Department of Physics, TU Darmstadt, Karolinenpl. 5, 64289 Darmstadt, Germany.
Department of Biology and Department of Computer Science and Department of Physics, TU Darmstadt, Karolinenpl. 5, 64289 Darmstadt, Germany.
Phys Rev E. 2017 Nov;96(5-1):052405. doi: 10.1103/PhysRevE.96.052405. Epub 2017 Nov 9.
The prediction of residue contacts in a protein solely from sequence information is a promising approach to computational structure prediction. Recent developments use statistical or information theoretic methods to extract contact information from a multiple sequence alignment. Despite good results, accuracy is limited due to usage of two-body interactions within a Potts model. In this paper we generalize this approach and propose a Hamiltonian with an additional three-body interaction term. We derive a mean-field approximation for inference of three-body couplings within a Potts model which is fast enough on modern computers. Finally, we show that our model has a higher accuracy in predicting residue contacts in comparison with the plain two-body-interaction model.
仅根据序列信息预测蛋白质中的残基接触是一种很有前途的计算结构预测方法。最近的研究进展使用统计或信息论方法从多重序列比对中提取接触信息。尽管取得了很好的结果，但由于在 Potts 模型中使用了二体相互作用，因此准确性有限。在本文中，我们推广了这种方法，并提出了一个具有附加三体相互作用项的哈密顿量。我们为 Potts 模型中的三体耦合推断推导出一个平均场近似，该近似在现代计算机上足够快。最后，我们表明与单纯的二体相互作用模型相比，我们的模型在预测残基接触方面具有更高的准确性。
