III: Small: Facilitating Search in the High-Dimensional Space of Molecular Interactions

蛋白质（受体）与小分子（配体）的结合通常是免疫反应和细胞信号传导等生物过程背后的潜在机制。了解受体和配体如何结合是解释这些生物现象的基础，也是创新药物发现和设计的基础。探索将包括设计分析结合途径和动力学的方法，重点是从多个用户运行中提取计算特征。该产品将用于pi在K-12学校和当地博物馆开展的外展活动。除了潜在地应用于尖端的计算生物物理学研究之外，这些资源还将提供理想的界面，向公众传授分子相互作用及其在过敏反应等生物过程中所起的作用。该奖项将开发通过交互式协作界面模拟生物分子结合的方法，该界面利用并集成了通过触觉界面对能量景观的多用户探索。这将通过促进分子对接高维能量景观的搜索来解决当前分子对接模拟的局限性。结果将包括一个众包的高维能量和分子结构数据集，从中提取结合事件的生物物理性质。这项工作的长期目标是开发一个快速，准确的系统，通过识别对接途径和配体-受体构象，利用众包信息来帮助药物发现。

The binding of proteins (receptors) to small molecules (ligands) is often the underlying mechanism behind biological processes such as immune response and cell signaling. Understanding how receptors and ligands bind is fundamental to explaining these biological phenomena, and for innovative drug discovery and design. The exploration will include designing methods for analyzing binding pathways and kinetics, focusing on the extraction of computational features from multiple user runs. The product of this will be used in outreach activities performed by the PIs in K-12 schools and local museums. In addition to being potentially applicable in cutting-edge computational biophysics research, the resources will also provide the ideal interface to teach the public about molecular interactions and the role they play in biological processes such as allergic reactions.This award will develop methods for simulating binding of biomolecules via an interactive collaborative interface that harnesses and integrates multi-user exploration of the energetic landscape through haptic interfaces. This will address the current limitations of molecular docking simulations by facilitating search in the high-dimensional energetic landscape of molecular docking. Results will include a crowd-sourced high-dimensional dataset of energies and molecular configuration from which to extract biophysical properties of binding events. The long-term objective of the work is to develop a fast, accurate system to aid drug discovery by identifying docking pathways and ligand-receptor conformations using crowd-sourced information.