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

蛋白质结构的排列对蛋白质功能的研究至关重要。将一种蛋白质的结合腔叠加到另一种蛋白质上，可以揭示形状的相似性，从而解释为什么两种蛋白质会结合相似的分子伴侣。叠加也可以揭示关键的差异，解释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辅助下进行的，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关键。该项目考虑了一种新的蛋白质结构对齐方法，通过最大化结合腔之间的重叠体积来产生叠加。将考虑两个核心研究方向：(1)开发快速可靠地探索连续空间的专业优化技术；(2)利用生物和生物物理数据来增强对准过程。知识价值：提出的工作推进蛋白质结构比较的研究与蛋白质结构的新表示和新的几何叠加技术。对密切相关蛋白质的新关注也与现有方法不同，现有方法通常针对具有遥远进化关系的蛋白质。该项目推进了数学优化技术，以适应重叠空腔体积的噪声和昂贵的估计。适应这种性质是优化中的一个新挑战，其中被优化的函数通常是不精确和昂贵的计算的结果，如模拟。空腔对准问题的低维数，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推进技术，以解决优化中的这一普遍挑战。在结构生物学中，拟议的工作将增加现有工作流程的自动化和精确性，使人们能够检查更多的结构，而不是人类可以充分考虑和识别分子的微妙之处，否则可能被忽视。更广泛的影响：该项目还侧重于开发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中的软件。研究本身和接口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项目，并训练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.