Protein language models can capture protein quaternary state.

Background: Determining a protein's quaternary state, i.e. the number of monomers in a functional unit, is a critical step in protein characterization.

Matching protein surface structural patches for high-resolution blind peptide docking.

Peptide docking can be perceived as a subproblem of protein–protein docking. However, due to the short length and flexible nature of peptides, many do not adopt one defined conformation prior to binding. Therefore, to tackle a peptide docking problem, not only the relative orientation, but also the bound conformation of the peptide needs to be modeled.

Harnessing protein folding neural networks for peptide-protein docking.

Highly accurate protein structure predictions by deep neural networks such as AlphaFold2 and RoseTTAFold have tremendous impact on structural biology and beyond. Here, we show that, although these deep learning approaches have originally been developed for the in silico folding of protein monomers, AlphaFold2 also enables quick and accurate modeling of peptide-protein interactions. Our simple implementation of AlphaFold2 generates peptide-protein complex models without requiring multiple sequence alignment information for the peptide partner, and can handle binding-induced conformational changes of the receptor.

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks.

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met.

Traumatic Ulcerative Granuloma with Stromal Eosinophilia: CD30 analysis and clonality for T cell receptor gene re-arrangement.

Introduction: Traumatic Ulcerative Granuloma with Stromal Eosinophilia (TUGSE) is a rare oral ulcerated lesion of uncertain etiology, showing eosinophil-rich granulation tissue, with occasional large atypical CD30 positive mononuclear cells. It had been suggested that it may represent an oral counterpart of cutaneous lymphomatoid papulosis, with a potential to evolve into CD30 + T cell lymphoma OBJECTIVES: To compare TUGSE and non-specific oral ulcers (NSU) clinically, histopathologically and by clonality analysis for T-cell receptor re-arrangement, aiming to determine whether TGUSE with atypical cells is a lymphomatous premalignant condition, and whether therapeutic approach should be radical or conservative.

Materials And Methods: Retrospective archival analysis included 17 TUGSE and 8 NSU cases.