Computational Active-Site Redesign and Binding Prediction via Molecular Ensembles

通过分子整体的计算活性位点重新设计和结合预测

• 批准号: 8025987
• 负责人: Bruce R. Donald
• 金额: $ 31.68万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-15 至 2014-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8025987
• 关键词: Active Sites; Algorithms; Amino Acids; Anabolism; Antifungal Antibiotics; Antineoplastic Agents; Antiviral Agents; Binding; Binding Proteins; Biochemical; Biological Assay; Biological Models; Biotechnology; Catalysis; Cations; Chemicals; Cities; Complex; Computer Assisted; Computer Simulation; Computer software; Cystic Fibrosis; Cystic Fibrosis Transmembrane Conductance Regulator; DNA Restriction Enzymes; Development; Drug Design; Effectiveness; Engineering; Entropy; Enzymes; Evaluation; Exhibits; Future Generations; Goals; Gramicidin; Hybrids; Immunosuppressive Agents; In Vitro; Lead; Leucine; Libraries; Ligands; Ligase; Measures; Methods; Modeling; Modification; Molecular; Molecular Conformation; Mutation; Peptides; Phenylalanine; Proteins; Reaction; Recovery; Research; Side; Site; Specificity; Speed; Statistical Mechanics; Structure; Substrate Interaction; System; Techniques; Testing; Time; Tyrosine; Vertebral column; Work; adenylate; base; combinatorial; design; enzyme substrate; flexibility; improved; in vitro testing; in vivo; inhibitor/antagonist; mutant; novel; novel therapeutic intervention; open source; peptide synthase; predictive modeling; research study

DESCRIPTION (provided by applicant): Realization of novel molecular function requires the ability to alter molecular complex formation. Enzymatic function can be altered by changing enzyme-substrate interactions via modification of an enzyme's active site. We propose a new algorithm for protein redesign, which combines a statistical mechanics-derived ensemble-based approach to computing the binding constant with the speed and completeness of a branch-and-bound pruning algorithm. In addition, we propose an efficient, deterministic approximation algorithm, capable of approximating our scoring function to arbitrary precision. Our ensemble-based algorithm, which flexibly models both protein and ligand using rotamer-based partition functions, has application in enzyme redesign, the prediction of protein-ligand binding, and computer-aided drug design. In preliminary studies, we redesigned the phenylalanine-specific adenylation domain of the non-ribosomal peptide synthetase Gramicidin Synthetase A (NRPS GrsA-PheA). Ensemble scoring, using a rotameric approximation to the partition functions of the bound and unbound states for GrsA-PheA, was used to switch the enzyme specificity toward leucine (Leu) and tyrosine (Tyr), using novel active site sequences computationally predicted by searching through the space of possible active site mutations. The top-scoring in silico mutants were created in vitro, and binding and catalytic activity were measured. Several of the top-ranked mutations exhibit the desired change in specificity from Phe to Leu or Tyr. When considering protein flexibility and molecular ensembles for protein design, a major challenge has been the development of ensemble-based redesign algorithms that efficiently prune mutations and conformations. The proposed K* ("K-star") method generalizes Boltzmann-based scoring to ensembles and applies the result to protein design. K prunes the vast majority of conformations, thereby reducing execution time and making a mutation search that considers both ligand and protein flexibility computationally feasible. In addition to redesigning PheA, the K algorithm will be used to reprogram the specificity of other NRPS domains, whose products include natural antibiotics, antifungals, antivirals, immuno- suppressants, and antineoplastics. We will also use our algorithms to redesign two restriction endonucleases (REs), and will apply K to design peptide inhibitors for the CAL (Cystic fibrosis transmembrane conductance regulator Associated Ligand) PDZ domain. Our algorithms will predict NRPS and RE mutants with putative novel function, and we will create the mutant proteins, and test our predictions by using biochemical activity assays and determining new crystal structures. We will test the predicted CAL-binding peptides both in vitro and in vivo. Project Narrative: Enzyme redesign provides a good test of our understanding of proteins. The long-term goal of our research is to develop novel algorithms to plan structure-based site-directed mutations to a protein's active site in order to modify its function. We will develop general planning software that can reprogram the specificity of many proteins, including NRPS domains, whose products include natural antibiotics, antifungals, antivirals, immuno- suppressants, and antineoplastics. These engineered enzymes should enable combinatorial biosynthesis of novel pharmacologically-active compounds, yielding new leads for drug design. The proposed application of our algorithms to restriction endonucleases and the CAL PDZ domain could lead to (respectively) biotechnology advances and novel therapeutic interventions for cystic fibrosis.

描述（由申请人提供）：新分子功能的实现需要改变分子复合物形成的能力。酶的功能可以通过修饰酶的活性位点来改变酶-底物相互作用。我们提出了一种新的蛋白质重新设计算法，它结合了统计力学派生的基于集合的方法来计算结合常数的速度和完整性的分支定界修剪算法。此外，我们提出了一个有效的，确定性的近似算法，能够近似我们的评分函数到任意精度。我们的集成为基础的算法，灵活地使用基于旋转异构体的配分函数的蛋白质和配体模型，在酶的重新设计，蛋白质-配体结合的预测，和计算机辅助药物设计的应用。在初步研究中，我们重新设计了非核糖体肽合成酶短杆菌肽合成酶A（NRPS GrsA-PheA）的苯丙氨酸特异性腺苷酸化结构域。使用对GrsA-PheA的结合和未结合状态的配分函数的旋转异构体近似的Enhancement评分，使用通过搜索可能的活性位点突变的空间计算预测的新活性位点序列，用于将酶特异性切换到亮氨酸（Leu）和酪氨酸（Tyr）。在体外产生得分最高的计算机突变体，并测量结合和催化活性。几个排名靠前的突变表现出从Phe到Leu或Tyr的特异性的期望变化。当考虑蛋白质的灵活性和蛋白质设计的分子集合时，一个主要的挑战是开发基于集合的重新设计算法，有效地修剪突变和构象。所提出的K*（“K-star”）方法将基于玻尔兹曼的评分推广到系综，并将结果应用于蛋白质设计。K修剪了绝大多数的构象，从而减少了执行时间，并使突变搜索，同时考虑配体和蛋白质的灵活性计算可行。除了重新设计PheA之外，K算法还将用于重新编程其他NRPS结构域的特异性，其产品包括天然抗生素、抗真菌剂、抗病毒药、免疫抑制剂和抗真菌塑料。我们还将使用我们的算法来重新设计两种限制性内切核酸酶（RE），并将应用K来设计CAL（囊性纤维化跨膜传导调节相关配体）PDZ结构域的肽抑制剂。我们的算法将预测具有推定新功能的NRPS和RE突变体，我们将创建突变蛋白，并通过使用生化活性测定和确定新的晶体结构来测试我们的预测。我们将在体外和体内测试预测的CAL结合肽。 项目叙述：酶的重新设计为我们对蛋白质的理解提供了一个很好的测试。我们研究的长期目标是开发新的算法，以计划基于结构的定点突变到蛋白质的活性位点，以修改其功能。我们将开发通用规划软件，可以重新编程许多蛋白质的特异性，包括NRPS结构域，其产品包括天然抗生素，抗真菌药，抗病毒药，免疫抑制剂和抗真菌塑料。这些工程酶应该能够组合生物合成新的药理活性化合物，产生新的药物设计的线索。我们的算法限制性内切核酸酶和CAL PDZ域的拟议应用可能导致（分别）生物技术的进步和囊性纤维化的新的治疗干预。