Periodic Reporting for period 1 - EnLaCES (Energy Landscapes from Cryo-EM and Simulations)
Période du rapport: 2021-10-01 au 2023-09-30
The project has two parts, each facilitating further work with direct importance for society. Our collaborative attitude also benefits society as has been especially evident during the pandemic. One key example was our study on the "Spanish variant” of SARS-CoV-2, which involves several groups across Madrid, Barcelona and Valencia, providing reassurance on the small but significant structural and functional consequences of a potentially worrying mutation that spread across Spain and beyond during summer 2020 and other times during the pandemic.
The first objective is the development of new computational methods and pipelines to address this problem using a range of interdisciplinary approaches from fields including statistics, CryoEM image processing and computational biophysics (molecular simulations and related methods). A key aim for this part is the creation of user-friendly, open source software, which will allow other scientists to easily obtain more meaningful results to guide their biological studies and drug/vaccine development projects and will assist other researchers in developing better methods in the future.
The second objective is direct application of our new tools as well as existing ones to known biological systems, including AMPA-type glutamate receptors (AMPARs) that are critical in learning and memory and implicated in various diseases, as well as others. In particular, human epidermal growth factor receptors (HERs) that are important causative agents and drug targets in cancer and the SARS-CoV-2 spike that drives cell infection and immune invasion by variants and is the main component of most COVID-19 vaccines were also subjects of in-depth study. The results from this part help inform future research in these areas.
Another component of the early work was an exploration of a new way of describing molecular motions as deformations called Zernike3D that we alluded to in our proposal with first signs of usefulness for continuous image classification. We first confirmed its utility in capturing structural changes using reconstructed volumes and atomic structures including those based on molecular simulations in a study published in the International Union of Crystallography Journal (IUCrJ, also for CryoEM; Herreros et al. 2021). We later refined our pipeline for using it for continuous classification of 2D images and published the complete method in Nat Communications (Herreros et al. 2023).
These starting points enabled the main work towards objective 1: the creation of a plugin within the Scipion workflow engine software of the host lab for the ProDy Python package for protein dynamics described in detail in a paper in the International Journal of Molecular Sciences (IJMS; Krieger et al., 2023) and the integration of Zernike3D, ProDy and other continuous heterogeneity analysis methods into a shared framework called the Scipion Flexibility Hub described in a publication in Acta Crystallogr D Struct Biol (Herreros et al. 2023). The ProDy plugin enabled the creation of more interpretable landscapes through principal component analysis of refined structures from Flexibility Hub including comparison to existing structures in the protein data bank and connection to additional computational biophysics approaches. We are also exploring better methods for simulations and landscape analysis with our collaborators in Barcelona and new collaborators Dr Pilar Cossio at the Flatiron Institute in New York City and Dr Erik Thiede at Cornell University in New York State.
The main novel results towards objective 2 were insights into mechanisms for the unique slowness of AMPARs containing the GluA1 subunit and its activity dependence for synaptic integration, which has been published in Nature with the researcher as co-first author (Zhang, Ivica, Krieger et al., 2023). These properties along with its calcium permeability enable the integration of rather different receptors into synapses under certain conditions that change their signal processing properties, driving long-term plasticity which is essential for learning and memory. Understanding the principles behind this process at the level of macromolecular structure and dynamics will guide further studies into their role and behaviour in healthy and disease conditions at the cell and tissue levels, and facilitate the development of better and more specific therapeutics against diseases such as Alzheimer’s and Schizophrenia.
Our biological results are also beyond the state of the art. For example, we are the first to study AMPARs lacking the GluA2 subunit that preferentially locks the receptor in certain states, shining light on general mechanisms including other states in line with functional studies and providing first insights into how different subunits can endow AMPARs with different kinetic properties relevant for particular circuitries and brain regions and impact their synaptic incorporation.
Both our new methods and biological studies may be beneficial for detailed development of state- and subunit-specific pharmaceuticals that exhibit better efficacy and fewer side effects.