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

Antibiotic resistance in Neisseria gonorrhoeae: broad-spectrum drug target identification using subtractive genomics

Neisseria gonorrhoeae is a Gram-negative aerobic diplococcus bacterium that primarily causes sexually transmitted infections through direct human sexual contact. It is a major public health threat due to its impact on reproductive health, the widespread presence of antimicrobial resistance, and the lack of a vaccine. In this study, we used a bioinformatics approach and performed subtractive genomic methods to identify potential drug targets against the core proteome of N. gonorrhoeae (12 strains). In total, 12,300 protein sequences were retrieved, and paralogous proteins were removed using CD-HIT. The remaining sequences were analyzed for non-homology against the human proteome and gut microbiota, and screened for broad-spectrum analysis, druggability, and anti-target analysis. The proteins were also characterized for unique interactions between the host and pathogen through metabolic pathway analysis. Based on the subtractive genomic approach and subcellular localization, we identified one cytoplasmic protein, 2Fe-2S iron-sulfur cluster binding domain-containing protein (NGFG RS03485), as a potential drug target. This protein could be further exploited for drug development to create new medications and therapeutic agents for the treatment of N. gonorrhoeae infections.

Inhibitor Assessment against the LpxC Enzyme of Antibiotic-resistant Acinetobacter baumannii Using Virtual Screening, Dynamics Simulation, and in vitro Assays

BACKGROUND

Bacterial resistance is currently a significant global public health problem. Acinetobacter baumannii has been ranked in the list of the World Health Organization as the most critical and priority pathogen for which new antibiotics are urgently needed. In this context, computational methods play a central role in the modern drug discovery process. The purpose of the current study was to identify new potential therapeutic molecules to neutralize MDR A. baumannii bacteria.

METHODS

A total of 3686 proteins retrieved from the A. baumannii proteome were subjected to subtractive proteomic analysis to narrow down the spectrum of drug targets. The SWISS-MODEL server was used to perform a 3D homology model of the selected target protein. The SAVES server was used to evaluate the overall quality of the model. A dataset of 74500 analogues retrieved from the PubChem database was docked with LpxC using the AutoDock software.

RESULTS

In this study, we predicted a putative new inhibitor for the Lpxc enzyme of A. baumannii. The LpxC enzyme was selected as the most appropriate drug target for A. baumannii. According to the virtual screening results, N-[(2S)-3-amino-1-(hydroxyamino)-1-oxopropan-2-yl]-4-(4-bromophenyl) benzamide (CS250) could be a promising drug candidate targeting the LpxC enzyme. This molecule shows polar interactions with six amino acids and non-polar interactions with eight other residues. In vitro experimental validation was performed through the inhibition assay.

CONCLUSION

To the best of our knowledge, this is the first study that suggests CS250 as a promising inhibitory molecule that can be exploited to target this gram-negative pathogen.

Identification of New Drug Target in Staphylococcus lugdunensis by Subtractive Genomics Analysis and Their Inhibitors through Molecular Docking and Molecular Dynamic Simulation Studies

Staphylococcus lugdunensis is a coagulase-negative, Gram-positive, and human pathogenic bacteria. S. lugdunensis is the causative agent of diseases, such as native and prosthetic valve endocarditis, meningitis, septic arthritis, skin abscesses, brain abscess, breast abscesses, spondylodiscitis, post-surgical wound infections, bacteremia, and peritonitis. S. lugdunensis displays resistance to beta-lactam antibiotics due to the production of beta-lactamases. This study aimed to identify potential novel essential, human non-homologous, and non-gut flora drug targets in the S. lugdunensis strain N920143, and to evaluate the potential inhibitors of drug targets. The method was concerned with a homology search between the host and the pathogen proteome. Various tools, including the DEG (database of essential genes) for the essentiality of proteins, the KEGG for pathways analysis, CELLO V.2.5 for cellular localization prediction, and the drug bank database for predicting the druggability potential of proteins, were used. Furthermore, a similarity search with gut flora proteins was performed. A DNA-binding response-regulator protein was identified as a novel drug target against the N920143 strain of S. lugdunensis. The three-dimensional structure of the drug target was modelled and validated with the help of online tools. Furthermore, ten thousand drug-like compounds were retrieved from the ZINC15 database. The molecular docking approach for the DNA-binding response-regulator protein identified ZINC000020192004 and ZINC000020530348 as the most favorable compounds to interact with the active site residues of the drug target. These two compounds were subjected to an MD simulation study. Our analysis revealed that the identified compounds revealed more stable behavior when bound to the drug target DNA-binding response-regulator protein than the apostate.

An insight in Salmonella typhi associated autoimmunity candidates' prediction by molecular mimicry

Autoimmune diseases develop when the immune system targets healthy cells and tissues of an individual. In developing countries, S. typhi (a gram-negative pathogenic bacteria) remains a major public health issue. This study aimed to employ bioinformatics analyses to determine the 3D structural-based molecular mimicry and sequence of S. typhi and human host proteins. In addition, to classify possible antigenic microbial peptides homologous to human peptides and comprehend the molecular basis of S. typhi-related autoimmune disorders. Protein sequences were obtained from the NCBI database, and redundancy was removed using the CD-HIT tool. The BLASTp comparative sequence analysis was followed for molecular mimicry identification of human and S. typhi protein sequences. The PathDIP database was utilized to simulate essential physical relationships between proteins and curated pathways for metabolic processes. Subsequently, the IEDB database was used to find cross-reactive MHC class-II binding epitopes that could trigger an autoimmune reaction. SPARKS-X computational biology resource was also used to determine the structural homology between human and S. typhi peptides. The BLASTp study showed that S. typhi and the human host have several proteins holding considerable sequence similarities based on a set threshold of e ≤ 10-6 and bit score ≥100. The PathDIP putatively identified that these proteins enriched in a total of 68 metabolic pathways by a significant P-value (P < 0.005). The PSORTb analysis predicted that 26 out of these proteins are cytosolic, 1 predicted to be periplasmic protein, and 1 predicted to be localized in the cytoplasmic membrane. IEDB data analysis predicted many S.typhi and human homologs epitopes as a good binder of human HLA, i.e. DRB1*01:01, DPA1*03:01/DPB1*04:02, and DQA1*01:02/DQB1*06:02 with IC₅₀ < 50 nM. Finally, the docking data demonstrated that homolog lead epitopes promisingly interact with HLA and immune TLR4 receptors by exhibiting the best docking scores and molecular interactions. The analyses ultimately identified several potential candidate proteins and peptides that could cause S.typhi infection-mediated autoimmune diseases in humans.

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.

Therapeutic target identification via differential genome analysis of antibiotic resistant Shigella sonnei and inhibitor evaluation against a selected drug target

Shigella sonnei has been implicated in bloody diarrhea (accompanied by abdominal pain and fever) and is an emerging pathogen of concern, especially in developing countries. The major means of transmission is the fecal-oral route while sexual transmission has also been reported. In children, the impact might be stunted growth due to life-threatening illness. Resistance has been reported in this species for several types of antibiotics. In this study, we retrieved the antibiotic-resistant labeled whole genome sequences of the species from the PATRIC database and performed a pan-genome analysis to filter out core genes. Antibiotic resistance was studied in the core, accessory and unique genome. Core genes were utilized as seed substance for essentiality analysis and drug candidate assignment. Product of the gene aroG, i.e. chorismate biosynthetic process 3-deoxy-7-phosphoheptulonate synthase enzyme, responsible for aromatic amino acid family biosynthetic process, was taken for further downstream processing. Natural product libraries of flavonoids (n = 178), ZINC database derived inhibitor compounds of the 3-deoxy-7-phosphoheptulonate synthase enzyme (n = 112), and streptomycin compounds (n = 737) were docked to find out potent inhibitors, followed by dynamics simulation of 50 ns each for top compounds.. Physicochemical and ADMET profiling of the top compounds was done to analyze their safety for consumption. We propose that the top compounds: Phytoene from Streptomycin library and ZINC000036444158 (synonym:1,16-bis[(dihydroxyphosphinyl)oxy]hexadecane) from 3-deoxy-7-phosphoheptulonate synthase inhibitor library of ZINC database (and used as a control in this study) should be tested in vitro against Shigella sonnei, to fully determine their efficacy. This could add to the drying pipeline of potent drug molecules against emerging pathogens.

Core proteome mediated therapeutic target mining and multi-epitope vaccine design for Helicobacter pylori

Helicobacter pylori is a Gram-negative spiral-shaped bacterium that infects half of the human population worldwide and causes chronic inflammation. In the present study, we used the art of computational biology for therapeutic drug targets identification and a multi-epitope vaccine against multi-strains of H. pylori. For drug target identification, we used different tools and softwares to identify human non-homologous but pathogen essential proteins, with virulent properties and involved in unique metabolic pathways of H. pylori. For this purpose, the core proteome of 84 strains of H. pylori was retrieved from EDGAR 2.3 database. There were 59,808 proteins sequences in these strains. Duplicates and paralogous protein sequence removal was followed by human non-homologous protein miningPathogen essential and virulent proteins were subjected to pathway analysis Subcellular localization of the virulent proteins was predicted and druggability was also checked, leading to 30 druggable targets based on their similarity with the approved drug targets in Drugbank. For immunoinformatics analysis, we selected two outer membrane proteins (HPAKL86_RS06305 and HPSNT_RS00950) and subjected to determined immunogenic B and T-Cell epitopes. The B and T-Cell overlapped epitopes were selected to design 9 different vaccine constructs by using linkers and adjuvants. Least allergenic and most antigenic construct (C-8) was selected as a promiscuous vaccine to elicit host immune response. Cloning and in silico expression of the constructed vaccine (C-8) was done to produce a clone having the desired (gene) vaccine construct. In conclusion, the prioritized therapeutic targets for 84 strains of H.pylori will be useful for future therapy design. Vaccine design may also prove useful in the quest for targeting multi-strains of H. pylori in patients.