Watching Proteins Function with Time-resolved X-ray Crystallography
Overview
Authors
Affiliations
Macromolecular crystallography was immensely successful in the last two decades. To a large degree this success resulted from use of powerful third generation synchrotron X-ray sources. An expansive database of more than 100,000 protein structures, of which many were determined at resolution better than 2 Å, is available today. With this achievement, the spotlight in structural biology is shifting from determination of static structures to elucidating dynamic aspects of protein function. A powerful tool for addressing these aspects is time-resolved crystallography, where a genuine biological function is triggered in the crystal with a goal of capturing molecules in action and determining protein kinetics and structures of intermediates (Schmidt ., 2005a; Schmidt 2008; Neutze and Moffat, 2012; Šrajer 2014). In this approach, short and intense X-ray pulses are used to probe intermediates in real time and at room temperature, in an ongoing reaction that is initiated synchronously and rapidly in the crystal. Time-resolved macromolecular crystallography with 100 ps time resolution at synchrotron X-ray sources is in its mature phase today, particularly for studies of reversible, light-initiated reactions. The advent of the new free electron lasers for hard X-rays (XFELs; 5-20 keV), which provide exceptionally intense, femtosecond X-ray pulses, marks a new frontier for time-resolved crystallography. The exploration of ultra-fast events becomes possible in high-resolution structural detail, on sub-picosecond time scales (Tenboer ., 2014; Barends ., 2015; Pande ., 2016). We review here state-of-the-art time-resolved crystallographic experiments both at synchrotrons and XFELs. We also outline challenges and further developments necessary to broaden the application of these methods to many important proteins and enzymes of biomedical relevance.
A Review on Perception of Binding Kinetics in Affinity Biosensors: Challenges and Opportunities.
McCann B, Tipper B, Shahbeigi S, Soleimani M, Jabbari M, Nasr Esfahani M ACS Omega. 2025; 10(5):4197-4216.
PMID: 39959045 PMC: 11822510. DOI: 10.1021/acsomega.4c10040.
Exploring the dynamics of allostery through multi-dimensional crystallography.
Hatton C, Mehrabi P Biophys Rev. 2024; 16(5):563-570.
PMID: 39618789 PMC: 11604904. DOI: 10.1007/s12551-024-01224-3.
KINNTREX: a neural network to unveil protein mechanisms from time-resolved X-ray crystallography.
Biener G, Malla T, Schwander P, Schmidt M IUCrJ. 2024; 11(Pt 3):405-422.
PMID: 38662478 PMC: 11067743. DOI: 10.1107/S2052252524002392.
Deep residual networks for crystallography trained on synthetic data.
Mendez D, Holton J, Lyubimov A, Hollatz S, Mathews I, Cichosz A Acta Crystallogr D Struct Biol. 2024; 80(Pt 1):26-43.
PMID: 38164955 PMC: 10833344. DOI: 10.1107/S2059798323010586.
Sample-minimizing co-flow cell for time-resolved pump-probe X-ray solution scattering.
Kosheleva I, Henning R, Kim I, Kim S, Kusel M, Srajer V J Synchrotron Radiat. 2023; 30(Pt 2):490-499.
PMID: 36891863 PMC: 10000795. DOI: 10.1107/S1600577522012127.