Development of a Next-Generation Nucleic Acid Force Field

下一代核酸力场的开发

• 批准号: 10736458
• 负责人: JAY PONDER
• 金额: $ 31.22万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10736458
• 关键词: Acids; Address; Algorithms; Anti-Bacterial Agents; Antibiotics; Antiviral Agents; Area; Binding; Biology; COVID-19; COVID-19 pandemic; Carbohydrates; Cell Nucleus; Cells; Charge; Chemical Structure; Chemicals; Communities; Complement; Complex; Computer Models; Computer software; Coupled; Coupling; DNA; Data; Development; Disease; Drug Design; Electrostatics; Entropy; Environment; Flavin Mononucleotide; Free Energy; Future; G-Quartets; Generations; Genomics; Growth; Ions; Life; Ligand Binding; Ligands; Machine Learning; Malignant Neoplasms; Medical; Medicine; Messenger RNA; Metal Ion Binding; Methodology; Methods; MicroRNAs; Modeling; Molecular; Molecular Conformation; Muscular Dystrophies; Mutation; Neurodegenerative Disorders; Nucleic Acid Binding; Nucleic Acids; Nucleotides; Oligonucleotides; Penetration; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Physics; Property; Proteins; Pseudouridine; Public Health; RNA; RNA vaccine; Research; Ribose; Rotation; Sampling; Site; Specificity; Structure; System; Tetrahymena; Therapeutic; Therapeutic Agents; Thermodynamics; Vertebral column; Water; Work; aptamer; base; behavior prediction; biological systems; cancer therapy; combat; computerized tools; design; enthalpy; experimental study; flexibility; group I ribozyme; hypercholesterolemia; improved; inorganic phosphate; insight; intermolecular interaction; models and simulation; molecular dynamics; molecular modeling; neural network; next generation; novel; novel therapeutics; nucleic acid structure; pandemic disease; predictive tools; quantum chemistry; simulation; simulation software; small molecule; tool; vaccine distribution

PROJECT SUMMARY/ABSTRACT Nucleic acids (NAs) are the major information carrying molecules of life. The ability to use computation to model the structure, dynamic and interactions of DNA and RNA is a key adjunct to experimental study of these biomolecules. For example, pseudouridine-containing mRNA vaccines against Covid-19 are a critical tool in battling the pandemic. DNAs, mRNAs, and miRNAs are targets for a number of antibacterial and antiviral drugs. Design of small molecule drugs binding to nucleic acids in the treatment of cancers and neurodegenerative diseases is one of the hottest topics of current pharmaceutical research. Under this project, we will investigate several key aspects of nucleic acids, and develop the polarizable multipole AMOEBA+ model for simulation of NAs and their interactions. This new force field will be further enhanced via coupling of a machine learning-based potential for local valence features with classical long-range nonbonded interactions. The resulting AMOEBA+NN force field promises chemical accuracy in the calculation of binding for NA systems. Parameters for the AMOEBA+ and AMOEBA+NN potentials will be generated using the new, automated Poltype2 package. Implementation of the force fields into the existing GPU-capable Tinker9 molecular dynamics software will enable state-of-the-art simulation and binding free energy estimation. The applicability of molecular simulation to design of therapeutics is limited by efficiency and accuracy of the calculations. The objective of this proposal is to enable routine, accurate computation of the thermodynamics of binding of small-molecule ligands to NAs. Toward that end, several current systems of biological relevance will be investigated, including binding of metal ions to G-quadruplex structures, fluorogenic ligands with RNA aptamers, novel antibiotic drugs with the FMN riboswitch, and conformational dynamics of the P5abc domain of the Tetrahymena group I ribozyme. The structures and functions of NAs are highly dependent upon their ionic environment. The interplay between RNA local structural dynamics and global/tertiary folding is an intriguing question being addressed experimentally. The ability to simulate these complex energetic effects in the design of novel small molecule drugs and synthetically modified oligonucleotides will be an important growth area for future medical advances. Development of the accurate and transferable next-generation AMOEBA+ and AMOEBA+NN force fields will open new paths toward understand and prediction of the behavior of natural and designed nucleic acid molecules.

项目摘要/摘要 核酸（NAS）是携带生命分子的主要信息。使用的能力 对DNA和RNA的结构，动态和相互作用进行建模的计算是关键辅助 这些生物分子的实验研究。例如，含伪氨酸的mRNA 针对Covid-19的疫苗是与大流行作斗争的关键工具。 DNA，mRNA和 miRNA是许多抗菌药物和抗病毒药物的靶标。小分子的设计 在癌症治疗和神经退行性疾病治疗中与核酸结合的药物是 当前药物研究的最热门话题之一。在这个项目下，我们将 研究核酸的几个关键方面，并发展出可极化的多极 变形虫+模型，用于模拟NAS及其相互作用。这个新的力场将进一步 通过耦合基于机器学习的本地价特征的潜力来增强 经典的远程非键相互作用。由此产生的变形虫+NN力场承诺 计算Na系统结合的化学精度。变形虫的参数+ 将使用新的自动化Poltype2软件包生成变形虫+NN电位。 将力场的实施到现有的具有GPU的Tinker9分子动力学中 软件将实现最新的模拟和结合自由能估计。 分子模拟对治疗剂设计的适用性受效率的限制，并且 计算的准确性。该提案的目的是启用常规，准确 小分子配体与NAS结合的热力学计算。朝那个 结束时，将研究几种当前的生物学相关性系统，包括结合 金属离子对G季链结构，带有RNA适体的荧光配体，新型抗生素 具有FMN核糖开关的药物，以及P5ABC域的构象动力学 四膜虫组I核酶。 NAS的结构和功能高度依赖 他们的离子环境。 RNA局部结构动力学与全球/第三纪之间的相互作用 折叠是一个有趣的问题，正在实验中解决。模拟这些的能力 新型小分子药物设计和合成修饰的复杂能量效应 寡核苷酸将是未来医疗进展的重要增长领域。发展 准确且可转移的下一代变形虫+和变形虫+ NN力场将 开放新的途径，可以理解和预测自然行为和设计的行为 核酸分子。