Year: 2025
Type: article
Abstract: With the growing number of AI-predicted protein structures, automated methods of broad-scale analysis are required to parse this volume of data. The application of mathematically defined topologies to protein science enables such analysis. Building on the foundation of lasso peptides, complex lasso motifs are their macroscopic analogs in proteins, promising novel discoveries in drug design and the biopolymer industry. Here we present AlphaLasso, a web server designed to find and analyze lasso-type topologies in protein structures. It finds cysteine, amide, ester, and thioester or user-specified closing bridges. The modern visualization interface provides extensive capabilities to study lasso motifs, such as structure smoothing, creating topology maps, searching for similar proteins, in-depth model evaluation, and metadata annotation. This rich feature set makes AlphaLasso a powerful tool useful in biology, biophysics, chemistry, and mathematics. To enable large-scale analysis, we have precomputed the lasso topologies of high-quality models from the AlphaFold Database, finding >14 million proteins with lasso motifs closed by cysteine bridges, 2.2 million of which are complex lassos. Lasso motifs classified by complexity are available to users via an interactive website, supporting comparison with user-submitted structures. AlphaLasso is available at https://alphalasso.cent.uw.edu.pl/.
Source: Nucleic Acids Research
DOI: 10.1093/nar/gkaf375
Institutions: SGH Warsaw School of Economics, University of Warsaw
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,992
Funder: Narodowe Centrum Nauki
Award: G528991778
OpenAlex ID: W4410190596