CORE C

核心C

基本信息

批准号：
10474993
负责人：
Rommie E Amaro
金额：
$ 28.32万
依托单位：
UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
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 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10474993
关键词：
3-Dimensional 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 data-driven model design experimental study homologous recombination improved in silico in vivo inhibitor 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 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突变酶源。多行证据表明APOBEC诱变是肿瘤细胞中突变的持续来源，并且主要酶是负责是单链（SS）DNA胞嘧啶脱氨酶Apobec3b（A3b）。因此，我们的计划是统一测试了总体假设，即A3b抑制作用将防止大部分新突变在雌激素受体阳性乳腺癌中，从而提高了当前疗法的耐用性并导致在更好的总体结果中。项目1、2和3的重点是通过精心井井有条涉及生物学，化学生物学和结构生物学方法的多学科团队。核心C - 计算化学与生物物理学提供了计算建模主链来支持这些主干通过2个整合的特定目标进行项目。 AIM 1涵盖了物理详细的发展 APOBEC生物分子系统的3D结构模型，包括那些证明挑战的结构模型实验中，例如在项目1中探索的不同的大分子调节络合物，或长度，野生型A3B与项目3中的ssDNA复合在一起。分子动力学（MD）模拟将用于预测原子水平的相互作用，这些动态3- 尺寸模型将指导项目团队的湿实验。由此产生的数据将驱动核心C到开发进一步的精制模型，以由项目团队进行其他测试。 AIM 2由Silico Small组成分子筛选和铅优化。创新的MD分析框架，例如马尔可夫州建模，将用于从许多短时间模拟中提取长时间的动态，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活动。这种方法的关键优势是识别能够结合化学的加密口袋问题，但通常不存在X射线结构。一系列基于配体和接收器的方法将是在硅中使用，以增加APOBEC抑制剂的多样性。 Core C还将在硅，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负债并最大化实验效率。抑制剂和问题将通过与项目2和1和核心D的持续合作开发。鉴定或预测的候选分子的生物学测试将促进其他回合计算改进，最终通过项目3和体内肿瘤演化进行结构研究核心B的实验。