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  1. Abstract

    Current predictors of DNA-binding residues (DBRs) from protein sequences belong to two distinct groups, those trained on binding annotations extracted from structured protein-DNA complexes (structure-trained) vs. intrinsically disordered proteins (disorder-trained). We complete the first empirical analysis of predictive performance across the structure- and disorder-annotated proteins for a representative collection of ten predictors. Majority of the structure-trained tools perform well on the structure-annotated proteins while doing relatively poorly on the disorder-annotated proteins, and vice versa. Several methods make accurate predictions for the structure-annotated proteins or the disorder-annotated proteins, but none performs highly accurately for both annotation types. Moreover, most predictors make excessive cross-predictions for the disorder-annotated proteins, where residues that interact with non-DNA ligand types are predicted as DBRs. Motivated by these results, we design, validate and deploy an innovative meta-model, hybridDBRpred, that uses deep transformer network to combine predictions generated by three best current predictors. HybridDBRpred provides accurate predictions and low levels of cross-predictions across the two annotation types, and is statistically more accurate than each of the ten tools and baseline meta-predictors that rely on averaging and logistic regression. We deploy hybridDBRpred as a convenient web server at and provide the corresponding source code at

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  2. All-inorganic nanocrystals (NCs) are of great importance in a range of electronic devices. However, current all-inorganic NCs suffer from limitations in their optical properties, such as low fluorescence efficiencies. Here, we develop a general surface treatment strategy to obtain intensely luminescent all-inorganic NCs (ILANs) by using designed metal salts with noncoordinating anions that play a dual role in the surface treatment process: (i) removing the original organic ligands and (ii) binding to unpassivated Lewis basic sites to preserve the photoluminescent (PL) properties of the NCs. The absolute photoluminescence quantum yields (PLQYs) of red-emitting CdSe/ZnS NCs, green-emitting CdSe/CdZnSeS/ZnS NCs and blue-emitting CdZnS/ZnS NCs in polar solvents are 97%, 80% and 72%, respectively. Further study reveals that the passivated Lewis basic sites of ILANs by metal cations boost the efficiency of radiative recombination of electron-hole pairs. While the passivation of Lewis basic sites leads to a high PLQY of ILANs, the exposed Lewis acidic sites provide the possibility for in situ tuning of the functions of NCs, creating opportunities for direct optical patterning of functional NCs with high resolution. 
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    Free, publicly-accessible full text available December 1, 2024
  3. Free, publicly-accessible full text available August 1, 2024
  4. Free, publicly-accessible full text available July 26, 2024
  5. Abstract

    The DescribePROT database of amino acid-level descriptors of protein structures and functions was substantially expanded since its release in 2020. This expansion includes substantial increase in the size, scope, and quality of the underlying data, the addition of experimental structural information, the inclusion of new data download options, and an upgraded graphical interface. DescribePROT currently covers 19 structural and functional descriptors for proteins in 273 reference proteomes generated by 11 accurate and complementary predictive tools. Users can search our resource in multiple ways, interact with the data using the graphical interface, and download data at various scales including individual proteins, entire proteomes, and whole database. The annotations in DescribePROT are useful for a broad spectrum of studies that include investigations of protein structure and function, development and validation of predictive tools, and to support efforts in understanding molecular underpinnings of diseases and development of therapeutics. DescribePROT can be freely accessed at

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  6. Free, publicly-accessible full text available March 8, 2024
  7. Abstract

    In this work, we provide clear evidence of magnetic anisotropy in the local orbital moment of a molecular thin film based on the SCO complex [Fe(H2B(pz)2)2(bipy)] (pz = pyrazol−1−yl, bipy = 2,2′−bipyridine). Field dependent x-ray magnetic circular dichroism measurements indicate that the magnetic easy axis for the orbital moment is along the surface normal direction. Along with the presence of a critical field, our observation points to the existence of an anisotropic energy barrier in the high-spin state. The estimated nonzero coupling constant of ∼2.47 × 10−5eV molecule−1indicates that the observed magnetocrystalline anisotropy is mostly due to spin–orbit coupling. The spin- and orbital-component anisotropies are determined to be 30.9 and 5.04 meV molecule−1, respectively. Furthermore, the estimatedgfactor in the range of 2.2–2.45 is consistent with the expected values. This work has paved the way for an understanding of the spin-state-switching mechanism in the presence of magnetic perturbations.

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  8. Abstract

    Using optical characterization, it is evident that the spin state of the spin crossover molecular complex [Fe{H2B(pz)2}2(bipy)] (pz = tris(pyrazol-1-1y)-borohydride, bipy = 2,2ʹ-bipyridine) depends on the electric polarization of the adjacent polymer ferroelectric polyvinylidene fluoride-hexafluoropropylene (PVDF-HFP) thin film. The role of the PVDF-HFP thin film is significant but complex. The UV–Vis spectroscopy measurements reveals that room temperature switching of the electronic structure of [Fe{H2B(pz)2}2(bipy)] molecules in bilayers of PVDF-HFP/[Fe{H2B(pz)2}2(bipy)] occurs as a function of ferroelectric polarization. The retention of voltage-controlled nonvolatile changes to the electronic structure in bilayers of PVDF-HFP/[Fe{H2B(pz)2}2(bipy)] strongly depends on the thickness of the PVDF-HFP layer. The PVDF-HFP/[Fe{H2B(pz)2}2(bipy)] interface may affect PVDF-HFP ferroelectric polarization retention in the thin film limit.

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