Adaptive Protein Design and Optimization (APDO): An Energy-Driven Framework for Protein Structure Optimization

Abstract

Description Adaptive Protein Design and Optimization (APDO) is a lightweight, modular research framework that demonstrates how protein-like three-dimensional structures can emerge purely through adaptive energy minimization. Unlike traditional protein folding pipelines that rely on computationally expensive molecular dynamics or physics-heavy force fields, APDO operates on a simplified energy landscape and iterative optimization loop. Despite its abstraction, the framework consistently converges toward lower-energy, structured conformations from random initial states. This project provides a proof-of-concept that protein structure optimization is fundamentally governed by energy landscapes rather than simulation fidelity. APDO is designed for research, education, and experimentation in protein design, molecular optimization, and AI-driven scientific discovery. Key Contributions Demonstrates energy-driven emergence of protein-like structures Fully modular architecture (energy, optimization, core logic) Lightweight and reproducible on standard CPU environments Extendable to ML-based energy models and hybrid pipelines Applications Protein design • Molecular optimization • Computational biology education • AI-assisted scientific modeling Keywords Protein Design, Energy Minimization, Computational Biology, Optimization Algorithms, AI for Science, Protein Folding, Structural Biology License MIT License https://github.com/pksms078-ai/Adaptive-Protein-Design-and-Optimization-APDO-/releases/tag/APDO1