Stability Prediction for Mutations in the Cytosolic Domains of Cystic Fibrosis Transmembrane Conductance Regulator

Malkeet Singh Bahia, Netaly Khazanov, Qingxian Zhou, Zhengrong Yang, Chi Wang, Jeong S. Hong, Andras Rab, Eric J. Sorscher, Christie G. Brouillette, John F. Hunt, Hanoch Senderowitz

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Cystic Fibrosis (CF) is caused by mutations to the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) chloride channel. CFTR is composed of two membrane spanning domains, two cytosolic nucleotide-binding domains (NBD1 and NBD2) and a largely unstructured R-domain. Multiple CF-causing mutations reside in the NBDs and some are known to compromise the stability of these domains. The ability to predict the effect of mutations on the stability of the cytosolic domains of CFTR and to shed light on the mechanisms by which they exert their effect is therefore important in CF research. With this in mind, we have predicted the effect on domain stability of 59 mutations in NBD1 and NBD2 using 15 different algorithms and evaluated their performances via comparison to experimental data using several metrics including the correct classification rate (CCR), and the squared Pearson correlation (R2) and Spearman's correlation (ρ) calculated between the experimental ΔTm values and the computationally predicted ΔΔG values. Overall, the best results were obtained with FoldX and Rosetta. For NBD1 (35 mutations), FoldX provided R2 and ρ values of 0.64 and-0.71, respectively, with an 86% correct classification rate (CCR). For NBD2 (24 mutations), FoldX R2, ρ, and CCR were 0.51,-0.73, and 75%, respectively. Application of the Rosetta high-resolution protocol (Rosetta_hrp) to NBD1 yielded R2, ρ, and CCR of 0.64,-0.75, and 69%, respectively, and for NBD2 yielded R2, ρ, and CCR of 0.29,-0.27, and 50%, respectively. The corresponding numbers for the Rosetta's low-resolution protocol (Rosetta_lrp) were R2 = 0.47, ρ =-0.69, and CCR = 69% for NBD1 and R2 = 0.27, ρ =-0.24, and CCR = 63% for NBD2. For NBD1, both algorithms suggest that destabilizing mutations suffer from destabilizing vdW clashes, whereas stabilizing mutations benefit from favorable H-bond interactions. Two triple consensus approaches based on FoldX, Rosetta_lpr, and Rosetta_hpr were attempted using either "majority-voting"or "all-voting". The all-voting consensus outperformed the individual predictors, albeit on a smaller data set. In summary, our results suggest that the effect of mutations on the stability of CFTR's NBDs could be largely predicted. Since NBDs are common to all ABC transporters, these results may find use in predicting the effect and mechanism of the action of multiple disease-causing mutations in other proteins.

Original languageEnglish
Pages (from-to)1762-1777
Number of pages16
JournalJournal of Chemical Information and Modeling
Issue number4
StatePublished - 26 Apr 2021

Bibliographical note

Funding Information:
The authors are grateful to the Planning and Budgeting Committee (PBC) of the Council for Higher Education in Israel for providing postdoctoral fellowship to Dr. Malkeet Singh Bahia at Bar-Ilan University, Ramat Gan, Israel. The authors are also thankful to the developers of different tools employed in this work for providing free academic versions as well as to Mendeley’s developers for providing a free installation of the Mendeley reference manager. The authors also thank Prof. Nikolay Dokholyan for providing the academic version of the ERIS program. H.S. acknowledges the support of BSF Grant No. 2013391 and of CFF Grant No. SENDER13XX0. J.F.H. and C.W. acknowledge the long-term grant support from the US Cystic Fibrosis Foundation, HUNT18G0 and HUNT13XX0.

Publisher Copyright:
© 2021 American Chemical Society.


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