Modernizing biomolecular NMR: The POKY suite

TL;DR

The POKY suite modernizes biomolecular NMR by providing an integrated, user-friendly platform with AI tools to streamline data analysis and enhance accessibility.

Contribution

The POKY suite introduces a unified cyber infrastructure with AI integration to simplify and modernize biomolecular NMR workflows.

Findings

POKY integrates AI components like automation and unsupervised learning to reduce user burden in NMR data analysis.

The platform creates a synergy between experimental NMR data and structure prediction models.

POKY streamlines the entire NMR process from spectral processing to structure calculation.

Abstract

Biomolecular NMR spectroscopy has been a keystone in structural biology for decades. It can provide unique, atomic-level insights into protein dynamics, interactions, and conformational ensembles. However, its complex workflows and fragmented data analysis pipelines are often perceived as significant barriers to entry. This review highlights the POKY suite as a comprehensive solution that modernizes and streamlines the entire biomolecular NMR process. From spectral processing to structure calculation, POKY creates a single user-friendly cyber infrastructure for a seamless and efficient NMR data analysis environment. A key aspect of its design is the integration of various artificial intelligence components to streamline complex tasks and reduce user burden, such as automation, unsupervised learning, and more. While recent advances within in silico artificial intelligence prediction models have raised questions about the role of experimental data, POKY provides a clear answer. This ecosystem can create a powerful synergy between the experimental data with structure prediction. Modernizing the experimental workflow, POKY makes NMR more accessible and powerful, reinforcing its vital role in structural biology.

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