Junru Zhu

Bio: Junru Zhu is an academic researcher from Nanjing University of Chinese Medicine. The author has contributed to research in topics: Virtual screening & Docking (molecular). The author has an hindex of 2, co-authored 3 publications receiving 26 citations.

Combined pharmacophore modeling, 3D-QSAR and docking studies to identify novel HDAC inhibitors using drug repurposing.

Abstract: Histone deacetylases (HDACs), a critical family of epigenetic enzymes, has emerged as a promising target for antitumor drugs. Here, we describe our protocol of virtual screening in identification o...

Discovery of Novel Serine/Threonine Protein phosphatase 1 Inhibitors from Traditional Chinese Medicine through Virtual Screening and Biological Assays.

Abstract: Protein phosphatase 1 (PP1) is a critical regulator of several processes, such as muscle contraction, neuronal signaling, glycogen synthesis, and cell proliferation. Dysregulation of PP1 has recent...

Determination of ensemble-average pairwise root mean-square deviation from experimental B-factors.

Abstract: Root mean-square deviation (RMSD) after roto-translational least-squares fitting is a measure of global structural similarity of macromolecules used commonly. On the other hand, experimental x-ray B-factors are used frequently to study local structural heterogeneity and dynamics in macromolecules by providing direct information about root mean-square fluctuations (RMSF) that can also be calculated from molecular dynamics simulations. We provide a mathematical derivation showing that, given a set of conservative assumptions, a root mean-square ensemble-average of an all-against-all distribution of pairwise RMSD for a single molecular species, (1/2), is directly related to average B-factors () and (1/2). We show this relationship and explore its limits of validity on a heterogeneous ensemble of structures taken from molecular dynamics simulations of villin headpiece generated using distributed-computing techniques and the Folding@Home cluster. Our results provide a basis for quantifying global structural diversity of macromolecules in crystals directly from x-ray experiments, and we show this on a large set of structures taken from the Protein Data Bank. In particular, we show that the ensemble-average pairwise backbone RMSD for a microscopic ensemble underlying a typical protein x-ray structure is approximately 1.1 A, under the assumption that the principal contribution to experimental B-factors is conformational variability.

Assessing Performance: National Versus Regional Patterns

Abstract: This chapter asks whether standard theories of differences between Canada and the United States (U.S.) can explain disparities in critical social and political outcomes in the two countries. On six measures of system performance (homicides, infant mortality, poverty, economic inequality, voter turnout, and women legislators) Canada consistently delivers far better outcomes than the U.S., but examination of subnational variation reveals a more complex pattern. Most indicators differ more among U.S. states than among Canadian provinces. Within the U.S., outcomes in the northern tier of states usually resemble those in neighboring Canada more closely than they do the rest of the U.S., especially the South, which performs worst by every measure. Standard institutional and cultural theories of differences between the countries cannot explain regional variation within the U.S. nor the similarity of Northern Border states to Canada. Although obvious differences between Canadian and U.S. political institutions help account for greater homogeneity among provinces, explaining the overall pattern may require invoking such causes as climate, ethnic diversity, size of political units, and subnational political cultures.

Dual inhibitors of SARS-CoV-2 proteases: pharmacophore and molecular dynamics based drug repositioning and phytochemical leads.

Abstract: SARS-related coronaviruses poses continual threat to humanity by rapidly mutating and emerging as severe pandemic outbreaks, including the current nCoV-19 pandemic. Hence a rapid drug repositioning and lead identification strategy are required to mitigate these outbreaks. We report a pharmacophore and molecular dynamics-based approach for drug repositioning and lead identification against dual targets (3CLp and PLp) of SARS-CoV-2. The pharmacophore model of 3CLp inhibitors was apolar with two aromatic and two H-bond acceptors, whereas that of PLp was relatively polar, bearing one aromatic and three H-bond acceptors. Pharmacophore-based virtual screening yielded six existing FDA-approved drugs and twelve natural products with both the pharmacophoric features. Among them are nelfinavir, tipranavir and licochalcone-D, which has shown better binding characteristics with both the proteases compared to lopinavir. The molecular dynamics revealed that the connecting loop (residues 176-199) of 3CLp is highly flexible, and hence, inhibitors should avoid high-affinity interactions with it. Lopinavir, due to its high affinity with the loop region, exhibited unstable binding. Further, the van der Waals size of the 3CLp inhibitors positively correlated with their binding affinity with 3CLp. However, the van der Waals size of a ligand should not cross a threshold of 572A3, beyond which the ligands are likely to make high-affinity interaction with the loop and suffer unstable binding as observed in the case of lopinavir. Similarly, the total polar surface area of the ligands were found to be negatively correlated with their binding affinity with PLp.