RBRDetector: Improved prediction of binding residues on RNA‐binding protein structures using complementary feature‐ and template‐based strategies

Computational prediction of RNA‐binding residues is helpful in uncovering the mechanisms underlying protein‐RNA interactions. Traditional algorithms individually applied feature‐ or template‐based prediction strategy to recognize these crucial residues, which could restrict their predictive power. To improve RNA‐binding residue prediction, herein we propose the first integrative algorithm termed RBRDetector (RNA‐Binding Residue Detector) by combining these two strategies. We developed a feature‐based approach that is an ensemble learning predictor comprising multiple structure‐based classifiers, in which well‐defined evolutionary and structural features in conjunction with sequential or structural microenvironment were used as the inputs of support vector machines. Meanwhile, we constructed a template‐based predictor to recognize the putative RNA‐binding regions by structurally aligning the query protein to the RNA‐binding proteins with known structures. The final RBRDetector algorithm is an ingenious fusion of our feature‐ and template‐based approaches based on a piecewise function. By validating our predictors with diverse types of structural data, including bound and unbound structures, native and simulated structures, and protein structures binding to different RNA functional groups, we consistently demonstrated that RBRDetector not only had clear advantages over its component methods, but also significantly outperformed the current state‐of‐the‐art algorithms. Nevertheless, the major limitation of our algorithm is that it performed relatively well on DNA‐binding proteins and thus incorrectly predicted the DNA‐binding regions as RNA‐binding interfaces. Finally, we implemented the RBRDetector algorithm as a user‐friendly web server, which is freely accessible at http://ibi.hzau.edu.cn/rbrdetector . Proteins 2014; 82:2455–2471. © 2014 Wiley Periodicals, Inc.     

Stress and the developing hippocampus: a double-edged sword?

The mechanisms that regulate neuronal function are a sum of genetically determined programs and experience. The effect of experience on neuronal function is particularly important during development, because early-life positive and adverse experience (stress) may influence the still “plastic” nervous system long-term. Specifically, for hippocampal-mediated learning and memory processes, acute stress may enhance synaptic efficacy and overall learning ability, and conversely, chronic or severe stress has been shown to be detrimental. The mechanisms that enable stress to act as this “double-edged sword” are unclear. Here, we discuss the molecular mediators of the stress response in the hippocampus with an emphasis on novel findings regarding the role of the neuropeptide known as corticotropin-releasing hormone (CRH). We highlight the physiological and pathological roles of this peptide in the developing hippocampus, and their relevance to the long-term effects of early-life experience on cognitive function during adulthood.     

O‐GlcNAcylation of protein kinase A catalytic subunits enhances its activity: a mechanism linked to learning and memory deficits in Alzheimer's disease

Alzheimer's disease (AD) is characterized clinically by memory loss and cognitive decline. Protein kinase A (PKA)‐CREB signaling plays a critical role in learning and memory. It is known that glucose uptake and O‐GlcNAcylation are reduced in AD brain. In this study, we found that PKA catalytic subunits (PKAcs) were posttranslationally modified by O‐linked N‐acetylglucosamine (O‐GlcNAc). O‐GlcNAcylation regulated the subcellular location of PKAcα and PKAcβ and enhanced their kinase activity. Upregulation of O‐GlcNAcylation in metabolically active rat brain slices by O‐(2‐acetamido‐2‐deoxy‐d ‐glucopyranosylidenamino) N‐phenylcarbamate (PUGNAc), an inhibitor of N‐acetylglucosaminidase, increased the phosphorylation of tau at the PKA site, Ser214, but not at the non‐PKA site, Thr205. In contrast, in rat and mouse brains, downregulation of O‐GlcNAcylation caused decreases in the phosphorylation of CREB at Ser133 and of tau at Ser214, but not at Thr205. Reduction in O‐GlcNAcylation through intracerebroventricular injection of 6‐diazo‐5‐oxo‐l ‐norleucine (DON), the inhibitor of glutamine fructose‐6‐phosphate amidotransferase, suppressed PKA‐CREB signaling and impaired learning and memory in mice. These results indicate that in addition to cAMP and phosphorylation, O‐GlcNAcylation is a novel mechanism that regulates PKA‐CREB signaling. Downregulation of O‐GlcNAcylation suppresses PKA‐CREB signaling and consequently causes learning and memory deficits in AD.     

Synaptic transmission and plasticity in the amygdala

Numerous studies in both rats and humans indicate the importance of the amygdala in the acquisition and expression of learned fear. The identification of the amygdala as an essential neural substrate for fear conditioning has permitted neurophysiological examinations of synaptic processes in the amygdala that may mediate fear conditioning. One candidate cellular mechanism for fear conditioning is long-term potentiation (LTP), an enduring increase in synaptic transmission induced by high-frequency stimulation of excitatory afferents. At present, the mechanisms underlying the induction and expression of amygdaloid LTP are only beginning to be understood, and probably involve both theN-methyl-d-aspartate (NMDA) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionate (AMPA) subclasses of glutamate receptors. This article will examine recent studies of synaptic transmission and plasticity in the amygdala in an effort to understand the relationships of these processes to aversive learning and memory.     

国际基因工程机器大赛对本科生科研教育的启示

近年来,国际基因工程机器大赛(International genetically engineered machine,iGEM,简称iGEM大赛)在全球迅猛发展。仅2017年iGEM大赛全球注册队伍就达到了史无前例的313支,中国地区有98支iGEM团队报名参赛并取得了优异成绩。与国内已有的诸多大学生创新项目、科研培养项目不同,iGEM的组织模式是以学生为主体的研究型学习。该模式取得了丰富的教育效果,体现了新的教育理念,对于我国高校组织本科生课外科研训练有较大的借鉴意义。文中以北京大学参加iGEM大赛为线索,介绍国际基因工程机器大赛(iGEM)的背景和基本情况并以一个参赛周期为序再现北京大学iGEM团队组织和参赛的主要过程。通过与其他本科生科研训练的组织模式进行比较,探讨iGEM对本科生科研训练意义,并总结iGEM的组织经验和对本科生科研能力培养以及组织本科生科研学术竞赛的启示,希望能为国内高校的iGEM活动组织以及本科教育改革提供借鉴。     

基因工程综合实训教学改革与创新

为培养学生的岗位职业能力,实现与岗位零对接,基因工程综合实训以工作任务为线索确定教学内容,以产品生产流程为载体设计教学过程,以职业能力为依据改革教学方法,以发展性评价为手段,强化技能形成。实践证明,"基因工程综合实训"教学改革,有利于培养学生的动手能力和实践创新能力,有利于促进以职业能力培养为核心的教育。     

Conceptual Method of Temperature Sensation in Bionic Hand by Extraordinary Perceptual Phenomenon

Lack of temperature sensation of myoelectric prosthetic hand limits the daily activities of amputees.To this end,a non-invasive temperature sensation method is proposed to train amputees to sense temperature with psychophysical sensory substitution.In this study,22 healthy participants took part besides 5 amputee participants.The duration time of the study was 31 days with five test steps according to the Leitner technique.An adjustable temperature mug and a Peltier were used to change the temperature of the water/phantom digits to induce temperature to participants.Also,to isolate the surround-ings and show colors,a Virtual Reality(VR)glass was employed.The statistical results conducted are based on the response of participants with questionnaire method.Using Chi-square tests,it is concluded that participants answer the experiment significantly correctly using the Leitner technique(P value＜0.05).Also,by applying the"Repeated Measures ANOVA",it is noticed that the time of numbness felt by participants had significant(P value＜0.001)difference.Participants could remember lowest and highest temperatures significantly better than other temperatures(P value＜0.001);furthermore,the well-trained amputee participant practically using the prosthesis with 72.58％could identify object's temperature with only once time experimenting the color temperature.     

基于机器学习的药物-靶标相互作用预测*

近年来,随着计算机硬件、软件工具和数据丰度的不断突破,以机器学习为代表的人工智能技术在生物、基础医学和药学等领域的应用不断拓展和融合,极大地推动了这些领域的发展,尤其是药物研发领域的变革。其中,药物-靶标相互作用(drug-target interactions, DTI)的识别是药物研发领域中的重要难题和人工智能技术交叉融合的热门方向,研究人员在DTI预测方面做了大量的工作,构建了许多重要的数据库,开发或拓展了各类机器学习算法和工具软件。对基于机器学习的DTI预测的基本流程进行了介绍,并对利用机器学习预测DTI的研究进行了回顾,同时对不同的机器学习方法运用于DTI预测的优缺点进行了简单总结,以期对开发更加有效的预测算法和DTI预测的发展提供帮助。     

HIV-1 Neutralizing Antibody Signatures and Application to Epitope-Targeted Vaccine Design

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葛根素对血管性痴呆大鼠海马突触传递长时程增强的影响

目的：探讨葛根素对血管性痴呆大鼠长时程增强（LTP）的影响。方法：采用Morris水迷宫和LTP诱导法检测血管性痴呆模型大鼠空间学习记忆能力和海马突触传递的改变。结果：模型组大鼠不同时间点测得的Morris水迷宫逃逸潜伏期均较假手术组明显延长,海马LTP诱导率明显降低,而药物组大鼠EL均短于模型组,但LTP诱导率明显增强。结论：葛根素可增强血管性痴呆大鼠突触传递功能,改善其长期存在的学习记忆障碍。