Accurate and efficient density functional theory calculations of intermolecular interactions and conformational energies

项目总结 关键的生物物理性质，如药物结合部位和酶催化产生 使用量子力学进行计算机建模，但在实际应用的准确性方面存在局限性 量子方法阻碍了进展。在过去的五年里，这种情况发生了变化 随着密度泛函理论(DFT)精确度的令人兴奋的(和持续的)改进。 新的和更好的密度泛函为构象的应用打开了新的机会 搜索，分子识别，配基结合，以及从头计算的所有领域 被用于生物物理化学。然而，这些泛函需要非常大的和 计算要求很高的基组，以达到其高精度。使用较小的基数集 导致不收敛的结果，通常具有不可接受的误差。有一种未得到满足的需求 显著降低了实现大基集精度的计算成本。 该方案的中心创新是使用最小自适应基函数(MAB) 为此，取代了传统的大型基准集。MAB是一组很小(最小)的 函数，由传统的大基通过原子阻塞自适应地形成，稀疏 转型。DFT计算是在自适应基础上执行的，然后是对偶基 更正。这潜在地允许非常大的计算加速，同时产生精确度 几乎无法与传统执行的计算代价高昂的计算区分开来 在大目标的基础上。 第一阶段的研究有三个主要目标。首先，这项研究将建立 MAB协议对一系列生物物理相关能量差异的准确性。第二, 这项研究将导致一个仔细合理的估计，通过 MAB方法，并将产生新的软件实现的几种算法 必须优化的步骤。第三，人与生物圈办法的修改和改进将 被尽可能地寻找和需要。所得结果将为基集极限密度泛函理论奠定基础 计算大大减少了计算成本，从而潜在地极大地扩展了其 对生物物理建模的有用性。

Project summary Key biophysical properties such as drug binding sites and enzyme catalysis arise can be computer-modeled using quantum mechanics, but limitations in the accuracy of practical quantum methods have held back progress. Over the past five years, this situation has changed with exciting, (and ongoing) improvements in the accuracy of density functional theory (DFT). New and better density functionals open new opportunities for applications in conformational searching, molecular recognition, ligand binding, and all the areas where ab initio calculations are employed in biophysical chemistry. However, these functionals require very large and computationally demanding basis sets to attain their high accuracy. Use of smaller basis sets leads to unconverged results with often unacceptable errors. There is an unmet need to significantly reduce the computational cost of achieving large basis set accuracy. The central innovation of this proposal is to use minimal adaptive basis functions (MAB) for this purpose, in place of traditional large basis sets. The MAB is a small (minimal) set of functions, adaptively formed from a traditional large basis via an atom-blocked, sparse transformation. The DFT calculation is performed in the adaptive basis, followed by a dual basis correction. This potentially permits very large computational speedups, while yielding accuracy virtually indistinguishable from a computationally costly calculation performed conventionally in the large target basis. The Phase I research has three principal objectives. First, the research will establish the accuracy of the MAB protocol for a range of biophysically relevant energy differences. Second, the research will lead to a carefully justified estimate of the speed-up that is attainable with the MAB approach, and will produce a new software implementation of several of the algorithmic steps that must be optimized. Third, modifications and improvements of the MAB approach will be sought as possible and needed. The results will lay the groundwork for basis set limit DFT calculations at greatly reduced computational cost, thereby potentially greatly expanding their usefulness for biophysical modeling.