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.

项目概要/摘要 核酸（NA）是生命中携带信息的主要分子。使用能力 DNA 和 RNA 的结构、动态和相互作用建模的计算是一个关键的辅助手段 对这些生物分子进行实验研究。例如，含有假尿苷的mRNA Covid-19 疫苗是抗击这一流行病的重要工具。 DNA、mRNA 和 miRNA 是许多抗菌和抗病毒药物的靶标。小分子设计 与核酸结合的药物可用于治疗癌症和神经退行性疾病 当前药物研究最热门的话题之一。在这个项目下，我们将 研究核酸的几个关键方面，并开发可极化多极子 用于模拟 NA 及其相互作用的 AMOEBA+ 模型。这个新的力场将进一步 通过将基于机器学习的局部价特征潜力与 经典的长程非键相互作用。由此产生的 AMOEBA+NN 力场有望 NA 系统结合计算的化学准确性。 AMOEBA+ 的参数 AMOEBA+NN 势将使用新的自动化 Poltype2 软件包生成。 将力场应用到现有的支持 GPU 的 Tinker9 分子动力学中 软件将实现最先进的模拟和结合自由能估计。 分子模拟在治疗设计中的适用性受到效率和 计算的准确性。该提案的目标是实现常规、准确 计算小分子配体与 NA 结合的热力学。朝那个方向 最后，将研究几个当前的生物相关系统，包括结合 G-四链体结构的金属离子、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 结构域的构象动力学 四膜虫 I 组核酶。 NA的结构和功能高度依赖于 他们的离子环境。 RNA局部结构动力学与全局/三级结构之间的相互作用 折叠是一个正在通过实验解决的有趣问题。模拟这些的能力 新型小分子药物设计和合成修饰中的复杂能量效应 寡核苷酸将是未来医学进步的重要增长领域。发展 准确且可转移的下一代 AMOEBA+ 和 AMOEBA+NN 力场将 为理解和预测自然和设计行为开辟新途径 核酸分子。