Molecular Modeling Section (MMS), Dipartimento di Scienze del Farmaco, Università di Padova , via Marzolo 5, 35131 Padova, Italy.
J Chem Inf Model. 2014 Feb 24;54(2):372-6. doi: 10.1021/ci400766b. Epub 2014 Feb 3.
Supervised MD (SuMD) is a computational method that allows the exploration of ligand-receptor recognition pathway investigations in a nanosecond (ns) time scale. It consists of the incorporation of a tabu-like supervision algorithm on the ligand-receptor approaching distance into a classic molecular dynamics (MD) simulation technique. In addition to speeding up the acquisition of the ligand-receptor trajectory, this implementation facilitates the characterization of multiple binding events (such as meta-binding, allosteric, and orthosteric sites) by taking advantage of the all-atom MD simulations accuracy of a GPCR-ligand complex embedded into explicit lipid-water environment.
有监督 MD（SuMD）是一种计算方法，可在纳秒（ns）时间尺度内探索配体-受体识别途径的研究。它由在配体-受体接近距离上将类似于禁忌的监督算法纳入经典分子动力学（MD）模拟技术组成。除了加快配体-受体轨迹的获取外，这种实现还通过利用嵌入到明确定义的脂质-水环境中的 GPCR-配体复合物的全原子 MD 模拟的准确性，方便了对多个结合事件（如元结合、变构和正位结合）的特征描述。
