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bioRxiv · 10.1101/2022.05.25.493427

NeRFax: An efficient and scalable conversion from the internal representation to Cartesian space

Dutton, O.·Hoffmann, F.·Tamiola, K.
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Abstract

MotivationAccurate modelling of protein ensembles requires sampling of a large number of 3D conformations. A number of sampling approaches that use internal coordinates have been proposed, yet poor performance in the conversion from internal to Cartesian coordinates limits their applicability. ResultsWe describe here NeRFax, an efficient method for the conversion from internal to Cartesian coordinates that utilizes the platform-agnostic JAX Python library. The relative benefit of NeRFax is demonstrated here, on peptide chain reconstruction tasks. Our novel approach offers 35-175x times performance gains compared to previous state-of-the-art methods, whereas >10,000x speedup is reported in a reconstruction of a biomolecular condensate of 1,000 chains. AvailabilityNeRFax has purely open-source dependencies and is available at https://github.com/PeptoneLtd/nerfax. Contactoliver@peptone.io

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Dutton, O., Hoffmann, F., Tamiola, K.. 2022-05-29. NeRFax: An efficient and scalable conversion from the internal representation to Cartesian space. https://doi.org/10.1101/2022.05.25.493427

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