CJ
chimaobi james ononamadu
Natural Product and Computer-aided Research Unit, Department of Biochemistry and Forensic Science, Nigeria Police Academy, Wudil
Kano State, Nigeria
About this Research Topic
Background
Tropical disease drug discovery is an interdisciplinary field at the intersection of medicinal chemistry, computational biology, and global health. Despite decades of medical innovation, drug discovery and development for NTDs has lagged behind those for other diseases of low- and middle-income countries. The persistence and spread of these diseases are exacerbated by the emergence of drug resistance, limited access to effective therapies, and the slow pace of novel intervention development. While natural products have delivered several cornerstone therapeutics, their complex structures, scarcity, and the labor-intensive process of isolating bioactive compounds still hamper rapid drug discovery. Advances in computer-aided drug discovery (CADD) – such as virtual screening, molecular modeling, and machine learning – offer hope for accelerating the translation of natural product diversity into effective leads. However, key questions persist regarding the integration of these approaches, prioritization of targets, and transferability of computational models to the rich but underexplored landscape of natural products.
Recent research has demonstrated the potential for combining natural product discovery with cutting-edge computational methods to identify novel drug candidates and unravel their molecular mechanisms. High-throughput genomic and proteomic analyses have started to illuminate new druggable targets within tropical pathogens, while in silico approaches increasingly guide the prioritization of natural extracts and compounds for experimental validation. Furthermore, machine learning models enable rapid prediction of pharmacological activity, toxicity, and resistance, significantly reducing the attrition rate in early-stage discovery. Yet, there are substantial gaps in harnessing the full richness of plant, marine, and microbial natural products – particularly in adapting computational tools to account for their unique chemical properties and the complex, often multi-targeted nature of their bioactivity.
This Research Topic aims to advance the integration of natural product chemistry and computer-aided drug discovery to accelerate therapeutic innovation for tropical diseases. We seek investigations that address critical questions such as the identification of novel druggable targets through pathogen genomics and bioinformatics, the development of AI models using natural product-specific datasets, and the application of systems-level computational approaches to elucidate multi-target effects of complex extracts. By bridging ethnopharmacology and modern computational workflows, we strive to foster collaborative research that leads to safer, more effective, and resistance-resilient therapies aligned with global health priorities.
The scope of this Research Topic encompasses basic, translational, and applied research uniting natural product-based approaches and computational methodologies to confront the challenges of tropical diseases. Research predominantly focused on non-tropical or non-infectious diseases will fall outside this domain. We welcome contributions addressing, but not limited to, the following themes:
• Computational identification and characterization of novel druggable targets in tropical pathogens;
• Virtual screening and in silico prioritization of natural product libraries for antitropical disease activity;
• Mechanistic studies disentangling how natural products or derivatives interact with pathogen-specific molecular targets;
• Application of AI, machine learning, and predictive modeling for activity, ADMET, and toxicity profiling of natural products;
• Integrated workflows combining phytochemistry, bioassay-guided fractionation, and computational target prediction;
• Discovery and optimization of marine and microbial natural products using computational and cheminformatic tools;
• Network pharmacology and polypharmacology analyses revealing multi-target or synergistic mechanisms;
• Computational design of natural product-inspired therapeutics to overcome resistance mutations;
• Preclinical and clinical investigations involving natural products or semi-synthetic derivatives targeting tropical diseases.
Submissions will be deemed out of scope if they are in silico-only without experimental or clinical validation, advance uncharacterized multi-herb efficacy claims, or rely on non-mechanistic anecdotal evidence.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
- Brief Research Report
- Case Report
- Classification
- Clinical Trial
- Community Case Study
- Curriculum, Instruction, and Pedagogy
- Data Report
- Editorial
- FAIR² Data
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Keywords: Computer-Aided Drug Design (CADD), Natural Product Discovery, Anti-protozoal Agents, Neglected Tropical Diseases (NTDs), Molecular Docking and Dynamics, Structure-Activity Relationship (SAR), Target Identification and Validation
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
