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Baofeng Zhang

Researcher at City University of New York

Publications -  18
Citations -  203

Baofeng Zhang is an academic researcher from City University of New York. The author has contributed to research in topics: Crystal structure & Coordination polymer. The author has an hindex of 8, co-authored 17 publications receiving 170 citations. Previous affiliations of Baofeng Zhang include Brown University & Tsinghua University.

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Asynchronous replica exchange software for grid and heterogeneous computing

TL;DR: The architecture of a software for performing asynchronous replica exchange molecular simulations on volunteered computing grids and heterogeneous high performance clusters is described and applications of the software for the modeling of association equilibria of supramolecular and macromolecular complexes are illustrated.
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Synthesis, crystal structure, and magnetic property of a novel 2D polymer [Co(PDC)(4,4-bpy)](CH3OH)

TL;DR: In this article, a two-dimensional (2D) layer polymeric structure consisting of six-coordinated cobalt(II) units has been determined by X-ray diffraction.
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A Novel 3D CuI Metal–Organic Framework with Middle‐Size Channels Despite the Sixfold ThSi2 Interpenetrating Topological Structure

TL;DR: In this paper, a new univalent copper coordination polymer with an unusual asymmetric ThSi2 topological structural network was synthesized and 1D middle-size channels were found despite the sixfold thSi2 interpenetrating topological structure.
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Free Energy-Based Virtual Screening and Optimization of RNase H Inhibitors of HIV-1 Reverse Transcriptase.

TL;DR: Binding free energy-based optimization of the lead compounds emerging from the virtual screen has yielded four compounds with very favorable binding properties, which will be the subject of further experimental investigations.
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Large scale free energy calculations for blind predictions of protein–ligand binding: the D3R Grand Challenge 2015

TL;DR: The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.