Computational Active-Site Redesign and Binding Prediction via Molecular Ensembles

描述（由申请人提供）：实现新的分子功能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与底物的相互作用。我们提出了一种新的蛋白质再设计算法，该算法结合了基于统计力学推导的基于集成的方法来计算结合常数，并结合了分支-绑定剪枝算法的速度和完整性。此外，我们提出了一个有效的，确定性的近似算法，能够逼近我们的评分函数到任意精度。我们的基于集成的算法使用基于旋转体的配分函数灵活地建模蛋白质和配体，在酶的重新设计、蛋白质与配体结合的预测和计算机辅助药物设计中具有应用价值。在初步研究中，我们重新设计了非核糖体肽合成酶Gramicidin合成酶A （NRPS GrsA-PheA）的苯丙氨酸特异性腺苷化结构域。通过对GrsA-PheA的结合和非结合状态的配分函数的旋转近似，利用通过搜索可能的活性位点突变空间计算预测的新活性位点序列，使用集合评分将酶特异性转向亮氨酸（Leu）和酪氨酸（Tyr）。在体外建立了得分最高的硅突变体，并测量了结合和催化活性。一些排名靠前的突变表现出从Phe到Leu或Tyr的期望特异性变化。当考虑蛋白质的灵活性和蛋白质设计的分子集成时，一个主要的挑战是开发基于集成的重新设计算法，有效地修剪突变和构象。提出的K*（“K-star”）方法将基于玻尔兹曼的评分推广到集合，并将结果应用于蛋白质设计。K修剪了绝大多数构象，从而减少了执行时间，并使考虑配体和蛋白质灵活性的突变搜索在计算上可行。除了重新设计PheA外，K算法还将用于重新编程其他NRPS结构域的特异性，这些结构域的产物包括天然抗生素、抗真菌药物、抗病毒药物、免疫抑制剂和抗肿瘤药物。我们还将使用我们的算法重新设计两个限制性内切酶（REs），并将应用K来设计CAL（囊性纤维化跨膜传导调节剂相关配体）PDZ结构域的肽抑制剂。我们的算法将预测具有新功能的NRPS和RE突变体，我们将创建突变蛋白，并通过生化活性分析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。

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.