ArticleArchives of microbiology2025
Uncovering therapeutic targets in Leishmania donovani through comparative network topology analysis.
Article in Archives of microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
2 authors.
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Abstract
Leishmaniasis is a significant vector-borne health problem affecting 88 countries, transmitted by the bite of female sandflies (phlebotomine). It manifests in various clinical forms, such as diffuse cutaneous leishmaniasis, mucocutaneous leishmaniasis, and visceral leishmaniasis (VL). The most chronic and possibly fatal form, VL, is caused by Leishmania donovani (L. donovani). The critical need for novel, effective therapeutic targets is highlighted by the escalating costs, toxicity, and side effects of existing treatments, as well as the increasing occurrence of drug-resistant parasites. The emergence of computational biology domains, including Bioinformatics and systems biology, has opened up a plethora of opportunities for researching and discovering therapeutic compounds for illnesses using in-silico techniques. Enzymes involved in key metabolic pathways of L. donovani were used to construct a PPI network, followed by topological analysis employing centrality measures such as degree, closeness, bottleneck, and betweenness centrality (BC). Gene Ontology (GO) enrichment indicated that the most connected proteins are involved in essential biological processes, including redox regulation, energy metabolism, and nucleic acid synthesis. MCODE clustering identified high-degree hub proteins within top modules. From this integrative network-based analysis, we propose four proteins that recur across multiple pathways and exhibit high centrality and modularity scores, underscoring their functional significance. These proteins likely serve as chokepoints or regulatory hubs, making them promising multi-pathway drug targets. Their inhibition may disrupt multiple vital cellular functions simultaneously, offering an effective strategy against multidrug-resistant L. donovani strains. This study provides a computational framework to prioritize and validate novel therapeutic targets in L. donovani, contributing to the development of more effective treatments for visceral leishmaniasis.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.