Public/Private Collaboration for High-Quality Protein-Ligand Data

高质量蛋白质配体数据的公共/私人合作

• 批准号: 7942255
• 负责人: HEATHER A CARLSON
• 金额: $ 45.84万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7942255
• 关键词: Academia; Address; Affinity; Algorithms; Area; BIRC4 gene; Binding; Calorimetry; Chemicals; Collaborations; Communities; Community Developments; Community Outreach; Community Participation; Complex; Computer software; Crystallography; Data; Data Collection; Data Set; Databases; Deposition; Development; Dissociation; Docking; Drug Design; Drug Industry; Equipment; Financial Support; Imagery; Inhibitory Concentration 50; Investigation; Ligands; Literature; MDM2 gene; Michigan; Modeling; Mothers; NCI Scholars Program; Online Systems; Pharmaceutical Preparations; Population; Principal Investigator; Production; Property; Protein Databases; Protein Structure Initiative; Proteins; Research; Research Personnel; Resource Sharing; Resources; Scientist; Solubility; Source Code; Structure; Surface Plasmon Resonance; System; Techniques; Time; United States National Institutes of Health; Visit; assay development; base; cost; data mining; data sharing; design; improved; meetings; open source; programs; repository; text searching

DESCRIPTION (provided by applicant): One critical need for the development of reliable docking and scoring (d/s) is a large dataset containing high quality experimental protein-ligand complex structures, together with accurate binding affinity data. An online d/s resource (d/sResource) will be created by taking advantage of the PIs extensive expertise in this area and through community participation. SA1 will build the largest, freely accessible database of protein-ligand complexes with experimentally determined binding affinities from literature. This new resource will build off of the two largest protein-ligand datasets in existence: Wang's PDBbind and Carlson's Binding MOAD. SA2 will generate new experimental data. The lack of consistency between binding affinity data generated from different research groups and using different experimental techniques/conditions is another major hurdle. To address this deficiency, dissociation constants (Kds) for selected protein-ligand complexes will be determined using two complementary techniques: isothermal calorimetry and surface plasmon resonance. Furthermore, important physicochemical properties for the ligands will be determined (logP/logD, pKa, and solubility), and additional crystal structures will be solved. SA3 will curate data from the community. Deposition of large datasets will be requested from pharma, the NIH, and academia. This Aim includes solving partially completed crystal structures deposited into the d/sResource and analysis of deposited data for diversity/similarity across the ligands and proteins to prioritize for further experimental investigation in SA2. SA4 outlines the proposed community outreach. The d/sResource will not be a Michigan-only endeavor. Data will be deposited in many repositories: structures into the PDB, ITC data into BindingDB, and chemical information into Pubchem and NIST databases. Collaborations will be sought with other groups. Contests and meetings for d/s will be held, and a Visiting Scholars Program will be established to encourage new developments and facilitate the sharing of resources. The project will provide a unique resource that is needed to improve in the field of structure-based drug design. Better techniques will save time and money in the development of new treatments, ultimately providing new drugs more quickly and at less expense to the greater population.

描述（由申请人提供）：开发可靠的对接和评分（d/s）的一个关键需求是包含高质量实验蛋白质-配体复合物结构以及准确的结合亲和力数据的大型数据集。将利用 PI 在该领域的广泛专业知识并通过社区参与来创建在线 d/s 资源 (d/sResource)。 SA1 将建立最大的、可免费访问的蛋白质-配体复合物数据库，并通过文献实验确定结合亲和力。这个新资源将建立在现有的两个最大的蛋白质配体数据集的基础上：Wang 的 PDBbind 和 Carlson 的 Binding MOAD。 SA2将生成新的实验数据。另一个主要障碍是不同研究小组使用不同实验技术/条件生成的结合亲和力数据之间缺乏一致性。为了解决这一缺陷，将使用两种互补技术来确定所选蛋白质-配体复合物的解离常数（Kds）：等温量热法和表面等离子共振。此外，还将确定配体的重要物理化学性质（logP/logD、pKa 和溶解度），并解决其他晶体结构。 SA3 将整理来自社区的数据。制药公司、美国国立卫生研究院和学术界将要求保存大型数据集。该目标包括解决沉积到 d/sResource 中的部分完成的晶体结构，以及分析沉积数据的配体和蛋白质的多样性/相似性，以便优先考虑 SA2 中的进一步实验研究。 SA4 概述了拟议的社区外展活动。 d/sResource 将不仅仅是密歇根州的一项工作。数据将存储在许多存储库中：结构存储在 PDB 中，ITC 数据存储在 BindingDB 中，化学信息存储在 Pubchem 和 NIST 数据库中。将寻求与其他团体的合作。将举办d/s竞赛和会议，并设立访问学者计划，以鼓励新的发展并促进资源共享。 该项目将提供改进基于结构的药物设计领域所需的独特资源。更好的技术将节省开发新疗法的时间和金钱，最终更快、以更少的费用向更多人群提供新药。