Protein interactions are key in vital biological processes. In many cases, particularly in
regulation, this interaction is between a protein and a shorter peptide fragment. Such …

The state-of-the-art to assess the structural quality of docking models is currently based on
three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and …

Nanoparticle bioreactivity critically depends upon interaction between proteins and
nanomaterials (NM). The formation of the “protein corona”(PC) is the effect of such …

Peptide-protein interactions between a smaller or disordered peptide stretch and a folded
receptor make up a large part of all protein-protein interactions. A common approach for …

Motivation It is important to assess the quality of modeled biomolecules to benchmark and
assess the performance of different prediction methods. DockQ has emerged as the …

Alzheimer's disease is a progressive neurodegenerative disorder and as the exact cause of
the disease remains unknown, it still has no cure to date. Due to the fact that, until recently …

Background Protein-protein docking is a valuable computational approach for investigating
protein-protein interactions. Shape complementarity is the most basic component of a …

Motivation In recent years, the end-to-end deep learning method for single-chain protein
structure prediction has achieved high accuracy. For example, the state-of-the-art method …

Protein–protein interactions are the basis of many protein functions, and understanding the
contact and conformational changes of protein–protein interactions is crucial for linking the …

Transfer learning (TL) algorithms aim to improve the prediction performance in a target task
(eg the prediction of cisplatin sensitivity in triple-negative breast cancer patients) via …