Investigating conformational landscape of neuronal receptors using AlphaFold 2
||Investigating conformational landscape of neuronal receptors using AlphaFold 2|
||Erik Lindahl <email@example.com>|
||Kungliga Tekniska högskolan|
||2022-09-20 – 2023-04-01|
Determining atomic resolution structures of multiple functional states of protein has great potential in the development of future therapeutics to target these states and regulate biomolecular function. However, this goal has been substantially hindered by a lack of high-resolution structures, particularly in critical functional states or in the presence of drugs. Though computer simulations could provide solutions, efficient sampling of the conformational space is difficult due to the long timescale, typically in the order of hundreds of microseconds to milliseconds, at which most protein functions. AlphaFold2 (AF2), an artificial intelligence program from DeepMind, has recently demonstrated the capability of generating an ensemble of protein states covering the conformational landscape of protein function [Del Alamo et al. eLife 2022]. While models of most proteins generated using the default AF2 pipeline are conformationally homogeneous and nearly identical to one another, reducing the depth of the input multiple sequence alignments by stochastic subsampling can lead to the generation of accurate models in multiple conformations.
This project will devise a hybrid approach combining AlphaFold2, MD simulations techniques such as Markov state modeling, and experimental techniques, such as electrophysiology, to not only determine the structures of the conformational states but also determine the energetics and kinetics functional relevance of these states. This approach will be applied to neuronal receptors, a biomedically relevant protein family that are critical mediators of electrochemical signal transduction in neurons and other excitable cells. While the AF2 will be run on Berzelius, simulations will be performed in our local cluster, Dardel, and EuroHPC platforms where we already have allocations. Experiments will be performed in our in-house voltage- and patch-clamp electrophysiology setup.
My group has a long track record in the modeling field where we develop the Gromacs MD toolkit [Abraham et al. SoftwareX 2015] and RELION cryo-EM analysis software Kimanius et al. eLife 2016]. In the field of membrane proteins, the group has significant expertise in its molecular modeling, experimental electrophysiology, and cryo-EM and has published numerous works on the conformational transitions and allosteric modulation of ion- channels/transporters [Kim et al. Nature 2020, Bergh et al. eLife 2021].