Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session D08: Molecular Machines IFocus
|
Hide Abstracts |
Sponsoring Units: DBIO Chair: Ruxandra Dima, University of Cincinnati Room: Room 131 |
Monday, March 6, 2023 3:00PM - 3:12PM |
D08.00001: Probing Allosteric Communication of Bacterial ClpP Peptidase using Dynamic Network Analysis and Machine Learning Ashan Dayananda, Timothy S. H Dennison, Riina Tehver, George N Stan Energy-dependent proteolysis plays an essential role in controlling metabolic pathways and the cell cycle. The ClpP peptidase oligomerizes as two stacked heptameric rings, each of which encloses a degradation chamber. To ensure selective degradation, substrate proteins' access to the chamber is controlled by a gating mechanism of its axial pore that involves conformational transition of N-terminal loops of ClpP subunits. Hexameric ring ATPases, such as ClpX and ClpA, which unfold proteins targeted for degradation, axially cap each ClpP ring and allosterically induce gate-opening. To elucidate the gating mechanism, we performed all-atom molecular dynamics simulations and normal mode analysis of both "closed" and "open" states of wild-type (wt) ClpP and several mutants. Analysis of collective variables that distinguish each state of ClpP, reveals that the backbone hydrogen bond formation in the N-terminal loops and changes in solvent accessible surface area of exposed hydrophobic residues are the largest contributors to the substrate translocation to the degradation chamber. Principal components and normal modes highlight key motions and hotspot residues for allostery. Dynamic network analysis reveals stronger coupling between N-terminal loops and ATPase binding sites in the "open" state. Our machine learning approaches, combined with SHapley Additive exPlanations (SHAP) values, identify structural features and their relative importance for characterizing wt ClpP and mutants. |
Monday, March 6, 2023 3:12PM - 3:24PM |
D08.00002: Superdiffusive Motion of Influenza A Viruses on Surfaces Siddhansh Agarwal, Greg Huber, Daniel A Fletcher Viral infections depend on the ability of the invading pathogen to move through the extracellular environment to reach host cells. In the case of Influenza A virus (IAV), this means traversing a thick layer of mucus above airway epithelial cells. The glycosylated biopolymers (mucins) that make up the mucus layer present glycans that bind to receptors on the virus envelop and can be cleaved by enzymes also on the virus envelop. It was recently observed that IAV can move in a persistent and directed manner through the spatial organization of binding and cleaving activity on the viral envelop — employing a 'burnt-bridge' Brownian ratchet-like mechanism. A mean squared displacement (MSD) analysis of IAV trajectories on glycan-coated coverslips reveals superdiffusive motion on relevant time scales. Here we present a stochastic model that captures the fundamental mechanism of IAV motion on surfaces. The model describes the rectification of the stochastic binding, unbinding and cleaving events into directed motion that agrees with experimental observations. The model also suggests a concentration gradient sensing strategy that may be exploited by IAV to navigate through the mucus layer. |
Monday, March 6, 2023 3:24PM - 3:36PM |
D08.00003: Stochastic dynamics and ribosome-RNAP interactions in Transcription-Translation Coupling Xiangting Li, Tom Chou Under certain cellular conditions, transcription and mRNA translation in prokaryotes appear to be "coupled," in which the formation of mRNA transcript and production of its associated protein are temporally correlated. Such transcription-translation coupling (TTC) has been evoked as a mechanism that speeds up the overall process, provides protection against premature termination, and/or regulates the timing of transcript and protein formation. What molecular mechanisms underlie ribosome-RNAP coupling and how they can perform |
Monday, March 6, 2023 3:36PM - 3:48PM |
D08.00004: The Mammalian Meiotic Spindle: A Living Material Colm P Kelleher, Daniel J Needleman Meiosis is the specialized form of cell division that creates gametes. During meiosis, genetic material from the "mother" cell is copied and divided between several "daughter" cells. To facilitate this task, the mother cell builds a self-organized structure, the meiotic spindle, that organizes and moves chromosomes over length-scales of tens of microns and time-scales of several hours. While we have a (nearly) complete "parts list" of the dozens of bio-molecules that make up the spindle, it is far from clear how these molecules self-organize to create the material properties that allow the spindle to produce forces and transmit them to chromosomes over the required length- and time-scales. In this talk, I will present data and analysis that suggests that, despite its formidable bio-molecular complexity, important aspects of the large-scale structure and dynamics of spindles in living cells can be understood via a relatively simple continuum picture in which the spindle is modeled as an active nematic liquid crystal. |
Monday, March 6, 2023 3:48PM - 4:24PM |
D08.00005: Protein remodeling and translocation mediated by AAA+ nanomachines in the degradation and disaggregation pathways: computational studies Invited Speaker: George N Stan Protein degradation and disaggregation are essential quality control mechanisms that protect against cellular stresses. AAA+ nanomachines, such as the hexameric ring-shaped Clp (Caseinolytic protease) ATPases or the 26S eukaryotic proteasome, mediate these mechanisms by unfolding and translocating substrate proteins (SPs) through a narrow central channel. The primary remodeling action involves applying repetitive mechanical forces onto the substrate proteins through a set of ATPase loops that protrude into the channel. The fate of the substrate protein is largely dependent not on its global stability, but on the local mechanical strength near the pulled terminal, and on the direction of force application. To probe the effect of SP structure and force directionality, we used coarse-grained and atomistic, implicit solvent, modeling of diverse substrates, such as the I27 domain of the muscle protein titin, dihydrofolate reductase, green fluorescent protein (GFP), and knotted proteins.
We find that Clp surface plasticity modulates direction-dependent pulling mechanisms by favoring specific SP orientations. This action is complemented by the crowding effect of multiple SP domains, which yields slower rotational diffusion of the multidomain SP compared with monomeric domains in allosteric cycles of the ClpY ATPase. Our atomistic simulations of Clp-mediated degradation of knotted proteins reveal dependence of unknotting and translocation on tension propagation, sequence direction, non-native contacts and intermediates with strong local mechanical resistance. In coarse-grained models of protein degradation mediated by the 26S proteasome, we use machine learning approaches to characterize dynamic competition between GFP refolding and translocation in sequence direction-dependent (N-C and C-N) mechanisms. Simulations of the ClpB disaggregase, using an atomistic, explicit solvent description, reveal the networks of inter- and intraprotomer interactions that underlie dynamic stability of the ring structure. Relaxation times of the pore loop 1 are consistent with experimental single-molecule FRET values. |
Monday, March 6, 2023 4:24PM - 4:36PM |
D08.00006: Probing Severing Enzyme's Functional States with Molecular Simulations and Machine Learning Approaches Maria S Kelly Severing enzymes, such as spastin, are microtubule (MT) associated proteins that interact with the MT lattice by removing tubulin and causing internal breaks for regulating MT's various functions. Spastin is an ATPase that forms homohexameric states in the presence of ATP and tubulin carboxy-terminal tails (CTTs), which protrude from the surface of the MT. Elucidating the main states of spastin and their allosteric networks, which are responsible for the function of this machine, along with spastin's interaction with the MT lattice are still outstanding problems, given the size and the complexity of the machine and its substrate. Here, we built a Markov State Model of all-atomistic simulations of the spastin motor in order to identify kinetically relevant protein conformations. Using biochemical descriptors, we then characterized each distinct conformation and applied machine learning classification algorithms to attribute descriptor differences to specific allosteric sites, which can be compared to experimentally determined allosteric networks. Our coarse-grained studies of one of these spastin conformations on a MT lattice yielded tubulin extraction pathways as a function of spastin's orientation relative to the lattice and the binding strength. Taken together, our studies can collectively enhance our understanding of the severing mechanism and its dependencies. |
Monday, March 6, 2023 4:36PM - 4:48PM |
D08.00007: Determining quaternary allostery of the spastin motor through bioinformatics and graph networks Amanda C Macke, Maria S Kelly, Shehani Kahawatte, Abigail Miller, Ruxandra Dima Microtubule severing enzymes are multimeric nanomachines that are essential for regulating the cytoskeleton of a cell. Spastin is one of these motors that is found in particularly high concentration in neurons. Key loss of function mutations in this motor have been associated with human disease. Thus, its function and dynamics are intricately connected and necessary to understand. We set out to probe this connection by focusing on allosteric networks in the quaternary states of spastin. While recent approaches, which take advantage of evolutionary information and machine learning methods, investigated allostery in single chain proteins, only few studies have probed large multimeric proteins. We employed a coevolutionary mutual information analysis, integrated with our molecular dynamics simulations of the bound and unbound ligand states, and we built a mathematical graph to visualize the allosteric networks based on learned parameters. We found that in addition to other allosteric regions previously identified in experiments, one of the central pore loops is a crucial hot spot. Moreover, we found a novel allosteric region in the helical bundle domain, important for nucleotide binding and protein-protein binding between protomers. These findings establish the power of our approach in characterizing the allostery of quaternary structures. |
Monday, March 6, 2023 4:48PM - 5:00PM |
D08.00008: Effect of molecular walkers on microtubule substrates Jutta Luettmer-Strathmann, Matthew Murrow Motor proteins are molecular motors that convert chemical energy into directed motion. Kinesin molecules, for example, step in a hand-over-hand fashion on microtubules to transport cargo within a cell. In recent work, we developed a model for a molecular walker that can be simulated efficiently with Brownian dynamics simulations in 3-d. By studying the biological system of kinesins on microtubules, we were able to mimic key aspects of its structure and interactions that allow us to simulate a highly efficient molecular walker on a rigid microtubule. Recent experimental studies suggests that kinesin binding causes conformational changes in microtubules that increase the binding affinity of kinesins to the substrate. To investigate this, we include the motion of microtubule units in our simulations and study the effect of the motor protein on the microtubule substrate. In this work, we present simulation results for a coarse-grained microtubule model that responds to the stepping of molecular walkers and investigate the character and range of the conformational changes. |
Monday, March 6, 2023 5:00PM - 5:12PM |
D08.00009: Kinesin Model for Brownian Dynamics Simulations of Stepping Efficiency Matthew Murrow, Jutta Luettmer-Strathmann The motor protein kinesin plays an integral role in cell function, transporting, for example, cargo from the center to the periphery of a cell. Kinesin molecules have been shown experimentally to walk along microtubules in a hand-over-hand stepping motion, carrying their cargo eight nanometers per step. However, details of the stepping process are still under investigation. Kinesins are difficult to study with atomistic simulations due to the size of the proteins and the long time-scales involved. In this work we develop a 3D model of kinesin stepping on a rigid microtubule substrate that can be simulated efficiently with Brownian dynamics simulations. The interactions governing the motor protein conformations and the interactions between kinesin sites and the microtubule sites are designed to reproduce important aspects of the biological system. We perform simulations spanning many kinesin steps to investigate the stepping efficiency of the motor protein for different neck linkers. We find that neck linkers close to the wild-type length yield a stepping efficiency of about 90%, in agreement with experimental data. In addition, we find that increasing the neck-linker length leads to a decrease in efficiency, as has also been observed in experiments.
|
Monday, March 6, 2023 5:12PM - 5:24PM |
D08.00010: Inferring subsystem efficiencies in bipartite molecular machines Matthew Leighton, David A Sivak Molecular machines transduce energy between different forms in order to accomplish innumerable tasks within living organisms. Many of these machines are composed of two coupled subsystems, like F0F1-ATP synthase or a transport motor pulling a diffusive cargo. While subsystem efficiencies of these molecular machines have been measured in isolation, less is known about how they behave when coupled together and acting in concert. In this work we derive upper and lower bounds on the subsystem efficiencies of individual components of a bipartite molecular machine. Our results are well-suited to infer these subsystem efficiencies from limited experimental data. We demonstrate their utility by estimating the efficiencies of the F0 and F1 subsystems, as well as that of a kinesin motor while it pulls a diffusive cargo. |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700