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Natural Products and Synthetic Molecules: Development of Novel Anticancer Drugs

A Special Issue of International Journal of Molecular Sciences (ISSN 1422-0067) belonging to the section "Bioactives and Nutraceuticals".

Deadline for manuscript submissions: 30 April 2027 | Viewed by 911

Editor


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Guest Editor
Research Laboratory of Natural Products and Bioactive Molecules, Nova Friburgo Health Institute, Fluminense Federal University—UFF, Nova Friburgo 28625-650, RJ, Brazil
Interests: microRNA; molecular sciences; biomedicines; brain sciences; non-coding RNA

Special Issue Information

Dear Colleagues,

The Special Issue aims to provide a comprehensive overview of recent advances and emerging challenges in anticancer drug discovery, bridging natural product research and synthetic chemistry with molecular and translational oncology.

This Special Issue welcomes original research articles and review papers focused on the discovery, characterization, and biological evaluation of anticancer agents derived from natural products, plant extracts, essential oils, synthetic molecules, and nature-inspired compounds. Particular emphasis is placed on studies reporting the identification, isolation, and chemical characterization of bioactive compounds from complex matrices, as well as on the rational design and optimization of synthetic and semi-synthetic molecules.

In addition, this Special Issue seeks to highlight innovative strategies in drug repurposing, aiming to identify new anticancer applications for approved or investigational drugs, supported by robust molecular and pharmacological evidence.

Contributions integrating molecular biology approaches to elucidate mechanisms of action, signaling pathways, cell cycle regulation, apoptosis, autophagy, and drug resistance are strongly encouraged. Studies employing in vitro, in vivo, and in silico models, including molecular docking, dynamics simulations, pharmacokinetic predictions, and systems biology approaches, are particularly welcome, provided they are supported by solid experimental validation.

Overall, this Special Issue aims to foster interdisciplinary research and stimulate discussion on current challenges and future perspectives in the development of safer, more effective, and mechanistically well-characterized anticancer drugs.

Suggested topics include the following:

  • Discovery of novel anticancer molecules from natural and synthetic sources;
  • Chemical characterization of bioactive compounds in plant extracts and essential oils;
  • Structure–activity relationship (SAR) and medicinal chemistry approaches;
  • Drug repurposing and repositioning strategies for cancer therapy;
  • Molecular mechanisms of anticancer activity;
  • In vitro and in vivo evaluation of anticancer efficacy and toxicity;
  • In silico modeling, molecular docking and pharmacokinetic prediction;
  • Resistance mechanisms and combination therapies;
  • Translational approaches in anticancer drug development.

Dr. Vinícius D’Ávila Bitencourt Pascoal
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • anticancer drugs
  • natural products
  • synthetic molecules
  • bioactive compounds
  • molecular biology

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Published Papers (1 paper)

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Research

24 pages, 4557 KB  
Article
PAD4-DB: A Curated Structure–Activity Resource Reveals Hub-Organized Activity Cliffs and Scaffold-Dependent SAR Ruggedness in PAD4 Inhibitors
by Nidhal Tarhouni, Ahmed Bayoudh, Amira Mahfoudhi, Bilel Hadrich, Karim Kriaa and Imen Kallel
Int. J. Mol. Sci. 2026, 27(18), 8302; https://doi.org/10.3390/ijms27188302 (registering DOI) - 17 Sep 2026
Viewed by 121
Abstract
Peptidylarginine deiminase 4 (PAD4) is an increasingly prominent therapeutic target in oncology, inflammatory disease, and neutrophil extracellular trap (NET)-associated pathologies, yet public bioactivity data for PAD4 inhibitors remain fragmented across multiple repositories with substantial redundancy and inconsistent annotation. Here, we present PAD4-DB, a [...] Read more.
Peptidylarginine deiminase 4 (PAD4) is an increasingly prominent therapeutic target in oncology, inflammatory disease, and neutrophil extracellular trap (NET)-associated pathologies, yet public bioactivity data for PAD4 inhibitors remain fragmented across multiple repositories with substantial redundancy and inconsistent annotation. Here, we present PAD4-DB, a curated structure–activity relationship resource integrating 3093 unique inhibitors (consensus pIC50 range 2.00–8.52; median 6.84) from PubChem, ChEMBL, and BindingDB through a reproducible pipeline encompassing structure standardization, activity normalization, source-independence assessment, and deduplication. Quantitative analysis of 358,416 compound pairs with Tanimoto similarity ≥0.6 indicates that the sampled PAD4 SAR landscape is predominantly smooth: only 94 pairs meeting the stringent activity-cliff criterion (Tanimoto ≥ 0.8; |ΔpIC50| ≥ 2.0) were identified, representing 0.026% of all related pairs and 0.78% of the 12,071 cliff-candidate pairs. Of these, 80 (85.1%) received structural support from matched molecular pair (MMP) analysis. Severe cliffs were non-randomly distributed, with four hub compounds collectively accounting for 53.2% of all severe cliff pairs, while 96.8% of multi-member scaffold series remained completely smooth. Provenance analysis further showed that 82.9% of the dataset was classified as pipeline-dependent under the provenance-scoring framework across repositories rather than independent source measurements, underscoring the importance of provenance-aware confidence weighting in downstream modeling. PAD4-DB therefore provides a reproducible foundation for PAD4 inhibitor discovery and a curated benchmark for evaluating similarity-based and machine-learning approaches in a chemically structured SAR landscape containing rare but highly concentrated activity cliffs. Full article
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