Bridging drug discovery through hierarchical subtractive genomics against asd, trpG, and secY of pneumonia causing MDR Staphylococcus aureus.

Staphylococcus aureus (S. aureus) is an opportunistic gram-positive, non-motile, and non-sporulating bacteria that induces pneumonia, a provocative lung infection affecting mainly the terminal bronchioles and the small air sacs known as alveoli. Recently, it has developed antibiotic resistance to the available consortium as per the WHO reports; thereby, novel remedial targets and resilient medications to forestall and cure this illness are desperately needed. Here, using pan-genomics, a total of 1,387 core proteins were identified. Subtractive proteome analyses further identified 12 proteins that are vital for bacteria. One membrane protein (secY) and two cytoplasmic proteins (asd and trpG) were chosen as possible therapeutic targets concerning minimum % host identity, essentiality, and other cutoff values, such as high resistance in the MDR S. aureus. The UniProt AA sequences of the selected targets were modelled and docked against 3 drug-like chemical libraries. The top-ranked compounds i.e., ZINC82049692, ZINC85492658 and 3a of Isosteviol derivative for Aspartate-semialdehyde dehydrogenase (asd); ZINC38222743, ZINC70455378, and 5 m Isosteviol derivative for Anthranilate synthase component II (trpG); and finally, ZINC72292296, ZINC85632684, and 7 m Isosteviol derivative for Protein translocase subunit secY (secY), were further subjected to molecular dynamics studies for thermodynamic stability and energy calculation. Our study proposes new therapeutic targets in S. aureus, some of which have previously been reported in other pathogenic microorganisms. Owing to further experimental validation, we anticipate that the adapted methodology and the predicted results in this work could make major contributions towards novel drug discovery and their targets in S. aureus caused pneumonia.

Screening inhibitors against the Ef-Tu of Fusobacterium nucleatum: a docking, ADMET and PBPK assessment study.

The oral pathogen Fusobacterium nucleatum has recently been associated with an elevated risk of colorectal cancer (CRC), endometrial metastasis, chemoresistance, inflammation, metastasis, and DNA damage, along with several other diseases. This study aimed to explore the disruption of protein machinery of F. nucleatum via inhibition of elongation factor thermo unstable (Ef-Tu) protein, through natural products. No study on Ef-Tu inhibition by natural products or in Fusobacterium spp. exists till todate. Ef-Tu is an abundant specialized drug target in bacteria that varies from human Ef-Tu. Elfamycins target Ef-Tu and hence, Enacyloxin IIa was used to generate pharmacophore for virtual screening of three natural product libraries, Natural Product Activity and Species Source (NPASS) (n = 30000 molecules), Tibetan medicinal plant database (n = 54 molecules) and African medicinal plant database (n > 6000 molecules). Peptaibol Septocylindrin B (NPC141050), Hirtusneanoside, and ZINC95486259 were prioritized from these libraries as potential therapeutic candidates. ADMET profiling was done for safety assessment, physiological-based pharmacokinetic modeling in human and mouse for getting insight into drug interaction with body tissues and molecular dynamics was used to assess stability of the best hit NPC141050 (Septocylindrin B). Based on the promising results, we propose further in vitro, in vivo and pharmacokinetic testing on the lead Septocylindrin B, for possible translation into therapeutic interventions.

Exploring and targeting potential druggable antimicrobial resistance targets ArgS, SecY, and MurA in Staphylococcus sciuri with TCM inhibitors through a subtractive genomics strategy.

Staphylococcus sciuri (also currently Mammaliicoccus sciuri) are anaerobic facultative and non-motile bacteria that cause significant human pathogenesis such as endocarditis, wound infections, peritonitis, UTI, and septic shock. Methicillin-resistant S. sciuri (MRSS) strains also infects animals that include healthy broilers, cattle, dogs, and pigs. The emergence of MRSS strains thereby poses a serious health threat and thrives the scientific community towards novel treatment options. Herein, we investigated the druggable genome of S. sciuri by employing subtractive genomics that resulted in seven genes/proteins where only three of them were predicted as final targets. Further mining the literature showed that the ArgS (WP_058610923), SecY (WP_058611897), and MurA (WP_058612677) are involved in the multi-drug resistance phenomenon. After constructing and verifying the 3D protein homology models, a screening process was carried out using a library of Traditional Chinese Medicine compounds (consisting of 36,043 compounds). The molecular docking and simulation studies revealed the physicochemical stability parameters of the docked TCM inhibitors in the druggable cavities of each protein target by identifying their druggability potential and maximum hydrogen bonding interactions. The simulated receptor-ligand complexes showed the conformational changes and stability index of the secondary structure elements. The root mean square deviation (RMSD) graph showed fluctuations due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points where the pattern of the RMSD and root mean square fluctuation (RMSF) (< 1.0 Å) support any major domain shifts within the structural framework of the protein-ligand complex and placement of ligand was well complemented within the binding site. The ß-factor values demonstrated instability at few points while the radius of gyration for structural compactness as a time function for the 100-ns simulation of protein-ligand complexes showed favorable average values and denoted the stability of all complexes. It is assumed that such findings might facilitate researchers to robustly discover and develop effective therapeutics against S. sciuri alongside other enteric infections.

Genomic landscape of the emerging XDR Salmonella Typhi for mining druggable targets clpP, hisH, folP and gpmI and screening of novel TCM inhibitors, molecular docking and simulation analyses.

Typhoid fever is transmitted by ingestion of polluted water, contaminated food, and stool of typhoid-infected individuals, mostly in developing countries with poor hygienic environments. To find novel therapeutic targets and inhibitors, We employed a subtractive genomics strategy towards Salmonella Typhi and the complete genomes of eight strains were primarily subjected to the EDGAR tool to predict the core genome (n = 3207). Human non-homology (n = 2450) was followed by essential genes identification (n = 37). The STRING database predicted maximum protein-protein interactions, followed by cellular localization. The virulent/immunogenic ability of predicted genes were checked to differentiate drug and vaccine targets. Furthermore, the 3D models of the identified putative proteins encoded by the respective genes were constructed and subjected to druggability analyses where only "highly druggable" proteins were selected for molecular docking and simulation analyses. The putative targets ATP-dependent CLP protease proteolytic subunit, Imidazole glycerol phosphate synthase hisH, 7,8-dihydropteroate synthase folP and 2,3-bisphosphoglycerate-independent phosphoglycerate mutase gpmI were screened against a drug-like library (n = 12,000) and top hits were selected based on H-bonds, RMSD and energy scores. Finally, the ADMET properties for novel inhibitors ZINC19340748, ZINC09319798, ZINC00494142, ZINC32918650 were optimized followed by binding free energy (MM/PBSA) calculation for ligand-receptor complexes. The findings of this work are expected to aid in expediting the identification of novel protein targets and inhibitors in combating typhoid Salmonellosis, in addition to the already existing therapies.

Leveraging molecular docking to understand Congo red degradation by Staphylococcus caprae MB400.

Congo red (CR) is a genotoxic, sulphonated azo dye and poses significant pollution problem. We hereby report its degradation by Staphylococcus caprae MB400. The bacterium initially propagated as a suspected contaminant upon CR dye supplemented nutrient agar plates, forming zones of clearance around its growth area. The bacterium was purified, gram stained and identified as Staphylococcus caprae via 16S rRNA gene sequencing. Dye decolourization was analysed in liquid culture, and Fourier-transform infrared spectroscopy (FTIR) was conducted for analysis of degraded product/metabolites. A decolourization of ~ 96.0% at 100 µg/ml concentration and pH 7 after 24 h of incubation was observed. Structure of the azoreductase enzyme, responsible for breakage of the bond in the dye and ultimately decolourization, was predicted, and molecular docking was harnessed for understanding the mechanism behind the reduction of azo bond (-N=N-) and conversion to metabolites. Our analysis revealed 12 residues critical for structural interaction of the azoreductase enzyme with this dye. Among these, protein backbone region surrounding four residues, i.e. Lys65, Phe122, Ile166 and Phe169, showed major displacement changes, upon binding with the dye. However, overall the conformational changes were not large.

Therapeutic target mapping from the genome of Kingella negevensis and biophysical inhibition assessment through PNP synthase binding with traditional medicinal compounds.

Kingella negevensis belongs to the Neisseriaceae family. It is implied that it has significant virulence potential due to RTX toxin production, which can cause hemolysis. It usually colonizes the orophayrynx of pediatric population, along with Kingella kingae but has also been isolated from vagina. Todate no report on its drug targets is present, therefore putative therapeutic targets were identified from its genomic sequence data. Traditional Chinese (n > 36,000) and Indian medicinal compounds (n > 2000) were then screened against its pyridoxine 5'-phosphate synthase, a vital therapeutic target. Prioritized TCM compounds included ZINC02525131, ZINC33833737 and ZINC85486932, and Cadiyenol, 9,11,13-Octadecatrienoic acid and 6-Gingerol from Indian medicinal library. Molecular dynamics simulation of top compounds revealed ZINC02525131 as having best stability for 100 ns, compared to Cadiyenol. ADMET profiling was then done, along with physiologically based pharmacokinetic simulation of these compounds in a population of 200 individuals, for 12 h to see fate of the ingested compound. Additionally, the impact of these compounds in a population with cirrhosis and renal impairment was also simulated. We imply in light of all the studied parameters of safety and bioavailability, etc., that 6-Gingerol from Zingiber officinalis rhizome must be proceeded further for in vitro and in vivo testing for inhibition of K. negevensis.

Subtractive sequence analysis aided druggable targets mining in Burkholderia cepacia complex and finding inhibitors through bioinformatics approach.

Burkholderia cepacia complex (BCC) is a group of gram-negative bacteria composed of at least 20 different species that cause diseases in plants, animals as well as humans (cystic fibrosis and airway infection). Here, we analyzed the proteomic data of 47 BCC strains by classifying them in three groups. Phylogenetic analyses were performed followed by individual core region identification for each group. Comparative analysis of the three individual core protein fractions resulted in 1766 ortholog/proteins. Non-human homologous proteins from the core region gave 1680 proteins. Essential protein analyses reduced the target list to 37 proteins, which were further compared to a closely related out-group, Burkholderia gladioli ATCC 10,248 strain, resulting in 21 proteins. 3D structure modeling, validation, and druggability step gave six targets that were subjected to further target prioritization parameters which ultimately resulted in two BCC targets. A library of 12,000 ZINC drug-like compounds was screened, where only the top hits were selected for docking orientations. These included ZINC01405842 (against Chorismate synthase aroC) and ZINC06055530 (against Bifunctional N-acetylglucosamine-1-phosphate uridyltransferase/Glucosamine-1-phosphate acetyltransferase glmU). Finally, dynamics simulation (200 ns) was performed for each ligand-receptor complex, followed by ADMET profiling. Of these targets, details of their applicability as drug targets have not yet been elucidated experimentally, hence making our predictions novel and it is suggested that further wet-lab experimentations should be conducted to test the identified BCC targets and ZINC scaffolds to inhibit them.

Mining therapeutic targets from the antibiotic-resistant Campylobacter coli and virtual screening of natural product inhibitors against its riboflavin synthase.

Campylobacter coli resides in the intestine of several commonly consumed animals, as well as water and soil. It leads to campylobacteriosis when humans eat raw/undercooked meat or come into contact with infected animals. A common manifestation of the infection is fever, nausea, headache, and diarrhea. Increasing antibiotic resistance is being observed in this pathogen. The increased incidence of C. coli infection, and post-infection complications like Guillain-Barré syndrome, make it an important pathogen. It is essential to find novel therapeutic targets and drugs against it, especially with the emergence of antibiotic-resistant strains. In the current study, genomes of 89 antibiotic-resistant strains of C. coli were downloaded from the PATRIC database. Potent drug targets (n = 36) were prioritized from the core genome (n = 1,337 genes) of this species. Riboflavin synthase was selected as a drug target and pharmacophore-based virtual screening was performed to predict its inhibitors from the NPASS (n = ~ 30,000 compounds) natural product library. The top three docked compounds (NPC115144, NPC307895, and NPC470462) were selected for dynamics simulation (for 50 ns) and ADMET profiling. These identified compounds appear safe for targeting this pathogen and can be further validated by experimental analysis before clinical trials.

Identification of Disalicyloyl Curcumin as a Potential DNA Polymerase Inhibitor for Marek's Disease Herpesvirus: A Computational Study Using Virtual Screening and Molecular Dynamics Simulations.

Marek's disease virus (MDV) is a highly contagious and persistent virus that causes T-lymphoma in chickens, posing a significant threat to the poultry industry despite the availability of vaccines. The emergence of new virulent strains has further intensified the challenge of designing effective antiviral drugs for MDV. In this study, our main objective was to identify novel antiviral phytochemicals through in silico analysis. We employed Alphafold to construct a three-dimensional (3D) structure of the MDV DNA polymerase, a crucial enzyme involved in viral replication. To ensure the accuracy of the structural model, we validated it using tools available at the SAVES server. Subsequently, a diverse dataset containing thousands of compounds, primarily derived from plant sources, was subjected to molecular docking with the MDV DNA polymerase model, utilizing AutoDock software V 4.2. Through comprehensive analysis of the docking results, we identified Disalicyloyl curcumin as a promising drug candidate that exhibited remarkable binding affinity, with a minimum energy of -12.66 Kcal/mol, specifically targeting the DNA polymerase enzyme. To further assess its potential, we performed molecular dynamics simulations, which confirmed the stability of Disalicyloyl curcumin within the MDV system. Experimental validation of its inhibitory activity in vitro can provide substantial support for its effectiveness. The outcomes of our study hold significant implications for the poultry industry, as the discovery of efficient antiviral phytochemicals against MDV could substantially mitigate the economic losses associated with this devastating disease.

Pan-genomics, drug candidate mining and ADMET profiling of natural product inhibitors screened against Yersinia pseudotuberculosis.

Yersinia pseudotuberculosis belongs to the family Enterobacteriaceae and is responsible for scarlatinoid fever, food poisoning, post-infectious complications like erythema nodosum/reactive arthritis as well as pseudoappendicitis in children. Genome sequences of the 23 whole genomes from NCBI were utilized for conducting the pan-genomic analysis. Essential proteins from the core region were obtained and drug targets were identified using a hierarchal in silico approach. Among these, multidrug resistance protein sub-unit mdtC was chosen for further analysis. This protein unit confers resistance to antibiotics upon forming a tripartite complex with units A and B in Escherichia coli. Details of the function have not yet been elucidated experimentally in Yersinia spp. Computational structure modeling and validation were followed by screening against phytochemical libraries of traditional Indian (Ayurveda), North African, and traditional Chinese flora using Molecular Operating Environment software version 2019.0102. ADMET profiling and descriptor study of best docked compounds was studied. Since phytotherapy is the best resort to antibiotic resistance so these compounds should be tested experimentally to further validate the results. The obtained information could aid wet-lab scientists to work on the scaffold of screened drug-like compounds from natural resources. This could be useful in our quest for antibiotic-resistant therapy against Y. pseudotuberculosis.

Crystal Structure of an SSB Protein from Salmonella enterica and Its Inhibition by Flavanonol Taxifolin.

Single-stranded DNA (ssDNA)-binding proteins (SSBs) play a central role in cells by participating in DNA metabolism, including replication, repair, recombination, and replication fork restart. SSBs are essential for cell survival and thus an attractive target for potential anti-pathogen chemotherapy. In this study, we determined the crystal structure and examined the size of the ssDNA-binding site of an SSB from Salmonella enterica serovar Typhimurium LT2 (SeSSB), a ubiquitous opportunistic pathogen which is highly resistant to antibiotics. The crystal structure was solved at a resolution of 2.8 Å (PDB ID 7F25), indicating that the SeSSB monomer possesses an oligonucleotide/oligosaccharide-binding (OB) fold domain at its N-terminus and a flexible tail at its C-terminus. The core of the OB-fold in the SeSSB is made of a six-stranded ß-barrel capped by an α-helix. The crystal structure of the SeSSB contained two monomers per asymmetric unit, which may indicate the formation of a dimer. However, the gel-filtration chromatography analysis showed that the SeSSB forms a tetramer in solution. Through an electrophoretic mobility shift analysis, we characterized the stoichiometry of the SeSSB complexed with a series of ssDNA dA homopolymers, and the size of the ssDNA-binding site was determined to be around 22 nt. We also found the flavanonol taxifolin, also known as dihydroquercetin, capable of inhibiting the ssDNA-binding activity of the SeSSB. Thus, this result extended the SSB interactome to include taxifolin, a natural product with a wide range of promising pharmacological activities.

Comprehensive comparative genomic and microsatellite analysis of SARS, MERS, BAT-SARS, and COVID-19 coronaviruses.

The coronavirus disease 2019 (COVID-19) pandemic has spread around the globe very rapidly. Previously, the evolution pattern and similarity among the COVID-19 causative organism severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and causative organisms of other similar infections have been determined using a single type of genetic marker in different studies. Herein, the SARS-CoV-2 and related ß coronaviruses Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV,  bat coronavirus (BAT-CoV) were comprehensively analyzed using a custom-built pipeline that employed phylogenetic approaches based on multiple types of genetic markers including the whole genome sequences, mutations in nucleotide sequences, mutations in protein sequences, and microsatellites. The whole-genome sequence-based phylogeny revealed that the strains of SARS-CoV-2 are more similar to the BAT-CoV strains. The mutational analysis showed that on average MERS-CoV and BAT-CoV genomes differed at 134.21 and 136.72 sites, respectively, whereas the SARS-CoV genome differed at 26.64 sites from the reference genome of SARS-CoV-2. Furthermore, the microsatellite analysis highlighted a relatively higher number of average microsatellites for MERS-CoV and SARS-CoV-2 (106.8 and 107, respectively), and a lower number for SARS-CoV and BAT-CoV (95.8 and 98.5, respectively). Collectively, the analysis of multiple genetic markers of selected ß viral genomes revealed that the newly born SARS-COV-2 is closely related to BAT-CoV, whereas, MERS-CoV is more distinct from the SARS-CoV-2 than BAT-CoV and SARS-CoV.

An Overview of Algorithms and Associated Applications for Single Cell RNA-Seq Data Imputation.

Single cell RNA-Seq technology enables the assessment of RNA expression in individual cells. This makes it popular in experimental biology for gleaning specifications of novel cell types as well as inferring heterogeneity. Experimental data conventionally contains zero counts or dropout events for many single cell transcripts. Such missing data hampers the accurate analysis using standard workflows, designed for massive RNA-Seq datasets. Imputation for single cell datasets is done to infer the missing values. This was traditionally done with ad-hoc code but later customized pipelines, workflows and specialized software appeared for this purpose. This made it easy to benchmark and cluster things in an organized manner. In this review, we have assembled a catalog of available RNA-Seq single cell imputation algorithms/workflows and associated softwares for the scientific community performing single-cell RNA-Seq data analysis. Continued development of imputation methods, especially using deep learning approaches, would be necessary for eradicating associated pitfalls and addressing challenges associated with future large scale and heterogeneous datasets.

Pan-Genome Reverse Vaccinology Approach for the Design of Multi-Epitope Vaccine Construct against Escherichia albertii.

Escherichia albertii is characterized as an emerging pathogen, causing enteric infections. It is responsible for high mortality rate, especially in children, elderly, and immunocompromised people. To the best of our knowledge, no vaccine exists to curb this pathogen. Therefore, in current study, we aimed to identify potential vaccine candidates and design chimeric vaccine models against Escherichia albertii from the analysis of publicly available data of 95 strains, using a reverse vaccinology approach. Outer-membrane proteins (n = 4) were identified from core genome as vaccine candidates. Eventually, outer membrane Fimbrial usher (FimD) protein was selected as a promiscuous vaccine candidate and utilized to construct a potential vaccine model. It resulted in three epitopes, leading to the design of twelve vaccine constructs. Amongst these, V6 construct was found to be highly immunogenic, non-toxic, non-allergenic, antigenic, and most stable. This was utilized for molecular docking and simulation studies against six HLA and two TLR complexes. This construct can therefore be used for pan-therapy against different strains of E. albertii and needs to be tested in vitro and in vivo.

Virtual Screening of Natural Products against Type II Transmembrane Serine Protease (TMPRSS2), the Priming Agent of Coronavirus 2 (SARS-CoV-2).

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused about 2 million infections and is responsible for more than 100,000 deaths worldwide. To date, there is no specific drug registered to combat the disease it causes, named coronavirus disease 2019 (COVID-19). In the current study, we used an in silico approach to screen natural compounds to find potent inhibitors of the host enzyme transmembrane protease serine 2 (TMPRSS2). This enzyme facilitates viral particle entry into host cells, and its inhibition blocks virus fusion with angiotensin-converting enzyme 2 (ACE2). This, in turn, restricts SARS-CoV-2 pathogenesis. A three-dimensional structure of TMPRSS2 was built using SWISS-MODEL and validated by RAMPAGE. The natural compounds library Natural Product Activity and Species Source (NPASS), containing 30,927 compounds, was screened against the target protein. Two techniques were used in the Molecular Operating Environment (MOE) for this purpose, i.e., a ligand-based pharmacophore approach and a molecular docking-based screening. In total, 2140 compounds with pharmacophoric features were retained using the first approach. Using the second approach, 85 compounds with molecular docking comparable to or greater than that of the standard inhibitor (camostat mesylate) were identified. The top 12 compounds with the most favorable structural features were studied for physicochemical and ADMET (absorption, distribution, metabolism, excretion, toxicity) properties. The low-molecular-weight compound NPC306344 showed significant interaction with the active site residues of TMPRSS2, with a binding energy score of -14.69. Further in vitro and in vivo validation is needed to study and develop an anti-COVID-19 drug based on the structures of the most promising compounds identified in this study.

Genome of Serratia nematodiphila MB307 offers unique insights into its diverse traits.

A pigment-producing species of Serratia was isolated from the rhizosphere of a heavy metal resistant Cannabis sativa plant growing in effluent-affected soil of Hattar Industrial Estate, Haripur, Pakistan. Here, we report the genome sequence of this bacterium, which has been identified as Serratia nematodiphila on the basis of whole genome comparison using the OrthoANI classification scheme. The bacterium exhibited diverse traits, including plant growth promotion, antimicrobial, bioremediation, and pollutant tolerance capabilities including metal tolerance, azo dye degradation, ibuprofen degradation, etc. Plant growth-promoting exoenzyme production as well as phosphate solubilisation properties were observed. Genes for phosphate solubilisation, siderophore production, and chitin destruction were identified in addition to other industrially important enzymes like nitrilase and lipase. Secondary metabolite producing apparatus for high value chemicals in the whole genome was also analysed. The number of antibiotic resistance genes was then profiled in silico, through a match with Antibiotic Resistant Gene and CAR database. This is the first report of a S. nematodiphila genome from a polluted environment. This could significantly contribute to the understanding of pollution tolerance, antibiotic resistance, association with nematodes, production of bio-pesticide, and their role in plant growth promotion.

Prediction of post translation modifications at the contact site between Anaplasma phagocytophilum and human host during autophagosome induction using a bioinformatic approach.

Autophagy is crucial for maintaining physiological homeostasis, but its role in infectious diseases is not yet adequately understood. The binding of Anaplasma translocated substrate-1 (ATS1) to the human Beclin1 (BECN1) protein is responsible for the modulation of autophagy pathway. ATS1-BECN1 is a novel type of interaction that facilitates Anaplasma phagocytophilum proliferation, leading to intracellular infection via autophagosome induction and segregation from the lysosome. Currently, there is no report of post translational modifications (PTMs) of BECN1 or cross-talk required for ATS-BECN1 complex formation. Prediction/modeling of the cross-talk between phosphorylation and other PTMs (O-ß-glycosylation, sumoylation, methylation and palmitoylation) has been attempted in this study, which might be responsible for regulating function after the interaction of ATS1 with BECN1. PTMs were predicted computationally and mapped onto the interface of the docked ATS1-BECN1 complex. Results show that BECN1 phosphorylation at five residues (Thr91, Ser93, Ser96, Thr141 and Ser234), the interplay with O-ß-glycosylation at three sites (Thr91, Ser93 and Ser96) with ATS1 may be crucial for attachment and, hence, infection. No other PTM site at the BECN1 interface was predicted to associate with ATS1. These findings may have significant clinical implications for understanding the etiology of Anaplasma infection and for therapeutic studies.

Survey of compound microsatellites in multiple Lactobacillus genomes.

Distinct simple sequence repeats with 2 or more individual microsatellites joined together or lying adjacent to each other are identified as compound microsatellites. Investigation of such composite microsatellites in the genomes of genus Lactobacillus was the aim of this study. In silico inspection of microsatellite clustering in genomes of 14 Lactobacillus species revealed a wealth of compound microsatellites. All of the mined compound microsatellites were imperfect, were composed of variant motifs, and increased in all genomes, with maximum distance (dMAX) increments of 10 to 50. The majority of these repeats were present in the coding regions. A correlation of microsatellite to compound microsatellite density was detected. The difference established in compound microsatellite division among eukaryotes, Escherichia coli, and lactobacilli is suggestive of diverse genomic features and elementary distinction between creation and fixation methods of compound microsatellites among these organisms.

Pan-genome mediated therapeutic target mining in Kingella kingae and inhibition assessment using traditional Chinese medicinal compounds: an informatics approach.

Kingella kingae causes bacteremia, endocarditis, osteomyelitis, septic arthritis, meningitis, spondylodiscitis, and lower respiratory tract infections in pediatric patients. Usually it demonstrates disease after inflammation of mouth, lips or infections of the upper respiratory tract. To date, therapeutic targets in this bacterium remain unexplored. We have utilized a battery of bioinformatics tools to mine these targets in this study. Core genes were initially inferred from 55 genomes of K. kingae and 39 therapeutic targets were mined using an in-house pipeline. We selected aroG product (KDPG aldolase) involved in chorismate pathway, for inhibition analysis of this bacterium using lead-like metabolites from traditional Chinese medicinal plants. Pharmacophore generation was done using control ZINC36444158 (1,16-bis[(dihydroxyphosphinyl)oxy]hexadecane), followed by molecular docking of top hits from a library of 36,000 compounds. Top prioritized compounds were ZINC95914016, ZINC33833283 and ZINC95914219. ADME profiling and simulation of compound dosing (100 mg tablet) was done to infer compartmental pharmacokinetics in a population of 300 individuals in fasting state. PkCSM based toxicity analysis revealed the compounds ZINC95914016 and ZINC95914219 as safe and with almost similar bioavailability. However, ZINC95914016 takes less time to reach maximum concentration in the plasma and shows several optimal parameters compared to other leads. In light of obtained data, we recommend this compound for further testing and induction in experimental drug design pipeline.Communicated by Ramaswamy H. Sarma.

Computational approach for drug discovery against Gardnerella vaginalis in quest for safer and effective treatments for bacterial vaginosis.

Bacterial vaginosis (BV), primarily attributed to Gardnerella vaginalis, poses significant challenges due to antibiotic resistance and suboptimal treatment outcomes. This study presents an integrated approach to identify potential drug targets and screen compounds against this bacterium by leveraging a computational methodology. Subtractive proteomics of the reference strain ASM286196v1/UMB0386 (assembly accession: GCA_002861965.1) facilitated the prioritization of proteins with essential bacterial functions and pathways as potential drug targets. We selected 3-deoxy-7-phosphoheptulonate synthase (aroG gene product; also known as DAHP synthase) for downstream analysis. Molecular docking was employed in PyRx (AutoDock Vina) to predict binding affinities between aroG inhibitors from the ZINC database and 3-deoxy-7-phosphoheptulonate synthase. Molecular dynamics simulations of 100 ns, using GROMACS, validated the stability of drug-target interactions. Additionally, ADMET profiling aided in the selection of compounds with favorable pharmacokinetic properties and safety profile for human hosts. PBPK profiling showed that ZINC98088375 had the highest bioavailability and efficient systemic circulation. Conversely, ZINC5113880 demonstrated the lowest absorption rate (39.661%). Moreover, cirrhosis, steatosis, and renal impairment appeared to influence blood concentration of the drug, impacting bioavailability. The integrative -omics approach utilized in this study underscores the potential of computer-aided drug design and offers a rational strategy for targeted inhibitor discovery against G. vaginalis. The strategy is an attempt to address the limitations of current BV treatments, including antibiotic resistance, and pave way for the development of safer and more effective therapeutics.