Structural and functional prediction, evaluation, and validation in the post-sequencing era
The surge of genome sequencing data has underlined substantial genetic variants of uncertain significance (VUS). The decryption of VUS discovered by sequencing poses a major challenge in the post-sequencing era. Although experimental assays have progressed in classifying VUS, only a tiny fraction of...
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Elsevier
2024-12-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037023005056 |
| _version_ | 1797372121578471424 |
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| author | Chang Li Yixuan Luo Yibo Xie Zaifeng Zhang Ye Liu Lihui Zou Fei Xiao |
| author_facet | Chang Li Yixuan Luo Yibo Xie Zaifeng Zhang Ye Liu Lihui Zou Fei Xiao |
| author_sort | Chang Li |
| collection | DOAJ |
| description | The surge of genome sequencing data has underlined substantial genetic variants of uncertain significance (VUS). The decryption of VUS discovered by sequencing poses a major challenge in the post-sequencing era. Although experimental assays have progressed in classifying VUS, only a tiny fraction of the human genes have been explored experimentally. Thus, it is urgently needed to generate state-of-the-art functional predictors of VUS in silico. Artificial intelligence (AI) is an invaluable tool to assist in the identification of VUS with high efficiency and accuracy. An increasing number of studies indicate that AI has brought an exciting acceleration in the interpretation of VUS, and our group has already used AI to develop protein structure-based prediction models. In this review, we provide an overview of the previous research on AI-based prediction of missense variants, and elucidate the challenges and opportunities for protein structure-based variant prediction in the post-sequencing era. |
| first_indexed | 2024-03-08T18:30:18Z |
| format | Article |
| id | doaj.art-ff2abe6194e1426295abe653a55d1cea |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-03-08T18:30:18Z |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-ff2abe6194e1426295abe653a55d1cea2023-12-30T04:43:22ZengElsevierComputational and Structural Biotechnology Journal2001-03702024-12-0123446451Structural and functional prediction, evaluation, and validation in the post-sequencing eraChang Li0Yixuan Luo1Yibo Xie2Zaifeng Zhang3Ye Liu4Lihui Zou5Fei Xiao6Clinical Biobank, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, ChinaBeijing Normal University, Beijing, ChinaInformation Center, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, ChinaThe Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, ChinaThe Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, ChinaThe Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; Corresponding authors at: The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.Clinical Biobank, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; Beijing Normal University, Beijing, China; Corresponding authors at: The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.The surge of genome sequencing data has underlined substantial genetic variants of uncertain significance (VUS). The decryption of VUS discovered by sequencing poses a major challenge in the post-sequencing era. Although experimental assays have progressed in classifying VUS, only a tiny fraction of the human genes have been explored experimentally. Thus, it is urgently needed to generate state-of-the-art functional predictors of VUS in silico. Artificial intelligence (AI) is an invaluable tool to assist in the identification of VUS with high efficiency and accuracy. An increasing number of studies indicate that AI has brought an exciting acceleration in the interpretation of VUS, and our group has already used AI to develop protein structure-based prediction models. In this review, we provide an overview of the previous research on AI-based prediction of missense variants, and elucidate the challenges and opportunities for protein structure-based variant prediction in the post-sequencing era.http://www.sciencedirect.com/science/article/pii/S2001037023005056Missense variantsArtificial intelligenceProtein structurePost-sequencing eraClinical interpretation |
| spellingShingle | Chang Li Yixuan Luo Yibo Xie Zaifeng Zhang Ye Liu Lihui Zou Fei Xiao Structural and functional prediction, evaluation, and validation in the post-sequencing era Computational and Structural Biotechnology Journal Missense variants Artificial intelligence Protein structure Post-sequencing era Clinical interpretation |
| title | Structural and functional prediction, evaluation, and validation in the post-sequencing era |
| title_full | Structural and functional prediction, evaluation, and validation in the post-sequencing era |
| title_fullStr | Structural and functional prediction, evaluation, and validation in the post-sequencing era |
| title_full_unstemmed | Structural and functional prediction, evaluation, and validation in the post-sequencing era |
| title_short | Structural and functional prediction, evaluation, and validation in the post-sequencing era |
| title_sort | structural and functional prediction evaluation and validation in the post sequencing era |
| topic | Missense variants Artificial intelligence Protein structure Post-sequencing era Clinical interpretation |
| url | http://www.sciencedirect.com/science/article/pii/S2001037023005056 |
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