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  1. Free, publicly-accessible full text available February 1, 2023
  2. Semiconductors with O(meV) band gaps have been shown to be promising targets to search for sub-MeV mass dark matter (DM). In this paper we focus on a class of materials where such narrow band gaps arise naturally as a consequence of spin-orbit coupling (SOC). Specifically, we are interested in computing DM-electron scattering and absorption rates in these materials using state- of-the-art density functional theory (DFT) techniques. To do this, we extend the DM interaction rate calculation to include SOC effects which necessitates a generalization to spin-dependent wave functions. We apply our new formalism to calculate limits for several DM benchmarkmore »models using an example ZrTe5 target and show that the inclusion of SOC can substantially alter projected constraints.« less
    Free, publicly-accessible full text available February 1, 2023
  3. Free, publicly-accessible full text available November 3, 2022
  4. Musier-Forsyth, Karin (Ed.)
    RNA-binding proteins play crucial roles in various cellular functions, and contain abundant disordered protein regions. The disordered regions in RNA-binding proteins are rich in repetitive sequences, such as poly-K/R, poly-N/Q, poly-A, and poly-G residues. Our bioinformatic analysis identified a largely neglected repetitive sequence family we define as electronegative clusters (ENCs) that contain acidic residues and/or phosphorylation sites. The abundance and length of ENCs exceed other known repetitive sequences. Despite their abundance, the functions of ENCs in RNA-binding proteins are still elusive. To investigate the impacts of ENCs on protein stability, RNA-binding affinity, and specificity, we selected one RNA-binding protein, themore »ribosomal biogenesis factor 15 (Nop15) as a model. We found that the Nop15 ENC increases protein stability and inhibits nonspecific RNA binding, but minimally interferes with specific RNA binding. To investigate the effect of ENCs on sequence specificity of RNA binding, we grafted an ENC to another RNA-binding protein, Ser/Arg-rich splicing factor 3 (SRSF3). Using RNA Bind-n-Seq, we found that the engineered ENC inhibits disparate RNA motifs differently, instead of weakening all RNA motifs to the same extent. The motif site directly involved in electrostatic interaction is more susceptible to the ENC inhibition. These results suggest that one of functions of ENCs is to regulate RNA binding via electrostatic interaction. This is consistent with our finding that ENCs are also overrepresented in DNA-binding proteins, while underrepresented in halophiles, in which nonspecific nucleic acid binding is inhibited by high concentrations of salts.« less
    Free, publicly-accessible full text available July 9, 2022
  5. Free, publicly-accessible full text available June 1, 2022
  6. Free, publicly-accessible full text available June 1, 2022
  7. We develop a hybrid approach that combines the Monte Carlo (MC)method, a variational implicit-solvent model (VISM), and a binary level-set method forthe simulation of biomolecular binding in an aqueous solvent. The solvation free energy for the biomolecular complex is estimated by minimizing the VISM free-energy functional of all possible solute−solvent interfaces that are used as dielectric boundaries. This functional consists of the solute volumetric, solute−solvent interfacial, solute−solvent van der Waals interaction, and electrostatic free energy. A technique of shifting the dielectric boundary is used to accurately predict the electrostatic part of the solvation free energy.Minimizing such a functional in eachmore »MC move is made possible by our new and fast binary level-set method. This method is based on the approximation of surface area by the convolution of an indicator function with a compactly supported kernel and is implemented by simple flips of numerical grid cells locally around the solute−solvent interface. We apply our approach to the p53-MDM2 system for which the two molecules are approximated by rigid bodies. Our efficient approach captures some of the poses before the final bound state. All atom molecular dynamics simulations with most of such poses quickly reach the final bound state.Our work is a new step toward realistic simulations of biomolecular interactions. With further improvement of coarse graining and MC sampling, and combined with other models, our hybrid approach can be used to study the free-energy landscape and kinetic pathways of ligand binding to proteins.« less