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Pathogenicity patterns in cytochrome P450 family
Anna Špačková1,2, Nina Kadášová1, Ivana Hutařová Vařeková1,3
1Department of Physical Chemistry, Faculty of Science, Palacký University, Olomouc 771 46, Czech Republic.
Motivation:
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.
Results:
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.
Availability And Implementation:
Data and source code can be found at https://github.com/annaspac/P450_pathogenicity_codes.
Insights
Pathogenicity increases along protein tunnels towards cofactor binding sites in human cytochrome P450s (CYPs). This highlights the critical role of these pathways and cofactor interactions in maintaining enzyme function and drug metabolism.
Area of Science:
- Biochemistry
- Genetics
- Computational Biology
Background:
- Cytochrome P450 proteins are vital for human metabolism, including drug and hormone processing.
- Known variants often have limited experimental pathogenicity data, necessitating predictive approaches.
- Computational tools allow for predicting the impact of virtually all possible amino acid mutations.
Purpose of the Study:
- To comprehensively explore pathogenicity patterns within the human cytochrome P450 protein family.
- To identify key structural features influencing protein function and variant pathogenicity.
- To provide insights into disease-associated variants and drug metabolism.
Main Methods:
- Utilized SIFT, AlphaMissense, and PrimateAI-3D algorithms for pathogenicity analysis.
- Investigated human cytochrome P450 proteins.
- Employed MOLE software to identify protein tunnels.
Main Results:
- Pathogenicity shows a progressive increase along identified protein tunnels towards the cofactor binding site.
- The integrity of protein tunnels and the cofactor environment is crucial for enzymatic function.
- Single amino acid changes can disrupt molecular guidance to active sites, impacting protein function.
Conclusions:
- Structural pathways, particularly protein tunnels, are fundamental for cytochrome P450 functionality.
- Cofactor interactions are essential for maintaining enzymatic activity.
- Understanding these patterns aids in interpreting disease-associated variants and predicting drug metabolism efficacy.
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