Statistical mechanics of RNA folding
Statistical mechanics of RNA folding
批准号:
8431812
负责人:
SHI-JIE CHEN
金额:
$24.96万
依托单位国家:
美国
项目类别:
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-03-01 至 2015-07-14
关键词:
AdoptedAlgorithmsBacteriaBase PairingBenchmarkingBiological ProcessCell physiologyCollaborationsComplexDataDatabasesDevelopmentEntropyFree EnergyGene Expression RegulationGrantLeadMediatingMethodsModelingMolecular ConformationNucleotidesRNARNA FoldingRNA SequencesRNA VirusesResearch DesignSamplingSpecificityStatistical MechanicsStructureSystemTestingTherapeuticbasecrosslinkdesignmodel developmentnovelnovel strategiespredictive modelingpublic health relevanceresearch studystemstructural biologysuccesstheoriesthree dimensional structurevirtual
中文摘要
描述(申请人提供):目前的结构测定实验跟不上稳步出现的RNA序列和新功能的步伐。这强调了对RNA三级折叠的准确自由能模型的迫切要求,根据该模型,人们可以从序列中预测结构。此外,越来越多的人支持这样的观点,即大型结构RNA在履行其生物功能的过程中可能采用多种构象状态,而不是只有一种构象状态,在RNA病毒的复制和细菌中核糖开关介导的基因表达调控的中心原则中尤其如此。尽管在机理研究方面已经取得了长足的进展,但从序列中准确预测RNA三级折叠仍然是一个悬而未决的问题。理解和预测从RNA结构波动到大的构象变化的RNA折叠的第一个也是最重要的要求是一个准确的自由能模型。在这笔赠款的支持下,我们开发了一个新的基于虚拟键的RNA自由能模型,该模型能够比其他现有的简单三级结构(假结)模型更好地预测。我们现在建议通过研究全原子、更大、更复杂的RNA三级折叠来超越简单的伪结。我们的方法将建立在严格的第一原理分析计算的基础上。该方法的一个关键优点是构象采样(熵)的完备性和确定性。不正确的熵会导致糟糕的预测。使用实验数据的初步测试表明,与现有的折叠算法相比,我们的方法在准确性和特异性方面都有显著改进。这一成功证明了这笔赠款中提出的新方法的高度前景。我们的具体目标是:(A)系统地建立三级折叠自由能的模型。(B)开发一种处理复杂、较大三级褶皱的新方法。(C)开发三维全原子模型。(D)利用实验结构数据对模型进行系统测试和改进。
英文摘要
DESCRIPTION (provided by applicant): The current experiments on structural determination cannot keep up the pace with the steadily emerging RNA sequences and new functions. This underscores the urgent request for an accurate free energy model for RNA tertiary folds, from which one can predict structures from sequences. Furthermore, there is increasing support for the idea that large structured RNAs may adopt a variety of conformational states, rather than just one, during the course of performing its biological function, this is particularly so in the replication of RNA viruses and a central tenet of riboswitch-mediated regulation of gene expression in bacteria. Although considerable progress has been made in mechanistic studies, accurate prediction for RNA tertiary folding from sequence remains an unsolved problem. The first and most important requirement for understanding and predicting of RNA folding from RNA structural fluctuations to large conformational changes is an accurate free energy model. Support from this grant has allowed us to develop a novel virtual bond-based RNA free energy model that enables much better predictions than other existing models for simple tertiary structures (pseudoknots). We now propose to go beyond the simple pseudoknots by studying all-atom, larger, more complex RNA tertiary folds. Our approach will be based on rigorous, first principles analytical calculations. A key advantage of the approach is the completeness and certainty in conformational sampling (entropy). Incorrect entropy results in poor predictions. Preliminary tests using experimental data have shown significant improvements from our approach in both accuracy and specificity than existing folding algorithms. The success attests the high promise of the new approach proposed in this grant. Our specific aims are: (a) Systematic model development for tertiary folding free energies. (b) Developing a novel approach for complex, larger tertiary folds. (c) Developing a 3D all-atom model. (d) Systematic test and refinement of the model using experimental structural data.
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