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Plata M, Sharma M, Utz M, Werner JM. Fully Automated Characterization of Protein-Peptide Binding by Microfluidic 2D NMR. J Am Chem Soc 2023; 145:3204-3210. [PMID: 36716203 PMCID: PMC9912330 DOI: 10.1021/jacs.2c13052] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
We demonstrate an automated microfluidic nuclear magnetic resonance (NMR) system that quantitatively characterizes protein-ligand interactions without user intervention and with minimal sample needs through protein-detected heteronuclear 2D NMR spectroscopy. Quantitation of protein-ligand interactions is of fundamental importance to the understanding of signaling and other life processes. As is well-known, NMR provides rich information both on the thermodynamics of binding and on the binding site. However, the required titrations are laborious and tend to require large amounts of sample, which are not always available. The present work shows how the analytical power of NMR detection can be brought in line with the trend of miniaturization and automation in life science workflows.
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Affiliation(s)
- Marek Plata
- School
of Chemistry, University of Southampton, SouthamptonSO17 1BJ, United Kingdom
| | - Manvendra Sharma
- School
of Chemistry, University of Southampton, SouthamptonSO17 1BJ, United Kingdom
| | - Marcel Utz
- School
of Chemistry, University of Southampton, SouthamptonSO17 1BJ, United Kingdom,Email
for M.U.:
| | - Jörn M. Werner
- School
for Biological Sciences, University of Southampton, B85 Life Science Building, University
Rd, SouthamptonSO17 1BJ, United Kingdom,Email for J.M.W.:
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2
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Laveglia V, Giachetti A, Cerofolini L, Haubrich K, Fragai M, Ciulli A, Rosato A. Automated Determination of Nuclear Magnetic Resonance Chemical Shift Perturbations in Ligand Screening Experiments: The PICASSO Web Server. J Chem Inf Model 2021; 61:5726-5733. [PMID: 34843238 PMCID: PMC8715503 DOI: 10.1021/acs.jcim.1c00871] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Indexed: 11/28/2022]
Abstract
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.
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Affiliation(s)
- Vincenzo Laveglia
- Consorzio
Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Andrea Giachetti
- Consorzio
Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Linda Cerofolini
- Consorzio
Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Kevin Haubrich
- School
of Life Sciences, Division of Biological Chemistry and Drug Discovery, The University of Dundee, James Black Centre, Dow Street, DD1 5EH, Dundee, United Kingdom
| | - Marco Fragai
- Consorzio
Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
- Magnetic
Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
- Department
of Chemistry, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
| | - Alessio Ciulli
- School
of Life Sciences, Division of Biological Chemistry and Drug Discovery, The University of Dundee, James Black Centre, Dow Street, DD1 5EH, Dundee, United Kingdom
| | - Antonio Rosato
- Consorzio
Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
- Magnetic
Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
- Department
of Chemistry, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
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3
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Zieba M, Klukowski P, Gonczarek A, Nikolaev Y, Walczak MJ. Gaussian process regression for automated signal tracking in step-wise perturbed Nuclear Magnetic Resonance spectra. Appl Soft Comput 2018. [DOI: 10.1016/j.asoc.2018.03.046] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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4
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Banelli T, Vuano M, Fogolari F, Fusiello A, Esposito G, Corazza A. Automation of peak-tracking analysis of stepwise perturbed NMR spectra. JOURNAL OF BIOMOLECULAR NMR 2017; 67:121-134. [PMID: 28213793 DOI: 10.1007/s10858-017-0088-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Accepted: 01/19/2017] [Indexed: 06/06/2023]
Abstract
We describe a new algorithmic approach able to automatically pick and track the NMR resonances of a large number of 2D NMR spectra acquired during a stepwise variation of a physical parameter. The method has been named Trace in Track (TINT), referring to the idea that a gaussian decomposition traces peaks within the tracks recognised through 3D mathematical morphology. It is capable of determining the evolution of the chemical shifts, intensity and linewidths of each tracked peak.The performances obtained in term of track reconstruction and correct assignment on realistic synthetic spectra were high above 90% when a noise level similar to that of experimental data were considered. TINT was applied successfully to several protein systems during a temperature ramp in isotope exchange experiments. A comparison with a state-of-the-art algorithm showed promising results for great numbers of spectra and low signal to noise ratios, when the graduality of the perturbation is appropriate. TINT can be applied to different kinds of high throughput chemical shift mapping experiments, with quasi-continuous variations, in which a quantitative automated recognition is crucial.
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Affiliation(s)
- Tommaso Banelli
- Dipartimento di Area Medica, Università di Udine, P.le Kolbe, 4, 33100, Udine, Italy
| | - Marco Vuano
- Dipartimento di Area Medica, Università di Udine, P.le Kolbe, 4, 33100, Udine, Italy
| | - Federico Fogolari
- INBB, Viale Medaglie d'Oro, 306, 00136, Roma, Italy
- Dipartimento di Scienze Matematiche Informatiche e Fisiche, Università di Udine, Via delle Scienze, 206, 33100, Udine, Italy
| | - Andrea Fusiello
- Dipartimento Politecnico di Ingegneria e Architettura, Università di Udine, Via delle Scienze, 208, 33100, Udine, Italy
| | - Gennaro Esposito
- INBB, Viale Medaglie d'Oro, 306, 00136, Roma, Italy
- Dipartimento di Scienze Matematiche Informatiche e Fisiche, Università di Udine, Via delle Scienze, 206, 33100, Udine, Italy
- Science & Math Division, New York University Abu Dhabi, Saadiyat Campus, PO Box 129188, Abu Dhabi, UAE
| | - Alessandra Corazza
- Dipartimento di Area Medica, Università di Udine, P.le Kolbe, 4, 33100, Udine, Italy.
- INBB, Viale Medaglie d'Oro, 306, 00136, Roma, Italy.
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5
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Köhler C, Recht R, Quinternet M, de Lamotte F, Delsuc MA, Kieffer B. Accurate protein-peptide titration experiments by nuclear magnetic resonance using low-volume samples. Methods Mol Biol 2015; 1286:279-96. [PMID: 25749962 DOI: 10.1007/978-1-4939-2447-9_22] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
NMR spectroscopy allows measurements of very accurate values of equilibrium dissociation constants using chemical shift perturbation methods, provided that the concentrations of the binding partners are known with high precision and accuracy. The accuracy and precision of these experiments are improved if performed using individual capillary tubes, a method enabling full automation of the measurement. We provide here a protocol to set up and perform these experiments as well as a robust method to measure peptide concentrations using tryptophan as an internal standard.
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Affiliation(s)
- Christian Köhler
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, 1, rue Laurent Fries, BP 10142, 67404, Illkirch Cedex, France
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