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Nature communications · 2026

Genomic landscape of drug binding and pharmacogenetic variation across diverse populations using SNPdrug3D.

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Malik Ashar J, Kenanov Dimitar, Chong Cheng-Shoong, Ozturk Mert Burak, Wang Qiqi, Chang Hong-Yun, Hebrard Maxime, Ho Ying Swan, Wang Zhenxun, Limviphuvadh Vachiranee, Miyajima Jhoann M T, Kannan Srinivasaraghavan, Magallanes Roberto Tirado, Sim Xueling, Chai Jin Fang, Davila Sonia, Yeo Khung Keong, Leong Khai Pang, Goh Liuh Ling, Karnani Neerja, Eriksson Johan Gunnar, Cheng Ching-Yu, Wong Tien Yin, Loh Marie, Dalan Rinkoo, Khor Chiea Chuen, Chew Guo-Liang, Lim Weng Khong, Ngeow Joanne, Chambers John C, Tai E Shyong, Bertin Nicolas, Tan Chris Soon Heng, Koh Judice, Tan Patrick, SG10K_Health Consortium, Verma Chandra S, Maurer-Stroh Sebastian

Аннотация

One of the promises of precision medicine is to understand and act on inter-individual genetic differences in drug responses. SNPdrug3D contains the complete genomic landscape of missense single nucleotide variants (SNV) across the human proteome and at a population-wide level that could affect drug binding. Here, we map SNVs in over 80,000 individuals from the Singapore SG10K Health and gnomAD cohorts to identify ~1.17 million variants mapped to residues near ~6000 bound drugs in protein-drug complexes and experimentally verify effects of selected SNVs, including previously uncharacterized variants, on drug binding in relevant proteins ranging from kinases to cytochrome P450s (CYPs). The latter led to a specific predictor for interpreting variants in the CYP family that outperforms existing tools in the prediction of pharmacogenetic effects based on database-annotated (AUROC = 0.9) or assay-based (AUROC = 0.8) test sets. By placing variants and drugs in structural contexts, SNPdrug3D aids drug development by pre-emptively flagging potential resistance sites based on population-specific variability.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты