparison with using the similarity alignment method.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-769) contains supplementary material, which is available to authorized users.

In silico characterization of putative drug targets in Staphylococcus saprophyticus, causing bovine mastitis

The bovine mastitis caused by coagulase negative staphylococci (CNS) has increased in many herds of urban and rural areas of India. Emergence of multi drug resistant bacteria has further made its management more complex and serious. Therefore, innovation of novel specific drug for the treatment of disease caused by particular organism remained to be a challenge. Hence, in the present study a bacterium was isolated from milk of the cow with bovine mastitis and was identified as S. saprophyticus, 44 pathways of S. saprophyticus retrieved (KEGG) from web server were found to be non homologous to the host Bos taurus, out of which 39 pathways were found to be in cytoplasm, 2 in cell wall and 3 in the cell membrane. The knowledge of the present study could make the drug discovery easier which have high affinity to the target site of the causative organism.

Para-(benzoyl)-phenylalanine as a potential inhibitor against LpxC of Leptospira spp.: homology modeling, docking, and molecular dynamics study

Leptospira interrogans, a Gram-negative bacterial pathogen is the main cause of human leptospirosis. Lipid A is a highly immunoreactive endotoxic center of lipopolysaccharide (LPS) that anchors LPS into the outer membrane of Leptospira. Discovery of compounds inhibiting lipid-A biosynthetic pathway would be promising for dissolving the structural integrity of membrane leading to cell lysis and death of Leptospira. LpxC, a unique enzyme of lipid-A biosynthetic pathway was identified as common drug target of Leptospira. Herein, homology modeling, docking, and molecular dynamics (MD) simulations were employed to discover potential inhibitors of LpxC. A reliable tertiary structure of LpxC in complex with inhibitor BB-78485 was constructed in Modeller 9v8. A data-set of BB-78485 structural analogs were docked with LpxC in Maestro v9.2 virtual screening workflow, which implements three stage Glide docking protocol. Twelve lead molecules with better XP Gscore compared to BB-78485 were proposed as potential inhibitors of LpxC. Para-(benzoyl)-phenylalanine - that showed lowest XP Gscore (-10.35 kcal/mol) - was predicted to have best binding affinity towards LpxC. MD simulations were performed for LpxC and para-(benzoyl)-phenylalanine docking complex in Desmond v3.0. Trajectory analysis showed the docking complex and inter-molecular interactions was stable throughout the entire production part of MD simulations. The results indicate para-(benzoyl)-phenylalanine as a potent drug molecule against leptospirosis. An animated Interactive 3D Complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:10.

Comparative genomics analysis of Mycobacterium ulcerans for the identification of putative essential genes and therapeutic candidates

Mycobacterium ulcerans, the causative agent of Buruli ulcer, is the third most common mycobacterial disease after tuberculosis and leprosy. The present treatment options are limited and emergence of treatment resistant isolates represents a serious concern and a need for better therapeutics. Conventional drug discovery methods are time consuming and labor-intensive. Unfortunately, the slow growing nature of M. ulcerans in experimental conditions is also a barrier for drug discovery and development. In contrast, recent advancements in complete genome sequencing, in combination with cheminformatics and computational biology, represent an attractive alternative approach for the identification of therapeutic candidates worthy of experimental research. A computational, comparative genomics workflow was defined for the identification of novel therapeutic candidates against M. ulcerans, with the aim that a selected target should be essential to the pathogen, and have no homology in the human host. Initially, a total of 424 genes were predicted as essential from the M. ulcerans genome, via homology searching of essential genome content from 20 different bacteria. Metabolic pathway analysis showed that the most essential genes are associated with carbohydrate and amino acid metabolism. Among these, 236 proteins were identified as non-host and essential, and could serve as potential drug and vaccine candidates. Several drug target prioritization parameters including druggability were also calculated. Enzymes from several pathways are discussed as potential drug targets, including those from cell wall synthesis, thiamine biosynthesis, protein biosynthesis, and histidine biosynthesis. It is expected that our data will facilitate selection of M. ulcerans proteins for successful entry into drug design pipelines.

Subtractive genomics approach to identify putative drug targets and identification of drug-like molecules for beta subunit of DNA polymerase III in Streptococcus species

The prolonged use of the antibiotics over the years has transformed many organisms resistant to multiple drugs. This has made the field of drug discovery of vital importance in curing various infections and diseases. The drugs act by binding to a specific target protein of prime importance for the cell's survival. Streptococcus agalactiae, Streptococcus pneumoniae, and Streptococcus pyogenes are the few gram positive organisms that have developed resistance to drugs. It causes pneumonia, meningitis, pharyngitis, otitis media, sinusitis, bacteremia, pericarditis, and arthritis infections. The present study was carried out to identify potential drug targets and inhibitors for beta subunit of DNA polymerase III in these three Streptococcus species that might facilitate the discovery of novel drugs in near future. Various steps were adopted to find out novel drug targets. And finally 3D structure of DNA polymerase III subunit beta was modeled. The ligand library was generated from various databases to find the most suitable ligands. All the ligands were docked using Molegro Virtual Docker and the lead molecules were investigated for ADME and toxicity.