The Development and Experimental Verification of Computational Methods to Design and Predict the Properties of Therapeutic Proteins

计算软件开发与实验验证项目总结 治疗性蛋白质的设计方法 治疗性蛋白质是现代医学中的重要工具，它们在治疗严重疾病中的应用 例如癌症和自身免疫性疾病每年都在继续增长。抗体是最重要的 治疗性蛋白质的类别。它们自然地出现在免疫系统中，在那里它们强烈结合并 特别是对外来分子，作为免疫系统其余部分的旗帜，通过指示存在 应该从身体中清除的物质。医学专业人士使用抗体使他们能够 引导患者的免疫反应，改善其健康结局。 虽然抗体提供了巨大的好处，但它们也并非没有局限性。它们又大又精致 生产成本相对较高，难以在高浓度下形成，以及对 它们的储存条件。另外，目前使用的实验方法 开发新的抗体是耗时的，虽然它们可以控制分子，但抗体结合(即 抗原)，针对这些分子的特定区域(即表位)是极其困难的。最后，还有 许多实验和临床应用，目前使用的抗体，尽管不是最多的 适当的蛋白质，因为没有方便的替代品可用。 在过去的十年中，计算蛋白质设计的进展将给这一发展带来革命性的变化。 抗体和其他治疗性蛋白质。最近，奥本大学的潘塔兹实验室创造了 能够在短短几分钟内设计抗体或其他50种结合蛋白中的任何一种的软件 个人计算机与任何所需抗原的任何目标表位相结合。这方面的初步实验结果 方法看起来很有前途。在未来五年，实验室计划在此基础上创建一个 治疗蛋白质开发工作流程具有前所未有的灵活性。建议的研究包括：1) 改进计算设计和选择标准，以提高实验的可行性，从而提供 最终用户相信他们的设计将按预期运行；2)将设计能力扩展到 包括特定的相互作用，允许设计对pH敏感的结合蛋白和酶；3)扩展 从结合蛋白质到多肽的设计原则，使任何基于氨基酸的结合设计成为可能 部分；以及4)设计一种合成结合蛋白，具有抗体的所有好处，而不是 缺点。每个项目都将涉及计算开发和实验验证。 总之，这项研究将允许快速设计一种用于治疗的优化结合蛋白 申请。无论是开发个性化的癌症治疗方法，还是对抗抗药性细菌， 或者对抗新出现的大流行，医生将能够及时开发新的治疗方法。

Project Summary for The Development and Experimental Verification of Computational Methods to Design Therapeutic Proteins Therapeutic proteins are an important tool in modern medicine, and their use in treating serious illnesses such as cancer and autoimmune diseases continues to grow annually. Antibodies are one of the most important classes of therapeutic proteins. They occur naturally in the immune system, where they bind strongly and specifically to foreign molecules, acting as flags to the rest of the immune system by indicating the presence of materials that should be eliminated from the body. The use of antibodies by medical professionals allows them to guide patients’ immune responses to improve their health outcomes. Although antibodies offer tremendous benefits, they are not without their limitations. They are large, delicate proteins that are relatively expensive to produce, difficult to formulate at high concentrations, and sensitive to the conditions at which they are stored. Additionally, the experimental methods that are currently used to develop new antibodies are time consuming and while they can control the molecule the antibodies bind (i.e. antigens), it is extremely difficult to target specific regions (i.e. epitopes) of those molecules. Finally, there are many experimental and clinical applications where antibodies are currently used despite not being the most appropriate protein for the purpose because there are not convenient alternatives available. Advances in computational protein design over the last decade are poised to revolutionize the development of antibodies and other therapeutic proteins. Recently, the Pantazes Lab at Auburn University has created software capable of designing antibodies or any of 50+ other binding proteins in as little as a few minutes on a personal computer to bind any target epitope of any desired antigen. Preliminary experimental results of this method appear very promising. Over the next five years, the lab plans on building on this foundation to create a therapeutic protein development workflow with unprecedented flexibility. Proposed research includes: 1) Improving the computational design and selection criteria to enhance experimental viability, thereby providing end users confidence that what they design will function as predicted; 2) Expanding the design capabilities to include specific interactions, permitting the design of pH-sensitive binding proteins and enzymes; 3) Extending the design principles from binding proteins to peptides, enabling the design of any amino acid based binding moiety; and 4) Designing a synthetic binding protein with all of the benefits of antibodies and none of the drawbacks. Each project will involve both computational development as well as experimental validation. Altogether, this research will allow for the rapid design of an optimized binding protein for therapeutic applications. Whether it is developing personalized cancer treatments, fighting an antibiotic-resistant bacteria, or countering an emerging pandemic, doctors will be able to develop novel treatments in a timely manner.