Automated Determination of Nuclear Magnetic Resonance Chemical Shift Perturbations in Ligand Screening Experiments: The PICASSO Web Server
| Autor: | Kevin Haubrich, Marco Fragai, Linda Cerofolini, Andrea Giachetti, Vincenzo Laveglia, Antonio Rosato, Alessio Ciulli |
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| Rok vydání: | 2021 |
| Předmět: |
Web server
Magnetic Resonance Spectroscopy web server Computer science General Chemical Engineering Library and Information Sciences Ligands 010402 general chemistry Tracking (particle physics) computer.software_genre 01 natural sciences Spectral line 03 medical and health sciences Protein sequencing Nuclear magnetic resonance medicinal chemistry Application Note Humans structural biology Amino Acid Sequence drug screening Nuclear Magnetic Resonance Biomolecular 030304 developmental biology 0303 health sciences Chemical shift Proteins Experimental data General Chemistry Small molecule NMR 0104 chemical sciences Computer Science Applications Identification (information) computer Algorithms |
| Zdroj: | Andrea Giachetti Journal of Chemical Information and Modeling |
| ISSN: | 1549-960X 1549-9596 |
| Popis: | Nuclear magnetic resonance (NMR) is an effective, commonly used experimental approach to screen small organic molecules against a protein target. A very popular method consists of monitoring the changes of the NMR chemical shifts of the protein nuclei upon addition of the small molecule to the free protein. Multidimensional NMR experiments allow the interacting residues to be mapped along the protein sequence. A significant amount of human effort goes into manually tracking the chemical shift variations, especially when many signals exhibit chemical shift changes and when many ligands are tested. Some computational approaches to automate the procedure are available, but none of them as a web server. Furthermore, some methods require the adoption of a fairly specific experimental setup, such as recording a series of spectra at increasing small molecule:protein ratios. In this work, we developed a tool requesting a minimal amount of experimental data from the user, implemented it as an open-source program, and made it available as a web application. Our tool compares two spectra, one of the free protein and one of the small molecule:protein mixture, based on the corresponding peak lists. The performance of the tool in terms of correct identification of the protein-binding regions has been evaluated on different protein targets, using experimental data from interaction studies already available in the literature. For a total of 16 systems, our tool achieved between 79% and 100% correct assignments, properly identifying the protein regions involved in the interaction. |
| Databáze: | OpenAIRE |
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