Frontiers in Cryo-Electron Microscopy | EK19

Feb 3, 2021 ‐ Feb 4, 2021



Sessions

Studying the 50S Ribosomal Subunit Assembly Process for New Antibiotic Target Discovery

Feb 3, 2021 12:00am ‐ Feb 3, 2021 12:00am

Identification: EK19-EPOSTER-PALACIOS-ARMANDO

Studying the 50S Ribosomal Subunit Assembly Process for New Antibiotic Target Discovery Armando Palacios1,2, Amal Seffouh1,2, Dushyant Jahagirdar1,2 and Joaquin Ortega1,2 1Department of Anatomy and Cell Biology, McGill University, Montreal, Quebec H3A 0C7, Canada. 2Centre for Structural Biology, McGill University, Montreal, Quebec H3G 0B1, Canada. The rapid emergence of multi- and pan-drug resistant bacteria across the globe is alarming. It’s estimated that by 2050, ten million people will die each year from infections caused by drug-resistant bacteria. Widespread antibiotic resistance and the lack of new antibiotics has caused researchers to look for new targets to combat bacterial infections. Bacterial ribosome biogenesis is a promising target for new antibiotic development. Despite the ribosome being a common target for antibiotics, its assembly pathway has remained relatively unexplored. YphC is an under characterized and widely conserved enzyme that plays multiple roles in the late-stage assembly of the bacterial 50S ribosomal subunit. Previous studies have revealed biochemical and structural information pertaining to the GTPase function of YphC. We are using microscale thermophoresis and cryogenic electron microscopy to study how and when YphC intervenes in this assembly process. We have found out that it plays a major role in the formation of several important ribosomal landmarks, the central protuberance and the E, P and A sites.

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Bias and variance in Single Particle Analysis

Feb 3, 2021 12:00am ‐ Feb 3, 2021 12:00am

Identification: EK19-EPOSTER-SORAZANO-CARLOSOSCAR

Bias and variance in Single Particle Analysis C.O.S. Sorzano, A. Jimenez-Moreno, D. Maluenda, M. Martınez, E. Ramirez-Aportela, R. Melero, A. Cuervo, J. Conesa, J. Filipovic, P. Conesa, L. del Cano, Y.C. Fonseca, J. Jimenez-de la Morena, P. Losana, R. Sanchez-Garcia, D. Strelak, E. Fernandez-Gimenez, F. de Isidro, D. Herreros, J.L. Vilas, R. Marabini, J.M. Carazo Center of Biotechnology, Spanish Natl. Research Council (CSIC) Cryo-Electron Microscopy (cryoEM) has become a well-established technique to elucidate the three-dimensional (3D) structure of biological macromolecules. Projection images from thousands of macromolecules assumed to be structurally identical are combined into a single 3D map that represents the Coulomb potential of the macromolecule under study. In this article, we discuss possible caveats along the image processing path and how to avoid them in order to have a reliable 3D structure. Some of these problems are very well known in the community and we may refer to them as sample related (like specimen denaturation at interfaces or non-uniform projection geometry leading to underrepresented projection directions). The rest are algorithmic related, and while some of them have been discussed in-depth in the literature, like using an incorrect choice of the initial volume, there are others that have received much less attention but, however, they are fundamental in any data analysis approach. Chiefly among them, we refer to instabilities in the estimation of many of the key parameters required for a correct three-dimensional reconstruction that happen all along the processing workflow and that may affect significantly the reliability of the whole process. In the field, the term overfitting has been coined to refer to some particular kind of artifacts. We argue that overfitting is actually the statistical bias in key steps of particle estimation in the 3D reconstruction process, including intrinsic algorithmic bias. We also show that common tools (FSC) and strategies (gold standard), that we normally use to detect or prevent overfitting, do not fully protect us against it. Alternatively, we propose that detecting the biases that lead to overfitting is much easier when addressed at the level of parameter estimation, rather than detecting it once we have combined the particle images into a 3D map. Parameter bias can be detected by comparing the results from multiple algorithms (or at least, independent executions of the same algorithm). Then, these multiple executions could be averaged in order to have a lower variance estimate of the underlying parameters.

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The Myosin II Coiled-Coil Domain Atomic Structure in its Native Environment

Feb 3, 2021 12:00am ‐ Feb 3, 2021 12:00am

Identification: EK19-eposter-rahmani-hamidreza

The Myosin II Coiled-Coil Domain Atomic Structure in its Native Environment Hamidreza Rahmani, Zhongjun Hu, Nadia Daneshparvar, Dianne W. Taylor and Kenneth A. Taylor The atomic structure of the complete myosin tail of native thick filaments from Lethocerus indicus flight muscle is described and compared to crystal structures of recombinant human cardiac myosin tail segments. Overall, the agreement is good with three exceptions: the proximal S2, where the filament has heads attached but the crystal structure doesn’t and skip regions 2 and 4. At the head-tail junction the tail α-helices are asymmetrically structured encompassing well-defined unfolding of 12 residues for one myosin tail and ~6 residues of the other. Different degrees of α-helix unwinding are observed for both α-helices, thereby providing an atomic resolution description of coiled-coil “uncoiling” at the head-tail junction. Asymmetry is observed in the non-helical C-termini; one C-terminal segment is intercalated between ribbons of myosin tails the other apparently terminating at Skip 4 of another myosin tail. Between skip residues, crystal and filament structures agree well. Skips 1 and 3 also agree well and show the expected α-helix unwinding and coiled-coil untwisting in response to skip residue insertion. Skips 2 and 4 are different. Skip 2 is accommodated in an unusual manner through an increase in α-helix radius and the corresponding reduction in rise/residue. Skip 4 remains helical in one chain, with the other chain unfolded, apparently influenced by the acidic myosin C-terminus. The atomic model may shed some light on the phenomenon of thick filament mechanosensing and is a first step in understanding the complex roles that thick filaments of all species undergo during muscle contraction.

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Structural Determination of the Dicer-2•R2D2 Complex

Feb 3, 2021 12:00am ‐ Feb 3, 2021 12:00am

Identification: EK19-EPOSTER-DONELICK-HELEN

Structural Determination of the Dicer-2•R2D2 Complex Helen M. Donelick, Peter S. Shen, and Brenda L. Bass University of Utah. Salt Lake City, Utah, USA In Drosophila melanogaster, Dicer-2 is essential for multiple RNA interference functions, including small interfering RNA (siRNA) biogenesis. These siRNAs are 21-23 nucleotides in length (Elbashir et al., 2001), and one strand is loaded onto Argonaute-2 to form the active RNA-induced silencing complex (RISC). Loading the guide strand onto Argonaute-2 requires the formation of the RISC loading complex, which includes Dicer-2, siRNA, and R2D2, a dsRNA binding protein. R2D2 appears to interact with the Dicer-2 helicase domain (Nishida et al., 2013). The Dicer-2•R2D2 complex binds tightly to siRNA, and without R2D2, siRNAs are generated but cannot be passed on to Argonaute-2; therefore, R2D2 is essential for functional RNA interference (Liu et al., 2003, 2006). Although the RISC loading complex is vital for RNA interference, little is known about how this complex passes the guide strand, and no structural information exists on how the complex is formed. It has been suggested that the helicase domain of many Dicer proteins is the domain where accessory proteins can bind and modulate function (Hansen et al., 2020). A high-resolution structure of this complex will provide details into how R2D2 modulates the function of Dicer-2, which can then be validated with biochemical techniques. To acquire a structure, we built on cryo-EM work performed by my co-mentors. We performed single-particle analysis on a dataset collected on the University of Utah Titan Krios. The complex consisted of Dicer-2•R2D2, siRNA, and ATP. Our preliminary analysis of this structure shows an extra density on the helicase domain, not accounted for by an apo-Dicer-2 model. It appears this extra density on the helicase domain is R2D2, but the current resolution is still low; thus, exactly how this accessory factor regulates Dicer-2 remains unknown. We are continuing to analyze our dataset and utilize Topaz (Belper et al., 2019) to help find underrepresented views of the complex. With additional data collection and analysis, we feel confident we can obtain a high-resolution structure of this complex and find key domain interactions that we can mutate and test biochemically.

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An expedited genes-to-drug approach using cryo-EM enabled structure based drug design

Feb 3, 2021 12:00am ‐ Feb 3, 2021 12:00am

Identification: EK19-EPOSTER-BORRELLI-KENNETH

An expedited genes-to-drug approach using cryo-EM enabled structure based drug design Structure-Based Drug Design (SBDD) imparts cost-efficiency, timeliness and superior properties to target-based small molecule drug discovery. As a result, it is a preferred means of drug discovery whenever structural enablement is feasible. Advances in protein production, cryo-electron microscopy (cryo-EM) and computational chemistry are now available to extend the benefits of SBDD to more high-value drug targets. Here, we present the approach taken by Thermo Fisher Scientific and Schrödinger for joint development of new therapeutics with an example program. GeneArt® Gene-to-Proteins was used to create highly pure native protein with a concentration of 5mg/ml. The Thermo Scientific iSPA Workflow was used to solve protein ligand complex structures to a resolution of 2.6Å. Finally the Schrödinger Drug Discovery Platform used these structures to to create a validated structure-based model of the binding affinity of congeneric ligands capable of correctly separating strong binders ( < 100nM), intermediate binders ( 100nM-1uM) and weak binders ( < 1uM) with 73% accuracy from a set of 62 previously patented ligands. Author List Kenneth Borrelli, Schrodinger - kenneth.borrelli@schrodinger.com Leah Frye, Schrodinger - leah.frye@schrodinger.com Shulu Feng, Schrodinger - shulu.feng@schrodinger.com Mazdak Radjainia, ThermoFisher Scientific, mazdak.radjainia@thermofisher.com Micheal Liss, ThermoFisher Scientific, Michael.Liss@thermofisher.com Ieva Drulyte, ThermoFisher Scientific, ieva.drulyte@thermofisher.com

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Welcome RemarksWelcome Remarks

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Welcome Remarks

Feb 3, 2021 10:00am ‐ Feb 3, 2021 10:10am

Identification: ek19-esym-session-welcome


Large and Dynamic AssembliesLarge and Dynamic Assemblies

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Large and Dynamic Assemblies

Feb 3, 2021 10:00am ‐ Feb 3, 2021 1:00pm

Identification: _esym-session-dynamic

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ATPase Structure and DynamicsATPase Structure and Dynamics

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ATPase Structure and Dynamics

Feb 3, 2021 10:35am ‐ Feb 3, 2021 11:00am

Identification: ek19-esym-session-Rubinstein-John

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Cryo‑EM in Cancer BiologyCryo‑EM in Cancer Biology

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Cryo‑EM in Cancer Biology

Feb 3, 2021 11:00am ‐ Feb 3, 2021 11:25am

Identification: ek19-esym-session-Subramaniam-Sriram

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Coffee BreakCoffee Break

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Coffee Break

Feb 3, 2021 11:25am ‐ Feb 3, 2021 11:40am

Identification: ek19-esym-session-break-01

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