Development of an Experimental-Computational Integrated Technology to Address the Residence Time of GPCR Ligands

开发解决 GPCR 配体停留时间问题的实验计算集成技术

• 批准号: BB/P004245/1
• 负责人: Andrea Townsend-Nicholson
• 金额: $ 19.35万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FP004245%2F1
• 关键词: Development; Experimental; Computational; Integrated; Technology

G protein-coupled receptors (GPCRs) are cell surface receptors that constitute the largest superfamily of membrane proteins, translating chemical messages from outside the cell into responses inside the cell, regulating almost every aspect of cellular activity. GPCRs have enormous physiological and biomedical importance, being the primary site of action of 60% of modern drugs. There are over 800 human GPCRs known today, involved in a diversity of diseases including cancer, pain, inflammation, depression and anxiety. Despite this, drugs have been developed for just 50 of these GPCRs. This renders GPCRs one of the most important classes of current pharmacological targets. Despite a huge effort by the pharmaceutical industry to design novel drugs for GPCR targets, there is tremendous attrition along R&D pipelines. Many promising drug candidates eventually fail in clinical trials due to a demonstrated lack of efficacy. A retrospective analysis of those that have successfully made it to the market has revealed that their beneficial effects in patients may be attributed to their long drug-target residence times (RTs) - the length of time for which a drug (ligand) stays bound to its receptor target. There is substantial evidence that ~70% of long RT therapeutics displayed higher efficacy than comparable faster-dissociating drugs, supporting a growing recognition that drug-target RT may be of even greater importance than affinity, therapeutically. Recentl publications have emphasized the pivotal role of RT optimisation in the early phases of drug discovery, suggesting that detailed structure-based studies of RT should be introduced in the early phases of drug discovery to prevent "fail late, fail expensive" scenarios. However, it should be emphasized that the criteria for "long" or "short" RT may vary for different targets and for different clinical indications. For therapies requiring prolonged target occupancy, a long RT drug offers advantages, as it remains bound to the target and continuously exerts its pharmacological effect even when most of the free drug has already been eliminated from blood circulation. On the other hand, there are cases where a mechanism-based toxicity can outweigh the therapeutic advantages of long receptor occupancy and a rapidly-dissociating short RT compound would be preferred. A sizeable gap exists between current academic research directed at understanding the kinetics and molecular details of the drug binding process and the needs of the pharmaceutical industry. This gap must be bridged in order to successfully apply academic knowledge to the drug discovery process. The general requirements of the pharmaceutical industry from any drug discovery approach are: (1) the method should be universally applicable to drug discovery projects; (2) the method should be effective and cost-efficient; and, (3) it should satisfy the immediate need for such information to be provided in "real-time". Currently, no technology for RT can satisfy all of these requirements. Efforts to include RT in the drug development process have focused on the adoption of either experimental or computational approaches. Each is very promising but provides only half the picture. Experimental methods can measure the RT but can't rationalize why certain compounds have longer RT than the others or suggest ways to modify a ligand's structure to improve its RT profile. On the other hand, computational methods are only able to provide this essential information if robust experimental data are available.This FLIP proposal aims, through collaboration between academia and industry, to combine experimental and computational methods in an integrated methodology that will provide a powerful tool to optimise the RTs of ligands in the early stage of drug development in a way that meets the needs of the pharmaceutical industry and brings benefit to people suffering from disorders caused or influenced by defects in GPCRs.

G蛋白偶联受体（GPCR）是细胞表面受体，构成最大的膜蛋白超家族，将细胞外的化学信息翻译成细胞内的反应，调节细胞活动的几乎每个方面。GPCR具有巨大的生理和生物医学重要性，是60%现代药物的主要作用部位。目前已知有超过800种人类GPCR，涉及多种疾病，包括癌症，疼痛，炎症，抑郁和焦虑。尽管如此，仅为其中50种GPCR开发了药物。这使得GPCR成为当前最重要的药理学靶点之一。尽管制药业做出了巨大的努力来设计针对GPCR靶点的新药，但在研发管道上沿着巨大的磨损。许多有前途的候选药物最终由于缺乏疗效而在临床试验中失败。对那些成功进入市场的药物的回顾性分析表明，它们对患者的有益作用可能归因于它们的长药物靶向停留时间（RT）-药物（配体）与其受体靶点结合的时间长度。有大量证据表明，约70%的长RT治疗剂显示出比可比的更快解离药物更高的疗效，支持越来越多的认识，即药物靶向RT在治疗上可能比亲和力更重要。最近的出版物强调了RT优化在药物发现早期阶段的关键作用，这表明在药物发现的早期阶段应该引入详细的基于结构的RT研究，以防止“失败晚，失败昂贵”的情况。然而，应该强调的是，对于不同的靶点和不同的临床适应症，“长”或“短”RT的标准可能会有所不同。对于需要延长靶点占有率的治疗，长RT药物具有优势，因为即使大部分游离药物已经从血液循环中消除，它仍与靶点结合并持续发挥其药理学作用。另一方面，在某些情况下，基于机制的毒性可能超过长受体占用的治疗优势，并且快速解离的短RT化合物将是优选的。目前的学术研究旨在了解药物结合过程的动力学和分子细节，与制药工业的需求之间存在着相当大的差距。必须弥合这一差距，以便成功地将学术知识应用于药物发现过程。制药行业对任何药物发现方法的一般要求是：（1）该方法应普遍适用于药物发现项目;（2）该方法应有效且具有成本效益;以及（3）它应满足“实时”提供此类信息的迫切需要。目前，没有一种RT技术可以满足所有这些要求。将RT纳入药物开发过程的努力集中在采用实验或计算方法上。每一个都很有希望，但只提供了一半的情况。实验方法可以测量RT，但不能合理解释为什么某些化合物比其他化合物具有更长的RT，或者提出修改配体结构以改善其RT曲线的方法。另一方面，计算方法只有在可靠的实验数据可用的情况下才能提供这些基本信息。将联合收割机的实验和计算方法结合在一个综合的方法中，这将提供一个强大的工具，以满足制药工业的需求的方式，在药物开发的早期阶段优化配体的RT并为患有由GPCR缺陷引起或影响的疾病的人带来益处。

项目成果

Rapid and accurate assessment of GPCR-ligand interactions Using the fragment molecular orbital-based density-functional tight-binding method.

• DOI: 10.1002/jcc.24850
• 发表时间: 2017-09-05
• 期刊: Journal of computational chemistry
• 影响因子: 3
• 作者: Morao I;Fedorov DG;Robinson R;Southey M;Townsend-Nicholson A;Bodkin MJ;Heifetz A
• 通讯作者: Heifetz A

Computational prediction of GPCR oligomerization.

• DOI: 10.1016/j.sbi.2019.04.005
• 发表时间: 2019-04
• 期刊: Current opinion in structural biology
• 影响因子: 6.8
• 作者: A. Townsend-Nicholson;N. Altwaijry;Andrew Potterton;Iñaki Morao;Alexander Heifetz

Ensemble-Based Steered Molecular Dynamics Predicts Relative Residence Time of A2A Receptor Binders.

• DOI: 10.1021/acs.jctc.8b01270
• 发表时间: 2019-03
• 期刊: Journal of chemical theory and computation
• 影响因子: 5.5
• 作者: Andrew Potterton;Fouad S. Husseini;M. Southey;M. Bodkin;Alexander Heifetz;P. Coveney;A. Townsend-Nicholson

Synergistic Use of GPCR Modeling and SDM Experiments to Understand Ligand Binding.

协同使用 GPCR 建模和 SDM 实验来了解配体结合。

• DOI: 10.1007/978-1-4939-7465-8_15
• 发表时间: 2018
• 期刊: Methods in molecular biology (Clifton, N.J.)
• 作者: Potterton A