Schrödinger药物虚拟筛选流程模块在大学生物和化学信息学教学中的应用

摘要

介绍了Schr?dinger药物虚拟筛选的基本原理和流程,结合大学生物和化学信息学课程的相关教学内容,分别描述了蛋白受体的预处理、类药性五原则、毒药物动力学(ADME)、泛筛选干扰化合物(PAINS)、高通量虚拟筛选、标准精度筛选、高精度筛选和MM/GBSA的打分排序原理和使用方法.该软件可以在大学生物和化学信息学的教学中演示,有助于提高学生对蛋白结构、分子构象、药物虚拟筛选和计算机辅助分子设计的理解,该软件有很好的图形界面,可以给学生直观的体验,大大丰富了大学课堂的教学内容.此外,该软件在药物设计领域里面也有很好的应用价值,大大节约了药物筛选的成本,提高了药物发现的效率.%This paper introduces the basic principle and workflow of virtual screening of drugs in Schr?dinger. In combination with the college bioinformatics and chemoinformatics course, it illustrates the principle and usage method of protein preparation, Lipinski's Rule of Five, ADME, Pan-assay Interference Compounds (PAINS), high throughput virtual screening, standard precision screening, extra precision screening and score ranking of MM/GBSA. The Schr?dinger can be demonstrated to improve students' understanding of protein structure, molecular conformation,virtual drug screening and computer-aided molecular design in the college bioinformatics and chemoinformatics teaching. Due to the friendly graphical interface, Schr?dinger can give students the intuitive experience and enrich the college course. In addition, Schr?dinger has a good application value in the drug design field. It can reduce the cost of drug screening and improve the efficiency of drug discovery.