Leishmaniasis is a neglected tropical disease caused by parasitic intracellular protozoa of the genus Leishmania. The visceral form of this disease caused by Leishmania donovani continues to constitute a major public health crisis, especially in countries of endemicity. In some cases, it is asymptomatic and comes with acute and chronic clinical outcomes such as weight loss, pancytopenia, hepatosplenomegaly, and death if left untreated. Over the years, the treatment of VL has relied solely on chemotherapeutic agents, but unfortunately, these drugs are now faced with challenges. Despite all efforts, no successful vaccine has been approved for VL. This could be as a result of limited knowledge/understanding of the immune mechanisms necessary to regulate parasite growth. Using a computational approach, this study explored the prospect of harnessing the properties of a disulfide isomerase protein of L. donovani amastigotses to develop a multi-epitope subunit vaccine candidate against the parasite. We designed a 248-amino acid multi-epitope vaccine with a predicted antigenicity probability of 0.897372. Analyses of immunogenicity, allergenicity, and multiple physiochemical parameters indicated that the constructed vaccine candidate was stable, non-allergenic, and immunogenic, making it compatible with humans and hence, a potentially viable and safe vaccine candidate against Leishmania spp. Parasites.

The emergence of multidrug-resistant Neisseria gonorrhoeae has intensified the need for innovative therapeutic strategies. One promising but underexplored target is the Hfq protein, a key regulator in bacterial stress response and pathogenesis. In this study, we employed a computer-aided drug discovery approach to screen phytochemicals from traditionally used anti-gonorrheal plants for their potential to inhibit Hfq. Molecular docking identified several compounds, including Hellebrigenin 3-acetate, Carpaine, β-amyrin, α-amyrin, Rosarin, Oleanolic acid, and Epigallocatechin 3-O-gallate, with binding affinities surpassing that of the reference drug, Ceftriaxone. Molecular dynamics simulations revealed that Carpaine and Oleanolic acid formed the most stable Hfq complexes, exhibiting low RMSD values (0.73 nm and 0.66 nm) and compact Rg profiles (~ 1.4 nm), indicating strong structural stabilization. ADMET analysis suggested moderate intestinal absorption and oral bioavailability, though some compounds showed risks of liver toxicity and CYP2D6 inhibition. Carpaine demonstrated the most favorable binding free energy and prolonged systemic retention, making it an up-and-coming lead candidate. Importantly, evolutionary analysis confirmed the conservation of the Hfq active site, further supporting its viability as a therapeutic target. These findings reveal the potential of plant-derived compounds, particularly Carpaine and Oleanolic acid, as novel Hfq inhibitors, providing a strong foundation for future experimental validation and the development of alternative therapies against multidrug-resistant N. gonorrhoeae.

Motivation: Cervical cancer remains a leading cause of gynecological mortality, with existing treatments often limited by resistance and suboptimal efficacy. While Coffea arabica is rich in phytochemicals with reported anticancer properties, their relevance to cervical cancer-specific molecular targets remains underexplored. Here, we integrated transcriptomic profiling, cheminformatics, and survival modeling to evaluate the therapeutic potential of C. arabica compounds in cervical cancer. Results: From 158 bioactive compounds with favorable pharmacokinetic and drug-likeness properties, we predicted gene targets and intersected them with 1779 differentially expressed genes identified from bulk RNA-sequencing of 304 cervical cancer tumors and 47 normal cervical tissues. This yielded 43 C. arabica gene targets that were significantly dysregulated in cervical cancer. Pathway enrichment revealed involvement in tumorigenesis, immune modulation, and cell cycle regulation, with fold enrichment computed as the ratio of observed-to-expected gene overlap. Survival analysis identified 14 of these genes as markers of poor prognosis, with matrix metalloproteinase-7 (MMP7) emerging as an independent prognostic marker of adverse outcome. A Random-Forest-Regression model trained on 499 experimentally validated MMP7 inhibitors identified carnosol—a C. arabica compound—as a top-ranking candidate with high predicted activity. These findings nominate carnosol as a promising therapeutic lead for cervical cancer and lay the groundwork for future experimental validation. Availability and implementation: The data supporting the findings of this study, including bulk RNA-seq gene expression data, survival, and phenotype data, are available through the TCGA database. These data can be accessed via the Xenabrowser platform (https://xenabrowser.net) using the reference identifier [TCGA Cervical Cancer (CESC)]. Corresponding healthy cervical tissue RNA-seq data, are available through the Genotype-Tissue Expression (GTEx) project (https://www.gtexportal.org/home/). The codes used for differential gene expression (DGE) analysis, pathway enrichment, and survival analysis, as well as scripts for generating volcano plots (DGE analysis), Kaplan-Meier survival plots, and boxplots (gene expression), and machine learning implementations are available on GitHub (https://github.com/Ponaskillzyy/Coffea_arabica_Potential_in_Cervical_Cancer).