Publications by Freyr Sverrisson

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The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols an ...

Physical interactions between proteins are essential for most biological processes governing life. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This k ...

In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies. The first chapter introduces th ...

The present application relates to a computer-implemented systems and methods for protein interaction design using surface fingerprints. The method comprises predicting at least one target interface site with high binding propensity, wherein, optionally, t ...

Proteins' biological functions are defined by the geometric and chemical structure of their 3D molecular surfaces. Recent works have shown that geometric deep learning can be used on mesh-based representations of proteins to identify potential functional s ...

The present invention concerns a computer-system-implemented method for predicting properties of a protein molecule, comprising the steps of: receiving an input representation of the protein molecule; applying a surface generator to produce a molecular sur ...

Freyr Sverrisson

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Rosetta FunFolDes - A general framework for the computational design of functional proteins

De novo design of protein interactions with learned surface fingerprints

Predicting protein interactions using geometric deep learning on protein surfaces

Systems and methods for de novo design of protein interactions with learned surface fingerprints

Fast end-to-end learning on protein surfaces

A method and system for fast end-to-end learning on protein surfaces

Decrypting interaction fingerprints in protein molecular surfaces

De Novo Design of Site-specific Protein Binders Using Surface Fingerprints