Prediction and Validation Tools for Novel Membrane Interaction Surfaces from Protein Structures

一般认为，大约四分之一的基因组编码跨膜蛋白，其中许多是重要的受体和药物靶点。其余的大部分通常被认为是可溶性蛋白质，包括信号和代谢酶。然而，未知数量的这些蛋白实际上与膜表面可逆结合，这些相互作用决定了这些蛋白在细胞内的位置，并调节它们的酶和信号活动。事实上，可以认为，蛋白质的位置与其内在活性一样重要，限制了它在黏性和区隔化的细胞中获得局部集中的底物、辅因子和配体。如果没有一种有效的方法来识别和测试这些膜相互作用表面，我们对蛋白质功能的认识将继续受到限制，我们在分子生物学和生物化学方面的研究进展将受到限制。因此，我们正在开发新的计算和生物物理方法来准确检测和验证蛋白质-膜相互作用，这些相互作用可以定位细胞内的蛋白质，为理解细胞过程和疾病机制提供新的见解和工具。已知多种蛋白质模块，包括BAM、FYVE、PH和PX结构域结合膜表面以响应细胞刺激、生长和分化的变化。我们建议通过分析这些蛋白的结构特性，可以阐明和推广膜结合原理，并发现全新的pmp类别。相互作用是多种多样的。一些蛋白质通过对单个磷脂头基团的可逆识别特异性地动态结合膜，而另一些蛋白质则紧密结合，锚定在双分子层上，帮助组装分子复合物并催化反应。然而，我们的研究揭示了共同的主题，包括暴露的疏水环、基本斑块和极化表面。这些特性通过一种算法集成在一起，该算法可以在几秒钟内自动识别膜结构中的结合位点。一旦经过适当的训练，该方法将允许用户准确预测新型pmp，实验方法和脂质/胶束文库将允许研究人员有效地验证这些发现。缺乏快速和准确的工具来检测与膜相互作用的蛋白质表面，阻碍了分子和细胞生物学领域的进展，并且限制了蛋白质组学和脂质组学领域之间的相互作用。由于缺乏对膜蛋白相互作用的理解，研究“粘性”膜相互作用域和微妙的双层结构的技术困难更加复杂。因此，需要一种方便的、有洞察力的计算和新的实验工具来分析蛋白质膜识别。我们的解决方案旨在提供足够的信息，允许用户设计和测试蛋白质如何靶向特定的膜结构域，预测它们在膜表面的空间方向，并揭示是否构象变化可能伴随结合事件。蛋白质膜相互作用决定了许多细胞器和分子复合物的组织和调节活动，这一事实确保了广泛的适用性。一些脂质结合域影响细胞的增殖、分化、存活、迁移、粘附和侵袭。其他涉及神经发生、血管生成、伤口愈合、免疫和发育性疾病。我们的研究将能够更深入地了解它们之间的相互作用，以帮助设计配体和抑制剂，并可能有助于设计脂质通常结合的治疗剂。将使用选定的人类蛋白质开发和应用这些工具，以实现高影响和疾病相关性，并在可能的情况下进行标准化，以最大限度地适用于任何蛋白质

It is generally thought that about one quarter of genomes encodes transmembrane proteins, many of which are important receptors and drug targets. Most of the remainder are typically assumed to be soluble proteins including signalling and metabolic enzymes. However an unknown number of these actually bind reversibly to membrane surfaces, and these interactions determine where these proteins are located inside cells, and regulate their enzymatic and signaling activities. In fact, it can be argued that a protein's location is just as important as its intrinsic activity, restricting its access to locally concentrated substrates, cofactors and ligands within the viscous and compartmentalized cell. Without an effective way to identify and test these membrane interaction surfaces, our knowledge of protein function will continue to be limited and our research progress in molecular biology and biochemistry will be restricted. Hence we are developing new computational and biophysical methods to accurately detect and validate protein-membrane interactions which localize proteins inside cells, providing new insights and tools for understanding cellular processes and disease mechanisms. A variety of protein modules including BAM, FYVE, PH and PX domains are known to bind membrane surfaces in response to changes cell stimulation, growth and differentiation. We propose that by analyzing the structural properties of such proteins, the principles of membrane binding can be elucidated and generalized, and entirely new classes of PMPs can be found. The interactions are diverse. Some proteins bind membranes specifically yet dynamically by reversible recognition of individual phospholipid headgroups, yet others bind tightly, being anchored to the bilayer where they help assemble molecular complexes and catalyze reactions. Yet our studies have revealed common themes including exposed hydrophobic loops, basic patches and polarized surfaces. These properties are integrated here by an algorithm that automatically identifies membrane binding sites from structures in seconds. Once suitably trained, this method will allow users to accurately predict the new types of PMPs, and experimental methods and lipid/micelle libraries will be available to allow researchers to efficiently validate such discoveries. The lack of fast and accurate tools to detect protein surfaces that interact with membranes has impeded progress in the fields of molecular and cellular biology, and has limited interactions between the fields of proteomics and lipidomics. The dearth of understanding about membrane protein interactions is compounded by technical difficulties of studying 'sticky' membrane interacting domains and delicate bilayer structures. Thus there is a real need for convenient and insightful computational and new experimental tools to analyze protein membrane recognition. Our solution aims to provide sufficient information to allow users to design and test how proteins are targeted to specific membrane domains, to predict their spatial orientations on membrane surfaces, and to reveal whether conformational changes could accompany binding events. Broad applicability is ensured by the fact that protein membrane interactions determine the organization and regulated activities of so many cellular organelles and molecular complexes. Some lipid binding domains influence cell proliferation, differentiation, survival, migration, adhesion and invasion. Others are involved in neurogenesis, angiogenesis, wound healing, immunity and developmental diseases. Our research will enable a deeper understanding of their interactions in sufficient detail to aid in the design of ligands and inhibitors, and may aid in the design of therapeutic agents where lipids normally bind. The tools will be developed and applied using selected human proteins to achieve high impact and disease relevancy, and will be standardized where possible to maximize applicability to any protei