COMPUTER SIMULATION THEORY OF GLOBULAR PROTEIN DYNAMICS

计算生物学最重要的未解决问题之一是无法从氨基酸序列预测蛋白质的三维结构。实际上，解决蛋白质折叠问题需要同时解决两个相互关联的问题。从无数错误折叠的构象中识别原生状态的潜力部分地克服了这两个问题。一种二级和三级约束信息的手段，使分子流向天然区域。然而，这种方法通常会产生两到三个低能拓扑。因此，我们建议开发改进的协议来预测二级结构和三级约束从多个序列信息。此外，由于原生状态拓扑的生成和分割也至关重要地依赖于对潜力的非约束、经验贡献，因此这些术语也必须得到改进。特别是，侧链埋藏将被更充分地描述，局部序列比对将被用来开发更敏感的对电位。此外，一旦低能拓扑被生成，自洽的三级约束将被导出，从而产生较少扭曲的原生构象。这将通过开发计算上更有效的还原蛋白采样技术以及开发计算上更有效的还原蛋白模型来提高对原生样物的能量选择性。为了确定该方法在三级结构预测中的有效性范围，将对大量已知和未知结构的序列进行应用。通过参与盲预测、竞赛（包括CASP3）、对其他蛋白质进行盲预测，以及通过互联网将所有软件传播给其他研究人员，将对该算法进行重要的独立测试。

One of the most important unsolved problems of computational biology is the inability to predict the three-dimensional structure of a protein from its amino acid sequence. In practice, the solution to the protein folding problem demands that two interrelated problems be simultaneously addressed. Potentials that recognize the native state from the myriad of misfolded conformations partly surmounting both problems. A means of secondary and tertiary restraint information to funnel the molecule towards native-like regions. However, such approaches typically generate two to three low energy topologies. Thus, we propose to develop improved protocols to predict secondary structure and tertiary restraints from multiple sequence information. Furthermore, since native state topology generation and section is also crucially dependent on the non-restraint, empirical contributions to the potential, these terms must also be improved. In particular, side chain burial will be more adequately described and local sequence alignments will be employed to develop much more sensitive pair potentials. Furthermore, once low energy topologies are generated, self-consistent tertiary restraints will be derived so that less distorted native-like conformations will be generated. This should enhance the energetic selectivity for native-like as well as by developing computationally more efficient reduced protein sampling techniques as well as by developing computationally more efficient reduced protein models. To establish the range of validity of this approach to tertiary structure prediction, application will be made to large number of sequences of known as well as unknown structure. Significant, independent testing of this algorithm will be done by participating in blind prediction, contests, including CASP3, by making blind predictions of other proteins, and by disseminating all software to other investigators over the Internet.