Dataset Information

Rapid prediction of protein natural frequencies using graph neural networks.

ABSTRACT: Natural vibrational frequencies of proteins help to correlate functional shifts with sequence or geometric variations that lead to negligible changes in protein structures, such as point mutations related to disease lethality or medication effectiveness. Normal mode analysis is a well-known approach to accurately obtain protein natural frequencies. However, it is not feasible when high-resolution protein structures are not available or time consuming to obtain. Here we provide a machine learning model to directly predict protein frequencies from primary amino acid sequences and low-resolution structural features such as contact or distance maps. We utilize a graph neural network called principal neighborhood aggregation, trained with the structural graphs and normal mode frequencies of more than 34 000 proteins from the protein data bank. combining with existing contact/distance map prediction tools, this approach enables an end-to-end prediction of the frequency spectrum of a protein given its primary sequence.

SUBMITTER: Guo K

PROVIDER: S-EPMC9189858 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Rapid prediction of protein natural frequencies using graph neural networks.

Guo Kai K Buehler Markus J MJ

Digital discovery 20220401 3

Natural vibrational frequencies of proteins help to correlate functional shifts with sequence or geometric variations that lead to negligible changes in protein structures, such as point mutations related to disease lethality or medication effectiveness. Normal mode analysis is a well-known approach to accurately obtain protein natural frequencies. However, it is not feasible when high-resolution protein structures are not available or time consuming to obtain. Here we provide a machine learning ...[more]

PMID: 35769204

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Dataset Information

Rapid prediction of protein natural frequencies using graph neural networks.

Publications

Rapid prediction of protein natural frequencies using graph neural networks.

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