Discrete molecular dynamics can predict helical prestructured motifs in disordered proteins.
Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating α-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts α-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect α-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available.
MTA-SE Molecular Biophysics Research Group, Hungarian Academy of Sciences, Budapest, Hungary; Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary.
Dániel
D
Szöllősi
Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary.
Tamás
T
Horváth
Department of Bioinformatics, University of Science and Technology, Yuseong-gu, Daejeon, Korea; Biomedical Translational Research Center, Division of Convergent Biomedical Research, Korea Research Institute of Bioscience and Biotechnology, Yuseong-gu, Daejeon, Korea.
Kyou-Hoon
KH
Han
Department of Biochemistry and Biophysics, UNC at Chapel Hill, Chapel Hill, North Carolina, United States of America.
Nikolay V
NV
Dokholyan
Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary; VIB Department of Structural Biology, Vrije Universiteit Brussel, Brussels, Belgium.
Péter
P
Tompa
Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary.
Lajos
L
Kalmár
MTA-SE Molecular Biophysics Research Group, Hungarian Academy of Sciences, Budapest, Hungary; Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary; Institute of Molecular Pharmacology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary.
Tamás
T
Hegedűs
D005998:Glycine / Q000737:chemistry; D006801:Humans; D064267:Intrinsically Disordered Proteins / Q000737:chemistry*; D008565:Membrane Proteins / Q000737:chemistry; D056004:Molecular Dynamics Simulation; D019906:Nuclear Magnetic Resonance, Biomolecular; D017433:Protein Structure, Secondary; D013816:Thermodynamics
D064267:Intrinsically Disordered Proteins; D008565:Membrane Proteins; D005998:Glycine