Computational mapping of proteins for the binding of ligands

配体结合的蛋白质计算图谱

基本信息

批准号：
8888024
负责人：
SANDOR VAJDA
金额：
$ 37.28万
依托单位：
BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
依托单位国家：
美国
项目类别：
财政年份：
2003
资助国家：
美国
起止时间：
2003-02-01 至 2017-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8888024
关键词：
Accounting Affinity Algorithms Allosteric Site Binding Binding Proteins Binding Sites Biological Complex Computing Methodologies Consensus Data Development Drug Targeting Free Energy Goals Grant Homology Modeling Hot Spot Image Compression Interleukin-2 Laboratories Letters Libraries Ligands Maps Membrane Proteins Methods Modeling Molecular Conformation Molecular Probes Monitor Monte Carlo Method Phosphotransferases Positioning Attribute Process Property Protein Family Protein Region Proteins Relative (related person)Request for Proposals Rest Role Sampling Side Site Specificity Speed Surface Techniques Testing Time Virtual Library Water Work base conformer cost design flexibility functional group improved interest molecular dynamics novel strategies protein protein interaction public health relevance research study screening simulation small molecule virtual

项目摘要

DESCRIPTION (provided by applicant): The proposal requests the renewal of the grant "Computational Mapping of Proteins for the Binding of Ligands". Mapping globally samples the surface of target proteins using fragment sized molecular probes. The general goals of mapping are determining binding hot spots, i.e., regions of proteins that are major contributors to the binding free energy, and identifying fragments with preferential binding to these hot spots. The main advantage of studying hot spots is that they are more conserved than binding sites are. We pursue four aims. First, we improve the efficiency of flexible mapping by performing side chain search directly within the global mapping algorithm, and extend the algorithm to models with flexible loops and to homology models. The method will be used for large scale mapping calculations to answer interesting biological questions such as the existence of druggable cryptic sites in the kinome. Second, we develop an effective combination of computational and experimental methods for the identification of fragments binding to a given hot spot, and working with collaborators attempt to find fragment hits for a number of drug targets, in the process generating fragment binding data needed for improving computational methods. Third, we develop an algorithm for virtual fragment screening in order to reduce the number of fragments that need to be experimentally tested. The resulting methods will provide direct input for fragment based ligand discovery (FBLD), thereby reducing the high costs of the approach and making it more accessible to academic laboratories. Fourth, we will further improve the accuracy of mapping by explicit modeling of solvation. The method is based on decomposing the protein into flexible side chains with multiple conformers, the rest of the protein, two copies of a probe in a number of conformations, and two water molecules. We sample the interaction energies for all feasible relative orientations of all pairs using very efficient fast Fourier tranform correlation methods, and store the detailed energy grids in lookup tables, compressed using wavelet transforms. Due to the additivity of pairwise interaction energies, the energy of any conformation can be quickly evaluated by adding pre-calculated internal energy components to interaction energies, all extracted from lookup tables. The use of energy tables will speed up the calculation of partition functions, refinement of fragment positions using Monte Carlo simulations, and determining escape times by stochastic roadmap simulation. All new algorithms will be implemented in our FTMap server (http://ftmap.bu.edu), which already has over 1200 registered users.

描述（由申请人提供）：该提案请求更新拨款“配体结合的蛋白质计算图谱”，使用片段大小的分子探针对目标蛋白质的表面进行全局采样。图谱的总体目标是确定结合热。研究热点的主要优点是它们比结合位点更保守。我们追求四个目标：首先，我们通过直接在全局映射算法中执行侧链搜索来提高灵活映射的效率，并将该算法扩展到具有灵活循环的模型和同源模型。绘制计算来回答有趣的生物学问题，例如激酶组中是否存在可药物化的神秘位点其次，我们开发了计算和实验方法的有效组合来识别与给定热点结合的片段，并与合作者一起尝试寻找。多种药物的片段命中第三，我们开发了一种虚拟片段筛选算法，以减少需要实验测试的片段数量，所得方法将为基于片段的方法提供直接输入。第四，我们将通过溶剂化的显式建模进一步提高作图的准确性，该方法基于将蛋白质分解为柔性面。具有多个构象异构体的链，其余的蛋白质，两个副本我们使用非常有效的快速傅里叶变换相关方法对所有对的所有可能相对方向的相互作用能量进行采样，并将详细的能量网格存储在查找表中，并使用小波变换进行压缩。由于成对相互作用能量的可加性，通过将预先计算的内部能量分量添加到相互作用能量中，可以快速评估任何构象的能量，所有这些都从查找表中提取，能量表的使用将加快配分函数的计算。 ,使用蒙特卡洛模拟细化碎片位置，并通过随机路线图模拟确定逃逸时间所有新算法都将在我们的 FTMap 服务器 (http://ftmap.bu.edu) 中实现，该服务器已经拥有超过 1200 名注册用户。

项目成果

期刊论文数量（19）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Fragments and hot spots in drug discovery.

药物发现的片段和热点。

DOI：
10.18632/oncotarget.4968
发表时间：
2015
期刊：
Oncotarget
影响因子：
0
作者：
Vajda,Sandor;Whitty,Adrian;Kozakov,Dima
通讯作者：
Kozakov,Dima

Characterization of protein-ligand interaction sites using experimental and computational methods.

DOI：
发表时间：
2006-05
期刊：
Current opinion in drug discovery & development
影响因子：
0
作者：
S. Vajda;F. Guarnieri
通讯作者：
S. Vajda;F. Guarnieri

Stimulators of translation identified during a small molecule screening campaign.

在小分子筛选活动中发现的翻译刺激物。

DOI：
10.1016/j.ab.2013.10.026
发表时间：
2014
期刊：
Analytical biochemistry
影响因子：
2.9
作者：
Shin,Unkyung;Williams,DavidE;Kozakov,Dima;Hall,DavidR;Beglov,Dmitri;Vajda,Sandor;Andersen,RaymondJ;Pelletier,Jerry
通讯作者：
Pelletier,Jerry

Novel druggable hot spots in avian influenza neuraminidase H5N1 revealed by computational solvent mapping of a reduced and representative receptor ensemble.

DOI：
10.1111/j.1747-0285.2007.00614.x
发表时间：
2008-02
期刊：
CHEMICAL BIOLOGY & DRUG DESIGN
影响因子：
3
作者：
Landon, Melissa R.;Amaro, Rommie E.;Baron, Riccardo;Ngan, Chi Ho;Ozonoff, David;McCammon, J. Andrew;Vajda, Sandor
通讯作者：
Vajda, Sandor

Structure of the trehalose-6-phosphate phosphatase from Brugia malayi reveals key design principles for anthelmintic drugs.

DOI：
10.1371/journal.ppat.1004245
发表时间：
2014-07
期刊：
PLoS pathogens
影响因子：
6.7
作者：
Farelli JD;Galvin BD;Li Z;Liu C;Aono M;Garland M;Hallett OE;Causey TB;Ali-Reynolds A;Saltzberg DJ;Carlow CK;Dunaway-Mariano D;Allen KN
通讯作者：
Allen KN