AICZECHIA seminar: Learning to design protein-protein interactions with enhanced generalization

Datum / čas
Date(s) - 06.02.


Dear colleagues,

It is my pleasure to invite you to the next AICZECHIA seminar, which will be held online on Tuesday, 6.2. 2024 at 17:00. The speaker will be Anton Bushuiev, who will talk about a very fresh work just accepted to ICLR 2024 in the area of machine learning for molecular biology. The title and abstract are below. The talk will be accessible to non-specialists, so it should be a great opportunity to learn about this area.

The talk will be held online (Zoom link below) and the planned format is a 30 min talk followed by a 30 min open discussion session. The talk is open to the public so please distribute the announcement to your teams.

Zoom link:

Speaker: Anton Bushuiev

Affiliation: Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University

Title: Learning to design protein-protein interactions with enhanced generalization


Discovering mutations enhancing protein-protein interactions (PPIs) is critical for advancing biomedical research and developing improved therapeutics. While machine learning approaches have substantially advanced the field, they often struggle to generalize beyond training data in practical scenarios. The contributions of this work are three-fold. First, we construct PPIRef, the largest and non-redundant dataset of 3D protein-protein interactions, enabling effective large-scale learning. Second, we leverage the PPIRef dataset to pre-train PPIformer, a new SE(3)-equivariant model generalizing across diverse protein-binder variants. We fine-tune PPIformer to predict the effects of mutations on protein-protein interactions via a thermodynamically motivated adjustment of the pre-training loss function. Finally, we demonstrate the enhanced generalization of our new PPIformer approach by outperforming other state-of-the-art methods on new, non-leaking splits of standard labeled PPI mutational data and independent case studies optimizing a human antibody against SARS-CoV-2 and increasing the thrombolytic activity of staphylokinase.

To appear at the International Conference on Learning Representations (ICLR), 2024.

Anton Bushuiev is a first-year PhD student supervised by Josef Sivic at the Czech Institute of Informatics, Robotics and Cybernetics (CIIRC CTU). Anton obtained his bachelor’s and master’s degrees at the Czech Technical University in Prague, working on the applications of deep learning to cybersecurity and protein design. Anton’s current research focus is on developing machine learning models for practical drug design applications in collaboration with Loschmidt Laboratories at Masaryk University in Brno.