首页> 外文期刊>Journal of Biosciences >Use of secondary structural information and Cα-Cα distance restraints to model protein structures with MODELLER
【24h】

Use of secondary structural information and Cα-Cα distance restraints to model protein structures with MODELLER

机译:利用二级结构信息和Cα-Cα距离约束来利用MODELLER对蛋白质结构进行建模

获取原文
获取原文并翻译 | 示例
       

摘要

Protein secondary structure predictions and amino acid long range contact map predictions from primary sequence of proteins have been explored to aid in modelling protein tertiary structures. In order to evaluate the usefulness of secondary structure and 3D-residue contact prediction methods to model protein structures we have used the known Q3 (alpha-helix, beta-strands and irregular turns/loops) secondary structure information, along with residue-residue contact information as restraints for MODELLER. We present here results of our modelling studies on 30 best resolved single domain protein structures of varied lengths. The results shows that it is very difficult to obtain useful models even with 100% accurate secondary structure predictions and accurate residue contact predictions for up to 30% of residues in a sequence. The best models that we obtained for proteins of lengths 37, 70, 118, 136 and 193 amino acid residues are of RMSDs 4.17, 5.27, 9.12, 7.89 and 9.69, respectively. The results show that one can obtain better models for the proteins which have high percent of alpha-helix content. This analysis further shows that MODELLER restrain optimization program can be useful only if we have truly homologous structure(s) as a template where it derives numerous restraints, almost identical to the templates used. This analysis also clearly indicates that even if we satisfy several true residue-residue contact distances, up to 30% of their sequence length with fully known secondary structural information, we end up predicting model structures much distant from their corresponding native structures.
机译:已经探索了蛋白质一级结构的蛋白质二级结构预测和氨基酸长距离接触图预测,以帮助建模蛋白质三级结构。为了评估二级结构和3D残基接触预测方法对蛋白质结构建模的有用性,我们使用了已知的Q3(α-螺旋,β链和不规则匝/环)二级结构信息以及残基-残基接触信息作为对MODELLER的限制。我们在这里介绍我们对30种不同长度的最佳解析单域蛋白质结构进行建模研究的结果。结果表明,即使对序列中最多30%的残基具有100%准确的二级结构预测和准确的残基接触预测,也很难获得有用的模型。我们针对长度为37、70、118、136和193个氨基酸残基的蛋白质获得的最佳模型分别是RMSD 4.17、5.27、9.12、7.89和9.69。结果表明,对于具有高百分比的α-螺旋含量的蛋白质,可以获得更好的模型。该分析进一步表明,仅当我们具有真正同源的结构作为模板时,MODELLER约束优化程序才有用。在该结构中,它可以导出大量约束,几乎与所使用的模板相同。该分析还清楚地表明,即使我们满足几个真正的残基与残基的接触距离,并且具有众所周知的二级结构信息,其最长可达序列长度的30%,我们最终还是可以预测与其相应的天然结构相距甚远的模型结构。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号