Evidence map›Paper›PMID 40163147›Full record

ArticleMolecular diversity2026

Computational screening for natural compounds as potential immune checkpoint inhibitors against TIGIT, a new avenue in cancer immunotherapy.

Aritra Chakraborty, Amit Kumar

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular diversity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

2 authors.

Aritra ChakrabortyDepartment of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Simrol, 453552, India.
Amit KumarDepartment of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Simrol, 453552, India. amitk@iiti.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The TIGIT-PVR signalling pathway is a key mechanism of tumour immune evasion, making it an attractive target for cancer immunotherapy. Despite the recent advances in anti-TIGIT antibodies, monoclonal antibody-based therapeutics present significant challenges because of their immunogenicity and immune-related side effects. This study presents a new path involving natural compounds as potential small molecule inhibitors of TIGIT, providing a possible alternative to antibodies in cancer immunotherapy. Through a comprehensive in silico workflow combining structure-based virtual screening, ADMET analysis, Molecular docking and molecular dynamics simulations, six promising candidates, mostly of bacterial origin, were identified: Neomycin K, 4'-Deoxybutirosin A, 5-Glucosyl-neamine, S-11-A, 12-carbamoylstreptothricin E acid, and Zwittermicin A. These candidates demonstrated favourable binding energies, stable interactions, and the capacity to block TIGIT-PVR signalling. The compounds can potentially compete with PVR to bind to TIGIT, limiting the formation of the TIGIT-PVR complex, which typically activates an inhibitory cascade in T cells and NK cells, reducing their anti-tumour activity. By disrupting this interaction, the identified compounds have the potential to stimulate T cell and NK cell responses against cancer cells. Such natural compounds potentially provide better tissue penetration and reduced immunogenicity compared to conventional antibody therapies. The discovery of bacterial-derived compounds as TIGIT inhibitors presents a new direction in the investigation of microbial metabolites for cancer immunotherapy. This strategy not only identifies a new class of TIGIT inhibitors but also provides a robust computational framework for discovering and characterizing small molecule immune checkpoint inhibitors, paving the way for subsequent experimental validation to explore their efficacy in restoring anti-tumour immune responses and improving clinical outcomes for cancer patients.

Indexed as

Biological ProductsImmune Checkpoint InhibitorsImmunotherapyNeoplasmsReceptors, ImmunologicHumansMolecular Docking SimulationMolecular Dynamics SimulationBiological ProductsImmune Checkpoint InhibitorsReceptors, ImmunologicTIGIT protein, humanImmune checkpoint inhibitorImmunotherapyMicrobial metabolitesNatural compoundPVRTIGIT

Identifiers

What OpenQuestion 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 OpenQuestion graph.