Sarveswara Rao Vangala

This work introduces TRACEDD, a tool-first multi-agent framework in which large language models serve as the reasoning and orchestration layer while domain-validated computational tools supply structural, chemical, pharmacological, and synthetic predictions, and it demonstrates an end-to-end JAK2 workflow spanning target validation, structure retrieval or AlphaFold prediction, druggable pocket identification, reinforcement-learning-based de novo molecular generation, lead optimization, ADMET and bioactivity evaluation, literature evidence integration, and retrosynthesis planning, with each decision linked to explicit tool invocations and intermediate evidence.

This work introduces TRACEDD, a tool-first multi-agent framework in which large language models serve as the reasoning and orchestration layer while domain-validated computational tools supply structural, chemical, pharmacological, and synthetic predictions, and it demonstrates an end-to-end JAK2 workflow spanning target validation, structure retrieval or AlphaFold prediction, druggable pocket identification, reinforcement-learning-based de novo molecular generation, lead optimization, ADMET and bioactivity evaluation, literature evidence integration, and retrosynthesis planning, with each decision linked to explicit tool invocations and intermediate evidence.