NMR-based fragment screening and lead discovery accelerated by principal component analysis
| Autor: | Anup K. Upadhyay, Andrew M. Petros, Chaohong Sun, Andrew T. Namanja, Steven R. Van Doren, Jia Xu, Qi Sun, Haihong Wu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Principal Component Analysis Resolution (mass spectrometry) Chemistry Fragment-based lead discovery Nuclear magnetic resonance spectroscopy Computational biology Ligands 010402 general chemistry Ligand (biochemistry) 01 natural sciences Biochemistry Affinities Peptide Fragments 0104 chemical sciences 03 medical and health sciences 030104 developmental biology Fragment (logic) Drug Discovery Principal component analysis Nuclear Magnetic Resonance Biomolecular Two-dimensional nuclear magnetic resonance spectroscopy Spectroscopy Protein Binding |
| Zdroj: | Journal of Biomolecular NMR. 73:675-685 |
| ISSN: | 1573-5001 0925-2738 |
| DOI: | 10.1007/s10858-019-00279-9 |
| Popis: | Protein-based NMR spectroscopy has proven to be a very robust method for finding fragment leads to protein targets. However, one limitation of protein-based NMR is that the data acquisition and analysis can be time consuming. In order to streamline the scoring of protein-based NMR fragment screening data and the determination of ligand affinities using 2D NMR experiments we have developed a data analysis workflow based on principal component analysis (PCA) within the TREND NMR Pro software package. We illustrate this using four different proteins and sets of ligands which interact with these proteins over a range of affinities. Also, these PCA-based methods can be successfully applied even to systems where ligand binding to target proteins is in intermediate or even slow exchange on the NMR time scale. Finally, these methods will work for scoring of fragment binding data using protein spectra that are either highly overlapped or lower in resolution. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink