Evidence map›Paper›PMID 42801770›Full record

ReviewChemistry & biodiversity2026

Quantitative Structure-Activity Relationship Approaches for Exploring the Anticancer Potential of Flavonoids.

Mukta Gupta, Shanu Priya, Javed Ahmad, Kasim Sakran Abass, Awanish Mishra

Abstract readReview
In one paragraph

Review in Chemistry & biodiversity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Mukta GuptaSchool of Pharmaceutical Sciences, Lovely Professional University, Punjab, India.
Shanu PriyaSchool of Pharmaceutical Sciences, Lovely Professional University, Punjab, India.ORCID https://orcid.org/0000-0002-6055-0640
Javed AhmadDepartment of Pharmaceutics, College of Pharmacy, Najran University, Najran, Saudi Arabia.ORCID https://orcid.org/0000-0002-7025-751X
Kasim Sakran AbassDepartment of Physiology, Biochemistry, and Pharmacology, College of Veterinary Medicine, University of Kirkuk, Kirkuk, Iraq.ORCID https://orcid.org/0000-0002-5796-7170
Awanish MishraDepartment of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER) - Guwahati, Kamrup, Assam, India.ORCID https://orcid.org/0000-0001-7863-5581

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flavonoids are structurally diverse polyphenolic compounds widely distributed in fruits, vegetables, grains, and beverages, with considerable potential as anticancer agents. Their pleiotropic activities involve modulation of key cancer hallmarks, including oxidative stress, cell-cycle progression, apoptosis, autophagy, angiogenesis, invasion, and metastasis. These effects are mediated through multiple signaling pathways, including PI3K/Akt, MAPK, NF-κB, and STAT3. Understanding the relationship between flavonoid structure and biological activity is therefore essential for rational optimization of flavonoid-based therapeutics. Structure-activity relationship (SAR) and quantitative structure-activity relationship (QSAR) approaches provide systematic frameworks for correlating structural and physicochemical features, including hydroxylation, glycosylation, prenylation, electronic distribution, steric properties, and lipophilicity, with anticancer activity and target interactions. This review summarizes advances in flavonoid identification and characterization and critically examines computational approaches used to investigate their anticancer potential, including molecular docking, linear and nonlinear QSAR modeling, molecular similarity analysis, topological descriptors, semiempirical calculations, density functional theory, molecular dynamics simulations, and Free-Wilson analysis. Particular emphasis is placed on integrating computational predictions with experimental validation and addressing challenges related to pharmacokinetics, bioavailability, selectivity, and translation. Collectively, SAR/QSAR-guided strategies offer valuable tools for elucidating structure-activity relationships and accelerating the rational discovery and optimization of flavonoid-based anticancer candidates.

Indexed as

Antineoplastic AgentsFlavonoidsNeoplasmsQuantitative Structure-Activity RelationshipHumansMolecular Docking SimulationMolecular StructureAntineoplastic AgentsFlavonoidsanticancer activityapoptosis and autophagychemoinformaticsdrug discovery and developmentflavonoidsmolecular dockingPI3K/Akt signalingpolyphenolsquantitative structure–activity relationship (QSAR)structure–activity relationship (SAR)

Identifiers

PMID42801770
PMCPMC13616465

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.