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Accelerating Therapeutic Innovation: Advances in Computer-Aided Drug Discovery

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 25 September 2025 | Viewed by 150

Special Issue Editors


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Guest Editor
Department of Pharmacy, University of Naples Federico II, Via Domenico Montesano 49, 80131 Napoli, Italy
Interests: drug design; artificial intelligence; QSAR; molecular dynamics; molecular docking simulations

E-Mail Website
Guest Editor
Department of Pharmacy, “Drug Discovery Lab”, University of Naples “Federico II”, Via D. Montesano 49, 80131 Naples, Italy
Interests: drug discovery; medicinal chemistry; molecular modeling; polypharmacology; artificial intelligence; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue on Computer-Aided Drug Discovery and Design (CADD) aims to present the latest advances and applications of computational methods in modern drug discovery, considering the continuous improvement of high-performance computing technologies. The goal of CADD methods is to improve and accelerate the drug discovery process. This issue will cover a wide range of CADD techniques, including traditional structure- and ligand-based drug design, possibly complemented by innovative machine learning approaches. We invite submissions that explore the application of CADD to address new challenges in drug discovery, such as the identification of novel therapeutic agents. Emphasis will be placed on innovative strategies that have undergone experimental (in vitro) validation, effectively linking computational predictions to practical outcomes.

Dr. Pietro Delre
Prof. Dr. Antonio Lavecchia
Guest Editors

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Keywords

  • CADD
  • drug discovery
  • machine learning
  • virtual screening
  • drug-target interaction

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Published Papers (1 paper)

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Research

21 pages, 4579 KiB  
Article
Repurposing Biomolecules from Aerva javanica Against DDX3X in LAML: A Computer-Aided Therapeutic Approach
by Abdulaziz Asiri, Abdulwahed Alrehaily, Amer Al Ali, Mohammed H. Abu-Alghayth and Munazzah Tasleem
Int. J. Mol. Sci. 2025, 26(12), 5445; https://doi.org/10.3390/ijms26125445 - 6 Jun 2025
Abstract
Acute Myeloid Leukemia (LAML) is a life-threatening hematological malignancy, and the DEAD-box helicase 3 X-linked (DDX3X) gene is a potential yet underexplored target gene for LAML. Biomolecules derived from medicinal plants like Aerva javanica offer a great source of therapeutic candidates. [...] Read more.
Acute Myeloid Leukemia (LAML) is a life-threatening hematological malignancy, and the DEAD-box helicase 3 X-linked (DDX3X) gene is a potential yet underexplored target gene for LAML. Biomolecules derived from medicinal plants like Aerva javanica offer a great source of therapeutic candidates. This study aimed to investigate the role of DDX3X in LAML and identify plant-derived biomolecules that could inhibit DDX3X using computational approaches. Pan-cancer mutational profiling, a transcriptomic analysis, survival, protein–protein interaction networks, and a principal component analysis (PCA) were employed to elucidate functional associations and transcriptomic divergence. Subsequently, biomolecules from A. javanica were subjected to in silico screening using molecular docking and ADMET profiling. The docking protocol was validated using RK-33, a known DDX3X inhibitor. DDX3X was found to be linked to key leukemogenic pathways, including Wnt/β-catenin and MAPK signaling, indicating it to be a potential target. Molecular docking of A. javanica compounds revealed CIDs 15559724, 5490003, and 74819331 as potent DDX3X inhibitors with strong binding affinity and favorable pharmacokinetic and toxicity profiles compared to RK-33. This study highlights the importance of DDX3X in LAML pathogenesis and suggests targeting it using plant-derived inhibitors, which may require further in vitro and in vivo validation. Full article
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