Fast uncovering of protein sequence diversity from structure<sup>*</sup>

Abstract We present InvMSAFold, an inverse folding method for generating protein sequences that is optimized for diversity and speed. For a given structure, InvMSAFold generates the parameters of a probability distribution over the space of sequences with pairwise interactions, capturing the amino acid covariances observed in Multiple Sequence Alignments (MSA) of homologous proteins. This allows for the efficient generation of highly diverse protein sequences while preserving structural and functional integrity. We show that this increased diversity in sampled sequences translates into greater variability in biochemical properties, highlighting the exciting potential of our method for applications such as protein design. The orders of magnitude improvement in sampling speed compared to existing methods unlocks new possibilities for high-throughput virtual screening.

Authors

Institutions

Publication Details

Journal
Journal of Statistical Mechanics Theory and Experiment
Published
2025-08-01
DOI
https://doi.org/10.1088/1742-5468/adf0e7
Citations
1
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
0.81
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fast uncovering of protein sequence diversity from structure*

Carlo Lucibello, Christoph Feinauer, Barthelemy Meynard-Piganeau, Luca Alessandro Silva
1 citations
Journal of Statistical Mechanics Theory and Experiment
RNA and protein synthesis mechanisms
0.81
article

Fast uncovering of protein sequence diversity from structure*

Carlo Lucibello, Christoph Feinauer, Barthelemy Meynard-Piganeau, Luca Alessandro Silva
article en
1 citations

Abstract

Abstract We present InvMSAFold, an inverse folding method for generating protein sequences that is optimized for diversity and speed. For a given structure, InvMSAFold generates the parameters of a probability distribution over the space of sequences with pairwise interactions, capturing the amino acid covariances observed in Multiple Sequence Alignments (MSA) of homologous proteins. This allows for the efficient generation of highly diverse protein sequences while preserving structural and functional integrity. We show that this increased diversity in sampled sequences translates into greater variability in biochemical properties, highlighting the exciting potential of our method for applications such as protein design. The orders of magnitude improvement in sampling speed compared to existing methods unlocks new possibilities for high-throughput virtual screening.

Journal of Statistical Mechanics Theory and ExperimentVol. 2025(8)
Sorbonne Université (FR), Biologie Computationnelle, Quantitative et Synthétique (FR), Bocconi University (IT)
Openalex Percentile: Top 25%
RNA and protein synthesis mechanisms
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Fast uncovering of protein sequence diversity from structure<sup>*</sup> — Carlo Lucibello, Christoph Feinauer, et al. · Journal of Statistical Mechanics Theory and Experiment (2025) | TGRS Research Map | TGRS