Navigating the uncharted: AI-driven advances in protein structure, dynamics, interactions and ligand interactions for understudied families

Description

Shivani Singh, Ruhani Singh, and Sunita Sharma review artificial intelligence tools for studying neglected protein families in a 2026 article. Many protein groups lack lab structures, and older modeling methods struggle with them. Modern deep learning systems can now predict structures at near-lab quality, model how proteins bend and their disordered regions, and tackle contacts between proteins and between proteins and drug-like compounds.

Two case studies, covering orphan receptors and disordered regions, illustrate what the new tools can do for systems once considered hopeless. The authors also compare older and AI pipelines, summarize key model lines, and offer practice guidelines. Remaining challenges include lab validation, modeling movement, and ethical questions around generated data. The review serves as a roadmap for lighting up the dark parts of the protein world.

Catalog record

Source: https://europepmc.org/article/MED/PMC13523371