AlphaFold2 (AF2) and RoseTTaFold (RF) have revolutionized structural biology, serving as
highly reliable and effective methods for predicting protein structures. This article explores …

Peptides play a pivotal role in a wide range of biological activities through participating in up
to 40% protein–protein interactions in cellular processes. They also demonstrate remarkable …

Deep learning has made rapid advances in modelling molecular sequencing data. Despite
achieving high performance on benchmarks, it remains unclear to what extent deep learning …

Unspecific peroxygenases (UPOs) are fungal enzymes that attract significant attention for
their ability to perform versatile oxyfunctionalization reactions using H2O2. Unlike other …

Automated scientific discovery promises to accelerate progress across scientific domains,
but evaluating an agent's capacity for end-to-end scientific reasoning is challenging as …

We introduce ProteinWorkshop, a comprehensive benchmark suite for representation
learning on protein structures with Geometric Graph Neural Networks. We consider large …

Diffusion-based generative models have been successfully employed to create proteins with
novel structures and functions. However, the construction of such models typically depends …

The problem of protein structure determination is usually solved by X-ray crystallography.
Several in silico deep learning methods have been developed to overcome the high attrition …

Macrocycles are a promising therapeutic class. The incorporation of heterochiral and non-
natural chemical building-blocks presents challenges for rational design, however. With no …