Conformational Dynamics of Src-Kinases and Inhibition

Src 激酶的构象动力学和抑制

基本信息

批准号：
10215401
负责人：
BENOIT ROUX
金额：
$ 35.57万
依托单位：
UNIVERSITY OF CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2002
资助国家：
美国
起止时间：
2002-04-01 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10215401
关键词：
Accounting Active Sites Address Adopted Affect Affinity BMX gene Benchmarking Binding Biological Models Communities Complex Computing Methodologies Dasatinib Data Development Devices Disease Dissociation Drug Design Drug Industry Drug Kinetics Equilibrium Family Free Energy Hot Spot Imatinib Individual JAK2 gene KDR gene Kinetics Knowledge Ligand Binding Ligands Literature Lysine Maps Mechanics Methods Modality Modeling Molecular Molecular Conformation Pathway interactions Pharmaceutical Preparations Phase Phosphotransferases Play Process Protein Conformation Protein Family Protein Kinase Protein Tyrosine Kinase Proteins Proto-Oncogene Protein c-kit Publishing Research Roentgen Rays Role Sampling Site Solvents Specificity Structural Protein Structure Techniques Technology Testing Thermodynamics Time Validation Variant Work analog base cancer therapy computer framework design drug discovery flexibility genome-wide in vivo inhibitor/antagonist interest lead optimization member molecular dynamics novel protein structure protein-tyrosine kinase c-src quantum receptor residence scaffold side effect simulation src-Family Kinases success targeted treatment therapeutic target tool user-friendly web site

项目摘要

Project Summary The discovery of kinase-specific inhibitors is intensely pursued within the pharmaceutical industry. In spite of multitude of X-ray structures for this protein family, it is increasingly apparent that a number of critical challenges must be overcome to make structure-based drug design (SBDD) a completely reliable tool for the discovery process, especially in the later phases of a drug discovery (lead optimization) that deal with balancing of potency with selectivity, in vivo target engagement, and pharmacokinetic profile. Even when multiple X-ray structures for a selected target are available, our knowledge of all the relevant conformations relevant for ligand binding remains limited, thus hindering the full potential of SBDD. Lack in inhibitor selectivity often leads to undesired side effects caused by off-target binding. But while thermodynamic binding equilibrium considerations are critical, it is also important to go beyond to explain and predict the association/dissociation kinetic rates and the residence time of inhibitors. The latter can strongly affect many aspects of in vivo pharmacokinetics. All these issues become especially important when trying to rationally design and optimize specific covalent inhibitors whose mode of action is sensitive to both thermodynamic and kinetic factors. There is an urgent need to begin to systematically overcome these challenges for technologies like SBDD to play an increasing role in the development of targeted therapies based on kinase-specific inhibitors. A research plan comprising of four specific aims is proposed to develop a comprehensive computational/theoretical framework in order to systematically overcome and address these challenges. Our computational framework will integrate the information from explicit-solvent molecular dynamics simulations, adaptive enhanced sampling strategies, transition pathways from the string method, de novo structure prediction, and Markov state models. Specifically, we will develop, test and validate an integrated computational approach to accurately predict and rank-order all the accessible conformational variants of a target protein; then expand this approach to de-novo predict and rank-order all the accessible binding poses of a ligand in a given kinase of interest. We will also develop, test and validate an integrated computational approach to quantitatively determine and predict the associate/dissociation rates kon and koff of ligand binding, then expand this approach to simulate the formation of covalent linkage (reversible and irreversible) between a ligand and a target kinase, accounting for binding mode and reactivity. Finally, the computational framework will be used to investigate the molecular determinants for the specificity of a novel family of pan-kinase probes and test whether they are compatible with genome-wide profiling. The entire computational framework will be automated and streamlined user- friendly tools will be freely distributed to the general community through our web site. All results of this work will be made publically accessible to the whole community through our web site.

项目摘要在制药行业中，强烈追求了激酶特异性抑制剂的发现。尽管该蛋白质家族的多种X射线结构，越来越明显的是许多关键必须克服挑战以使基于结构的药物设计（SBDD）成为完全可靠的工具发现过程，尤其是在处理药物发现（铅优化）的后期阶段在选择性，体内目标参与和药代动力学概况之间平衡效能。即使什么时候可用于选定目标的多个X射线结构，我们对所有相关构象的了解与配体结合相关的含量仍然有限，从而阻碍了SBDD的全部潜力。缺乏抑制剂选择性通常会导致脱靶结合引起的不希望的副作用。但是，热力学结合平衡考虑因素至关重要，也要超越解释和预测关联/分离也很重要动力学率和抑制剂的停留时间。后者可以强烈影响体内的许多方面药代动力学。当试图合理设计和优化时，所有这些问题变得尤为重要特定的共价抑制剂，其作用方式对热力学和动力学因素均敏感。那里迫切需要系统地克服SBDD等技术的这些挑战基于激酶特异性抑制剂的靶向疗法的发展中的作用增加。研究计划提出了由四个特定目标组成的，以开发一个全面的计算/理论框架为了系统地克服并应对这些挑战。我们的计算框架将集成来自显式溶剂分子动力学模拟的信息，自适应增强的采样策略，从字符串方法，从头结构预测和马尔可夫状态模型的过渡途径。具体而言，我们将开发，测试和验证一种综合计算方法，以准确预测和靶蛋白的所有可访问构象变体的排序顺序；然后将这种方法扩展到De-Novo 预测和排序排序在给定的激酶中配体的所有可访问结合姿势。我们也会开发，测试和验证一种综合计算方法，以定量确定和预测辅助/解离率KON和配体结合的Koff，然后扩展这种方法以模拟形成配体和靶激酶之间的共价连接（可逆和不可逆）模式和反应性。最后，计算框架将用于研究分子新型泛组探针家族的特异性的决定因素，并测试它们是否兼容与全基因组分析。整个计算框架将是自动化和简化的用户友好工具将通过我们的网站自由分发给普通社区。这项工作的所有结果将通过我们的网站公开向整个社区公开访问。

项目成果

期刊论文数量（43）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

1H, 15N, and 13C resonance assignments of the intrinsically disordered SH4 and Unique domains of Hck.

本质上无序的 SH4 和 Hck 的独特结构域的 1H、15N 和 13C 共振分配。

DOI：
10.1007/s12104-018-9854-z
发表时间：
2019
期刊：
Biomolecular NMR assignments
影响因子：
0.9
作者：
Pond,MatthewP;Blachowicz,Lydia;Roux,Benoît
通讯作者：
Roux,Benoît

Locking the active conformation of c-Src kinase through the phosphorylation of the activation loop.

DOI：
10.1016/j.jmb.2013.10.001
发表时间：
2014-01-23
期刊：
Journal of molecular biology
影响因子：
5.6
作者：
Meng Y;Roux B
通讯作者：
Roux B

Identification of Druggable Kinase Target Conformations Using Markov Model Metastable States Analysis of apo-Abl.

使用马尔可夫模型亚稳态分析 apo-Abl 鉴定可药物激酶靶构象。

DOI：
10.1021/acs.jctc.9b01158
发表时间：
2020
期刊：
Journal of chemical theory and computation
影响因子：
5.5
作者：
Paul,Fabian;Meng,Yilin;Roux,Benoît
通讯作者：
Roux,Benoît

Perspective on computational and structural aspects of kinase discovery from IPK2014.

IPK2014 对激酶发现的计算和结构方面的看法。

DOI：
10.1016/j.bbapap.2015.03.014
发表时间：
2015
期刊：
Biochimica et biophysica acta
影响因子：
0
作者：
Martin,Eric;Knapp,Stefan;Engh,RichardA;Moebitz,Henrik;Varin,Thibault;Roux,Benoit;Meiler,Jens;Berdini,Valerio;Baumann,Alexander;Vieth,Michal
通讯作者：
Vieth,Michal

Src kinase conformational activation: thermodynamics, pathways, and mechanisms.