The rational design of new biomolecules, such as enzymes and therapeutic proteins, is essential for advancing medicine and creating sustainable chemical processes. However, conventional frameworks for discovering these molecules remain slow, fragmented, and largely rely on trial-and-error. This project promotes the progress of science by creating a new class of artificial intelligence (AI) models that can design complex biological molecules with unprecedented precision and speed. Specifically, this research will build an autonomous discovery engine that unifies the design of molecular sequences and their three-dimensional shapes into a single, self-improving system that can efficiently design molecules, learn from real-world experimental feedback, and continuously improve its own performance. By shifting the scientific process from manual orchestration to automated AI-driven discovery, this research will significantly reduce the time and cost required to develop life-saving therapeutics and sustainable biochemicals, thereby advancing the national health and prosperity. The project also contributes to the national interest by strengthening the biotechnology workforce through interdisciplinary training for students and public outreach programs that introduce young learners to the intersection of computer science and biology. Finally, all AI models, datasets, and software developed during this project will be shared publicly to broadly enhance the national research infrastructur