Computational linguistics: A new tool for exploring biopolymer structures and statistical mechanics

被引:12
作者
Dill, Ken A.
Lucas, Adam
Hockenmaier, Julia
Huang, Liang
Chiang, David
Joshi, Aravind K.
机构
[1] Univ Calif San Francisco, Dept Pharmaceut Chem, San Francisco, CA 94143 USA
[2] St Marys Coll, Dept Math & Comp Sci, Moraga, CA 94575 USA
[3] Univ Penn, Inst Res Cognit Sci, Philadelphia, PA 19104 USA
[4] Univ Penn, Dept Comp & Informat Sci, Philadelphia, PA 19104 USA
[5] Univ So Calif, Inst Informat Sci, Marina Del Rey, CA 90292 USA
基金
美国国家科学基金会;
关键词
biopolymers; proteins; lattice models;
D O I
10.1016/j.polymer.2007.05.018
中图分类号
O63 [高分子化学(高聚物)];
学科分类号
070305 ; 080501 ; 081704 ;
摘要
Unlike homopolymers, biopolymers are composed of specific sequences of different types of monomers. In proteins and RNA molecules, one-dimensional sequence information encodes a three-dimensional fold, leading to a corresponding molecular function. Such folded structures are not treated adequately through traditional methods of polymer statistical mechanics. A promising new way to solve problems of the statistical mechanics of biomolecules comes from computational linguistics, the field that uses computers to parse and understand the sentences in natural languages. Here, we give two examples. First, we show that a dynamic programming rnethod of computational linguistics gives a fast way to search protein models for native structures. Interestingly, the computational search process closely resembles the physical folding process. Second, linguistics-based dynamic programming methods are also useful for computing partition functions and densities of states for some foldable biopolymers - helix-bundle proteins are reviewed here. In these ways, computational linguistics is helping to solve problems of the searching and counting of biopolymer conformations. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4289 / 4300
页数:12
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