# Pathogenicity patterns in cytochrome P450 family

**Authors:** Anna Špačková, Nina Kadášová, Ivana Hutařová Vařeková, Karel Berka

PMC · DOI: 10.1093/bioadv/vbaf231 · Bioinformatics Advances · 2025-10-14

## TL;DR

This paper explores how mutations in cytochrome P450 proteins affect their function, revealing patterns linked to structural tunnels and cofactor interactions.

## Contribution

The study identifies pathogenicity patterns in cytochrome P450 proteins by analyzing mutations across structural tunnels and cofactor binding sites.

## Key findings

- Pathogenicity increases along protein tunnels toward cofactor binding sites.
- Single amino acid changes can disrupt molecular pathways to active sites.
- Structural pathways are critical for maintaining cytochrome P450 functionality.

## Abstract

Cytochrome P450 proteins play a crucial role in human metabolism, ranging from hormone production to drug metabolism. While multiple commonly known variants have known effects on the individual cytochrome P450 protein performance, the pathogenicity information is usually experimentally limited to only a few mutations. Current pathogenicity prediction software enables the extension of the scope to virtually mutate all amino acids with all possible substitutional mutations. In this work, we do a comprehensive exploration that unveils pathogenicity patterns in the human cytochrome P450 family. Pathogenicity analysis was conducted across proteins using SIFT, AlphaMissense, and PrimateAI-3D algorithms.

Our findings indicate a progressive increase in pathogenicity along protein tunnels—identified via MOLE—toward the cofactor binding site, underscoring the essential role of cofactor interactions in enzymatic function. Notably, the integrity of tunnels and cofactor environment emerges as a critical factor, with even single amino acid alterations potentially disrupting molecular guidance to active sites. These insights highlight the fundamental role of structural pathways in preserving cytochrome P450 functionality, with implications for understanding disease-associated variants and drug metabolism.

Data and source code can be found at https://github.com/annaspac/P450_pathogenicity_codes.

## Linked entities

- **Proteins:** CYP71B9 (cytochrome P450, family 71, subfamily B, polypeptide 9)

## Full-text entities

- **Genes:** CYP2B6 (cytochrome P450 family 2 subfamily B member 6) [NCBI Gene 1555] {aka CPB6, CYP2B, CYP2B7, CYPIIB6, EFVM, IIB1}
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12534787/full.md

## References

43 references — full list in the complete paper: https://tomesphere.com/paper/PMC12534787/full.md

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Source: https://tomesphere.com/paper/PMC12534787