Molecular Recognition of Proteins and Ligand Design

项目总结/摘要 该研究计划的目的是开发改进的计算方法，用于模拟 生物分子系统，并将其应用于发现治疗人类疾病的新药，特别是 艾滋病毒/艾滋病、炎症性疾病和癌症。该方法结合了计算机辅助技术， 分子设计、合成有机化学、生物测定和结构生物学，即，晶体学 通过X射线衍射确定与其蛋白质靶结合的设计分子的结构。的 PI的团队开发和应用广泛使用的力场，这是生物分子建模的核心， 计算溶液中自由能变化的方法。初始活性化合物（“命中”）的发现是 通过虚拟筛选和用配体生长程序BOMB从头设计来促进。优化 然后，通过使用自由能微扰（FEP）计算来指导产生有效的药物样抑制剂的命中 采用蒙特卡罗（MC）统计力学和分子动力学（MD）模拟方法， 蛋白质抑制剂复合物在水中。该方法的可行性已通过 发现了许多针对多种蛋白质的有效抑制剂。它是高效药物发现的典范 这适用于对许多疾病的治疗。 目前主要的生物分子靶标是巨噬细胞迁移抑制因子（MIF）和JAK 2激酶。 破坏MIF的细胞因子信号传导具有治疗炎性疾病的已知潜力， 癌症，而JAK 2激酶的V617 F突变的激活作用的逆转预计将提供 治疗大多数骨髓增生性疾病。有机分子被设计，合成， 并进行测试以实现这些治疗目标。对于MIF，随着发现的进展， 两个化学系列的化合物与蛋白质结合得非常紧密， 前列腺癌细胞先导物优化也沿着JAK 2，对于JAK 2，期望的、选择性结合至靶细胞。 已经实现了用假激酶JH 2结构域代替JH 1激酶结构域。进一步探讨 这些和新的化学品系列计划提供多种结构多样的化合物， 用于临床前开发。对于这两个目标，活动数据的进展和解释都非常重要。 通过获得许多蛋白质-抑制剂复合物的高分辨率晶体结构来增强。在 此外，在力场和自由能的计算方面，还有许多技术上的进步 结合的复合物，这是用来指导分子的选择合成和测试。的 一个研究项目特别值得注意的是，它将最先进的计算和实验紧密地结合在一起 在一个实验室里。计算预测成功的即时反馈提供了一个 是寻求不断改进方法的重要推动力。

Project Summary/Abstract The purpose of the research program is to develop improved computational methods for the simulation of biomolecular systems and to apply them to discover new drugs for treatment of human diseases, especially HIV/AIDS, inflammatory diseases, and cancer. The approach combines technology for computer-aided molecular design, synthetic organic chemistry, biological assaying, and structural biology, i.e., crystallographic determination of structures of the designed molecules bound to their protein targets by X-ray diffraction. The PI’s group develops and applies widely used force fields, which are at the heart of biomolecular modeling, and methods for computing free energy changes in solution. Discovery of initial active compounds (“hits”) is facilitated by virtual screening and by de novo design with the ligand-growing program BOMB. Optimization of the hits to yield potent, drug-like inhibitors is then guided by free-energy perturbation (FEP) calculations using Monte Carlo (MC) statistical mechanics and molecular dynamics (MD) simulations for the inhibitors and protein-inhibitor complexes in water. The viability of the approach has been well established through the discovery of numerous potent inhibitors for multiple proteins. It serves as a model for efficient drug discovery that is applicable to the pursuit of remedies for numerous diseases. The principal biomolecular targets are now macrophage migration inhibitory factor (MIF) and JAK2 kinase. Disruption of the cytokine signaling of MIF has known potential for treatment of inflammatory diseases and cancer, while reversal of the activating effect of the V617F mutation for JAK2 kinase is expected to provide remedies for the majority of myeloproliferative disorders. Organic molecules are being designed, synthesized, and tested to achieve these therapeutic goals. For MIF, substantial progress has been made with the discovery of compounds in two chemical series that bind extraordinarily tightly to the protein and inhibit the growth of prostate cancer cells. Lead optimization is also well along for JAK2 for which desired, selective binding to the pseudokinase JH2 domain instead of the JH1 kinase domain has been achieved. Additional exploration of these and new chemical series is planned to provide multiple, structurally diverse compounds that are suitable for preclinical development. For both targets, the progress and interpretation of activity data are greatly enhanced by the acquisition of high-resolution crystal structures of many protein-inhibitor complexes. In addition, there continue to be numerous technical advances for the force fields and for computing free energies of binding for the complexes, which are used to guide the selection of molecules to synthesize and test. The research program is particularly notable for the close interplay of state-of-the-art computation and experiment in one laboratory. The immediate feedback on the success of the computational predictions provides an important driving force to seek ever improving methodology.