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Bridging Disparate Structural/Functional Scales: Multiscale Modeling of the Chromatin Fiber and RNA Tertiary Structures

桥接不同的结构/功能尺度：染色质纤维和 RNA 三级结构的多尺度建模

基本信息

批准号：
10220065
负责人：
Tamar Schlick
金额：
$ 46.95万
依托单位：
NEW YORK UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10220065
关键词：
Affect Area Atlases Biological Biology Biophysics Cell Differentiation process Cells Cellular Structures Chemistry Chromatin Chromatin Fiber Chromatin Loop Chromatin Structure Chromosome Structures Collaborations Communities Complex Computational Biology Computing Methodologies Degenerative Disorder Development Diagnosis Engineering Environment Epigenetic Process Gene Expression Gene Silencing Genes Genetic Genetic Diseases Genetic Materials Genome Grain Graph Higher Order Chromatin Structure Link Malignant Neoplasms Maps Mathematics Medicine Methods Modeling Molecular Molecular Computations Nanotechnology National Institute of General Medical Sciences Nucleic Acids Nucleosomes Polymers Process Property Protein Binding Domain Proteins RNA RNA Folding RNA-Binding Proteins Repression Sampling Structure Structure-Activity Relationship Syndrome Technology Transcriptional Activation Work cancer cell cancer genetics cancer therapy computer science data mining design experimental study genome-wide graph theory human disease improved innovation macromolecule molecular modeling multi-scale modeling novel programs sensor targeted treatment

项目摘要

Abstract Advances in both experimental and computational biology are helping make exciting discoveries in many fields of biology and biomedicine today. Together, physical experiments and modeling are solving fundamental puzzles in biology as well as applying the findings to medicine and technology through molecular design, targeted therapies, and nanotechnology. The PI's computational biology /biophysics lab focuses on solving fundamental structural and dynamical questions concerning nucleic acids and their complexes (notably chromatin and RNA) in collaboration with experimentalists by innovative molecular models and computational methods using ideas from mathematics, computer science, and engineering, as well as biology and chemistry. This MIRA project would consolidate three NIGMS projects on chromatin structure, RNA design, and RNA structure prediction to advance our fundamental understanding of structure/function relationships for chromatin and RNA using multiscale models that bridge disparate scales to allow unprecedented applications regarding chromatin and RNA folding. For chromatin, the detailed atomic information on nucleosomes and long-range contact maps available from genome-wide experiments will be bridged by a hierarchy of tunable coarse-grained models to link atomic, mesoscale, and polymer models to investigate the epigenetic modulation of chromatin higher-order structure by gene looping mechanisms in cancer cells; these structural mechanisms for repression/ activation of transcription have translational ramifications through targeted re-expression of those silenced genes by chromatin loop dissolution for cancer therapy. For RNA, the general problem of poor predictions of RNA and RNA/protein tertiary motifs will be tackled by exploiting the drastic variable reduction and natural modularity of 2D graphs to combine efficient coarse-grained graph sampling, graph theory substructuring, and data-mining with improved handling of pseudoknots, kink-turns, and RNA-protein-binding motifs in our program RAGTOP. We will contribute to community efforts like RNA-puzzles; design novel RNAs for predicted, but yet undiscovered, RNA-like fold motifs to produce a atlas of modules for design; and design riboswitches with desired fluorescent properties, as sensors. These works, with support from leading experts in chromatin and RNA structure and function, will help advance fundamental areas of biology /biomedicine including genome biophysics, chromatin higher-order structure, gene expression, and cell development and differentiation and hence the targeted treatment of human diseases associated with aberrant gene expression, including cancers, genetic disorders, and degenerative diseases. The resulting multiscale computing paradigms are widely applicable to other biomolecular processes and will be shared with the community at large.

摘要