Molecular Modelling Group, Indian Institute of Chemical Technology, Uppal Road, Taranaka, Hyderabad 500 607, India.
J Biomol Struct Dyn. 2013;31(5):522-37. doi: 10.1080/07391102.2012.703071. Epub 2012 Aug 9.
Molecular mechanics with Generalized Born surface area (MMGBSA) based binding energies (BEs) derived from the molecular dynamics (MD) trajectories are highly reliable and extensively used standards to estimate the strength of interactions between ligands and their receptor. MD simulations (5 ns) for 30 aromatic furan aminidino derivatives (anti-Pneumocystis carnii agents) have been carried out by using Amber program and BEs have been calculated by using Generalized Born (GB) method. Based on the generated data, we present a simple and effective method for the approximation of BEs without performing MD simulations and MMGBSA calculations. Quantum chemical (density functional theory based) and geometrical descriptors are used for the prediction of the BE values. All the developed models are statistically significant with high values of correlation and cross-validation coefficients. The prediction ability and effectiveness of the models are tested by the division of the data-set into four different training and test sets and the average error was only 4-7% (1.56-2.61 kcal/mol) of the actual BEs.
基于广义 Born 溶剂化表面面积（MMGBSA）的分子力学结合能（BE）源自分子动力学（MD）轨迹，是高度可靠且广泛用于估计配体与其受体之间相互作用强度的标准。使用 Amber 程序对 30 种芳香呋喃脒基衍生物（抗卡氏肺孢子虫药物）进行了 5ns 的 MD 模拟，并使用广义 Born（GB）方法计算了 BE。基于生成的数据，我们提出了一种无需进行 MD 模拟和 MMGBSA 计算即可近似 BE 的简单有效方法。量子化学（基于密度泛函理论）和几何描述符用于预测 BE 值。所有开发的模型均具有统计学意义，相关系数和交叉验证系数值较高。通过将数据集分为四个不同的训练集和测试集，测试了模型的预测能力和有效性，平均误差仅为实际 BE 的 4-7%（1.56-2.61kcal/mol）。
