The expanding scale and inherent complexity of biological data have encouraged a growing
use of machine learning in biology to build informative and predictive models of the …

Stability is a key ingredient of protein fitness, and its modification through targeted mutations
has applications in various fields, such as protein engineering, drug design, and deleterious …

Understanding the effects of mutations on protein stability is crucial for variant interpretation
and prioritisation, protein engineering, and biotechnology. Despite significant efforts …

Most proteins fold into 3D structures that determine how they function and orchestrate the
biological processes of the cell. Recent developments in computational methods for protein …

Predicting the effect of missense variations on protein stability and dynamics is important for
understanding their role in diseases, and the link between protein structure and function …

Proteins are highly dynamic molecules, whose function is intrinsically linked to their
molecular motions. Despite the pivotal role of protein dynamics, their computational …

Abstract Knowledge of protein structure can be used to predict the phenotypic consequence
of a missense variant. Since structural coverage of the human proteome can be roughly …

Protein–protein Interactions are involved in most fundamental biological processes, with
disease causing mutations enriched at their interfaces. Here we present mCSM-PPI2, a …

In December 2019, an initial cluster of interstitial bilateral pneumonia emerged in Wuhan,
China. A human-to-human transmission was assumed and a previously unrecognized entity …

Here, we report a webserver for the improved SDM, used for predicting the effects of
mutations on protein stability. As a pioneering knowledge-based approach, SDM has been …