An in silico strategy for identification of novel drug targets against Plasmodium falciparum

Identification, Genome Sequencing, and Characterizations of Helicobacter pylori Sourced from Pakistan

The stomach's colonization by Helicobacter pylori (H. pylori) results in gastritis, ulcers, and stomach cancer. Frequently, pain is treated with medication, but resistant H. pylori infections are not. Therefore, it is important to find pharmacological targets and improved treatments for resistant H. pylori strains. The aim of the current study was sampling, identification, drug susceptibility testing following genome sequencing and comparative genome-wide analysis of selected H. pylori strains from Pakistan with three representative strains for virulence and drug-resistant characteristics. Based on culture, biochemistry, and molecular biology, 84 strains of H. pylori were identified, which made up 47% of the enrolled cases. Among all H. pylori strains, the highest resistance was reported for metronidazole with 82 H. pylori strains (98%), followed by clarithromycin with 62 resistant strains (74%). Among metronidazole-resistant strains, 38 strains (46%) were also resistant to clarithromycin, contributing 61% of clarithromycin resistant cases. Two strains, HPA1 and HPA2, isolated from 'gastritis' and 'gastric ulcer' patients, respectively, were further processed for WGS. The draft genome sequences of H. pylori strains HPA1 and HPA2 encode 1.66 Mbp and 1.67 Mbp genome size, 24 and 4 contiguous DNA sequences, and 1650 and 1625 coding sequences, respectively. Both the genomes showed greater than 90% similarity with the reference strain H. pylori ATCC 43504/PMSS1. The antibiotic-resistant genes were identified among all the strains with overall similarity above 95%, with minor differences in the sequence similarity. Using the virulent gene data obtained from the Virulence Factor Database, 75 to 85 virulent genes were identified in the five genome assemblies with various key genes such as cytolethal distending toxin (cdt), type IV secretion system, cag PAI, plasticity region, cell-motility- and flagellar-associated genes, neutrophil-activating protein (HP-NAP), T4SS effector cytotoxin-associated gene A (cagA), and urease-associated genes ureA and ureB, etc. Sequence similarity between the virulence factors found in this study and reference genes was at least 90%. In summary, the results of our study showed the relationship between clinical results and specific H. pylori strains' (HPA1 and HPA2) genetics such as antibiotic resistance and specific virulence factors. These findings provide valued understanding of the epidemiology of H. pylori-associated diseases. Moreover, identification and genomics analysis have provided insights into the epidemiology, genetic diversity, pathogenicity, and potential drug resistance genes of H. pylori strains, offering a foundation for developing more targeted and effective medical interventions, including anti-virulent medications.

In silico analysis of Leishmania proteomes and protein-protein interaction network: Prioritizing therapeutic targets and drugs for repurposing to treat leishmaniasis

Leishmaniasis is a serious world health problem and its current therapies have several limitations demanding to develop novel therapeutics for this disease. The present study aims to prioritize novel broad-spectrum targets using proteomics and protein-protein interaction network (PPIN) data for 11 Leishmania species. Proteome comparison and host non-homology analysis resulted in 3605 pathogen-specific conserved core proteins. Gene ontology analysis indicated their involvement in major molecular functions like DNA binding, transportation, dioxygenase, and catalytic activity. PPIN analysis of these core proteins identified eight hub proteins (viz., vesicle-trafficking protein (LBRM2903_190011800), ribosomal proteins S17 (LBRM2903_34004790) and L2 (LBRM2903_080008100), eukaryotic translation initiation factor 3 (LBRM2903_350086700), replication factor A (LBRM2903_150008000), U3 small nucleolar RNA-associated protein (LBRM2903_340025600), exonuclease (LBRM2903_200021800), and mitochondrial RNA ligase (LBRM2903_200074100)). Among the hub proteins, six were classified as drug targets and two as vaccine candidates. Further, druggability analysis indicated three hub proteins, namely eukaryotic translation initiation factor 3, ribosomal proteins S17 and L2 as druggable. Their three-dimensional structures were modelled and docked with the identified ligands (2-methylthio-N6-isopentenyl-adenosine-5'-monophosphate, artenimol and omacetaxine mepesuccinate). These ligands could be experimentally validated (in vitro and in vivo) and repurposed for the development of novel antileishmanial agents.

The emergence of chloroquine-sensitive Plasmodium falciparum is influenced by selected communities in some parts of the Central Region of Ghana

Background

The return of chloroquine-sensitive Plasmodium falciparum in sub-Saharan Africa countries offers the opportunity for the reintroduction of chloroquine (CQ) either in combination with other drugs or as a single therapy for the management of malaria. This study assesses the influence of individual study sites on the selection of CQ sensitive P. falciparum markers in the Central region of Ghana.

Methods

Genomic DNA was extracted from an archived filter paper blood blot from Cape Coast, Elmina, Assin Fosu, and Twifo Praso using the Chelex DNA extraction method. The age metadata of the patients from whom the blood spots were taken was collected. The prevalence of CQ-sensitive markers of pfcrt K76 and pfmdr1 N86 was performed using nested PCR and RFLP. The data were analysed using Chi-square and Odd ratio.

Results

The overall prevalence of CQ-sensitive P. falciparum markers, pfcrt K76 and pfmdr1 N86 in the Central Region of Ghana were 142 out of 184 (77.17%) and 180 out of 184 (97.83%), respectively. The distribution of pfcrt K76 was assessed among the age groups per the individual study sites. 12 out of 33 (36.36%), 8 out of 33 (24.24%) and 6 out of 33 (18.18%) of pfcrt K76 CQ-sensitive marker were isolated from age 0 to 5 years, 16 to 30 years and 31 to 45 years old respectively at Cape Coast. Assin Fosu and Twifo Praso had the highest pfcrt K76 prevalence in 0–5 years, followed by 16–30 years and 6–15 years of age. The results showed that there was a significant prevalence of pfcrt K76 in all study sites; Cape Coast (χ² = 26.48, p < 0.0001), Assin Fosu (χ² = 37.67, p < 0.0001), Twifo Praso (χ² = 32.25, p < 0.0001) and Elmina (χ² = 17.88, p < 0.0001). Again, the likelihood to detect pfcrt K76 (OR (95% CI) was 7.105 (3.118–17.14), p < 0.0001 and pfmdr1 (2.028 (1.065–3.790), p < 0.001) among P. falciparum isolates from Cape Coast to be seven times and two times, respectively.

Conclusion

The study showed a significant selection and expansion of chloroquine-sensitive P. falciparum markers in all the selected study areas in the Central region. This finding has a significant implication for the future treatment, management, and control of P. falciparum malaria.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03985-8.

Computational/in silico methods in drug target and lead prediction

Drug-like compounds are most of the time denied approval and use owing to the unexpected clinical side effects and cross-reactivity observed during clinical trials. These unexpected outcomes resulting in significant increase in attrition rate centralizes on the selected drug targets. These targets may be disease candidate proteins or genes, biological pathways, disease-associated microRNAs, disease-related biomarkers, abnormal molecular phenotypes, crucial nodes of biological network or molecular functions. This is generally linked to several factors, including incomplete knowledge on the drug targets and unpredicted pharmacokinetic expressions upon target interaction or off-target effects. A method used to identify targets, especially for polygenic diseases, is essential and constitutes a major bottleneck in drug development with the fundamental stage being the identification and validation of drug targets of interest for further downstream processes. Thus, various computational methods have been developed to complement experimental approaches in drug discovery. Here, we present an overview of various computational methods and tools applied in predicting or validating drug targets and drug-like molecules. We provide an overview on their advantages and compare these methods to identify effective methods which likely lead to optimal results. We also explore major sources of drug failure considering the challenges and opportunities involved. This review might guide researchers on selecting the most efficient approach or technique during the computational drug discovery process.

Identification of Potential Drug Targets in Helicobacter pylori Using In Silico Subtractive Proteomics Approaches and Their Possible Inhibition through Drug Repurposing

The class 1 carcinogen, Helicobacter pylori, is one of the World Health Organization's high priority pathogens for antimicrobial development. We used three subtractive proteomics approaches using protein pools retrieved from: chokepoint reactions in the BIOCYC database, the Kyoto Encyclopedia of Genes and Genomes, and the database of essential genes (DEG), to find putative drug targets and their inhibition by drug repurposing. The subtractive channels included non-homology to human proteome, essentiality analysis, sub-cellular localization prediction, conservation, lack of similarity to gut flora, druggability, and broad-spectrum activity. The minimum inhibitory concentration (MIC) of three selected ligands was determined to confirm anti-helicobacter activity. Seventeen protein targets were retrieved. They are involved in motility, cell wall biosynthesis, processing of environmental and genetic information, and synthesis and metabolism of secondary metabolites, amino acids, vitamins, and cofactors. The DEG protein pool approach was superior, as it retrieved all drug targets identified by the other two approaches. Binding ligands (n = 42) were mostly small non-antibiotic compounds. Citric, dipicolinic, and pyrophosphoric acid inhibited H. pylori at an MIC of 1.5-2.5 mg/mL. In conclusion, we identified potential drug targets in H. pylori, and repurposed their binding ligands as possible anti-helicobacter agents, saving time and effort required for the development of new antimicrobial compounds.

Exploration of Binding Mechanism of a Potential Streptococcus pneumoniae Neuraminidase Inhibitor from Herbaceous Plants by Molecular Simulation

Streptococcus pneumoniae can cause diseases such as pneumonia. Broad-spectrum antibiotic therapy for Streptococcus pneumoniae is increasingly limited due to the emergence of drug-resistant strains. The development of novel drugs is still currently of focus. Abundant polyphenols have been demonstrated to have antivirus and antibacterial ability. Chlorogenic acid is one of the representatives that has been proven to have the potential to inhibit both the influenza virus and Streptococcus pneumoniae. However, for such a potential neuraminidase inhibitor, the interaction mechanism studies between chlorogenic acid and Streptococcus pneumoniae neuraminidase are rare. In the current study, the binding mechanism of chlorogenic acid and Streptococcus pneumoniae neuraminidase were investigated by molecular simulation. The results indicated that chlorogenic acid might establish the interaction with Streptococcus pneumoniae neuraminidase via hydrogen bonds, salt bridge, and cation-π. The vital residues involved Arg347, Ile348, Lys440, Asp372, Asp417, and Glu768. The side chain of Arg347 might form a cap-like structure to lock the chlorogenic acid to the active site. The results from binding energy calculation indicated that chlorogenic acid had strong binding potential with neuraminidase. The results predicted a detailed binding mechanism of a potential Streptococcus pneumoniae neuraminidase inhibitor, which will be provide a theoretical basis for the mechanism of new inhibitors.