Preprint Hypothesis Version 1 Preserved in Portico This version is not peer-reviewed

# Half-a-century Burial of ρ, θ and φ in PDB

Version 1 : Received: 23 March 2021 / Approved: 24 March 2021 / Online: 24 March 2021 (13:39:24 CET)

How to cite: Li, W. Half-a-century Burial of ρ, θ and φ in PDB. Preprints 2021, 2021030590. https://doi.org/10.20944/preprints202103.0590.v1. Li, W. Half-a-century Burial of ρ, θ and φ in PDB. Preprints 2021, 2021030590. https://doi.org/10.20944/preprints202103.0590.v1.

## Abstract

Since the launch of Protein Data Bank (PDB) in 1971, Cartesian coordinate system (CCS) has been the default approach to specify atomic positions in biomolecular experimental structures with X, Y and Z. In 2020, a local spherical coordinate system (LSCS) approach was proposed as an alternative to CCS, i.e., ρ, θ and φ. Recently, the continued application of deep learning technology in protein structure prediction (PSP) saw a leap forward in the accuracy of PSP, as evidenced by AlphaFold of Google’s DeepMind. However, there still is room for the improvement of the performances of PSP algorithms to date. Given that geometrically, CCS and LSCS are like the two sides of a coin, this short article puts forward a hypothesis that the time is now ripe to end the half-a-century burial of ρ, θ and φ in PDB, and use them as LSCS features for the design of novel PSP algorithms in future.

## Keywords

Protein structure prediction; Deep learning; AlphaFold; Cartesian coordinate system; Spherical coordinate system

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