CONFORMATIONAL ANALYSIS BY ENERGY EMBEDDING

构象计算的距离几何方法已经非常 成功地生产出满足严格几何条件的构象 限制，但没有办法衡量限制或 包括能量方面考虑。 我正在发展一种距离的延伸 不仅处理几何约束，而且还生成低 能量构象 在众多的应用中， 技术，我对研究蛋白质折叠特别感兴趣， 是分子生物学基础知识的核心。 我 初步结果表明，能量嵌入扩展到 距离几何可以成功地处理几何约束， 总是，并且还产生非常低能量的构象异构体。 随着算法 现在站起来，计算是相当耗时的，给定的蛋白质 在给定的势函数下， 构象 部分过程可以通过替换更快的 计算技术 意识到能量嵌入不是 为了保证找到全局能量最小值，必须对算法进行修改， 为了物理上的真实性， 而不是一个人 势函数的选择也必须是 检查得更彻底。 因为最终的结构非常依赖于 在使用的潜力上，某些功能可能比其他功能更好地引导 使分子达到令人满意的最终结果。 用于预测蛋白质 三级构象，一个特别好的“潜力”或一组 约束可以从许多经验折叠规则中推导出来， 现在已知。

The distance geometry approach to conformational calculations has been very successful in producing conformations satisfying strictly geometric constraints, but there has been no way to weight the constraints or to include energetic considerations. I am developing an extension of distance geometry that not only handles geometric constraints, but also produces low energy conformations. Among the numerous applications for such a technique, I am particularly interested in studying protein folding, which is of course central to the basic understanding of molecular biology. My preliminary results indicate that the energy embedding extension to distance geometry deals with geometric constraints as successfully as always, and also produces conformers of very low energy. As the algorithm now stands, the calculations are quite time consuming, and a given protein under a given potential function will always come to the same final conformaton. Parts of the process can be speeded up by substituting faster computational techniques. Realizing that energy embedding is not guaranteed to find global energy minima, the algorithm must be modified for the sake of physical realism to produce several low-energy structures instead of just one. The choice of potential function must also be examined more thoroughly. Since the final structure depends so critically on the potential used, some functions may be better than others at guiding the molecule to a satisfactory final result. For predicting protein tertiary conformation, a particularly good "potential" or set of constraints can be derived from the many empirical folding rules that are now known.