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New computational tools for predicting ion effects in RNA structures

用于预测 RNA 结构中离子效应的新计算工具

基本信息

批准号：
9237041
负责人：
SHI-JIE CHEN
金额：
$ 30.21万
依托单位：
UNIVERSITY OF MISSOURI-COLUMBIA
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：
2017-02-01 至 2021-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9237041
关键词：
Address Age Algorithms Bacteria Benchmarking Binding Binding Sites Biological Biology Catalytic RNA Cell physiology Charge Clustered Regularly Interspaced Short Palindromic Repeats Collaborations Complex Computational algorithm Computer Simulation Computer software Databases Dependence Development Drug Delivery Systems Drug Design Electrostatics Environment Foundations Free Energy Future Gene Expression Regulation Genome engineering Goals Guide RNA Hepatitis C Internet Ions Joints Laboratories Lead Measurement Mediating Metal Binding Site Metal Ion Binding Metals Methods Modeling Play Positioning Attribute Property RNA RNA Folding RNA Sequences Role Sampling Solid Structure System Techniques Testing Therapeutic Training Untranslated RNA Untranslated Regions Validation Viral Genome Viral Oncogene Virus Replication aptamer base computerized tools design experience experimental study flexibility genomic RNA human disease insertion/deletion mutation novel open source parallel computer predictive modeling predictive tools structural biology success theories tool user-friendly web-accessible

项目摘要

Project Summary The current computational tools cannot keep up the pace with steadily emerging RNA sequences and new functions such as riboswitch-mediated regulation of gene expression in bacteria, RNA-guided genome engineer- ing (CRISPR), and RNA-based drug design and delivery. One of the unsolved key issues is the prediction and understanding of the role of metal ions in RNA structure formation. The problem is critically important for RNA functions because RNAs are highly charged; thus, without the participation of the metal ions in the solution, RNAs simply won't fold. Furthermore, there is increasing support for the idea that metal ions in the cellular environment can play a signiﬁcant role in the regulation of gene expression by causing RNA structure changes. The biological importance of ion effects underscores the urgent request for computational tools for accurate prediction of the ion effects. The objective of this project is to develop successful computational tools, including models, software pack- ages, and web servers to predict and understand the role of metal ions in RNA structures and functions. By including the correlation and ﬂuctuation effects for metal ions, considerable progress has been made for the ion effects in small and simple RNA structures. However, accurate prediction for the ion (especially Mg2+) effects has not been possible for large, biologically important RNAs. We now propose to develop computational tools that can provide such accurate predictions. Our goals are (a) to develop and validate a novel sampling algorithm that enables predictions of the ion effects for large RNA structures, (b) to develop and validate a new model for predicting metal ion binding sites in RNA, (c) through collaboration with RNA structural biology laboratory to develop an ion effect model for ﬂexible RNA structures, and (d) to convert the computational models into user friendly, freely accessible, open-source software package and web servers. The proposed new algorithms will be directly applied to important problems related to human diseases such as the structure and stability of Hepatitis C virus genome RNA. Furthermore, the ability to predict the metal ion effects will allow us not only to understand the formation of RNA functional structures but also to design therapeutic strategies by weakening or strengthening ion binding and consequently changing the structures and stabilities of human disease-related RNAs.

项目总结