Adhikari Badri, Bhattacharya Debswapna, Cao Renzhi, Cheng Jianlin
Department of Computer Science, University of Missouri, Columbia, Missouri, 65211.
Proteins. 2015 Aug;83(8):1436-49. doi: 10.1002/prot.24829. Epub 2015 Jun 6.
Predicted protein residue-residue contacts can be used to build three-dimensional models and consequently to predict protein folds from scratch. A considerable amount of effort is currently being spent to improve contact prediction accuracy, whereas few methods are available to construct protein tertiary structures from predicted contacts. Here, we present an ab initio protein folding method to build three-dimensional models using predicted contacts and secondary structures. Our method first translates contacts and secondary structures into distance, dihedral angle, and hydrogen bond restraints according to a set of new conversion rules, and then provides these restraints as input for a distance geometry algorithm to build tertiary structure models. The initially reconstructed models are used to regenerate a set of physically realistic contact restraints and detect secondary structure patterns, which are then used to reconstruct final structural models. This unique two-stage modeling approach of integrating contacts and secondary structures improves the quality and accuracy of structural models and in particular generates better β-sheets than other algorithms. We validate our method on two standard benchmark datasets using true contacts and secondary structures. Our method improves TM-score of reconstructed protein models by 45% and 42% over the existing method on the two datasets, respectively. On the dataset for benchmarking reconstructions methods with predicted contacts and secondary structures, the average TM-score of best models reconstructed by our method is 0.59, 5.5% higher than the existing method. The CONFOLD web server is available at http://protein.rnet.missouri.edu/confold/.
预测的蛋白质残基-残基接触可用于构建三维模型,从而从头预测蛋白质折叠。目前人们花费了大量精力来提高接触预测的准确性,然而从预测接触构建蛋白质三级结构的方法却很少。在此,我们提出一种从头开始的蛋白质折叠方法,利用预测的接触和二级结构构建三维模型。我们的方法首先根据一组新的转换规则将接触和二级结构转化为距离、二面角和氢键约束,然后将这些约束作为输入提供给距离几何算法以构建三级结构模型。最初重建的模型用于重新生成一组物理上合理的接触约束并检测二级结构模式,然后用于重建最终的结构模型。这种整合接触和二级结构的独特两阶段建模方法提高了结构模型的质量和准确性,特别是生成了比其他算法更好的β折叠。我们使用真实的接触和二级结构在两个标准基准数据集上验证了我们的方法。在这两个数据集上,我们的方法分别比现有方法将重建蛋白质模型的TM分数提高了45%和42%。在使用预测的接触和二级结构对重建方法进行基准测试的数据集上,我们的方法重建的最佳模型的平均TM分数为0.59,比现有方法高5.5%。CONFOLD网络服务器可在http://protein.rnet.missouri.edu/confold/获取。