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Bibliographic Details
Main Authors: Scott, Cory B., Rothschild, Charlie, Nye, Benjamin
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2508.11641
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author Scott, Cory B.
Rothschild, Charlie
Nye, Benjamin
author_facet Scott, Cory B.
Rothschild, Charlie
Nye, Benjamin
contents We introduce a pipeline for representing a protein, or protein complex, as the union of signed distance functions (SDFs) by representing each atom as a sphere with the appropriate radius. While this idea has been used previously as a way to render images of proteins, it has not, to our knowledge, been widely adopted in a machine learning setting. Mirroring recent successful work applying SDFs to represent 3D geometry, we present a proof of concept that this representation of proteins could be useful in several biologically relevant applications. We also propose further experiments that are necessary to validate the proposed approach.
format Preprint
id arxiv_https___arxiv_org_abs_2508_11641
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Implicitly and Differentiably Representing Protein Surfaces and Interfaces
Scott, Cory B.
Rothschild, Charlie
Nye, Benjamin
Biomolecules
We introduce a pipeline for representing a protein, or protein complex, as the union of signed distance functions (SDFs) by representing each atom as a sphere with the appropriate radius. While this idea has been used previously as a way to render images of proteins, it has not, to our knowledge, been widely adopted in a machine learning setting. Mirroring recent successful work applying SDFs to represent 3D geometry, we present a proof of concept that this representation of proteins could be useful in several biologically relevant applications. We also propose further experiments that are necessary to validate the proposed approach.
title Implicitly and Differentiably Representing Protein Surfaces and Interfaces
topic Biomolecules
url https://arxiv.org/abs/2508.11641