Most proteins in cells are composed of multiple folding units (or domains) to perform
complex functions in a cooperative manner. Relative to the rapid progress in single-domain …

Accurate predictions of the three-dimensional structures of proteins from their amino acid
sequences have come of age. AlphaFold, a deep learning-based approach to protein …

AlphaFold2 revolutionized structural biology with the ability to predict protein structures with
exceptionally high accuracy. Its implementation, however, lacks the code and data required …

Abstract AlphaFold2 (ref.) has revolutionized structural biology by accurately predicting
single structures of proteins. However, a protein's biological function often depends on …

Quantifying the pathogenicity of protein variants in human disease-related genes would
have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of …

Proteins are essential to life, and understanding their structure can facilitate a mechanistic
understanding of their function. Through an enormous experimental effort 1, 2, 3, 4, the …

Structure prediction for proteins lacking homologous templates in the Protein Data Bank
(PDB) remains a significant unsolved problem. We developed a protocol, CI-TASSER, to …

RNA molecules adopt three-dimensional structures that are critical to their function and of
interest in drug discovery. Few RNA structures are known, however, and predicting them …

Computational biology and bioinformatics provide vast data gold-mines from protein
sequences, ideal for Language Models (LMs) taken from Natural Language Processing …

Prediction of protein structure from sequence has been intensely studied for many decades,
owing to the problem's importance and its uniquely well-defined physical and computational …