Evidence map›Paper›PMID 39012568›Full record

ArticleJournal of molecular modeling2024

Uncovering potential CDK9 inhibitors from natural compound databases through docking-based virtual screening and MD simulations.

Pooja Singh, Vikas Kumar, Tae Sung Jung, Jeong Sang Lee, Keun Woo Lee, Jong Chan Hong

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Article in Journal of molecular modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Targeting CDK9 with Molegro Virtual Docker.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Article
  4. Drug design for cyclin-dependent kinase 9 (CDK9) inhibitorsBiochemistry and biophysics reports · 2025
    Article
  5. 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

6 authors.

Pooja SinghDivision of Applied Life Science, (BK21 Four), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Gyeongsang National University (GNU), 501 Jinju-Daero, Jinju, 52828, Republic of Korea.ORCID http://orcid.org/0000-0003-3734-175X
Vikas KumarDepartment of Bio & Medical Big Data (BK4 Program), Division of Life Sciences, Research Institute of Natural Science (RINS), Gyeongsang National University (GNU), 501 Jinju-Daero, Jinju, 52828, Republic of Korea.ORCID http://orcid.org/0000-0003-4468-3459
Tae Sung JungLaboratory of Aquatic Animal Diseases, College of Veterinary Medicine, Research Institute of Natural Science, Gyeongsang National University, Jinju, 52828, Republic of Korea.
Jeong Sang LeeGSCRO, Research Spin-Off Company, Innopolis Jeonbuk, Jeonju, 55069, Korea.
Keun Woo LeeDepartment of Bio & Medical Big Data (BK4 Program), Division of Life Sciences, Research Institute of Natural Science (RINS), Gyeongsang National University (GNU), 501 Jinju-Daero, Jinju, 52828, Republic of Korea. kwlee@gnu.ac.kr.
Jong Chan HongDivision of Applied Life Science, (BK21 Four), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Gyeongsang National University (GNU), 501 Jinju-Daero, Jinju, 52828, Republic of Korea. jchong@gnu.ac.kr.

Funding

National Research Foundation of Korea (NRF) RS-2023-00301974
6 · The paper itself

Abstract

contextCyclin-dependent kinase 9 (CDK9) plays a significant role in gene regulation and RNA polymerase II transcription under basal and stimulated conditions. The upregulation of transcriptional homeostasis by CDK9 leads to various malignant tumors and therefore acts as a valuable drug target in addressing cancer incidences. Ongoing drug development endeavors targeting CDK9 have yielded numerous clinical candidate molecules currently undergoing investigation as potential CDK9 modulators, though none have yet received Food and Drug Administration (FDA) approval.

methodsIn this study, we employ in silico approaches including the molecular docking and molecular dynamics simulations for the virtual screening over the natural compounds library to identify novel promising selective CDK9 inhibitors. The compounds derived from the initial virtual screening were subsequently employed for molecular dynamics simulations and binding free energy calculations to study the compound's stability under virtual physiological conditions. The first-generation CDK inhibitor Flavopiridol was used as a reference to compare with our novel hit compound as a CDK9 antagonist. The 500-ns molecular dynamics simulation and binding free energy calculation showed that two natural compounds showed better binding affinity and interaction mode with CDK9 receptors over the reference Flavopiridol. They also showed reasonable figures in the predicted absorption, distribution, metabolism, excretion, and toxicity (ADMET) calculations as well as in computational cytotoxicity predictions. Therefore, we anticipate that the proposed scaffolds could contribute to developing potential and selective CDK9 inhibitors subjected to further validations.

Indexed as

Cyclin-Dependent Kinase 9Molecular Docking SimulationMolecular Dynamics SimulationProtein Kinase InhibitorsBiological ProductsFlavonoidsHumansPiperidinesProtein BindingalvocidibBiological ProductsCDK9 protein, humanCyclin-Dependent Kinase 9FlavonoidsPiperidinesProtein Kinase InhibitorsCancerCyclin-dependent kinases (CDKs)Molecular dockingMolecular dynamics simulationsVirtual screening

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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.