SUPR
Modeling of proteins with low-resolution experimental data
Dnr:

SNIC 2022/3-40

Type:

SNIC Large Compute

Principal Investigator:

Erik Lindahl

Affiliation:

Kungliga Tekniska högskolan

Start Date:

2023-01-01

End Date:

2024-01-01

Primary Classification:

10603: Biophysics

Secondary Classification:

10602: Biochemistry and Molecular Biology

Tertiary Classification:

10407: Theoretical Chemistry

Allocation

Abstract

The purpose of our work is to understand how channels and other proteins move between conformations, how large motions and allosteric modulation are induced by small external factors (e.g. ligand binding, changes in membrane potential, or lipid composition), and to develop techniques to combine several sources of experimental data such as cryo-EM, electrophysiology and neutron scattering with bioinformatics and simulation to create models of the entire ensemble of structural and functional states for ion channels and transporters. Our computational work supported by SNIC enables us to build atomic-resolution models to study features not readily available in experiments, such as transitions between states and finding new ways to use low-resolution experimental data. Our primary model system is the pentameric ligand-gated ion channels responsible for mediating chemical singling across the synapse in the nervous system, as well as their bacterial homologs. While we increasingly have structural data for these channels, we still do not understand the molecular mechanism of gating, and the desensitised state all channels end up in shortly after activation is still almost entirely uncharacterised. Here, we propose to use molecular dynamics simulations in combination with Markov State Models to determine both the free energy landscape of channel activation, as well as the kinetics of transitions between states, and how this is changed by allosteric modulation. We will similarly use simulations to explain the differences in molecular interactions between positive (enhancing) and negative (dampening) allosteric modulators, to identify state-specific binding, and understand the interplay between lipid and small-molecule modulation of ion channels. An important part of our work is that we are able to combine cryo-EM data with molecular dynamics through a newly developed cryo-EM density fitting code that avoids distorting local stereogeometry of proteins. Interestingly, this approach also appears to work surprisingly well to determine initial/approximate transition pathways, and as part of the project we will both try to use these to enhance MSM convergence and to see if we can replace expensive MSM sampling with much cheaper targeted fitting - at least when end state correspond to known structures. We will also attempt to combine both our MSM sampling and density fitting codes with new conformations predicted from AlphaFold, based on the idea that AF2 frequently generates a whole range of candidate clusters - and at least in a few cases lower-ranking clusters appear to have corresponded to alternative conformations. We will also use simulations to compute small-angle neutron scattering (SANS) spectra from open/closed-state channels and compare with experimental SANS data we are collecting in Grenoble. While SANS itself is extremely low resolution (essentially just describing shape), it provides the first accurate data about channel structure at room temperature, and comparing to simulations of existing structures could enable us to determine how well these correspond to functional channels, and in particular help us characterise the rapid desensitisation transitions occurring at room temperature in cells, but this far not explained with X-ray or cryo-EM structures.