Aszódi A, Munro R E, Taylor W R
Division of Mathematical Biology, National Institute for Medical Research, London, UK.
Fold Des. 1997;2(3):S3-6. doi: 10.1016/s1359-0278(97)00055-2.
A distance geometry based protein modelling algorithm is presented which relies on the projection of simple model chain coordinates into Euclidean spaces with gradually decreasing dimensionality. Fast embedding was achieved by performing separate distance matrix projections on subsets of the model points. Structural equivalences between the unknown target and related proteins with known structures were deduced either from a mixed sequence/structure multiple alignment or from the output of various fold recognition (threading) approaches. These equivalences were mapped onto the model as structure-specific conserved C alpha atom distances and secondary structure assignments. Additional nonspecific distance restraints derived from general stereochemical properties of folded protein chains were used to guide the modelling process. The method quickly constructed a large number of low-resolution models which could then serve as starting conformations for full-atom refinement. Structure predictions for some targets in the 'Asilomar Challenge' (CASP2) are presented to illustrate potential applications of the approach.
提出了一种基于距离几何的蛋白质建模算法，该算法依赖于将简单模型链坐标投影到维数逐渐降低的欧几里得空间中。通过对模型点的子集进行单独的距离矩阵投影实现快速嵌入。未知目标与具有已知结构的相关蛋白质之间的结构等效性，可从混合序列/结构多重比对或各种折叠识别（穿线）方法的输出中推导得出。这些等效性作为特定于结构的保守Cα原子距离和二级结构分配映射到模型上。从折叠蛋白质链的一般立体化学性质导出的其他非特异性距离约束用于指导建模过程。该方法快速构建了大量低分辨率模型，这些模型随后可作为全原子精修的起始构象。展示了对“阿西洛马挑战”（CASP2）中一些目标的结构预测，以说明该方法的潜在应用。
