Cloud-Based Platform for Protein Structure Determination and Dynamics Analysis
0:00 Introduction: Dan Matu, an application scientist from Booker, discusses a collaboration with ETH Zurich to develop a cloud-based platform called Anartist for automated protein structure determination.
0:44 Anartist Overview: Anartist automates peak picking, resonance assignment, and protein spectra analysis, aiming to save time and reduce effort in structure determination. The underlying platform is called artina.
1:16 Challenges in NMR Structure Determination: Manually determining protein structures using NMR is labor-intensive and time-consuming, requiring experienced and dedicated personnel, significant computational power, and years of training.
3:34 Bottleneck: Resonance Assignment: The major bottleneck in NMR structure determination is resonance assignment, which involves manually cross-referencing multiple spectra.
5:11 Artina's Three-Step Approach: Artina has three steps: Peak picking, shift assignment (backbone and sidechain predictions), and structure determination.
6:05 Real-World Application: A customer provided a cancer-related protein sample to test Anartist; a 20 kDa protein at 400 micromolar concentration, carbon and nitrogen labeled, measured at 800 MHz with a cryoprobe.
6:49 Automated Assignment Results: Automated peak picking and assignment achieved roughly 91% accuracy with automated measurements, referencing, and processing.
7:35 Structure Calculation and Validation: The automated structure calculation produced a result consistent with the expected crystal structure, despite some differences in the construct and missing loops.
8:25 Experiment Combination Optimization: Research is underway to determine the best combinations of NMR experiments for structure determination, considering factors like molecular size and labeling scheme.
9:17 Compromises in Experiment Design: Optimizing experiments involves trade-offs between sensitivity, spectrum quality, and robustness to miscalibration.
10:45 Potential Beyond Structure Determination: The true potential lies in using the resonance assignments generated by Anartist for dynamics analysis, with several applications such as characterizing confirmation chemical exchange and localizing interaction patches.
11:40 Automation of Dynamics Analysis: Dynamics analysis, including experimental setup, processing, referencing, and backbone assignment, has been automated using the Anartist platform.
12:12 Case Study: Ubiquitin: A case study with Ubiquitin using three dimentional experiments, resulted in 98.5% correct backbone assignments, which in turn where used to overlay and color code crystal structures with the protein's dynamic.
12:12 In-House Software: Acquired data is transferred to an in-house software called Dynamic Center to derive backbone assignments, analyze relaxation experiments, and calculate order parameters to measure flexibility.
12:14 Dynamic Center: Software that analyzes data generated, calculates barrow type order parameters, overlays with crystal structure.
13:32 Benefits of Automation: Automation allows for easier analysis of data, previously requiring command-line tools and manual data conversion.
14:13 Acknowledgements: Thanks were given to Pawel P Kowski and a cancer related protein sample contributor Peter G Mar Torino and of course euph for attention.