Bulletin of the American Physical Society
2019 Annual Meeting of the APS Four Corners Section
Volume 64, Number 16
Friday–Saturday, October 11–12, 2019; Prescott, Arizona
Session J03: Biophysics and Soft Condensed Matter II |
Hide Abstracts |
Chair: Stacy Copp, UC Irvine Room: AC1 113 |
Saturday, October 12, 2019 8:00AM - 8:24AM |
J03.00001: High-throughput approaches to understanding photoluminescence of DNA-stabilized silver clusters Invited Speaker: Stacy Copp Small clusters of 10-30 silver atoms with bright photoluminescence can be stabilized using DNA. The templating DNA sequence selects the size and shape of the silver cluster, resulting in optical properties that vary widely depending on DNA sequence. For instance, photoluminescence wavelengths of DNA-stabilized silver clusters can be tuned from about 500 nm up to at least 1000 nm by choice of DNA template sequence. Because the space of possible DNA sequences is large and the connection between sequence and optical properties is complex, we are using high-throughput methods to understand how the size and photoluminescence of a DNA-stabilized silver cluster is determined. I will present our studies of the excitation and emission spectra of several hundred unique DNA-stabilized silver clusters. Despite the great diversity of excitation and emission energies, overall trends of these measured quantities suggest universal mechanisms for the fluorescence process within DNA-stabilized silver clusters. These findings may lead to a better understanding of the fundamentals of these important biosensors. [Preview Abstract] |
Saturday, October 12, 2019 8:24AM - 8:36AM |
J03.00002: Predicting Cholesterol Interaction Sites on GPCRs using Coarse-Grained MD Rick Sexton, James Geiger, Zina Al-sahouri, Eugene Chun, Ming-Yue Lee, Wei Liu, Oliver Beckstein Cholesterol has been shown to be important to the function of G-protein coupled receptors (GPCRs), the largest class of signaling membrane proteins and the largest class of drug targets in the human genome. However, experiments cannot always reveal how a specific GPCR and cholesterol molecule interact. We developed a method based on molecular dynamics (MD) simulations to predict sites on the protein where the cholesterol may interact. A limitation of all-atom MD is the computational cost to sample even a few \textmu s of simulation time. In order to sample longer time scales (tens of \textmu s), coarse-grained MD simulations were preformed and analyzed for several GPCRs, including the beta-2 adrenergic receptor and the cannabinoid receptors CB1 and CB2. The computed off rates ($k_{\mathrm{off}})$ or equivalently, the average waiting time in the bound state, show a difference in cholesterol binding for CB1R and CB2R, where CB1R has been shown to bind to cholesterol and CB2R does not. For the proteins in which cholesterol binds, we identified several residues of interest that agree with electron densities from crystallographic measurements and known cholesterol binding motifs. In summary, we developed a physics-based method to predict cholesterol binding sites in GPCRs (and potentially other membrane proteins) and validated it using experimental data. [Preview Abstract] |
Saturday, October 12, 2019 8:36AM - 8:48AM |
J03.00003: Prediction of octanol-water partition coefficients for the SAMPL6 molecules using molecular dynamics simulations with OPLS-AA, AMBER and CHARMM force fields Shujie Fan, Oliver Beckstein, Bogdan Iorga All-atom molecular dynamics simulations were used to predict the octanol-water partition coefficient logPow of a range of small molecules as part of the SAMPL6 blind prediction challenge. All molecules were parameterized using the MOL2FF algorithm and LigParGen with the OPLS-AA force field, ACPYPE and GAFF with the AMBER99sb force field, and 8 of the molecules were parameterized using CGenFF with the CHARMM36 force field. logPow was calculated from the solvation free energy for the compounds in water and dry octanol, or water and "wet" octanol using windowed alchemical free energy perturbation calculations in explicit solvent. Within the data sets that contained all molecules, the GAFF set gave the best overall prediction of logPow with an overall RMSE in logPow of 1.8 log units and an overall ME of -1.7 compared to experimental data. Considering the eight molecules parameterized by CGenFF, the CGenFF set gave the best overall prediction with an overall RMSE of 1.3 and an overall ME of 0.2. Compared with dry octanol results, “wet” octanol improved the performance of MOL2FF and LigParGen data sets, but increased the RMSE and ME in logPow for GAFF and CGenFF. The signed errors of MOL2FF, LigPargen and GAFF suggest a systematic error which may be caused by insufficient sampling. [Preview Abstract] |
Saturday, October 12, 2019 8:48AM - 9:00AM |
J03.00004: Discovering Emergent Behaviors in Cellular Networks Using Supremum Models Cody Petrie, Mark Transtrum, Travis Maekawa, Casie Maekawa Biological cells grow and operate through a network of reactions of staggering complexity. Reflecting this complexity, cells can exhibit a wide range of different behaviors depending on their environment and internal state, making them very difficult to model. Dynamical models are often constructed by domain-specific experts who judiciously include only those mechanisms relevant to the phenomenon of interest. Individually these models can capture some of the possible dynamics of the full physical system, however there may be additional emergent dynamics which cannot be described by the reduced models. The problem we consider is how to predict new types of behaviors that the complex system can potentially realize, for example, during a different stage of development or during a disease such as cancer. We observe that the family of all such reduced models form a partially ordered set and propose a method for building "supremum" models using information geometry. These supremum models leverage the insights of the simplified models in order to capture the original dynamics while enabling new emergent behaviors. I illustrate using models of the Wnt signaling pathway, but the process can be applied to many complex systems. [Preview Abstract] |
Saturday, October 12, 2019 9:00AM - 9:12AM |
J03.00005: Substrate Binding and Conformational Change of the Bile Acid Transporter ASBT$_{\mathrm{NM}}$ Fiona Naughton, Alexander Cameron, Oliver Beckstein The apical sodium-dependent bile acid transporter (ASBT) allows reabsorption of bile acids from the intestine by coupling bile acid movement to the sodium gradient. Such transporters are attractive targets for drug delivery and in the treatment for hypercholesterolaemia. Several structures of bacterial homologues in both inward and outward facing conformations have been obtained experimentally, including a substrate-bound inward facing structure of the homologue from Neisseria meningitidis (ASBT$_{\mathrm{NM}})$. However, many details surrounding the binding of substrates and the conformational transition remain unclear. We have used computational methods to explore these details at an atomistic scale using the homologue ASBT$_{\mathrm{NM}}$ and the bile acid taurocholate. Models of \textit{apo }and substrate-bound ASBT$_{\mathrm{NM\thinspace }}$in the outward-facing conformation were generated. Biased molecular dynamics simulations were used to explore potential conformational changes and taurocholate movement, while alternate binding sites and the residues important for sodium and taurocholate binding were investigated with unbiased simulations. These results further our understanding of the important molecular details of ASBT function. [Preview Abstract] |
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