Fotografi av Björn Wallner

Björn Wallner

Professor, Avdelningschef

Computational structural bioinfoinformatics - protein structure prediction, modelling, and dynamics

Presentation

Professor and e-Science Faculty Björn Wallner, focusing on protein structure prediction, modelling and dynamics using AI and machine learning. 

He was the first to develop the multiple sequence sequence embeddings for deep learning applications, which now form the basis for AlphaFold. He has been deeply involved in developing the Rosetta software suite for modelling macromolecules. He successfully integrated sparse proximity constraints to achieve unprecedented accuracy, enabling molecular dynamics studies of proteins without known structure.

He has used computational modelling combined with experimental techniques to study mutation-dependent conformational ensembles in the P. Aeruginosa gene regulator MexR, responsible for antibiotic resistance. By combining explicit modelling of atomic interactions with ambiguous distance constraints for the first time he described the interaction between the disorded Myc protein to Pin1 at the molecular level.

In parallel he developed a predictor of local coordinate error of protein structure models that was ranked no 1 in the community-wide benchmark CASPs. The local error estimates have been incorporated into the Phaser software for molecular replacement making it possible to now solve the crystallographic phase problem for more targets using less accurate models. He has predicted protein-protein interactions combining structural comparison and modeling with sequence data and AI to pinpoint evolutionary events responsible for interactions. Recent publications in Bioinformatics, Structure and Nature Structural and Molecular Biology For recent publications: .Google Scholar

Publikationer

2024

Claudio Mirabello, Björn Wallner, Bjorn Nystedt, Stavros Azinas, Marta Carroni (2024) Unmasking AlphaFold to integrate experiments and predictions in multimeric complexes Nature Communications, Vol. 15, Artikel 8724 (Artikel i tidskrift) Vidare till DOI
Claudio Mirabello, Björn Wallner (2024) DockQ v2: improved automatic quality measure for protein multimers, nucleic acids, and small molecules Bioinformatics, Vol. 40, Artikel btae586 (Artikel i tidskrift) Vidare till DOI
Johannes Salomonsson, Björn Wallner, Linda Sjöstrand, Padraig D´arcy, Maria Sunnerhagen, Alexandra Ahlner (2024) Transient interdomain interactions in free USP14 shape its conformational ensemble Protein Science, Vol. 33, Artikel e4975 (Artikel i tidskrift) Vidare till DOI
Ceylan Sonmez, Beatrice Toia, Patrik Eickhoff, Andreea Medeea Matei, Michael El Beyrouthy, Björn Wallner, Max E. Douglas, Titia de Lange, Francisca Lottersberger (2024) DNA-PK controls Apollo's access to leading-end telomeres Nucleic Acids Research, Vol. 52, s. 4313-4327 (Artikel i tidskrift) Vidare till DOI

2023

Björn Wallner (2023) AFsample: improving multimer prediction with AlphaFold using massive sampling Bioinformatics, Vol. 39, Artikel btad573 (Artikel i tidskrift) Vidare till DOI

Nyheter

Publikationer

2024

Claudio Mirabello, Björn Wallner, Bjorn Nystedt, Stavros Azinas, Marta Carroni (2024) Unmasking AlphaFold to integrate experiments and predictions in multimeric complexes Nature Communications, Vol. 15, Artikel 8724 (Artikel i tidskrift) Vidare till DOI
Claudio Mirabello, Björn Wallner (2024) DockQ v2: improved automatic quality measure for protein multimers, nucleic acids, and small molecules Bioinformatics, Vol. 40, Artikel btae586 (Artikel i tidskrift) Vidare till DOI
Johannes Salomonsson, Björn Wallner, Linda Sjöstrand, Padraig D´arcy, Maria Sunnerhagen, Alexandra Ahlner (2024) Transient interdomain interactions in free USP14 shape its conformational ensemble Protein Science, Vol. 33, Artikel e4975 (Artikel i tidskrift) Vidare till DOI