# Charge Transfer Database for Bio-molecule Tight Binding Model Derived from Thousands of Proteins

## TL;DR

This study presents a comprehensive database of charge transfer couplings in proteins, derived from thousands of structures, revealing complex preferences and the limitations of using average structures for understanding charge transfer in bio-molecules.

## Contribution

It provides the first large-scale, data-driven database of amino acid pairwise charge transfer couplings from real protein structures, highlighting the complexity and variability in charge transfer preferences.

## Key findings

- Distinct charge transfer features among amino acid pairs
- Average structures are insufficient to represent charge transfer preferences
- Charge transfer couplings correlate with structural similarity

## Abstract

The anisotropic feature of charge transfer reactions in realistic proteins cannot be ignored, due to the highly complex chemical structure of bio-molecules. In this work, we have performed the first large-scale quantitative assessment of charge transfer preference in protein complexes by calculating the charge transfer couplings in all 20*20 possible amino acid side chain combinations, which are extracted from available high-quality structures of thousands of protein complexes. The charge transfer database quantitatively shows distinct features of charge transfer couplings among millions of amino acid side-chains combinations. The knowledge graph of charge transfer couplings reveals that only one average or representative structure cannot be regarded as the typical charge transfer preference in realistic proteins. This data driven model provides us an alternative route to comprehensively understand the pairwise charge transfer coupling parameters based structural similarity, without any require of the knowledge of chemical intuition about the chemical interactions.

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Source: https://tomesphere.com/paper/1802.07873