Molecular Recognition of Proteins and Ligand Design

项目摘要/摘要 研究计划的目的是开发改进的计算方法来模拟 生物分子系统及其在发现治疗人类疾病的新药方面的应用，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的技术 分子设计、合成有机化学、生物分析和结构生物学，即结晶学 用X射线衍射法测定与蛋白质靶标结合的设计分子的结构。这个 Pi的团队开发并应用了广泛使用的力场，这是生物分子建模的核心，并且 计算溶液中自由能变化的方法。最初活性化合物(HITS)的发现是 由虚拟筛选和从头开始设计的配体生长程序Bomb推动。系统的优化 然后，通过自由能微扰(FEP)计算来指导产生有效的类药物抑制剂的点击 缓蚀剂的蒙特卡罗(MC)统计力学和分子动力学(MD)模拟 水中的蛋白质抑制物复合体。这种方法的可行性已经通过 多种蛋白质的多种有效抑制剂的发现。它是高效药物发现的典范。 这适用于寻求多种疾病的治疗方法。 目前主要的生物分子靶点是巨噬细胞移动抑制因子(MIF)和JAK2激酶。 干扰MIF的细胞因子信号转导已知有治疗炎症性疾病和 癌症，而逆转V617F突变对JAK2激酶的激活作用有望提供 治疗大多数骨髓增生性疾病的药物。有机分子正在被设计、合成、 并进行测试以实现这些治疗目标。对于MIF来说，这一发现已经取得了实质性进展 由两个化学系列的化合物组成，这些化合物与蛋白质结合得非常紧密，并抑制了 前列腺癌细胞。对于JAK2，Lead优化也很顺利，对于JAK2来说，选择性地绑定到 获得了假性激酶JH2结构域，而不是JH1激活域。更多关于 这些和新的化学系列计划提供多种结构多样化的化合物 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很大 通过获取许多蛋白质抑制物复合体的高分辨率晶体结构而得到加强。在……里面 此外，在力场和计算自由能方面仍有许多技术进步。 用来指导分子的选择和合成和测试。这个 研究项目尤其值得注意的是最先进的计算和实验之间的密切互动 在一个实验室里。计算预测成功的即时反馈提供了一个 寻求不断改进方法论的重要动力。

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.