About this Research Topic
This Research Topic aims to investigate all aspects of the rapidly advancing field of AI and computer-aided drug design, ranging from ligand-based studies to structure-based studies for discovering drugs against tropical diseases. In addition, the scope of this special issue also incorporates all aspects of molecular modelling and computational chemistry relating to the design of drugs against tropical diseases, such as pharmacophore modelling, molecular docking, QSAR, and molecular dynamics simulations.
Therefore, this topic welcomes submissions relating to the following subthemes:
- Ligand-based studies: Exploration of pharmacophore modeling, quantitative structure-activity relationship (QSAR) analysis, and virtual screening strategies using drug-likeness studies and ADMET characteristics for identifying potential drug candidates against tropical diseases such as malaria, dengue fever, Zika virus, chikungunya, and leishmaniasis.
- Structure-based studies: Utilization of molecular docking, molecular dynamics simulations, and free energy calculations to investigate the interaction between drug molecules and target proteins/enzymes involved in tropical diseases like schistosomiasis, trypanosomiasis (African sleeping sickness), filariasis, tuberculosis, and leprosy.
- Artificial intelligence (AI) techniques: Novel applications of AI in protein structure prediction, bioactivity prediction, toxicity prediction, physicochemical property prediction, and other relevant areas to enhance drug discovery efforts for tropical diseases, including yellow fever, Japanese encephalitis, Buruli ulcer, and Chagas disease.
- Comparative computational studies: Comparative analyses of experimental findings and computational predictions of biological activity for compounds targeting tropical diseases, providing valuable insights and validation of computational approaches for diseases like Chagas disease, schistosomiasis, malaria, leishmaniasis, and dengue fever.
- Breakthroughs in AI for drug discovery: Contributions focusing on the use of AI in clinical trial design and monitoring, prediction of drug-drug interactions, identification of drug repurposing opportunities, and other emerging areas that have the potential to revolutionize the field of tropical disease drug discovery in diseases such as Ebola virus, Chagas disease, schistosomiasis, leishmaniasis, and African trypanosomiasis.
Keywords: pharmacophore modelling, molecular docking, artificial intelligence, deep learning, machine learning
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.