Novel machine learning approaches revolutionize protein knowledge
Breakthrough methods in machine learning (ML), protein structure prediction, and novel
ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models …
ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models …
AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms
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 …
improvements in protein structure prediction. We analyse confident AF2 models from 21 …
Embeddings from protein language models predict conservation and variant effects
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 …
the effect of single amino acid variants (SAVs) on protein function. While Deep Mutational …
Protein language-model embeddings for fast, accurate, and alignment-free protein structure prediction
Advanced protein structure prediction requires evolutionary information from multiple
sequence alignments (MSAs) from evolutionary couplings that are not always available …
sequence alignments (MSAs) from evolutionary couplings that are not always available …
Contrastive learning on protein embeddings enlightens midnight zone
Experimental structures are leveraged through multiple sequence alignments, or more
generally through homology-based inference (HBI), facilitating the transfer of information …
generally through homology-based inference (HBI), facilitating the transfer of information …
Computational approaches to predict protein functional families and functional sites
Understanding the mechanisms of protein function is indispensable for many biological
applications, such as protein engineering and drug design. However, experimental …
applications, such as protein engineering and drug design. However, experimental …
Nearest neighbor search on embeddings rapidly identifies distant protein relations
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 …
structural, and functional relations between proteins (also referred to as “homology …
SETH predicts nuances of residue disorder from protein embeddings
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 the release of AlphaFold2 results for UniProt. However, many proteins have so-called …
[PDF][PDF] CATHe: detection of remote homologues for CATH superfamilies using embeddings from protein language models
Motivation CATH is a protein domain classification resource that exploits an automated
workflow of structure and sequence comparison alongside expert manual curation to …
workflow of structure and sequence comparison alongside expert manual curation to …
A roadmap for the functional annotation of protein families: a community perspective
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 …
'big data'. Most interpretations of genomic analyses rely on accurate functional annotations …