State of the Art of Protein Structure Prediction as of 2025, as Evaluated by CASP16

Advancements in modeling complexes involving proteins, nucleic acids, small molecules ligands, and more

Figure composed by the author from screenshots of publicly available plots and presentations.

I recently came across a great blog post by a company called Nexco Analytics, whose experts in molecular modeling took the time to summarize all the outcomes of CASP16 which took place in late 2024:

Peeking Into CASP16 and the Future of Biomolecular Structure Prediction

The article is very detailed, so I made a small semi-automated summary of it— and then I encourage you to go read Nexco’s post in detail to find out all numbers, statistics, and also several examples of structure predictions that reflect what works well and what works bad. Here I go!

Short Introduction

CASP16 reaffirmed the dominance of deep learning, particularly AlphaFold2 and AlphaFold3, in biomolecular structure prediction, achieving high reliability in protein domain folding, considered largely a solved problem. However, challenges persist in modeling large, complex assemblies and…