CORE C

核心C

基本信息

批准号：
10225395
负责人：
Rommie E Amaro
金额：
$ 25.83万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-09 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10225395
关键词：
3-Dimensional Antiviral Agents BRCA1 gene Binding Sites Biochemical Biological Biological Assay Biological Testing Biology Biophysics Breast CDK4 gene Chemical Models Chemicals Clinical Collaborations Complex Computer Models Computing Methodologies Crystallization Cytosine Cytosine deaminase D Cells Data Deamination Defect Development Drug Kinetics Drug resistance Effectiveness Enzymes Estrogen receptor positive Evolution Excretory function Generations Goals Graph Inherited Kinetics Length Ligands Macromolecular Complexes Malignant Neoplasms Mammary Neoplasms Metabolism Metastatic breast cancer Modeling Molecular Monoclonal Antibodies Mutagenesis Mutation Neoplasm Metastasis Nucleic Acids Outcome PIK3CA gene Physiological Primary Neoplasm Process Property Proteins Regulation Reporting Resolution Roentgen Rays Role Single-Stranded DNA Source Structural Models Structure System Techniques Testing The Cancer Genome Atlas Thermodynamics Time Uracil Vertebral column absorption base biophysical chemistry biophysical model chemical binding computational chemistry data streams design experimental study homologous recombination improved in silico in vivo inhibitor/antagonist innovation insight lead optimization malignant breast neoplasm model development molecular dynamics molecular recognition multidisciplinary nanosecond neoplastic cell novel operation prevent programs receptor resistance mutation screening simulation small molecule structural biology three dimensional structure tumor

项目摘要

CORE C – COMPUTATIONAL CHEMISTRY & BIOPHYSICS ABSTRACT APOBEC is a recently discovered enzymatic source of mutation in breast cancer. Multiple lines of evidence indicate that APOBEC mutagenesis is an ongoing source of mutation in tumor cells and that the major enzyme responsible is the single-stranded (ss)DNA cytosine deaminase APOBEC3B (A3B). Our Program is therefore united in testing the overarching hypothesis that A3B inhibition will prevent a large proportion of new mutations in estrogen receptor-positive breast cancer, thereby improving the durability of current treatments and resulting in better overall outcomes. Projects 1, 2, and 3 are focused on testing this idea through a carefully organized multidisciplinary team involving biology, chemical biology, and structural biology approaches. Core C – Computational Chemistry & Biophysics provides the computational modeling backbone to support these Projects through 2 well-integrated specific aims. Aim 1 encompasses the development of physically detailed 3D structural models of APOBEC biomolecular systems, including those that prove challenging to resolve experimentally, such as the different macromolecular regulatory complexes being explored in Project 1, or full- length, wild-type A3B in complex with ssDNA in Project 3. In these examples and others, explicitly solvated molecular dynamics (MD) simulations will be used to predict atomic-level interactions, and these dynamic 3- dimensional models will guide wet experiments by the Project teams. The resulting data will drive Core C to develop further refined models for additional testing by the Project teams. Aim 2 consists of in silico small molecule screening and lead optimization. Innovative MD analysis frameworks, such as Markov state modeling, will be used to extract long-timescale dynamics from many short-timescale simulations and elucidate the thermodynamic and kinetic landscapes of APOBEC enzymes that control molecular recognition and functional activity. A key strength of this approach is identification of cryptic pockets that are capable of binding chemical probes but are often absent from x-ray structures. A range of ligand- and receptor-based approaches will be employed in silico to increase the diversity of APOBEC inhibitors. Core C will also perform lead optimization in silico, including computational Absorption Distribution Metabolism Excretion / Pharmacokinetics (ADME/PK) optimization to help avoid potential chemical liabilities and maximize experimental efficiencies. Inhibitors and probes will be developed through continual collaboration with Projects 2 and 1 and Core D. The biochemical and biological testing of candidate molecules identified or predicted in silico will fuel additional rounds of computational refinement, ultimately leading to structural studies by Project 3 and in vivo tumor evolution experiments by Core B.

核心 C – 计算化学与生物物理学抽象的 APOBEC 是最近发现的乳腺癌细胞系突变的酶促来源。多种证据。表明 APOBEC 诱变是肿瘤细胞中持续的突变来源，并且主要酶负责的是单链 (ss)DNA 胞嘧啶脱氨酶 APOBEC3B (A3B)，因此我们的程序是。联合检验 A3B 抑制将阻止大部分新突变的总体假设在雌激素受体阳性乳腺癌中，从而提高当前治疗的持久性和由此产生的项目 1、2 和 3 的重点是通过精心组织的测试来测试这个想法。涉及生物学、化学生物学和结构生物学方法的多学科团队核心 C – 计算化学和生物物理学提供了计算建模支柱来支持这些项目通过 2 个整合良好的具体目标实现，目标 1 包含物理细节的开发。 APOBEC 生物分子系统的 3D 结构模型，包括那些难以解决的模型实验性的，例如项目 1 中正在探索的不同大分子调控复合物，或全长度，野生型 A3B 与项目 3 中的 ssDNA 复合。在这些例子和其他例子中，明确溶剂化分子动力学 (MD) 模拟将用于预测原子级相互作用，这些动态 3- 维度模型将指导项目团队进行实验，所得数据将推动 Core C 的发展。开发进一步完善的模型以供项目团队进行额外测试，目标 2 包括计算机小型模型。分子筛选和先导化合物优化。创新的MD分析框架，例如马尔可夫状态建模，将用于从许多短时间尺度模拟中提取长时间尺度动态并阐明控制分子识别和功能的 APOBEC 酶的热力学和动力学景观这种方法的一个关键优势是识别能够结合化学物质的加密口袋。探针，但 X 射线结构中通常不存在一系列基于配体和受体的方法。用于增加 APOBEC 抑制剂多样性的计算机模拟也将进行先导化合物优化。计算机模拟，包括计算吸收分布代谢排泄/药代动力学 (ADME/PK) 优化有助于避免潜在的化学责任并最大限度地提高实验效率。探针将通过与项目 2 和 1 以及 Core D 的持续合作来开发。对硅燃料中识别或预测的候选分子进行生物测试将进行额外几轮计算细化，最终导致项目 3 的结构研究和体内肿瘤进化 Core B 的实验。