Protein Design Using Continuous Rotamers

Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE. Availability: Software is available under the Lesser GNU Public License v3. Contact the authors for source code.优化氨基酸构象与序列是计算蛋白质设计的核心问题。蛋白质设计算法在优化过程中必须还原蛋白质的真实柔性，否则将无法找到能量最低的最优序列。多数设计算法通过允许侧链在一组离散的低能状态间移动来实现侧链柔性，我们将此类状态称为刚性旋转异构体（rigid rotamer）。本研究表明，允许侧链具备连续柔性（我们称之为连续旋转异构体（continuous rotamer））可大幅提升蛋白质柔性建模效果。我们开展了一项大规模研究，对比了69个蛋白质核心区域重设计任务中，使用刚性旋转异构体模型与连续旋转异构体模型所得到的序列及最优能量构象。研究结果显示，在几乎所有重设计任务中，连续旋转异构体模型得到的序列均与刚性旋转异构体模型的结果不同，且能量更低。此外，连续旋转异构体模型得到的序列与天然序列的相似度更高。进一步研究表明，看似简便的在连续区域内采样更多刚性旋转异构体的方案，无法作为连续旋转异构体模型的实用替代方案：在计算可行的分辨率下，增加刚性旋转异构体的采样量从未优于连续旋转异构体模型，且几乎总会导致更高的能量值。最后，我们提出了一种基于终末消除（dead-end elimination, DEE）算法的新型蛋白质设计算法iMinDEE，该算法可使连续旋转异构体在更大规模的体系中得以应用。iMinDEE可在保证找到最优解的同时，以接近DEE算法的效率对搜索空间进行剪枝。可用性说明：软件遵循GNU宽通用公共许可证v3（Lesser GNU Public License v3）发布，如需获取源代码请联系作者。