Characterizing ligand-protein interactions with a cryo-EM data-driven modeling approach

MSCA (Marie Skłodowska-Curie)HORIZON-TMA-MSCA-PF-EFID: 101107036
EC Contribution
€2,227
Consortium Size
1 orgs
Start Year
2023
Summary

Visualizing protein-ligand interactions at atomic details is key to understand how ligands regulate macromolecular function. This knowledge could be leveraged to develop pharmaceutics utilizing the structure-based drug discovery platform. However, determining experimental structures of such complexes is often difficult using theVisualizing protein-ligand interactions at atomic details is key to understand how ligands regulate macromolecular function. This knowledge could be leveraged to develop pharmaceutics utilizing the structure-based drug discovery (SBDD) platform. However, determining experimental structures of such complexes is often difficult using the traditional time-consuming approach of hunting for suitable crystals for X-ray analysis. Recent breakthroughs in single-particle cryo-EM have overcome this limitation and enabled us to obtain atomic resolution structures of complex biomolecular systems. Though cryo-EM can now provide very high-resolution data of the overall system (less than 2 angstroms in many cases), unfortunately, resolutions of ligands are often significantly low to be useful for SBDD. Parallel to developments in cryo-EM, computational methods for modeling and refining structures into EM maps have been developed, but their main focus has been to build accurate protein structures. Here, I propose to exploit the increased computing power of molecular dynamics simulations offered by high-performance computing and algorithm development to develop a cryo-EM data-driven computational modeling approach to fit ligands into low-resolution EM maps. After testing in a large data set, this approach will be applied to identify ligand binding sites in new EM maps of a membrane protein and investigate how binding regulates the functional landscape of proteins. The findings of this proposal could open new avenues in the drug design platform by leveraging the power of cryo-EM and computational chemistry to accurately model ligand-protein complex structures.

Consortium (1)

Project Results (9)

Source: CORDIS, the EU research results database.

Publications (7)
Adaptive sampling–based structural prediction reveals opening of a GABA <sub>A</sub> receptor through the αβ interface
Science Advances· 2025DOI
Nandan Haloi, Samuel Eriksson Lidbrink, Rebecca J. Howard, Erik Lindahl
Cryo-EM ligand building using AlphaFold3-like model and molecular dynamics
PLOS Computational Biology· 2025DOI
Nandan Haloi, Rebecca J. Howard, Erik Lindahl
Discovering cryptic pocket opening and binding of a stimulant derivative in a vestibular site of the 5-HT <sub>3A</sub> receptor
Science Advances· 2025DOI
Nandan Haloi, Emelia Karlsson, Marc Delarue, Rebecca J. Howard, Erik Lindahl
Modeling cryo-EM structures in alternative states with AlphaFold2-based models and density-guided simulations
Communications Chemistry· 2025DOI
Tatiana Shugaeva, Rebecca J. Howard, Nandan Haloi, Erik Lindahl
Resolving the conformational ensemble of a membrane protein by integrating small-angle scattering with AlphaFold
PLOS Computational Biology· 2025DOI
Samuel Eriksson Lidbrink, Rebecca J. Howard, Nandan Haloi, Erik Lindahl
Interactive computational and experimental approaches improve the sensitivity of periplasmic binding protein-based nicotine biosensors for measurements in biofluids
Protein Engineering, Design and Selection· 2024DOI
Nandan Haloi, Shan Huang, Aaron L Nichols, Eve J Fine, Nicholas J Friesenhahn, Christopher B Marotta, Dennis A Dougherty, Erik Lindahl, Rebecca J Howard, Stephen L Mayo, Henry A Lester
Structure and dynamics of differential ligand binding in the human ρ-type GABAA receptor
Neuron· 2023DOI
John Cowgill, Chen Fan, Nandan Haloi, Victor Tobiasson, Yuxuan Zhuang, Rebecca J. Howard, Erik Lindahl
Deliverables (2)