Videos
NMR approaches for intrinsically disordered proteins
During the 91st session of the Global NMR Discussion Meetings held on November 5th, 2024, via Zoom, Prof. Julie Forman-Kay from the University of Toronto & SickKids Research Institute, Canada, gave a talk on the topic "NMR approaches for intrinsically disordered proteins". The recording serves as a tutorial.
Abstract: NMR is a powerful tool for obtaining site-specific information about dynamic systems, including intrinsically disordered proteins and protein regions (IDPs/IDRs) which do not adopt unique, stable folded structures. While computational approaches are increasingly powerful for stable proteins and protein domains, there is a huge need for experimental information about IDPs, IDRs and the highly dynamic complexes that they often make with other disordered proteins, folded domains and other biomolecules. The lecture will highlight examples of NMR studies of IDPs and their dynamic complexes, including condensed state models of those found in biomolecular condensates.
Find out more about Prof. Julie Forman-Kay's research: https://biochemistry.utoronto.ca/person/julie-d-forman-kay/
From genome to NMR spectrum
During the 41st session of the Global NMR Discussion Meetings on Zoom held on 25th January 2022, Prof. Rachel W. Martin, University of California, Irvine, USA, gave a talk on the topic "From genome to NMR spectrum".
The slides in the talk can be downloaded here: https://drive.google.com/file/d/1OPde...
Abstract: As structural biologists, we spend much of our time preparing samples for biomolecular NMR and collecting and analyzing the data. These experimental efforts are very time- and resource-intensive, suggesting that we should pay closer attention to systematically choosing targets for investigation. The advent of inexpensive nucleic acid sequencing technology has led to the rapid proliferation of genome and transcriptome data. Thus, tens of thousands of unique and potentially valuable enzymes have been “discovered” in principle, but in reality are languishing uncharacterized in databases. Furthermore, in many enzyme discovery studies, researchers choose proteins for investigation based on factors such as expression level in the host organism, which may not reflect suitability for the desired chemical application. In this talk, I will discuss our recent efforts toward developing a workflow for efficient target selection using bioinformatics and in silico methodology. Finally, I will present molecular modeling and experimental results, including NMR spectra, for Droserasin 1, a novel antimicrobial peptide we discovered from the genome of the carnivorous plant Drosera capensis.
Prof. Martin's Biography:
2002: PhD, Yale University, USA (with Prof. Kurt W. Zilm)
2002-2005: Postdoc, University of California, Berkeley (with Prof. Alex Pines)
2005-present: Professor, Department of Chemistry and Biochemistry, University of California, Irvine
Follow Prof. Rachel W. Martin and her work on social media:
Twitter: @rachelwmartin
Website: https://probemonkey.com/
Free online resources (sequence level):
• GenBank (repository of annotated DNA sequences): https://www.ncbi.nlm.nih.gov/genbank/
• BLAST (find similar nucleic acid/protein sequences to a given sequence): https://blast.ncbi.nlm.nih.gov/Blast.cgi
• Expasy translate tool (translate nucleic acid to protein): https://web.expasy.org/translate/
• Clustal Omega (align multiple sequences, can use nucleic acid or protein): https://www.ebi.ac.uk/Tools/msa/clust...
• UniProt (find what has been published for your protein): https://www.uniprot.org/
• SignalP (predict signal sequences / targeting sequences) https://services.healthtech.dtu.dk/se...
• Scampi (predict whether your protein is a membrane protein, if yes, predict topology): https://scampi.cbr.su.se/pred/help/ Free online resources (structure level):
• Rosetta, iTasser, AlphaFold (predict protein structures from amino acid sequence) https://www.rosettacommons.org/software https://zhanggroup.org/I-TASSER/ https://alphafold.ebi.ac.uk/ https://colab.research.google.com/git...
• Modeller (Make homology models if you have the structure of a similar protein) https://salilab.org/modeller/
• Protein Data Bank (find solved structures of biological macromolecules) https://www.rcsb.org/ (North America) https://www.ebi.ac.uk/pdbe/node/1 (Europe)