Evidence map›Paper›PMID 40471955›Full record

ArticlePloS one2025

KIFC1 inhibition: Exploring the potential of propolis-derived small molecules for targeting cancer progression through in silico analysis.

Muhammad Bilal Azmi, Simran Kumari, Sakina Aquil, Urooj Nizami, Arisha Sohail, Syed Danish Haseen Ahmed, Shamim Akhtar Qureshi

Abstract read
In one paragraph

Article in PloS one, 2025. 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. 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

7 authors.

Muhammad Bilal AzmiComputational Biochemistry Research Laboratory, Department of Biochemistry, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan.ORCID https://orcid.org/0000-0001-8320-4479
Simran KumariComputational Biochemistry Research Laboratory, Department of Biochemistry, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan.
Sakina AquilDow Medical College, Dow University of Health Sciences, Karachi, Pakistan.
Urooj NizamiDow Medical College, Dow University of Health Sciences, Karachi, Pakistan.
Arisha SohailComputational Biochemistry Research Laboratory, Department of Biochemistry, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan.ORCID https://orcid.org/0000-0001-5986-1786
Syed Danish Haseen AhmedComputational Biochemistry Research Laboratory, Department of Biochemistry, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan.
Shamim Akhtar QureshiDepartment of Biochemistry, University of Karachi, Karachi, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Propolis, a resinous compound produced by bees, possesses diverse medicinal properties and has gained significant attention for its potential in cancer therapy. This study investigated the therapeutic significance of propolis-derived compounds targeting the kinesin-like protein KIFC1, a motor protein overexpressed in various cancers, using a multistep computational methodology. Therefore, it is essential to utilize different in silico methods to predict their therapeutic potential. A 3D library of propolis-derived compounds sourced from previously published literature was compiled and screened for physicochemical properties, drug-likeness, and pharmacokinetic predictions using the SwissADME and BOILED-Egg permeation predictive model. Pharmacokinetic computations were used to filter out compounds that lacked drug-likeness attributes. KIFC1 3D homology model was selected from the AlphaFold database, its stereochemical properties were assessed and validated. Virtual screening was performed to identify the high-binding affinity-based top-ranked compounds. Furthermore, the active residues present in the druggable cavities were identified using the Cavity Blind (CB) docking tool to investigate grid-box-based residue-specific molecular docking and simulation analysis. We found five common propolis-derived compounds following the druglikeness rule, and having HBA (high binding affinity) for the KIFC1 protein, were subjected to CB docking to identify druggable binding pockets (recognition of consensus residues) on KIFC1 as well as residue-specific molecular docking and simulation. Grid-box-based docking experiments for exploring the molecular interactions of the five compounds above validated the inhibitory effects of kaempferide (∆G = -7.35 kcal/mol and Ki = 4.12 μM), luteolin (∆G = -6.74 kcal/mol and Ki = 11.48 μM), Izalpinin (∆G = -6.33 kcal/mol and Ki = 22.9 μM), 4',5,7-Trihydroxy-3,6-dimethoxyflavone (∆G = -6.14 kcal/mol and Ki = 31.71 μM), and 6-methoxykaempferol (∆G = -6.55 kcal/mol and Ki = 15.81 μM). Molecular dynamics simulation analysis at 100 nanoseconds examined the binding modes of five screened compounds and predicted molecular interactions with KIFC1 protein residues. Two propolis-derived compounds, 4',5,7-trihydroxy-3,6-dimethoxyflavone and 6-methoxy kaempferol, showed significant interactions with KIFC1 residues and exhibited stable binding pattern. MD simulations analysis showed minor variation in root-mean-square deviation and fluctuation, confirming their equilibrium with KIFC1 protein. The study enhances understanding of propolis compounds' inhibitory effects on KIFC1 protein, providing insights for potential treatment approaches and requiring further experimental (in vivo and in vitro) as well as clinical validation.

Indexed as

KinesinsNeoplasmsPropolisSmall Molecule LibrariesComputer SimulationHumansMolecular Docking SimulationMolecular Dynamics SimulationKinesinsPropolisSmall Molecule Libraries

Identifiers

PMID40471955
PMCPMC12140393

What Socratic holds

Textmetadata
LicenceCC BY
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.