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Pathogenicity Patterns in Cytochrome P450 Family

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AbstractMotivationCytochrome P450 proteins play a crucial role in human metabolism, from the production of hormones 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 allows one to extend the scope to virtually mutate all amino acids with missense 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 and AlphaMissense algorithms.ResultsOur 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, tunnel integrity 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.AvailabilityData and source code can be found athttps://github.com/annaspac/P450_pathogenicity_codesContactanna.spackova@upol.cz,karel.berka@upol.cz
Title: Pathogenicity Patterns in Cytochrome P450 Family
Description:
AbstractMotivationCytochrome P450 proteins play a crucial role in human metabolism, from the production of hormones 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 allows one to extend the scope to virtually mutate all amino acids with missense 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 and AlphaMissense algorithms.
ResultsOur 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, tunnel integrity 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.
AvailabilityData and source code can be found athttps://github.
com/annaspac/P450_pathogenicity_codesContactanna.
spackova@upol.
cz,karel.
berka@upol.
cz.

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