The Experts below are selected from a list of 264078 Experts worldwide ranked by ideXlab platform
Shuichi Hirono - One of the best experts on this subject based on the ideXlab platform.
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Identification of novel EED-EZH2 PPI inhibitors using an in silico fragment Mapping Method
Journal of Computer-Aided Molecular Design, 2021Co-Authors: Kensuke Misawa, Noriyuki Yamaotsu, Shuichi HironoAbstract:Enhancer of zeste homolog 2 (EZH2) is a histone lysine methyltransferase that is overexpressed in many cancers. Numerous EZH2 inhibitors have been developed as anticancer agents, but recent studies have also focused on protein–protein interaction (PPI) between embryonic ectoderm development (EED) and EZH2 as a novel drug discovery target. Because EED indirectly enhances EZH2 enzymatic activity, EED-EZH2 PPI inhibitors suppress the methyltransferase activity and inhibit cancer growth. By contrast to the numerous promising EZH2 inhibitors, there are a paucity of EED-EZH2 PPI inhibitors reported in the literature. Here, we aimed to discover novel EED-EZH2 PPI inhibitors by first identifying possible binders of EED using an in-house knowledge-based in silico fragment Mapping Method. Next, 3D pharmacophore models were constructed from the arrangement pattern of the potential binders mapped onto the EED surface. In all, 16 compounds were selected by 3D pharmacophore-based virtual screening followed by docking-based virtual screening. In vitro evaluation revealed that five of these compounds exhibited inhibitory activities. This study has provided structural insights into the discovery and the molecular design of novel EED-EZH2 PPI inhibitors using an in silico fragment Mapping Method.
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In silico fragment-Mapping Method: a new tool for fragment-based/structure-based drug discovery
Journal of Computer-Aided Molecular Design, 2018Co-Authors: Noriyuki Yamaotsu, Shuichi HironoAbstract:Here, we propose an in silico fragment-Mapping Method as a potential tool for fragment-based/structure-based drug discovery (FBDD/SBDD). For this Method, we created a database named Canonical Subsite–Fragment DataBase (CSFDB) and developed a knowledge-based fragment-Mapping program, Fsubsite. CSFDB consists of various pairs of subsite–fragments derived from X-ray crystal structures of known protein–ligand complexes. Using three-dimensional similarity-matching between subsites on one protein and another, Fsubsite compares the surface of a target protein with all subsites in CSFDB. When a local topography similar to the subsite is found on the surface, Fsubsite places a fragment combined with the subsite in CSFDB on the target protein. For validation purposes, we applied the Method to the apo-structure of cyclin-dependent kinase 2 (CDK2) and identified four compounds containing three mapped fragments that existed in the list of known inhibitors of CDK2. Next, the utility of our fragment-Mapping Method for fragment-growing was examined on the complex structure of tRNA-guanine transglycosylase with a small ligand. Fsubsite mapped appropriate fragments on the same position as the binding ligand or in the vicinity of the ligand. Finally, a 3D-pharmacophore model was constructed from the fragments mapped on the apo-structure of heat shock protein 90-α (HSP90α). Then, 3D pharmacophore-based virtual screening was carried out using a commercially available compound database. The resultant hit compounds were very similar to a known ligand of HSP90α. As a result of these findings, this in silico fragment-Mapping Method seems to be a useful tool for computational FBDD and SBDD.
Noriyuki Yamaotsu - One of the best experts on this subject based on the ideXlab platform.
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Identification of novel EED-EZH2 PPI inhibitors using an in silico fragment Mapping Method
Journal of Computer-Aided Molecular Design, 2021Co-Authors: Kensuke Misawa, Noriyuki Yamaotsu, Shuichi HironoAbstract:Enhancer of zeste homolog 2 (EZH2) is a histone lysine methyltransferase that is overexpressed in many cancers. Numerous EZH2 inhibitors have been developed as anticancer agents, but recent studies have also focused on protein–protein interaction (PPI) between embryonic ectoderm development (EED) and EZH2 as a novel drug discovery target. Because EED indirectly enhances EZH2 enzymatic activity, EED-EZH2 PPI inhibitors suppress the methyltransferase activity and inhibit cancer growth. By contrast to the numerous promising EZH2 inhibitors, there are a paucity of EED-EZH2 PPI inhibitors reported in the literature. Here, we aimed to discover novel EED-EZH2 PPI inhibitors by first identifying possible binders of EED using an in-house knowledge-based in silico fragment Mapping Method. Next, 3D pharmacophore models were constructed from the arrangement pattern of the potential binders mapped onto the EED surface. In all, 16 compounds were selected by 3D pharmacophore-based virtual screening followed by docking-based virtual screening. In vitro evaluation revealed that five of these compounds exhibited inhibitory activities. This study has provided structural insights into the discovery and the molecular design of novel EED-EZH2 PPI inhibitors using an in silico fragment Mapping Method.
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In silico fragment-Mapping Method: a new tool for fragment-based/structure-based drug discovery
Journal of Computer-Aided Molecular Design, 2018Co-Authors: Noriyuki Yamaotsu, Shuichi HironoAbstract:Here, we propose an in silico fragment-Mapping Method as a potential tool for fragment-based/structure-based drug discovery (FBDD/SBDD). For this Method, we created a database named Canonical Subsite–Fragment DataBase (CSFDB) and developed a knowledge-based fragment-Mapping program, Fsubsite. CSFDB consists of various pairs of subsite–fragments derived from X-ray crystal structures of known protein–ligand complexes. Using three-dimensional similarity-matching between subsites on one protein and another, Fsubsite compares the surface of a target protein with all subsites in CSFDB. When a local topography similar to the subsite is found on the surface, Fsubsite places a fragment combined with the subsite in CSFDB on the target protein. For validation purposes, we applied the Method to the apo-structure of cyclin-dependent kinase 2 (CDK2) and identified four compounds containing three mapped fragments that existed in the list of known inhibitors of CDK2. Next, the utility of our fragment-Mapping Method for fragment-growing was examined on the complex structure of tRNA-guanine transglycosylase with a small ligand. Fsubsite mapped appropriate fragments on the same position as the binding ligand or in the vicinity of the ligand. Finally, a 3D-pharmacophore model was constructed from the fragments mapped on the apo-structure of heat shock protein 90-α (HSP90α). Then, 3D pharmacophore-based virtual screening was carried out using a commercially available compound database. The resultant hit compounds were very similar to a known ligand of HSP90α. As a result of these findings, this in silico fragment-Mapping Method seems to be a useful tool for computational FBDD and SBDD.
Kaihua Liu - One of the best experts on this subject based on the ideXlab platform.
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ISCAS - An enhanced Neuro-Space Mapping Method for nonlinear microwave device modeling
2012 IEEE International Symposium on Circuits and Systems, 2012Co-Authors: Lin Zhu, Qi-jun Zhang, Kaihua LiuAbstract:In this article, a new Neuro-Space Mapping Method is presented aimed at using neural networks to automatically enhance nonlinear device models, such as FET models. Compared with previously published space Mapping Methods, our proposed Method produces better modeling accuracy and provides more effective combinations of Mapping structure with existing coarse model. In our proposed models, separate Mappings for voltage and current at gate and drain are used as the Mapping structure. Training Methods for Mapping neural networks are also proposed. Application examples on modeling MESFET devices and the use of new models in DC, S-parameter and combined DC and S-parameter simulation demonstrate that our proposed Neuro-Space Mapping model matches more closely with the device data than that by the traditional Neuro-Space Mapping Method for modeling nonlinear microwave devices.
Wang Men - One of the best experts on this subject based on the ideXlab platform.
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Spherical Texture Mapping Method for Large-scale Point Cloud Data
Computer Engineering, 2015Co-Authors: Wang MenAbstract:Data texture Mapping Methods based on the Delaunay triangular mesh are usually computationally slow and the quality of Mapping is low,making them unsuitable for large-scale point cloud data. In this paper,an improved spherical texture Mapping Method is developed for the reconstruction of point cloud data and it can be implemented based on the Qsplat algorithm. The Qsplat algorithm is used to re-establish the model of large-scale point cloud data. The spherical equal-ratio constraint texture Mapping is used to obtain the mathematical relationship among texture coordinates,sphere and the reconstructed model,realizing the spherical texture Mapping of large scale point data. Experimental results show that the speed and the quality of Mapping of the proposed Method are much improved compared with those traditional triangular texture Mapping Methods.
Jie Zhao - One of the best experts on this subject based on the ideXlab platform.
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Research on the Poincare Mapping Method of T-wave alternans based on morphology
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2013Co-Authors: Hui Guo, Jie ZhaoAbstract:This paper introduces an algorithm for detecting T wave alternans (TWA) using Poincare Mapping Method, which is a technique for nonlinear dynamic systems to display periodic behavior. Vector angle index (VAI) was used to determine the presence or absence of TWA. Adopting MIT/BIH Arrhythmia database and European ECG ST-T database to simulate, we used VAI via poincare Mapping Method for correlation analysis with Vtwa by way of the spectral Method. The cross-correlation coefficient between Vtwa and VAI is gamma = 0.860 1. The algorithm can identify the absence and presence of TWA accurately and provide idea for further study of TWA.
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On the basis of the morphology of the T-wave alternans: A Poincare Mapping Method research
Journal of Biomedical Science and Engineering, 2013Co-Authors: Hui Guo, Jie ZhaoAbstract:Presently T-wave alternans (TWA) has become a clinical index of non-invasive diagnosis for heart sudden death prediction, and detecting T-wave alternate accurately is particularly important. This paper introduces an algorithm for detecting TWA using Poincare Mapping Method which is a technique for nonlinear dynamic systems to display periodic behavior. Sample series of beat to beat cycles were selected to prepare Poincare Mapping Method. Vector Angle Index (VAI), which is the mean of the difference between θi (the angle between the line connecting the i point to the origin and the X axis) and 45 degrees was used to present the presence or absence of TWA. The value of 0.9 rad ≤ VAI ≤ 1.03 rad is accepted as a level determinative for presence of TWA. VAI via Poincare Mapping Method (PM) is used for correlation analysis with T-wave alternans voltage (Vtwa) by way of the spectral Method (SM). The cross-correlation coefficient between Vtwa and VAI is γ = 0.8601. The algorithm can identify the absence and presence of TWA accurately and provide idea for further study of TWA-PM.
