Computational analysis of proteins

蛋白质的计算分析

• 批准号: 9923028
• 负责人: Nick V. Grishin
• 金额: $ 31.41万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-05-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9923028
• 关键词: Animal Model; Atlases; Biological Phenomena; Biology; Butterflies; Catalogs; Classification; Collaborations; Communities; Computer Analysis; Computer software; Computing Methodologies; Databases; Disease; Distant; Evolution; Experimental Designs; Genetic Diseases; Genome; Genotype; Health; Human; Light; Link; Methods; Molecular; Mutation; Organism; Phenotype; Population Biology; Positioning Attribute; Protein Analysis; Protein Family; Proteins; Research; Sequence Alignment; Series; Services; Structure; Technology; Tertiary Protein Structure; Testing; Update; Work; base; biophysical techniques; experience; genome sequencing; innovation; method development; programs; sound

We develop computational methods for the analysis of proteins and use them to study evolution and predict protein spatial structures and functions. Our major recent advances are: 1) Statistically sound similarity search approaches based on matching of two sequence alignments augmented with known relationships between proteins in a database (COMPADRE); 2) Multiple sequence alignment program that is accurate for very distant sequences (PROMALS3D); 3) Comprehensive evolutionary classification of protein domains with known spatial structures (ECOD), a database that is updated weekly and catalogues most distant evolutionary connections between proteins; 4) Highly heterozygous genome sequencing, assembly and annotation pipeline that resulted in several dozen butterfly genomes sequenced by our group; 5) service to scientific community by being assessors in several structure prediction (CASP) and genome interpretation (CAGI) challenges. During the next 5 years, we would like to capitalize on our progress in the analysis of proteins and organisms and explore new research directions offered by developing technologies. Our work will be structured along the five major interconnected threads. 1) We will continue developing comprehensive evolutionary classification of proteins. We have the strongest track record and most extensive experience in this direction and are uniquely positioned to make a lasting impact. 2) We will develop computational methods to find distant protein homologs and multiply align them. This work will build upon our software we have been working on for almost two decades. These new methods will be used for protein classification, and expert analysis of protein families will offer fresh ideas for further methods development. 3) We will build the atlas of human mutations and rationalize their effects on proteins and human health. This project will rely upon our expertise in structure prediction, alignment and evolutionary connections between proteins, and will derive power from our dozens of collaborators, many of whom are clinicians who are dealing with interpretation of mutation effects. 4) At the organismal level, we will tackle the link between genotype and phenotype and a series of evolutionary and population biology questions using butterflies as model organisms. Many of these features are linked to proteins and their spatial structures. Integration of molecular biophysics techniques with organismal and evolutionary biology is innovative is promising to advance both fields. 5) We will continue collaborations with experimentalists to test our method and help them with experimental design. All five threads are tied by their connection to computational analysis of proteins, which is the main strength of our group.

我们开发用于分析蛋白质的计算方法，并使用它们来研究 进化和预测蛋白质的空间结构和功能。我们最近的重大进步 是：1）基于两个匹配的统计上听起来相似性搜索方法 序列比对在A中的蛋白质之间的已知关系增强 数据库（compadre）; 2）准确的多个序列对齐程序 非常遥远的序列（Promals3d）； 3）全面的进化分类 具有已知空间结构（ECOD）的蛋白质域，该数据库已更新 每周和目录蛋白质之间最遥远的进化连接； 4） 高度杂合基因组测序，组装和注释管道 导致我们组对数十个蝴蝶基因组进行了测序。 5）服务 科学界是在几个结构预测（CASP）和 基因组解释（CAGI）挑战。在接下来的5年中，我们想 利用我们在分析蛋白质和生物的进步并探索新的 开发技术提供的研究指示。我们的工作将是结构化的 沿五个主要的互连线。 1）我们将继续发展 蛋白质的全面进化分类。我们的轨道最强 在这个方向上记录和最丰富的经验，并具有独特的位置 产生持久的影响。 2）我们将开发计算方法以找到遥远的蛋白质 同源物并乘以对齐。这项工作将基于我们一直以来的软件 工作了将近二十年。这些新方法将用于蛋白质 分类和蛋白质家族的专家分析将提供新的想法以进一步 方法开发。 3）我们将建立人类突变的地图集并合理化其 对蛋白质和人类健康的影响。该项目将依靠我们的专业知识 蛋白质之间的结构预测，对齐和进化连接 从我们的数十名合作者那里获得权力，其中许多是临床医生 处理突变效应的解释。 4）在生物层，我们将解决 基因型与表型与一系列进化和种群之间的联系 生物学问题使用蝴蝶作为模型生物。这些功能中有许多是 与蛋白质及其空间结构有关。分子生物物理学的整合 具有生物和进化生物学的技术是有希望的 推进两个字段。 5）我们将继续与实验者合作，以测试我们的 方法并帮助他们进行实验设计。所有五个线程都被他们的 与蛋白质计算分析的联系，这是我们的主要优势 团体。