Dynamic design: manipulation of millisecond timescale motions on the energy landscape of Cyclophilin A

• Published in: bioRxiv
• Main Authors: Juarez-Jimenez, Jordi, Gupta, Arun A, Karunanithy, Gogulan, Mey, Antonia, Georgiou, Charis, Ioannidis, Charalampos, De Simone, Alessio, Barlow, Paul N, Hulme, Alison N, Walkinshaw, Malcolm D, Baldwin, Andrew J, Julien, Michel
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 17.09.2019; Cold Spring Harbor Laboratory
• Edition: 1.2
• Subjects: Biophysics; Drug development; NMR; Nuclear magnetic resonance; Protein engineering; Proteins
• DOI: 10.1101/490987
• ISSN: 2692-8205

Proteins need to interconvert between many conformations in order to function, many of which are formed transiently, and sparsely populated. Particularly when the lifetimes of these states approach the millisecond timescale, identifying the relevant structures and the mechanism by which they inter-convert remains a tremendous challenge. Here we introduce a novel combination of accelerated MD (aMD) simulations and Markov State modelling (MSM) to explore these excited conformational states. Applying this to the highly dynamic protein CypA, a protein involved in immune response and associated with HIV infection, we identify five principally populated conformational states and the atomistic mechanism by which they interconvert. A rational design strategy predicted that the mutant D66A should stabilise the minor conformations and substantially alter the dynamics whereas the similar mutant H70A should leave the landscape broadly unchanged. These predictions are confirmed using CPMG and R1ρ solution state NMR measurements. By accurately and reliably exploring functionally relevant, but sparsely populated conformations with milli-second lifetimes in silico, our aMD/MSM method has tremendous promise for the design of dynamic protein free energy landscapes for both protein engineering and drug discovery. Footnotes * Substantial edits to the main text to clarify novel aspects of the work. Expanded technical details on the procedures used to validate the models against experimental observables.