Breakthrough methods in machine learning (ML), protein structure prediction, and novel
ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models …

The emergence of SARS-CoV-2 variants stressed the demand for tools allowing to interpret
the effect of single amino acid variants (SAVs) on protein function. While Deep Mutational …

Deep-learning (DL) methods like DeepMind's AlphaFold2 (AF2) have led to substantial
improvements in protein structure prediction. We analyse confident AF2 models from 21 …

Advanced protein structure prediction requires evolutionary information from multiple
sequence alignments (MSAs) from evolutionary couplings that are not always available …

Experimental structures are leveraged through multiple sequence alignments, or more
generally through homology-based inference (HBI), facilitating the transfer of information …

Understanding the mechanisms of protein function is indispensable for many biological
applications, such as protein engineering and drug design. However, experimental …

Predictions for millions of protein three-dimensional structures are only a few clicks away
since the release of AlphaFold2 results for UniProt. However, many proteins have so-called …

Since 1992, all state-of-the-art methods for fast and sensitive identification of evolutionary,
structural, and functional relations between proteins (also referred to as “homology …

Motivation CATH is a protein domain classification resource that exploits an automated
workflow of structure and sequence comparison alongside expert manual curation to …

Over the last 25 years, biology has entered the genomic era and is becoming a science of
'big data'. Most interpretations of genomic analyses rely on accurate functional annotations …