ReviewMolecular biology reports2026
Towards precision antileishmanial drug discovery: Integrating multi-omics, functional genomics, artificial intelligence and host-directed therapeutics.
Review in Molecular biology reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Leishmaniasis remains one of the most neglected tropical diseases, affecting millions of people worldwide and posing a substantial public health burden in endemic regions. Current treatment options are limited by toxicity, high costs, prolonged treatment regimens, treatment failure, and the increasing emergence of drug-resistant parasites. Moreover, the remarkable genomic plasticity and adaptive capacity of Leishmania species, driven by mosaic aneuploidy and copy number variation, complicate durable target identification and underscore the need for precision-oriented therapeutic approaches. Recent developments in multi-omics strategies, CRISPR-based genome engineering, artificial intelligence, and host-directed therapeutics are transforming precision antileishmanial drug discovery. In this review, we explore how multi-omics technologies uncover pathways involved in parasite survival, virulence, and drug resistance. We examine the contributions of CRISPR-based technologies to functional genomic screening, target validation, and investigation of resistance mechanisms. Complementing these approaches, AI-assisted predictive modelling supports target prioritisation, virtual screening, and structure-guided drug discovery. We also discuss host-directed immunotherapy as a complementary strategy to parasite-directed therapies. Particular focus is placed on high-priority therapeutic pathways regulating redox homeostasis, sterol biosynthesis, MAP kinase signalling, mitochondrial electron transport, and arginine metabolism. Taken together, these strategies offer an integrated framework connecting target discovery, functional validation, computational prioritisation, and host immune modulation, while supporting a precision-oriented approach for the development of safer, more efficient, and resistance-resilient antileishmanial therapies.
Indexed as
Identifiers
42782436What OpenQuestion holds
Registered trials
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.