Modeling Molecular Recognition

该项目由分子与细胞生物科学部的分子生物物理学和化学部的理论与计算化学项目共同支持，旨在模拟蛋白质-蛋白质相互作用特异性的早期分子识别事件，并预测蛋白质相互作用。基于观察到扩散可达状态在对接前对其结合位点具有明确的吸引力，本项目的具体目标是：(1)开发并公开一组合适的蛋白质，以基准特异性和非特异性相互作用，通过使用经过验证的对接技术检测自由能景观的广泛最小值和最可能的可能结合位点集；(2)对蛋白质之间的相关相互作用进行建模，并开发半刚性全原子布朗动力学平台，以评估两种蛋白质在部分失溶的相遇复合物的自由能景观中从局部最小值移动所需的时间尺度。初步结果表明，在结合位点和其他偶然的局部最小值之间的逃逸时间有明显的分离。模拟将通过使用分子动力学生成的预先计算的构象集合来周期性地调整侧链以适应其局部环境，从而结合灵活性。该方法将作为一个web服务器来实现，根据相关自由能最小值的逃逸时间估计，自动评估任意两个蛋白质相互作用的可能性。该项目的主要思想是绕过结合的复合物，并使用停留时间或粘性，作为两个蛋白质是否物理相互作用的估计。在体内，蛋白质可能遇到许多潜在的结合伙伴。然而，在蛋白质结构中编码的一组显著的特异性和非特异性相互作用只允许与一种独特的底物结合。通过保持蛋白质之间的随机相遇不超过几纳秒，可以防止非特异性结合，而当与结合位点特征的广泛自由能最小值相关的停留时间足够长，以诱导合适的相互作用来锁定复合物时，就会触发分子识别。尽管有这些见解，到目前为止，还没有计算机方法来预测高亲和力复合物。在这一基本问题上的任何进展都必然会带来对蛋白质如何在细胞中协同工作的更好理解，从而促进生物科学各个方面的突破。结构基因组学革命以及预测蛋白质相互作用的技术将使在计算机上模拟生物过程成为可能。

The objective of this project, jointly supported by Molecular Biophysics in the Division of Molecular and Cellular Biosciences and the Theoretical and Computational Chemistry Program in the Chemistry Division, is to model the early molecular recognition events responsible for the specificity of protein-protein interactions and predict protein interactions. Based on the observation that diffusion accessible states have a definite attraction for their binding site prior to docking, the specific aims of this project are: (1) To develop and make public a suitable set of proteins to benchmark specific and non-specific interactions, detecting the broad minima of the free energy landscape and most likely set of possible binding sites by using validated docking techniques; and (2) to model the relevant interactions between proteins and develop a semi-rigid full-atom Brownian Dynamics platform to evaluate the time scale that two proteins take to move apart from local minima on the free energy landscape of partially desolvated encounter complexes. Preliminary results indicate a sharp separation in the escape time between the binding site and other incidental local minima. Simulations will incorporate flexibility by periodically adjusting side chains to their local environment using a molecular dynamics generated ensemble of pre-calculated conformations. This method will be implemented as a web-server to automatically evaluate the likelihood of any two proteins to interact based on estimates of the escape time from relevant free energy minima. The main idea of this project is to circumvent the bound complex and use the dwelling time, or stickiness, as an estimate for whether or not two proteins physically interact. In vivo, proteins may encounter many potential binding partners. However, a striking set of specific and non-specific interactions encoded in the protein structure tolerates binding only to a unique substrate. Non-specific binding is prevented by keeping random encounters between proteins to last no more than a few nanoseconds, while molecular recognition is triggered when the dwelling time associated with the broad free energy minimum that characterizes the binding site is long enough for induced fit interactions to latch the complex. Despite these insights, to date there is no in silico approach to predict the high affinity complexes. Any progress in this fundamental problem is bound to bring about a better understanding of how proteins work cooperatively in a cell, promoting breakthroughs in every aspect of the biological sciences. The structural genomics revolution along with technologies that predict protein interactions will make it possible to simulate biological processes in silico.