AF: Small: Volumetric Alignment of Protein Cavities for the Analysis of Ligand Binding Specificity

蛋白质结构的比对是研究蛋白质功能的基础。将一种蛋白质的结合腔叠加到另一种蛋白质上可以揭示形状相似之处，这解释了为什么两种蛋白质结合了相似的分子伴侣。叠加也可以暴露出关键的差异，这解释了为什么蛋白质有时会结合非常不同的伴侣。这些观察是由结构生物学专家在蛋白质结构比对的计算帮助下进行的，有助于构建我们对蛋白质结合偏好的原子水平的理解。蛋白质结合偏好是蛋白质工程、系统生物学、药物设计和其他领域许多紧迫挑战的症结所在。该项目考虑了一种新的蛋白质结构比对方法，该方法通过最大化结合空穴之间的重叠体积来产生重叠。将考虑两个核心研究方向：(1)开发专门的优化技术，快速可靠地探索连续的比对空间；(2)使用生物和生物物理数据来增强比对过程。智力优势：提出的工作通过新的蛋白质结构表示和新的几何叠加技术推进了蛋白质结构比较的研究。对密切相关蛋白质的新关注也与现有方法不同，现有方法通常针对进化关系较远的蛋白质。该项目推进了数学优化技术，以适应噪声和昂贵的重叠空腔体积估计。这种性质的适应在优化中是一个新出现的挑战，在这种情况下，被优化的函数通常是不精确和昂贵的计算的结果，比如模拟。型腔对准问题的低维性，加上在存在噪声和不精确的情况下进行优化的机会，创造了一个独特的机会来改进技术，以应对优化中的这一普遍挑战。在结构生物学方面，拟议的工作将为现有的工作流程增加自动化和精确度，使人们能够检查比人类完全考虑的更多的结构，并识别否则可能被忽视的分子细微之处。布罗德影响：该项目还专注于开发用于蛋白质结构比较的交互式软件。该软件将提供一个可视化和直观的界面，帮助来自非计算背景的学生和科学家更好地使用和理解结构生物信息学软件。研究本身和界面软件的开发将使具有单一学科背景的研究生和本科生接触到生物信息学的跨学科研究计划，并培训他们进行跨学科交流。

The alignment of protein structures is essential for the study of protein function. Superposing the binding cavities of one protein onto another can reveal shape similarities that explain why two proteins bind a similar molecular partner. Superposition can also expose critical differences that explain why proteins sometimes bind very different partners. These observations, made by experts in structural biology with the computational aid of protein structure alignments, help construct our atomic-level understanding of protein binding preferences. Protein binding preferences lie at the crux of many pressing challenges in protein engineering, systems biology, drug design, and other fields.This project considers a new approach to protein structure alignment that generates superposition by maximizing the overlapping volume between binding cavities. Two core research directions will be considered: (1) The development of specialized optimization techniques that rapidly and reliably explore the continuous space of alignments and (2) the usage of biological and biophysical data to enhance the alignment process.Intellectual Merit: The proposed work advances the study of protein structure comparison with new representations of protein structure and new geometric superposition techniques. A novel focus on closely related proteins also diverges from existing methods, which generally target proteins with distant evolutionary ties. The project advances techniques in mathematical optimization for accommodating the noisy and expensive estimation of overlapping cavity volume. Accommodations of this nature are an emerging challenge in optimization, where the function being optimized is frequently the result of imprecise and expensive computations, like simulations. The low dimensionality of the cavity alignment problem, coupled with the opportunity to optimize in the presence of noise and imprecision creates a unique opportunity to advance techniques for this general challenge in optimization. In structural biology, the proposed work will add automation and precision to existing workflows, enabling the examination of more structures than humans can fully consider and identifying molecular subtleties that might otherwise be overlooked.Broader Impacts: The project also focuses on developing interactive software for protein structure comparison. This software will provide a visual and intuitive interface, helping students and scientists from non-computational background to better use and understand software in structural bioinformatics. The research itself and the development of the interface software will expose graduate and undergraduate students with mono-disciplinary backgrounds to an interdisciplinary research program in bioinformatics, and train them in cross-disciplinary communication.