Molecular docking: a computational approach for the discovery of novel targets against visceral leishmaniasis

Area of Science:

• Parasitology
• Computational Biology
• Drug Discovery

Background:

• Leishmania donovani causes visceral leishmaniasis (VL), a lethal global health concern.
• Drug resistance necessitates novel therapeutic strategies against VL.
• Computational methods accelerate the identification of new antileishmanial drug candidates.

Purpose of the Study:

• To review in silico molecular docking studies for Leishmania targets.
• To highlight compounds with validated in vitro and in vivo antileishmanial activity.
• To emphasize the value of computational approaches in antileishmanial drug development.

Main Methods:

• Focus on molecular docking to identify compounds with high binding affinity to Leishmania proteins.
• Inclusion of studies with in vitro and in vivo validation of antileishmanial compounds.
• Discussion of various molecular docking software used in drug discovery.

Main Results:

• Identified potential drug candidates through in silico screening.
• Highlighted compounds demonstrating both in vitro and in vivo efficacy against Leishmania.
• Demonstrated the utility of computational screening in prioritizing drug candidates.

Conclusions:

• Computational approaches, particularly molecular docking, are effective for identifying antileishmanial drug candidates.
• In silico screening significantly reduces time and cost compared to traditional methods.
• This review supports the integration of computational methods early in the antileishmanial drug discovery pipeline.