Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering College Chongqing University, Chongqing, China.
PLoS One. 2013 Jul 23;8(7):e67844. doi: 10.1371/journal.pone.0067844. Print 2013.
Bioactive peptides and peptidomimetics play a pivotal role in the regulation of many biological processes such as cellular apoptosis, host defense, and biomineralization. In this work, we develop a novel structural matrix, Index of Natural and Non-natural Amino Acids (NNAAIndex), to systematically characterize a total of 155 physiochemical properties of 22 natural and 593 non-natural amino acids, followed by clustering the structural matrix into 6 representative property patterns including geometric characteristics, H-bond, connectivity, accessible surface area, integy moments index, and volume and shape. As a proof-of-principle, the NNAAIndex, combined with partial least squares regression or linear discriminant analysis, is used to develop different QSAR models for the design of new peptidomimetics using three different peptide datasets, i.e., 48 bitter-tasting dipeptides, 58 angiotensin-converting enzyme inhibitors, and 20 inorganic-binding peptides. A comparative analysis with other QSAR techniques demonstrates that the NNAAIndex method offers a stable and predictive modeling technique for in silico large-scale design of natural and non-natural peptides with desirable bioactivities for a wide range of applications.
生物活性肽和肽模拟物在调节许多生物过程中起着关键作用，如细胞凋亡、宿主防御和生物矿化。在这项工作中，我们开发了一种新的结构矩阵，即天然和非天然氨基酸指数（NNAAIndex），系统地表征了总共 22 种天然氨基酸和 593 种非天然氨基酸的 155 种物理化学性质，然后将结构矩阵聚类为 6 种具有代表性的性质模式，包括几何特征、氢键、连通性、可及表面积、积分矩指数以及体积和形状。作为原理验证，NNAAIndex 结合偏最小二乘回归或线性判别分析，用于使用三个不同的肽数据集设计新的肽模拟物，即 48 种苦味二肽、58 种血管紧张素转化酶抑制剂和 20 种无机结合肽，开发不同的 QSAR 模型。与其他 QSAR 技术的比较分析表明，NNAAIndex 方法为在计算机上大规模设计具有广泛应用前景的天然和非天然肽的理想生物活性提供了一种稳定且可预测的建模技术。
