Tehran University of Medical Sciences

Science Communicator Platform

Share By
Introducing Novel Screening Method for Natural Anticancer Compounds Through in Silico Investigation of Cancer Cell Targets Publisher



Ghavami G ; Jafari R ; Mohammadi A ; Muhammadnejad S ; Sardari S
Authors

Source: Health Biotechnology and Biopharma Published:2025


Abstract

The application of computational tools to predict protein targets of small molecules has gained prominence given that the rapid expansion of bioactivity databases. In this study, in silico procedures were used for high-throughput screening of 358 cancer cell targets. Structural similarity search methods with combinatorial docking approaches were utilized to investigate 82 candidate compounds from a plant source in order to explore their possible interactions with the pointed cancer cell targets. The interactions between the investigated ligands and receptors in the scope of the two mentioned databases were studied by docking process and evaluated based on the resulting scores of interaction energies. The resulting data demonstrated that 42 proteins in treated cancer cells with Morus alba. These findings could play a significant role in successful targeted based molecular therapy for cancer based on these natural products. © 2025 Elsevier B.V., All rights reserved.
Related Docs
View other Related Docs
1. New Phosphoramides Containing 2-Amino-1,4-Naphthaquinone Moiety As Anticancer and Antibacterial Agents: Experimental and Theoretical Evaluations, Process Biochemistry (2023)
2. Epigenetic-Based Cancer Therapeutics: New Potential Hdac8 Inhibitors, Journal of Biomolecular Structure and Dynamics (2022)
3. Repurposing of Compounds From Streptomyces Spp. As Potential Inhibitors of Aminoacyltransferase Fema: An Essential Drug Target Against Antibiotic-Resistant Staphylococcus Aureus, Current Computer-Aided Drug Design (2025)
Experts (# of related papers)
View all Related Experts
Massoud Amanlou (1)
Seyed Mohammad Ayyoubzadeh (1)
Other Related Docs
4. Discovery of Potential Fgfr3 Inhibitors Via Qsar, Pharmacophore Modeling, Virtual Screening and Molecular Docking Studies Against Bladder Cancer, Journal of Translational Medicine (2023)
5. Eschatological Scrutiny of Unprofessional Usage of Molecular Docking; How Unreliability in Computational Methods Arises From Amateurish Mistakes, Biocatalysis and Agricultural Biotechnology (2019)
6. Discovering Bioactive Pharmaceuticals From Natural Products for Type 2 Diabetes Mellitus Using Network Pharmacology, Molecular Docking, and Molecular Dynamics, Scientific Reports (2025)
7. Identification of Putative Drug Targets in Highly Resistant Gram-Negative Bacteria; and Drug Discovery Against Glycyl-Trna Synthetase As a New Target, Bioinformatics and Biology Insights (2023)
8. A New Sesquiterpenoid From the Shoots of Iranian Daphne Mucronata Royle With Selective Inhibition of Stat3 and Smad3/4 Cancer-Related Signaling Pathways, DARU# Journal of Pharmaceutical Sciences (2020)
9. Elucidating the Inhibitory Potential of Statins Against Oncogenic C-Met Tyrosine Kinase Through Computational and Cell-Based Studies, Iranian Journal of Pharmaceutical Research (2025)
10. The Role of Descriptors Extracted From Ligand-Target Interaction to Improve Conventional Qsar Model Performance in the Realm of Angiogenesis Receptor Modulation to Fight Cancer, Future Medicinal Chemistry (2025)
11. Molecular Docking As a Therapeutic Approach for Targeting Cancer Stem Cell Metabolic Processes, Frontiers in Pharmacology (2022)
12. In Silico Discovery of Novel Small-Molecule Pd-L1 Inhibitors Through a Multi-Stage Computational Workflow Integrating Machine Learning and Molecular Dynamics, Journal of Computer-Aided Molecular Design (2026)