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Importance of a crystalline water network in docking-based virtual screening: a case study of BRD4

PHYSICAL CHEMISTRY CHEMICAL PHYSICS 2019年第45期21卷 25276-25289页

作者： Zhong, Haiyang wang, Zhe wang, xuwen Liu, Hui Li, Dan Liu, Huanxiang Yao, Xiaojun Hou, Tingjun Lanzhou Univ State Key Lab Appl Organ Chem Lanzhou 730000 Peoples R China Lanzhou Univ Dept Chem Lanzhou 730000 Peoples R China Zhejiang Univ Coll Pharmaceut Sci Hangzhou 310058 Zhejiang Peoples R China Lanzhou Univ Sch Pharm Lanzhou 730000 Peoples R China Macau Univ Sci & Technol Macau Inst Appl Res Med & Hlth State Key Lab Qual Res Chinese Med Taipa Macao Peoples R China

As a member of the bromodomain and extra terminal domain (BET) protein family, bromodomain-containing protein 4 (BRD4) is an epigenetic reader and can recognize acetylated lysine residues in histones. BRD4 has been regarded as an essential drug target for cancers, inflammatory diseases and acute heart failure, and therefore the discovery of potent BRD4 inhibitors with novel scaffolds is highly desirable. In this study, the crystalline water molecules in BRD4 involved in ligand binding were analyzed first, and the simulation results suggest that several conserved crystalline water molecules are quite essential to keep the stability of the crystalline water network and therefore they need to be reserved in structure-based drug design. Then, a docking-based virtual screening workflow with the consideration of the conserved crystalline water network in the binding pocket was utilized to identify the potential inhibitors of BRD4. The in vitro fluorescence resonance energy transfer (HTRF) binding assay illustrates that 4 hits have good inhibitory activity against BRD4 in the micromolar regime, including three compounds with IC50 values below 5 mu M and one below 1 mu M (0.37 mu M). The structural analysis demonstrates that three active compounds possess novel scaffolds. Moreover, the interaction patterns between the hits and BRD4 were characterized by molecular dynamics simulations and binding free energy calculations, and then several suggestions for the further optimization of these hits were proposed.

关键词： Proteins

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南疆中熟陆地棉化学打顶与后期管理技术

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中国棉花 2022年第5期49卷 44-45页

作者：王刚陈兵王旭文马晓梅新疆农垦科学院新疆石河子832000

为满足南疆棉花生产全程机械化和节本高效的要求,根据多年小区试验与大田生产实践,结合南疆地区气候、土壤、品种等因素,提出了南疆中熟陆地棉化学打顶与后期管理技术,包括:适用范围、药剂选择、喷药要求、施药技术与注意事项、后期管... 详细信息

为满足南疆棉花生产全程机械化和节本高效的要求,根据多年小区试验与大田生产实践,结合南疆地区气候、土壤、品种等因素,提出了南疆中熟陆地棉化学打顶与后期管理技术,包括:适用范围、药剂选择、喷药要求、施药技术与注意事项、后期管理技术等,以期为该技术在南疆大面积示范推广提供参考。

关键词：南疆陆地棉化学打顶后期管理

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新疆棉花生产全程机械化机艺融合技术

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中国棉花 2022年第3期49卷 24-26页

作者：王刚陈兵王旭文马晓梅新疆农垦科学院新疆石河子832000

针对新疆棉花耕地连作障碍突出、肥水管理粗放、全程机械化比例偏低等因素导致的棉花生产成本高、棉农植棉效益下降等问题,分析了实现棉花生产机械化和轻简化转型升级的途径,总结了新疆棉花全程机械化机艺融合技术,包括:选地整地、精量... 详细信息

针对新疆棉花耕地连作障碍突出、肥水管理粗放、全程机械化比例偏低等因素导致的棉花生产成本高、棉农植棉效益下降等问题,分析了实现棉花生产机械化和轻简化转型升级的途径,总结了新疆棉花全程机械化机艺融合技术,包括:选地整地、精量精准播种、种植模式、深松、水肥药一体化、化学调控、无人机飞防、化学脱叶、机械采收、秸秆还田与残膜回收等各项技术,以期为新疆棉花可持续发展提供技术先导和引领示范。

关键词：棉花机械化机艺融合新疆

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FilterLAP: Filtering False-positive Mutation Calls via a Label Propagation Framework

FilterLAP: Filtering False-positive Mutation Calls via a Lab...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： wang, xuwen Zhu, Xiaoyan Xiao, Xiao wang, Shenjie Zhang, Xuanping Lai, Xin wang, Jiayin Xi An Jiao Tong Univ Sch Comp Sci & Technol Xian Peoples R China Xi An Jiao Tong Univ Shaanxi Engn Res Ctr Med & Hlth Big Data Xian Peoples R China Xi An Jiao Tong Univ Sch Publ Policy & Adm Xian Peoples R China

ISBN: (纸本)9781728118673

Benefiting from the recent advantages of genomic sequencing, detecting genomic mutations becomes a routine work in precise diagnoses and treatments for cancers. In clinical practices, many factors, such as tumor purity, clonal structure, etc., interfere the performance of calling mutations. The computational pipelines prefer to sensitively report the candidate calls, while a filter is applied for removing the false-positive calls. The existing filters rely on the whole genome/exome sequencing data, which can provide sufficient samples for training the filters. However, the gene-panel sequencing is more popular in clinical practices, but there is no practical filter for limited training samples. In light of this, we develop a semi-learning filter for gene-panel sequencing data, FilterLAP, which implemented via a label propagation framework. Given few labeled samples with a set of unlabeled ones, its basic idea is to predict the label information of unlabeled nodes from the label information of labeled nodes, and establishes a complete graph model by using the relationship between samples, by combining transductive inference with label propagation algorithm. For each node in the network, tags are propagated to adjacent nodes according to similarity and the probability distribution of similar nodes tends to be similar and can be divided into a class. We perform multiple sets of experiments on gene-panel sequencing data captured from Illumina platform. FilterLAP outperforms on both SNV and INDEL filtering, where the AUCs reach 0.90-0.97, and the average accuracies on overall mutation calls are over 90%. Comparing to GATK hard filters, FilterLAP present a 5% improvement on accuracy. These results demonstrate that the proposed method can better reduce the false positive mutation calls on gene-panel sequencing data. In addition, it is stable and efficient, which can be used as a practical tool for mutation call filtering for gene-panel sequencing data.

关键词： Cancer genomics NGS data analysis Gene-panel sequencing Mutation Filter transductive inference Label propagation

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IMageSEM at ImagecleFmed caption 2019 task: A two-stage medical concept detection strategy 20

IMageSEM at ImagecleFmed caption 2019 task: A two-stage medi...

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20th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2019

作者： Guo, Zhen wang, xuwen Zhang, Yu Li, Jiao Institute of Medical Information Medical Library Chinese Academy of Medical Sciences Peking Union Medical College Beijing100020 China

This paper presents the participation of the Image Semantics group (ImageSem) of the Institute of Medical Information at the ImageCLEFmed Caption task, which was launched by ImageCLEF 2019. The Concept Detection sub-task aims at identifying 5,528 semantic concepts from 70,786 training images and 10,000 test images. In this study, we proposed the two-stage concept detection strategy, including the medical image pre-classification based on body parts and the transfer learning-based multi-label classification model. We totally submitted 10 runs in the final evaluation. The evaluation results showed that we achieved an F1 Score of 0.2235, which ranked 8th overall. There is still a great room for improving the performance of concept detection from large-scale medical images. © 2019 CEUR-WS. All rights reserved.

关键词： Classification (of information)

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DNA methyltransferases: emerging targets for the discovery of inhibitors as potent anticancer drugs

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DRUG DISCOVERY TODAY 2019年第12期24卷 2323-2331页

作者： Yu, Jie Xie, Tianli wang, Zhe wang, xuwen Zeng, Su Kang, Yu Hou, Tingjun Zhejiang Univ Coll Pharmaceut Sci Hangzhou 310058 Zhejiang Peoples R China

DNA methyltransferases (DNMTs) are a conserved family of cytosine methylases with crucial roles in epigenetic regulation. They have been considered as promising therapeutic targets for the epigenetic treatment of cancer. Therefore, DNMT inhibitors (DNMTis) have attracted considerable interest in recent years for the modulation of the aberrant DNA methylation pattern in a reversible way. In this review, we provide a structure-based overview of the therapeutic importance of DNMTs against different cancer types, and then summarize recently investigated DNMTis as well as their inhibitory mechanisms, focusing on recent advances in the development of DNMTis with specificity and/or selectivity using computational approaches.

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脑震宁方对模型大鼠脑组织神经元的保护作用

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医药导报 2022年第1期41卷 17-23页

作者：赵乐刘海霞刘涛窦殿奎张晨曦王超群王永辉王旭文山西中医药大学基础医学院晋中030619 山西振东生物制药有限公司晋中030600 湖北中医药大学基础医学院武汉430065

目的探讨脑震宁方对模型大鼠脑组织神经元的保护作用。方法通过金属单摆闭合性击打方式,建立脑震荡模型,造模成功的大鼠随机分为模型对照组(给予等体积纯化水)、吡拉西坦组(0.324 g·kg^(-1))和脑震宁小、中、大剂量组(2.5,5.0,10.0... 详细信息

目的探讨脑震宁方对模型大鼠脑组织神经元的保护作用。方法通过金属单摆闭合性击打方式,建立脑震荡模型,造模成功的大鼠随机分为模型对照组(给予等体积纯化水)、吡拉西坦组(0.324 g·kg^(-1))和脑震宁小、中、大剂量组(2.5,5.0,10.0 g·kg^(-1)),每组10只,并设10只正常大鼠作为正常对照组(给予等体积纯化水)。各组大鼠分别按10 mL·kg^(-1)灌胃给药,每天1次,连续21 d。采用Weil氏染色和甲苯胺蓝染色检测大脑神经髓鞘和尼氏体结构改变,免疫组化法检测大脑诱导型一氧化氮合成酶(iNOS)、基质金属蛋白酶9(MMP-9)、胶质纤维酸性蛋白(GFAP)、白细胞介素6(IL-6)阳性表达,逆转录-聚合酶链反应(RT-PCR)检测脑组织细胞外信号调节激酶(ERK)、IL-6和MMP-9 mRNA表达。结果脑震宁方可减轻模型大鼠精神狂躁及脑组织神经髓鞘断裂、弯曲肿胀,促进神经元尼氏体恢复,提高GFAP和MMP-9表达,同时抑制脑组织ERK、IL-6和iNOS表达。结论脑震宁方可能通过抑制脑震荡后ERK信号通路激活,减轻炎症反应对以神经细胞髓鞘和尼氏体为主要病理改变的神经损伤,从而改善脑震荡产生的精神症状。

关键词：脑震宁方脑震荡神经元细胞外信号调节激酶信号通路

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Changes in water quality along the process of coal chemical reverse osmosis wastewater advanced treatment: Spectral analysis and molecular level exploration

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SEPARATION AND PURIFICATION TECHNOLOGY 2025年 360卷

作者： Yuan, Run Qin, Yihe wang, Hao He, xuwen Dongguan Univ Technol Sch Environm & Civil Engn Dongguan 523808 Peoples R China CNPC Res Inst Safety & Environm Technol Beijing 102206 Peoples R China China Univ Min & Technol Sch Chem & Environm Engn Beijing 100083 Peoples R China

Investigating changes in the organic pollutant composition of coal chemical wastewater during the advanced treatment process is crucial for enhancing the efficiency of wastewater treatment systems. In this study, the molecular composition and changes in dissolved organic matter (DOM) were analyzed in a typical coal gasification reverse osmosis concentrate during various advanced treatment processes, including flocculation, ultrafiltration, adsorption, and catalytic ozonation, were investigated using conventional water quality analysis, ultraviolet spectroscopy, fluorescence spectroscopy, molecular weight fractionation analysis, organic component fractionation methods, and Fourier-transform ion cyclotron resonance mass spectrometry. After the advanced treatment process, the concentrations of organic pollutants in the effluent decreased significantly, and the final treated effluent COD was reduced to 90 mg/L. Analysis of the molecular weight fractions showed that after treatment, the proportion of low-molecular-weight organic pollutants (<3k Da) in the coal chemical reverse osmosis concentrate exceeded 50 %. The mass-to-charge ratio of organics in wastewater ranged between 100 and 800, most DOM molecules were unsaturated reduced-state recalcitrant organic molecules, and the DOM molecules in wastewater were mainly distributed among lignin-like, condensed aromatic, and protein-like organics. Compared to the other advanced treatment processes, catalytic ozonation efficiently removed refractory ligninlike organics from wastewater. We revealed the characteristics of organic pollutants in coal chemical reverse osmosis concentrates during the advanced treatment process using various characterization methods, which can assist in further exploring the degradation mechanisms of organics in actual wastewater to enhance the efficiency of wastewater treatment units.

关键词： Water quality analysis Coal chemical wastewater Advanced treatment technology Dissolved organic pollutants

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GSDcreator: An Efficient and Comprehensive Simulator for Genarating NGS Data with Population Genetic Information

GSDcreator: An Efficient and Comprehensive Simulator for Gen...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： wang, Shenjie wang, Jiayin Xiao, Xiao Zhang, Xuanping wang, xuwen Zhu, Xiaoyan Lai, Xin Xi An Jiao Tong Univ Sch Comp Sci & Technol Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Shaanxi Engn Res Ctr Med & Hlth Big Data Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Sch Publ Policy & Adm Xian 710049 Shaanxi Peoples R China

ISBN: (纸本)9781728118673

In recent decades, NGS data analysis has become a major research field in bioinformatics, which presents great advantages in many application scenarios. Many algorithms and software were designed for analyzing the NGS data, while simulation datasets are urgently needed for testing software and optimizing their parameter configurations. Thus, a series of NGS data simulators have been published. However, the existing simulators cannot satisfy the requirements from many specific scenarios. First, they do not support many newly discovered variations. Second, complex structural variations are difficult to generate. In addition, along with the increase of population data, it is urgent to increase population information simulation. In this paper, we propose GSDcreator, a comprehensive NGS simulator that overcome the three weaknesses mentioned above. It can produce all known types of variation, where the complex of variations are also supported. Furthermore, it can capture many important real data features including population polymorphism, insert size distribution, adjacent site depth distribution, overall depth distribution, quality score distribution, amplification bias, sequencing errors and so on. It's highlighted that 1000 Genomes Project Database is taken as a reference and integrates population genetic information to simulate population polymorphism. To test the performance, we did a lot of experiments and found that simulated data produced by GSDcreator are quit mimic to the real sequencing data.

关键词： population genomics next-generation sequencing data analysis data simulator population information

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Finer soil properties mapping framework for broad-scale area: A case study of Hubei Province, China

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GEODERMA 2024年 449卷

作者： wang, Ruizhen Chen, Weitao Chen, Hao Qin, xuwen China Univ Geosci Key Lab Geol Survey & Evaluat Minist Educ Wuhan 430074 Peoples R China China Univ Geosci Fac Comp Sci Wuhan 430074 Peoples R China Minist Educ Engn Res Ctr Nat Resource Informat Management & Di Wuhan 430074 Peoples R China China Geol Survey China Aero Geophys Survey & Remote Sensing Ctr Nat Beijing 100083 Peoples R China

Fine-scale spatial distribution of soil physicochemical properties is crucial for soil quality management, agriculture planning and geotechnical engineering. Existing soil map databases are usually developed in national scale, potentially leading to issues of coarse resolution and restricted applicability in fine-scaled studies. For broad-scale area, conventional digital soil mapping methods are challenging due to the lack of representative soil profiles and their uneven distribution. This study addresses these challenges by developing a downscaling-based framework to map 11 soil physicochemical properties at a 30-m resolution. The methodology involves constructing regression models using soil properties derived from coarse national soil maps and soil-forming covariates. Predictions are subsequently refined using fine-resolution covariates. To capture fine-scale spatial variability across diverse landscapes, 30-m resolution remote sensing data, relief, climate, and spatial covariates were prepared. The fine-gridding framework employs tree-based machine learning models, particularly random forest (RF), to enhance prediction accuracy. Evaluation of the fine-gridded soil maps demonstrated commendable results, with high consistency in summary statistics, semi-variograms, and evaluation metrics compared to reference maps. Mass preservation of RF-predicted maps exhibit high performances with both concordance correlation coefficients (CCCs) and coefficients of determination (R(2)s) exceeding 0.9 across most scenarios. This study provides a robust approach for enhancing the spatial resolution of soil maps, facilitating their use in local fine-scale applications. The proposed strategy offers a valuable solution for broad-scale areas that require finer soil maps but lack sufficient qualified soil profiles.

关键词： Digital soil mapping Broad-scale Fine gridding Downscaling Machine learning

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