Identification of therapeutic drug target of Shigella Flexneri serotype X through subtractive genomic approach and in-silico screening based on drug repurposing.

Shigellosis, induced by Shigella flexneri, constitutes a significant health burden in developing nations, particularly impacting socioeconomically disadvantaged communities. Designated as the second most prevalent cause of diarrheal illness by the World Health Organization (WHO), it precipitates an estimated 212,000 fatalities annually. Within the spectrum of S. flexneri strains, serotype X is notably pervasive and resilient, yet its comprehensive characterization remains deficient. The present investigation endeavors to discern potential pharmacological targets and repurpose existing drug compounds against S. flexneri serotype X. Employing the framework of subtractive genomics, the study interrogates the reference genome of S. flexneri Serotype X (strain 2,002,017; UP000001884) to delineate its proteome into categories of non-homologous, non-paralogous, essential, virulent, and resistant constituents, thereby facilitating the identification of therapeutic targets. Subsequently, a screening of approximately 9000 compounds from the FDA library against the identified drug target aims to delineate efficacious agents for combating S. flexneri serotype X infections. The application of subtractive genomics methodology yields prognostic insights, unveiling non-paralogous proteins (n = 4122), non-homologues (n = 1803), essential (n = 1246), drug-like (n = 389), resistant (n = 167), alongside 42 virulent proteins within the reference proteome. This iterative process culminates in the identification of Serine O-acetyltransferase as a viable drug target. Subsequent virtual screening endeavors to unearth FDA-approved medicinal compounds capable of inhibiting Serine O-acetyltransferase. Noteworthy candidates such as DB12983, DB15085, DB16098, DB16185, and DB16262 emerge, exhibiting potential for mitigating S. flexneri Serotype X. Despite the auspicious findings, diligent scrutiny is imperative to ascertain the efficacy and safety profile of the proposed drug candidates vis-à-vis S. flexneri.

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.

Pharmacokinetics and drug-likeness of anti-cancer traditional Chinese medicine: molecular docking and molecular dynamics simulation study.

MCM7 (Minichromosome Maintenance Complex Component 7) is a component of the DNA replication licensing factor, which controls DNA replication. The MCM7 protein is linked to tumor cell proliferation and has a function in the development of several human cancers. Several types of cancer may be treated by inhibiting the protein, as it is strongly produced throughout this process. Significantly, Traditional Chinese Medicine (TCM), which has a long history of clinical adjuvant use against cancer, is rapidly gaining traction as a valuable medical resource for the development of novel cancer therapies, including immunotherapy. Therefore, the goal of the research was to find small molecular therapeutic candidates against the MCM7 protein that may be used to treat human cancers. A computational-based virtual screening of 36,000 natural TCM libraries is carried out for this goal using a molecular docking and dynamic simulation technique. Thereby, ∼8 novel potent compounds i.e., ZINC85542762, ZINC95911541, ZINC85542617, ZINC85542646, ZINC85592446, ZINC85568676, ZINC85531303, and ZINC95914464 were successfully shortlisted, each having the capacity to penetrate the cell as potent inhibitors for MCM7 to curb this disorder. These selected compounds were found to have high binding affinities compared to the reference (AGS compound) i.e. < -11.0 kcal/mol. ADMET and pharmacological properties showed that none of these 8 compounds poses any toxic property (carcinogenicity) and have anti-metastatic, and anticancer activity. Additionally, MD simulations were run to assess the compounds' stability and dynamic behavior with the MCM7 complex for about 100 ns. Finally, ZINC95914464, ZINC95911541, ZINC85568676, ZINC85592446, ZINC85531303, and ZINC85542646 are identified as highly stable within the complex throughout the 100 ns simulations. Moreover, the results of binding free energy suggested that the selected virtual hits significantly bind to the MCM7 which implied these compounds may act as a potential MCM7 inhibitor. However, in vitro testing protocols are required to further support these results. Further, assessment through various lab-based trial methods can assist with deciding the action of the compound that will give options in contrast to human cancer immunotherapy.Communicated by Ramaswamy H. Sarma.

Integrating core subtractive proteomics and reverse vaccinology for multi-epitope vaccine design against Rickettsia prowazekii endemic typhus.

Rickettsia prowazekii is an intracellular, obligate, gram-negative coccobacillus responsible for epidemic typhus. Usually, the infected body louse or its excrement when rubbed into the skin abrasions transmits the disease. The infection with R. prowazekii causes the highest death rate (> 20% without antibiotic treatment and now 1-7%), followed by epidemic typhus, which often manifests in unsanitary conditions (up to 15-30%). Conventionally, vaccine design has required pathogen growth and both assays (in vivo and in vitro), which are costly and time-consuming. However, advancements in bioinformatics and computational biology have accelerated the development of effective vaccine designs, reducing the need for traditional, time-consuming laboratory experiments. Subtractive genomics and reverse vaccinology have become prominent computational methods for vaccine model construction. Therefore, the RefSeq sequence of Rickettsia prowazekii (strain Madrid E) (Proteome ID: UP000002480) was subjected to subtractive genomic analysis, including factors such as non-similarity to host proteome, essentiality, subcellular localization, antigenicity, non-allergenicity, and stability. Based on these parameters, the vaccine design process selected specific proteins such as outer membrane protein R (O05971_RICPR PETR; OmpR). Eventually, the OmpR was subjected to a reverse vaccinology approach that included molecular docking, immunological simulation, and the discovery of B-cell epitopes and MHC-I and MHC-II epitopes. Consequently, a chimeric or multi-epitope-based vaccine was proposed by selecting the V11 vaccine and its 3D structure modeling along with molecular docking against TLR and HLA protein, in silico simulation, and vector designing. The obtained results from this investigation resulted in a new perception of inhibitory ways against Rickettsia prowazekii by instigating novel immunogenic targets. To further assess the efficacy and protective ability of the newly designed V11 vaccine against Rickettsia prowazekii infections, additional evaluation such as in vitro or in vivo immunoassays is recommended.

Effect of social influence, environmental awareness, and safety affordance on actual use of 5G technologies among Chinese students.

5G technology continues to evolve, and its potential to revolutionize various aspects of society is becoming increasingly evident. However, the successful adoption and utilization of 5G technology depends on various factors, particularly among consumers expected to be early adopters and critical drivers of technological advancements. This study investigates the effect of social influence, environmental awareness, and safety affordance on Chinese university students' actual use of 5G (AU5G) technologies. It also analyzed the mediating role of trustworthiness and intention to use 5G (ITU5G) between them and the moderating role of facilitation conditions between trustworthiness and ITU5G. Data was collected from university students (n = 364) in Beijing and was examined employing the structural equation modelling (SEM) approach. The outcomes confirm that trustworthiness and ITU5G significantly mediate the relationship between social influence, environmental awareness, and safety affordance on AU5G technologies among Chinese students. Further, the supportive facilitation conditions strengthen the relationship between trustworthiness and ITU5G. These findings are backed by UTAUT2 models that support the technology acceptance and adoption among the users. The study outcomes can help policymakers design strategies to address potential barriers and encourage greater uptake of 5G services among university students.

Pangenome diversification and resistance gene characterization in Salmonella Typhi prioritized RfaJ as a significant therapeutic marker.

BACKGROUND: Salmonella Typhi stands as the etiological agent responsible for the onset of human typhoid fever. The pressing demand for innovative therapeutic targets against S. Typhi is underscored by the escalating prevalence of this pathogen and the severe nature of its infections. Consequently, this study employs pangenome analysis to scrutinize 119 S. Typhi-resistant strains, aiming to identify the most promising therapeutic targets originating from its core genome. RESULTS: Subtractive genomics was employed to systematically eliminate non-homologous (n=1147), essential (n=551), drug-like (n=80), and pathogenicity-related (n=18) proteins from the initial pool of 3351 core genome proteins. Consequently, lipopolysaccharide 1,2-glucosyltransferase RfaJ was designated as the optimal pharmacological target due to its potential versatility. Furthermore, a compendium of 9000 FDA-approved compounds was repurposed for evaluation against the RfaJ drug target, with the specific intent of prioritizing novel, high-potency therapeutic candidates for combating S. Typhi. Ultimately, four compounds, namely DB00549 (Zafirlukast), DB15637 (Fluzoparib), DB15688 (Zavegepant), and DB12411 (Bemcentinib), were singled out as potential inhibitors based on the ligand-protein binding affinity (indicated by the lowest anticipated binding energy) and the overall stability of these compounds. Notably, molecular dynamics simulations, conducted over a 50 nanosecond interval, convincingly demonstrated the stability of these compounds in the context of the RfaJ protein. CONCLUSION: In summary, the present findings hold significant promise as an initial stride in the broader drug discovery endeavor against S. Typhi infections. However, the experimental validation of the identified drug target and drug candidate is further required to increase the effectiveness of the applied methodology.

Lead identification against Mycobacterium tuberculosis using highly enriched active molecules against pantothenate synthetase.

The Pantothenate synthetase (PS) from the Mycobacterium tuberculosis (Mtb) holds a crucial role in the survival and robust proliferation of bacteria through its catalysis of coenzyme A and acyl carrier protein synthesis. The present study undertook the PS drug target in complex with a co-crystallized ligand and subjected it to docking and virtual screening approaches. The experimental design encompassed three discrete datasets: an active dataset featuring 136 compounds, an inactive dataset comprising 56 compounds, and a decoys dataset curated from the zinc library, comprising an extensive compilation of approximately 53,000 compounds. The compounds' binding energies were observed to be in the range of -5 to ∼-14 kcal/mol. Additionally, binding energy results were further refined through Enrichment Factor analysis (EF). EF is a new statistical approach which uses the scores obtained from docking-based virtual screening and predicts the precision of the scoring function. Remarkably, the Enrichment Factor (EF) analysis produced exceptionally favorable outcomes, attaining an EF of approximately 49% within the uppermost 1% fraction of the compound distribution. Finally, a total of eight compounds, evenly distributed between the active dataset and the decoys dataset, emerged as potent inhibitors of the Pantothenate synthetase (PS) enzyme. The analysis of inhibition constants and binding energy revealed a notable correlation, with an r-squared value (r2) of 0.912 between the two parameters. Furthermore, the shortlisted compounds were subjected to 100 ns MD simulation to determine their stability and dynamics behavior. The decoy compounds that have been identified, exhibiting properties comparable to the active compounds, are postulated as potential candidates for targeting the Pantothenate synthetase (PS) enzyme to treat Mtb infection. Nevertheless, in the pursuit of a comprehensive investigation, it is advisable to undertake additional experimental validation as a component of the subsequent study.Communicated by Ramaswamy H. Sarma.

Delineating multi-epitopes vaccine designing from membrane protein CL5 against all monkeypox strains: a pangenome reverse vaccinology approach.

The recently identified monkeypox virus (MPXV or mpox) is a zoonotic orthopox virus that infects humans and causes diseases with traits like smallpox. The world health organization (WHO) estimates that 3-6% of MPXV cases result in death. As it might impact everyone globally, like COVID, and become the next pandemic, the cure for this disease is important for global public health. The high incidence and disease ratio of MPXV necessitates immediate efforts to design a unique vaccine candidate capable of addressing MPXV diseases. Here, we used a computational pan-genome-based vaccine design strategy for all currently reported 19 MPXV strains acquired from different regions of the world. Thus, this study's objective was to develop a new and safe vaccine candidate against MPXV by targeting the membrane CL5 protein; identified after the pangenome analysis. Proteomics and reverse vaccinology have covered up all of the MPXV epitopes that would usually stimulate robust host immune responses. Following this, only two mapped (MHC-I, MHC-II, and B-cell) epitopes were observed to be extremely effective that can be used in the construction of CL5 protein vaccine candidates. The suggested vaccine (V5) candidate from eight vaccine models was shown to be antigenic, non-allergenic, and stable (with 213 amino acids). The vaccine's candidate efficacy was evaluated by using many in silico methods to predict, improve, and validate its 3D structure. Molecular docking and molecular dynamics simulations further reveal that the proposed vaccine candidate ensemble has a high interaction energy with the HLAs and TRL2/4 immunological receptors under study. Later, the vaccine sequence was used to generate an expression vector for the E. coli K12 strain. Further study uncovers that V5 was highly immunogenic because it produced robust primary, secondary, and tertiary immune responses. Eventually, the use of computer-aided vaccine designing may significantly reduce costs and speed up the process of developing vaccines. Although, the results of this research are promising, however, more research (experimental; in vivo, and in vitro studies) is needed to verify the biological efficacy of the proposed vaccine against MPXV.Communicated by Ramaswamy H. Sarma.

The Gene Network Correlation Analysis of Obesity to Type 1 Diabetes and Cardiovascular Disorders: An Interactome-Based Bioinformatics Approach.

The current study focuses on the importance of Protein-Protein Interactions (PPIs) in biological processes and the potential of targeting PPIs as a new treatment strategy for diseases. Specifically, the study explores the cross-links of PPIs network associated with obesity, type 1 diabetes mellitus (T1DM), and cardiac disease (CD), which is an unexplored area of research. The research aimed to understand the role of highly connected proteins in the network and their potential as drug targets. The methodology for this research involves retrieving genes from the NCBI online gene database, intersecting genes among three diseases (type 1 diabetes, obesity, and cardiovascular) using Interactivenn, determining suitable drug molecules using NetworkAnalyst, and performing various bioinformatics analyses such as Generic Protein-Protein Interactions, topological properties analysis, function enrichment analysis in terms of GO, and Kyoto Encyclopedia of Genes and Genomes (KEGG), gene co-expression network, and protein drug as well as protein chemical interaction network. The study focuses on human subjects. The results of this study identified 12 genes [VEGFA (Vascular Endothelial Growth Factor A), IL6 (Interleukin 6), MTHFR (Methylenetetrahydrofolate reductase), NPPB (Natriuretic Peptide B), RAC1 (Rac Family Small GTPase 1), LMNA (Lamin A/C), UGT1A1 (UDP-glucuronosyltransferase family 1 membrane A1), RETN (Resistin), GCG (Glucagon), NPPA (Natriuretic Peptide A), RYR2 (Ryanodine receptor 2), and PRKAG2 (Protein Kinase AMP-Activated Non-Catalytic Subunit Gamma 2)] that were shared across the three diseases and could be used as key proteins for protein-drug/chemical interaction. Additionally, the study provides an in-depth understanding of the complex molecular and biological relationships between the three diseases and the cellular mechanisms that lead to their development. Potentially significant implications for the therapy and management of various disorders are highlighted by the findings of this study by improving treatment efficacy, simplifying treatment regimens, cost-effectiveness, better understanding of the underlying mechanism of these diseases, early diagnosis, and introducing personalized medicine. In conclusion, the current study provides new insights into the cross-links of PPIs network associated with obesity, T1DM, and CD, and highlights the potential of targeting PPIs as a new treatment strategy for these prevalent diseases.

A therapeutic epitopes-based vaccine engineering against Salmonella enterica XDR strains for typhoid fever: a Pan-vaccinomics approach.

A prevalent food-borne pathogen, Salmonella enterica serotypes Typhi, is responsible for gastrointestinal and systemic infections globally. Salmonella vaccines are the most effective, however, producing a broad-spectrum vaccine remains challenging due to Salmonella's many serotypes. Efforts are urgently required to develop a novel vaccine candidate that can tackle all S. Typhi strains because of their high resistance to multiple kinds of antibiotics (particularly the XDR H58 strain). In this work, we used a computational pangenome-based vaccine design technique on all available (n = 119) S. Typhi reference genomes and identified one TonB-dependent siderophore receptor (WP_001034967.1) as highly conserved and prospective vaccine candidates from the predicted core genome (n = 3,351). The applied pan-proteomics and Immunoinformatic approaches help in the identification of four epitopes that may trigger adequate host body immune responses. Furthermore, the proposed vaccine ensemble demonstrates a stable binding conformation with the examined immunological receptor (HLAs and TRL2/4) and has large interaction energy determined via molecular docking and molecular dynamics simulation techniques. Eventually, an expression vector for the Escherichia. coli K12 strain was constructed from the vaccine sequence. Additional analysis revealed that the vaccine may help to elicit strong immune responses for typhoid infections, however, experimental analysis is required to verify the vaccine's effectiveness based on these results. Moreover, the applied computer-assisted vaccine design may considerably decrease vaccine development costs and speed up the process. The study's findings are intriguing, but they must be evaluated in the experimental labs to confirm the developed vaccine's biological efficiency against XDR S. Typhi.Communicated by Ramaswamy H. Sarma.

Application of artificial intelligence in solar and wind energy resources: a strategy to deal with environmental pollution.

Environmental pollution has become a significant concern of nations. International organizations, local authorities, and social activists try to achieve sustainable development goals (SDGs) to protect the environment. However, this cannot be achieved without acknowledging the role of advanced technology applications. Previous studies found a significant relationship between technology and energy resources. But the need to highlight the significance of artificial intelligence (AI) in dealing with inevitable environmental issues still requires more attention. This study aims to analyze the application of AI applications in predicting, developing, and implementing wind and solar energy resources through a bibliometric analysis from 1991 to 2022. It uses bilioshiny of the "bibliometrix 3.0" package of R-programming for influential core aspects and keyword analysis and VOSviewer for co-occurrence analysis. The study provides significant implications for core authors, documents, sources, affiliations, and countries. It also provides keyword analysis and a co-occurrence network to cope with the conceptual integration of the literature. It reports three significant streams of literature in clusters: AI optimization and renewable energy resources; smart renewable energy resource challenges and opportunities; deep learning and machine learning forecasting; and energy efficiency. The findings will uncover the strategic perspective of AI technology for wind and solar energy generation projects.

Proteogenomic analysis of Serratia marcescens using computational subtractive genomics approach.

Serratia marcescens, a Gram-negative bacterium (Enterobacteriaceae) is a hospital-acquired opportunistic pathogen that infects the urinary and central nervous systems. The identification of new therapeutics against S. marcescens is crucial since it is now multi-drug resistant. Therefore, the current study was aimed to identify potential drug targets against S. marcescens strains i.e. WW4, SM39, and Db11 using comparative metabolic pathway analysis and subtractive genomics approach. The applied bioinformatics-based method was used to identify the unique metabolic pathways as the prioritized drug targets. The downstream analysis has led to the identification of three pathways that are specifically absent and/or present in the specific strain. Consequently, six proteins were identified through subtractive genomic analysis. The identified proteins were found as non-homologous and essential to the pathogen's survival as well as unique to the WW4 strain. The estimated features proposed it as a potential drug target. The selected protein was further subjected to in-depth structural analysis for the structure modeling, structure validation, and protein-protein interaction analysis. Furthermore, the library of ~1500 approved compounds was screened against selected drug target to identify potential drug candidates. The current work may help in repurposing of the drug compounds as novel medication against S. marcescens.

Pangenome profiling of novel drug target against vancomycin-resistant Enterococcus faecium.

Enterococcus faecium is a frequent causative agent of nosocomial infection mainly acquired from outgoing hospital patients (Hospital Acquired Infection-HAIs). They are largely involved in the outbreaks of bacteremia, UTI, and endocarditis with a high transmissibility rate. The recent emergence of VRE strain (i.e. vancomycin resistant enterococcus) turned it into high priority pathogen for which new drug research is of dire need. Therefore, in current study, pangenome and resistome analyses were performed for available antibiotic-resistant genomes (n = 216) of E. faecium. It resulted in the prediction of around 5,059 genes as an accessory gene, 1,076 genes as core and 1,558 genes made up a unique genome fraction. Core genes common to all strains were further used for the identification of potent drug targets by applying subtractive genomics approach. Moreover, the COG functional analysis showed that these genomes are highly enriched in metabolic pathways such as in translational, ribosomal, proteins, carbohydrates and nucleotide transport metabolism. Through subtractive genomics it was observed that 431 proteins were non-homologous to the human proteome, 166 identified as essential for pathogen survival while 26 as potential and unique therapeutic targets. Finally, 3-dehydroquinate dehydrogenase was proposed as a potent drug target for further therapeutic candidate identification. Moreover, the molecular docking and dynamic simulation technique were applied to performed a virtual screening of natural product libraries (i.e., TCM and Ayurvedic compounds) along with 3-amino-4,5-dihydroxy-cyclohex-1-enecarboxylate (DHS) as a standard compound to validate the study. Consequently, Argeloside I, Apigenin-7-O-gentiobioside (from Ayurvedic library), ZINC85571062, and ZINC85570908 (TCM library) compounds were identified as potential inhibitors of 3-dehydroquinate dehydrogenase. The study proposed new compounds as novel therapeutics, however, further experimental validation is needed as a follow-up.Communicated by Ramaswamy H. Sarma.

An integrated computational approach to infer therapeutic targets from Campylobacter concisus and peptidomimetic based inhibition of its pyrimidine metabolism pathway.

Campylobacter concisus is a commensal of the human oral flora that has been allied with persistent diarrhea and inflammatory bowel disease (IBD). In children under the age of two, Campylobacter infections are common in the developing countries and have frequently been associated with mortality. They are becoming a prevalent cause of bacterial diarrhea in early adulthood in developed countries as well. The need for identifying new therapeutic targets and drugs is crucial for curbing such infections. Therefore, we identified 18 cytoplasmic potential therapeutic candidates against the type strain of C. concisus and deoxycytidine triphosphate deaminase (dCTP deaminase), involved in pyrimidine synthesis was selected for screening of peptidomimetic inhibitors (n > 30,000 peptidomimetics) against it. To the best of our knowledge, this target has not been studied for Campylobacter spp. Three potent inhibitors of this enzyme were prioritized i.e. peptidomimetic 27, 64, and 150. Dynamics simulation of 100 ns was carried out to validate findings for top-scored inhibitors along with physiology-based pharmacokinetics to estimate behavior in human body and predict dosing parameters. This verification demonstrates a first-in-human pharmacokinetic simulation for these peptidomimetics and can help enhance confidence in these peptide-like structures. Moiety 27 (IUPAC name: 5-[(3,5-dimethyl-1H-pyrazol-1-yl)methyl]-N-{[2-(2-methoxyethyl)-1-oxo-1H,2H,3H,4H-pyrrolo[1,2-a]pyrazin-3-yl]methyl}furan-2-carboxamide), 64 (IUPAC name: 3-(2-methylpropyl)-1-{3-[5-(5-oxo-1-phenylpyrrolidin-3-yl)-1,2,4-oxadiazol-3-yl]phenyl}urea), and 150 (IUPAC name: N-(3-methoxypropyl)-1-[6-(4-methylphenyl)-4H,6H,7H-[1,2,3]triazolo[4,3-c][1,4]oxazine-3-carbonyl]piperidine-4-carboxamide) were identified as potent inhibitors of C. concisus.Communicated by Ramaswamy H. Sarma.

Pan-Genomics of Escherichia albertii for Antibiotic Resistance Profiling in Different Genome Fractions and Natural Product Mediated Intervention: In Silico Approach.

Escherichia albertii is an emerging, enteric pathogen of significance. It was first isolated in 2003 from a pediatric diarrheal sample from Bangladesh. In this study, a comprehensive in silico strategy was followed to first list out antibiotic-resistant genes from core, accessory and unique genome fractions of 95 available genomes of E. albertii. Then, 56 drug targets were identified from the core essential genome. Finally, ZipA, an essential cell division protein that stabilizes the FtsZ protofilaments by cross-linking them and serves as a cytoplasmic membrane anchor for the Z ring, was selected for further downstream processing. It was computationally modeled using a threading approach, followed by virtual screening of two phytochemical libraries, Ayurvedic (n = 2103 compounds) and Traditional Chinese Medicine (n = 36,043 compounds). ADMET profiling, followed by PBPK modeling in the central body compartment, in a population of 250 non-diseased, 250 cirrhotic and 250 renally impaired people was attempted. ZINC85624912 from Chinese medicinal library showed the highest bioavailability and plasma retention. This is the first attempt to simulate the fate of natural products in the body through PBPK. Dynamics simulation of 20 ns for the top three compounds from both libraries was also performed to validate the stability of the compounds. The obtained information from the current study could aid wet-lab scientists to work on the scaffold of screened drug-like compounds from natural resources and could be useful in our quest for therapy against antibiotic-resistant E. albertii.

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.

Immunoinformatic-guided designing of multi-epitope vaccine construct against Brucella Suis 1300.

Brucella suis mediates the transmission of brucellosis in humans and animals and a significant facultative zoonotic pathogen found in livestock. It has the capacity to survive and multiply in a phagocytic environment and to acquire resistance under hostile conditions thus becoming a threat globally. Antibiotic resistance is posing a substantial public health threat, hence there is an unmet and urgent clinical need for immune-based non-antibiotic methods to treat brucellosis. Hence, we aimed to explore the whole proteome of Brucella suis to predict antigenic proteins as a vaccine target and designed a novel chimeric vaccine (multi-epitope vaccine) through subtractive genomics-based reverse vaccinology approaches. The applied subsequent hierarchical shortlisting resulted in the identification of Multidrug efflux Resistance-nodulation-division (RND) transporter outer membrane subunit (gene BepC) that may act as a potential vaccine target. T-cell and B-cell epitopes have been predicted from target proteins using a number of immunoinformatic methods. Six MHC I, ten MHC II, and four B-cell epitopes were used to create a 324-amino-acid MEV construct, which was coupled with appropriate linkers and adjuvant. To boost the immunological response to the vaccine, the vaccine was combined with the TLR4 agonist HBHA protein. The MEV structure predicted was found to be highly antigenic, non-toxic, non-allergenic, flexible, stable, and soluble. To confirm the interactions with the receptors, a molecular docking simulation of the MEV was done using the human TLR4 (toll-like receptor 4) and HLAs. The stability and binding of the MEV-docked complexes with TLR4 were assessed using molecular dynamics (MD) simulation. Finally, MEV was reverse translated, its cDNA structure was evaluated, and then, in silico cloning into an E. coli expression host was conducted to promote maximum vaccine protein production with appropriate post-translational modifications. These comprehensive computer calculations backed up the efficacy of the suggested MEV in protecting against B. suis infections. However, more experimental validations are needed to adequately assess the vaccine candidate's potential. HIGHLIGHTS: • Subtractive genomic analysis and reverse vaccinology for the prioritization of novel vaccine target • Examination of chimeric vaccine in terms of allergenicity, antigenicity, MHC I, II binding efficacy, and structural-based studies • Molecular docking simulation method to rank based vaccine candidate and understand their binding modes.

Therapeutic Target Identification and Inhibitor Screening against Riboflavin Synthase of Colorectal Cancer Associated Fusobacterium nucleatum.

Colorectal cancer (CRC) ranks third among all cancers in terms of prevalence. There is growing evidence that gut microbiota has a role in the development of colorectal cancer. Fusobacterium nucleatum is overrepresented in the gastrointestinal tract and tumor microenvironment of patients with CRC. This suggests the role of F. nucleatum as a potential risk factor in the development of CRC. Hence, we aimed to explore whole genomes of F. nucleatum strains related to CRC to predict potential therapeutic markers through a pan-genome integrated subtractive genomics approach. In the current study, we identified 538 proteins as essential for F. nucleatum survival, 209 non-homologous to a human host, and 12 as drug targets. Eventually, riboflavin synthase (RiS) was selected as a therapeutic target for further processing. Three different inhibitor libraries of lead-like natural products, i.e., cyanobactins (n = 237), streptomycins (n = 607), and marine bacterial secondary metabolites (n = 1226) were screened against it. After the structure-based study, three compounds, i.e., CMNPD3609 (−7.63) > Malyngamide V (−7.03) > ZINC06804365 (−7.01) were prioritized as potential inhibitors of F. nucleatum. Additionally, the stability and flexibility of these compounds bound to RiS were determined via a molecular dynamics simulation of 50 ns. Results revealed the stability of these compounds within the binding pocket, after 5 ns. ADMET profiling showed compounds as drug-like, non-permeable to the blood brain barrier, non-toxic, and HIA permeable. Pan-genomics mediated drug target identification and the virtual screening of inhibitors is the preliminary step towards inhibition of this pathogenic oncobacterium and we suggest mouse model experiments to validate our findings.

Integrated Bioinformatics-Based Subtractive Genomics Approach to Decipher the Therapeutic Drug Target and Its Possible Intervention against Brucellosis.

Brucella suis, one of the causative agents of brucellosis, is Gram-negative intracellular bacteria that may be found all over the globe and it is a significant facultative zoonotic pathogen found in livestock. It may adapt to a phagocytic environment, reproduce, and develop resistance to harmful environments inside host cells, which is a crucial part of the Brucella life cycle making it a worldwide menace. The molecular underpinnings of Brucella pathogenicity have been substantially elucidated due to comprehensive methods such as proteomics. Therefore, we aim to explore the complete Brucella suis proteome to prioritize the novel proteins as drug targets via subtractive proteo-genomics analysis, an effort to conjecture the existence of distinct pathways in the development of brucellosis. Consequently, 38 unique metabolic pathways having 503 proteins were observed while among these 503 proteins, the non-homologs (n = 421), essential (n = 350), drug-like (n = 114), virulence (n = 45), resistance (n = 42), and unique to pathogen proteins were retrieved from Brucella suis. The applied subsequent hierarchical shortlisting resulted in a protein, i.e., isocitrate lyase, that may act as potential drug target, which was finalized after the extensive literature survey. The interacting partners for these shortlisted drug targets were identified through the STRING database. Moreover, structure-based studies were also performed on isocitrate lyase to further analyze its function. For that purpose, ~18,000 ZINC compounds were screened to identify new potent drug candidates against isocitrate lyase for brucellosis. It resulted in the shortlisting of six compounds, i.e., ZINC95543764, ZINC02688148, ZINC20115475, ZINC04232055, ZINC04231816, and ZINC04259566 that potentially inhibit isocitrate lyase. However, the ADMET profiling showed that all compounds fulfill ADMET properties except for ZINC20115475 showing positive Ames activity; whereas, ZINC02688148, ZINC04259566, ZINC04232055, and ZINC04231816 showed hepatoxicity while all compounds were observed to have no skin sensitization. In light of these parameters, we recommend ZINC95543764 compound for further experimental studies. According to the present research, which uses subtractive genomics, proteins that might serve as therapeutic targets and potential lead options for eradicating brucellosis have been narrowed down.