Evidence map›Paper›PMID 41701359›Full record

ReviewJournal of molecular modeling2026

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

Vinita Gouri, Akanksha Kanojia, Awanish Kumar, Mukesh Samant

Abstract readReview
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In one paragraph

Review in Journal of molecular modeling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Vinita GouriDepartment of Zoology, Kumaun University, Nainital, India.
Akanksha KanojiaSchool of Life Science, Jawaharlal Nehru University, New Delhi, India.
Awanish KumarDepartment of Biotechnology, National Institute of Technology, Raipur, Chhattisgarh, India. drawanishkr@gmail.com.ORCID http://orcid.org/0000-0002-0154-2421
Mukesh SamantDepartment of Zoology, D.S.B. Campus, Kumaun University, Nainital, India. mukeshsamant@gmail.com.ORCID http://orcid.org/0000-0001-8735-479X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextThe protozoan parasite Leishmania donovani is a major causative agent of visceral leishmaniasis (VL), a lethal disease posing significant public health challenges globally. Existing anti-VL drugs have become increasingly ineffective due to rising drug resistance, underscoring the urgent need for novel and effective therapeutic candidates. Computational approaches offer rapid and systematic methods for identifying potential drug targets and supporting rational drug design. This review discusses in silico molecular docking studies targeting various Leishmania proteins and their inhibitors, alongside the in vitro and in vivo validation of selected compounds, emphasizing their crucial roles in advancing antileishmanial drug discovery.

methodsIn the review, we have focused on a molecular docking study and explored potential compounds with high binding energy toward protein targets of Leishmania. Following the in silico screening, our review highlights compounds that exhibit both in vitro and in vivo antileishmanial properties, allowing for an assessment of their therapeutic efficacy. Different Software is available for molecular docking, has been mentioned in the review. Overall conclusion of this review supports the computational approach in drug discovery before the in vitro and in vivo study, which can save cost and time efficiency as well.

Indexed as

Antiprotozoal AgentsDrug DiscoveryLeishmania donovaniLeishmaniasis, VisceralMolecular Docking SimulationProtozoan ProteinsAnimalsHumansAntiprotozoal AgentsProtozoan ProteinsComputational approachDrug targetsLeishmania donovaniNew antileishmanial therapeuticsVisceral leishmaniasis

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.