NMR-based fragment screening and lead discovery accelerated by principal component analysis

Area of Science:

• Biochemistry
• Structural Biology
• Chemical Biology

Background:

• Protein-based NMR spectroscopy is a powerful technique for identifying fragment leads for protein targets.
• Current NMR data acquisition and analysis can be time-consuming, limiting throughput.
• Efficient analysis is crucial for drug discovery and understanding protein-ligand interactions.

Purpose of the Study:

• To develop and validate a streamlined data analysis workflow for protein-based NMR fragment screening.
• To enable faster scoring of fragment binding and determination of ligand affinities.
• To improve the efficiency of NMR-based drug discovery efforts.

Main Methods:

• Development of a data analysis workflow utilizing principal component analysis (PCA).
• Implementation of the workflow within the TREND NMR Pro software package.
• Application and validation using four different protein-ligand systems with varying affinities.

Main Results:

• The PCA-based workflow successfully streamlines the scoring of fragment screening data.
• Ligand affinities were accurately determined using 2D NMR experiments.
• The methods proved effective for protein-ligand systems in intermediate and slow exchange regimes.
• The workflow performed well even with highly overlapped or low-resolution protein spectra.

Conclusions:

• The developed PCA-based workflow significantly accelerates the analysis of protein NMR fragment screening data.
• This approach enhances the determination of ligand binding affinities, even for challenging systems.
• The TREND NMR Pro software package provides an efficient tool for NMR-based drug discovery and fragment-based lead identification.