Special Issue: Advances in Bioorganic Molecules for Anticancer Drug Development

Guest Editors:    

Dr. Luciano Porto Kagami, Faculty of Pharmacy, Laboratory of Medicinal Organic Synthesis – LaSOM®, Federal University of Rio Grande do Sul, Brazil

Dr. Aamir Saeed Malik, Professor, Department of Computer Systems, Faculty of Information Technology, Brno University of Technology (BUT), Czech Republic

Dr. Francisco Javier Ramírez-Arias, Professor, Faculty of Engineering Sciences and Technology,  Autonomous University of Baja California, Mexico

Manuscript Submission Deadline: July 15, 2026

Bioorganic chemistry is emerging as a powerful driver of next-generation anticancer therapies, offering molecular designs that overcome many limitations of conventional chemotherapeutics, such as poor selectivity, high toxicity, and drug resistance. Bioorganic molecules—derived from natural products or rational synthetic strategies—provide rich structural diversity that enables precise interactions with cancer-related biological targets, improving efficacy while reducing adverse effects. Rapid advances in molecular modeling, high-throughput screening, biomolecular engineering, and nanotechnology have accelerated their discovery and optimization, enhancing stability, bioavailability, and tumor-specific targeting through smart delivery systems and multifunctional nanoscale carriers.

The future of bioorganic anticancer drug discovery lies in interdisciplinary integration, combining synthetic chemistry, computational modeling, AI-driven design, omics-guided profiling, and personalized medicine approaches. These strategies enable more accurate target identification, prediction of biological interactions, and rational optimization to address tumor heterogeneity and resistance. Despite ongoing challenges—such as delivery barriers, toxicity, metabolic instability, and limited translational validation—continued convergence of experimental, computational, and clinical insights is rapidly advancing the field. This Special Issue invites high-quality experimental, computational, and translational contributions that address molecular design, predictive modeling, delivery strategies, and clinical relevance, with the goal of accelerating the translation of bioorganic molecules into safer, more effective, and patient-centered cancer therapies.

Suggested topic areas include, among others:

• Machine Learning Approaches in Designing Bioorganic Frameworks for Precision Oncology.
• Molecular Modeling and Simulation for Bioorganic Drug Discovery in Cancer Therapy.
• Nanotechnology-Enabled Delivery Systems for Bioorganic Anticancer Agents.
• Smart Delivery Mechanisms for Next-Generation Anticancer Therapeutics.
• Dynamic Simulations for Optimizing Bioorganic Molecules in Tumor-Targeted Therapies.
• Immunomodulatory Potential of Bioorganic Molecules in Cancer Therapeutics.
• Biomolecular Engineering for Tailored Bioorganic Molecules in Tumor Suppression.
• Predictive Analytics for Personalized Cancer Drug Discovery.
• Computational Docking Strategies in Anticancer Bioorganic Molecule Optimization.
• Structure-Activity Relationship Modeling in Advanced Oncology Research.
• Targeting Tumor Heterogeneity with Multifunctional Bioorganic Drug Systems.
• Sustainable Strategies for Translating Bioorganic Molecules into Clinical Anticancer Practice.

Please see our Instructions to authors here (/author-instructions/CBT) for manuscript questions. 

Please use manuscript type Advances in Bioorganic Molecules when submitting to the CBT Sage Track Submission site.  (https://mc.manuscriptcentral.com/cancerbiotherapy)