Evidence mapPaperPMID 38255306Full record

ReviewBiomedicines2024

Anticancer Drug Discovery Based on Natural Products: From Computational Approaches to Clinical Studies.

Pritee Chunarkar-Patil, Mohammed Kaleem, Richa Mishra, Subhasree Ray, Aftab Ahmad, Devvret Verma, Sagar Bhayye, Rajni Dubey, Himanshu Narayan Singh, Sanjay Kumar

Open access · goldAbstract readReview
In one paragraph

Review in Biomedicines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed
96.9field-weighted citation impact, top 1% of its field
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

137 citing papers in PubMed, 269 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

77 more citing papers are in PubMed but not listed here.

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

10 authors at 7 institutions in 4 countries.

Pritee Chunarkar-PatilDepartment of Bioinformatics, Rajiv Gandhi Institute of IT and Biotechnology, Bharati Vidyapeeth (Deemed to be University), Pune 411046, Maharashtra, India.ORCID 0000-0002-7705-8484
Mohammed KaleemDepartment of Pharmacology, Dadasaheb Balpande, College of Pharmacy, Nagpur 440037, Maharashtra, India.ORCID 0000-0003-4681-2031
Richa MishraDepartment of Computer Engineering, Parul University, Ta. Waghodia, Vadodara 391760, Gujarat, India.
Subhasree RayDepartment of Life Science, Sharda School of Basic Sciences and Research, Greater Noida 201310, Uttar Pradesh, India.
Aftab AhmadHealth Information Technology Department, The Applied College, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Devvret VermaDepartment of Biotechnology, Graphic Era (Deemed to be University), Dehradun 248002, Uttarkhand, India.
Sagar BhayyeDepartment of Bioinformatics, Rajiv Gandhi Institute of IT and Biotechnology, Bharati Vidyapeeth (Deemed to be University), Pune 411046, Maharashtra, India.ORCID 0000-0001-7441-8045
Rajni DubeyDivision of Cardiology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei 11031, Taiwan.ORCID 0000-0002-0506-7744
Himanshu Narayan SinghDepartment of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA.ORCID 0000-0003-4111-5165
Sanjay KumarBiological and Bio-Computational Lab, Department of Life Science, Sharda School of Basic Sciences and Research, Sharda University, Greater Noida 201310, Uttar Pradesh, India.ORCID 0000-0001-6296-0291
Bharati Vidyapeeth Deemed University · INSharda University · INColumbia University Irving Medical Center · USGraphic Era University · INKing Abdulaziz University · SAParul University · INTaipei Medical University Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Globally, malignancies cause one out of six mortalities, which is a serious health problem. Cancer therapy has always been challenging, apart from major advances in immunotherapies, stem cell transplantation, targeted therapies, hormonal therapies, precision medicine, and palliative care, and traditional therapies such as surgery, radiation therapy, and chemotherapy. Natural products are integral to the development of innovative anticancer drugs in cancer research, offering the scientific community the possibility of exploring novel natural compounds against cancers. The role of natural products like Vincristine and Vinblastine has been thoroughly implicated in the management of leukemia and Hodgkin's disease. The computational method is the initial key approach in drug discovery, among various approaches. This review investigates the synergy between natural products and computational techniques, and highlights their significance in the drug discovery process. The transition from computational to experimental validation has been highlighted through in vitro and in vivo studies, with examples such as betulinic acid and withaferin A. The path toward therapeutic applications have been demonstrated through clinical studies of compounds such as silvestrol and artemisinin, from preclinical investigations to clinical trials. This article also addresses the challenges and limitations in the development of natural products as potential anti-cancer drugs. Moreover, the integration of deep learning and artificial intelligence with traditional computational drug discovery methods may be useful for enhancing the anticancer potential of natural products.

Indexed as

anticancer drug discoveryclinical trialscomputational drug designdrug designmolecular dynamicsnatural product

Identifiers

PMID38255306
PMCPMC10813144
OpenAlexW4390906364

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.