Advances and Emerging Directions in Computational Protein Design

Computational protein design has rapidly evolved into a central tool in molecular biosciences, enabling the engineering of proteins with tailored stability, specificity, and function. Recent leaps in structural prediction, molecular simulation, and machine learning have drastically expanded our ability to explore and manipulate protein sequence–structure–function relationships. As biologics, enzymes, and synthetic proteins become increasingly important in medicine, biotechnology, and materials science, there is a growing need to integrate diverse computational approaches to accelerate discovery and deepen mechanistic understanding. This Research Topic aims to showcase current challenges and emerging opportunities in computational protein design. Key issues include improving stability and affinity prediction, integrating dynamics, advancing physics-based and data-driven models, and tightening the link between in silico design and experimental validation. With progress in generative models, structural prediction, adaptive simulations, and hybrid ML–physics methods, researchers can now probe protein sequence space with unprecedented detail. We welcome contributions introducing new methodologies, computational frameworks, or applications to biologically relevant systems that advance more predictive and generalizable design strategies.Areas of interest include, but are not limited to: • algorithmic and theoretical developments;• machine learning and AI-driven design;• molecular modeling and simulation;• integration of structure prediction with design workflows;• modeling of dynamics, allostery, and conformational ensembles;• computational enzyme engineering; design of antibodies and biologics;• and workflows that combine computation with high-throughput or structural experiments.Studies that bridge disciplines, such as structural biology, bioinformatics, chemistry, and biophysics, are particularly welcome, as are works offering transparent benchmarks, open-source tools, or reproducible computational pipelines. We encourage submissions of original research, method, perspective, review, and mini-review articles. Topic editors: Matheus Ferraz, Asim Bera Source: https://www.frontiersin.org/research-topics/79568/advances-and-emerging-directions-in-computational-protein-design