New drug production, from target identification to marketing approval, takes over 12 years
and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the …

The traditional computational modeling of protein structure, dynamics, and interactions
remains difficult for many protein systems. It is mostly due to the size of protein …

Deep-learning language models have shown promise in various biotechnological
applications, including protein design and engineering. Here we describe ProGen, a …

Protein design aims to build novel proteins customized for specific purposes, thereby
holding the potential to tackle many environmental and biomedical problems. Recent …

Whereas DNA viruses are known to be abundant, diverse, and commonly key ecosystem
players, RNA viruses are insufficiently studied outside disease settings. In this study, we …

Exploiting sequence–structure–function relationships in biotechnology requires improved
methods for aligning proteins that have low sequence similarity to previously annotated …

Abstract The MPI Bioinformatics Toolkit (https://toolkit. tuebingen. mpg. de) provides
interactive access to a wide range of the best‐performing bioinformatics tools and …

Language models have recently emerged as a powerful machine-learning approach for
distilling information from massive protein sequence databases. From readily available …

Highly accurate structure prediction methods are generating an avalanche of publicly
available protein structures. Searching through these structures is becoming the main …

Background HH-suite is a widely used open source software suite for sensitive sequence
similarity searches and protein fold recognition. It is based on pairwise alignment of profile …