Reva B A, Rykunov D S, Finkelstein A V, Skolnick J
Department of Molecular Biology, Scripps Research Institute, La Jolla, California 92037, USA.
J Comput Biol. 1998 Fall;5(3):531-8. doi: 10.1089/cmb.1998.5.531.
Lattice modeling of proteins is commonly used to study the protein folding problem. The reduced number of possible conformations of lattice models enormously facilitates exploration of the conformational space. In this work, we suggest a method to search for the optimal lattice models that reproduced the off-lattice structures with minimal errors in geometry and energetics. The method is based on the self-consistent field optimization of a combined pseudoenergy function that includes two force fields: an "interaction field," that drives the residues to optimize the chain energy, and a "geometrical field," that attracts the residues towards their native positions. By varying the contributions of these force fields in the combined pseudoenergy, one can also test the accuracy of potentials: the better the potentials, i.e., the more accurate the "interaction field," and the smaller the contribution of the "geometrical field" required for building accurate lattice models.
蛋白质的晶格模型常用于研究蛋白质折叠问题。晶格模型可能构象数量的减少极大地促进了对构象空间的探索。在这项工作中，我们提出了一种方法来寻找最优的晶格模型，该模型能以最小的几何和能量误差重现非晶格结构。该方法基于一个组合伪能量函数的自洽场优化，该函数包括两个力场：一个“相互作用场”，它驱动残基优化链能量；另一个“几何场”，它将残基吸引到其天然位置。通过改变这些力场在组合伪能量中的贡献，还可以测试势的准确性：势越好，即“相互作用场”越准确，构建准确晶格模型所需的“几何场”贡献就越小。
