Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure

Walker, Christopher C.; Meek, Garrett A.; Fobe, Theodore L.; Shirts, Michael R.

doi:10.1021/acs.jctc.1c00528

Title: Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure

Journal Article · Wed Sep 08 00:00:00 EDT 2021 · Journal of Chemical Theory and Computation

DOI:https://doi.org/10.1021/acs.jctc.1c00528· OSTI ID:1899344

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Univ. of Colorado, Boulder, CO (United States)

Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1–1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Furthermore, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.

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Research Organization:: Univ. of Colorado, Boulder, CO (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: SC0018651

OSTI ID:: 1899344

Alternate ID(s):: OSTI ID: 1839292

Journal Information:: Journal of Chemical Theory and Computation, Vol. 17, Issue 10; Related Information: https://github.com/shirtsgroup/cg_openmm; ISSN 1549-9618

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

References (63)

Therapeutic Potential of Foldamers: From Chemical Biology Tools To Drug Candidates? Gopalakrishnan, Ranganath; Frolov, Andrey I.; Knerr, Laurent Journal of Medicinal Chemistry, Vol. 59, Issue 21 https://doi.org/10.1021/acs.jmedchem.6b00376	journal	July 2016
De novo design and in vivo activity of conformationally restrained antimicrobial arylamide foldamers Choi, Sungwook; Isaacs, Andre; Clements, Dylan Proceedings of the National Academy of Sciences, Vol. 106, Issue 17 https://doi.org/10.1073/pnas.0811818106	journal	April 2009
De Novo Design of Antimicrobial Polymers, Foldamers, and Small Molecules: From Discovery to Practical Applications Tew, Gregory N.; Scott, Richard W.; Klein, Michael L. Accounts of Chemical Research, Vol. 43, Issue 1 https://doi.org/10.1021/ar900036b	journal	January 2010
A Rationally Designed Aldolase Foldamer Müller, Manuel M.; Windsor, Matthew A.; Pomerantz, William C. Angewandte Chemie International Edition, Vol. 48, Issue 5 https://doi.org/10.1002/anie.200804996	journal	January 2009
Folded biomimetic oligomers for enantioselective catalysis Maayan, G.; Ward, M. D.; Kirshenbaum, K. Proceedings of the National Academy of Sciences, Vol. 106, Issue 33 https://doi.org/10.1073/pnas.0903187106	journal	August 2009
Foldamer-Based Molecular Recognition Prince, Ryan B.; Barnes, Stephanie A.; Moore, Jeffrey S. Journal of the American Chemical Society, Vol. 122, Issue 12 https://doi.org/10.1021/ja993830p	journal	March 2000
Biomimetic Nanostructures: Creating a High-Affinity Zinc-Binding Site in a Folded Nonbiological Polymer Lee, Byoung-Chul; Chu, Tammy K.; Dill, Ken A. Journal of the American Chemical Society, Vol. 130, Issue 27 https://doi.org/10.1021/ja802125x	journal	July 2008
Free-floating ultrathin two-dimensional crystals from sequence-specific peptoid polymers Nam, Ki Tae; Shelby, Sarah A.; Choi, Philip H. Nature Materials, Vol. 9, Issue 5 https://doi.org/10.1038/nmat2742	journal	April 2010
Foldamers: A Manifesto Gellman, Samuel H. Accounts of Chemical Research, Vol. 31, Issue 4 https://doi.org/10.1021/ar960298r	journal	April 1998
A Field Guide to Foldamers Hill, David J.; Mio, Matthew J.; Prince, Ryan B. Chemical Reviews, Vol. 101, Issue 12 https://doi.org/10.1021/cr990120t	journal	December 2001
Aromatic Oligoamide Foldamers Huc, Ivan European Journal of Organic Chemistry, Vol. 2004, Issue 1 https://doi.org/10.1002/ejoc.200300495	journal	January 2004
Beyond de novo protein design — de novo design of non-natural folded oligomers Cheng, Richard P. Current Opinion in Structural Biology, Vol. 14, Issue 4 https://doi.org/10.1016/j.sbi.2004.07.001	journal	August 2004
Foldamers as versatile frameworks for the design and evolution of function Goodman, Catherine M.; Choi, Sungwook; Shandler, Scott Nature Chemical Biology, Vol. 3, Issue 5 https://doi.org/10.1038/nchembio876	journal	April 2007
Foldamers with Heterogeneous Backbones Horne, W. Seth; Gellman, Samuel H. Accounts of Chemical Research, Vol. 41, Issue 10 https://doi.org/10.1021/ar800009n	journal	October 2008
Recent advances in the development of aryl-based foldamers Saraogi, Ishu; Hamilton, Andrew D. Chemical Society Reviews, Vol. 38, Issue 6 https://doi.org/10.1039/b819597h	journal	January 2009
α/β-Peptide foldamers: state of the art Pilsl, Ludwig K. A.; Reiser, Oliver Amino Acids, Vol. 41, Issue 3 https://doi.org/10.1007/s00726-011-0894-2	journal	April 2011
Synthetic foldamers Guichard, Gilles; Huc, Ivan Chemical Communications, Vol. 47, Issue 21 https://doi.org/10.1039/c1cc11137j	journal	January 2011
Aromatic Amide Foldamers: Structures, Properties, and Functions Zhang, Dan-Wei; Zhao, Xin; Hou, Jun-Li Chemical Reviews, Vol. 112, Issue 10 https://doi.org/10.1021/cr300116k	journal	June 2012
Peptidic foldamers: ramping up diversity Martinek, Tamás A.; Fülöp, Ferenc Chem. Soc. Rev., Vol. 41, Issue 2 https://doi.org/10.1039/c1cs15097a	journal	January 2012
Enhanced sampling techniques in molecular dynamics simulations of biological systems Bernardi, Rafael C.; Melo, Marcelo C. R.; Schulten, Klaus Biochimica et Biophysica Acta (BBA) - General Subjects, Vol. 1850, Issue 5 https://doi.org/10.1016/j.bbagen.2014.10.019	journal	May 2015
Advances in enhanced sampling molecular dynamics simulations for biomolecules Wang, An-hui; Zhang, Zhi-chao; Li, Guo-hui Chinese Journal of Chemical Physics, Vol. 32, Issue 3 https://doi.org/10.1063/1674-0068/cjcp1905091	journal	June 2019
Statistically optimal analysis of samples from multiple equilibrium states Shirts, Michael R.; Chodera, John D. The Journal of Chemical Physics, Vol. 129, Issue 12 https://doi.org/10.1063/1.2978177	journal	September 2008
Rapid Computation of Thermodynamic Properties over Multidimensional Nonbonded Parameter Spaces Using Adaptive Multistate Reweighting Naden, Levi N.; Shirts, Michael R. Journal of Chemical Theory and Computation, Vol. 12, Issue 4 https://doi.org/10.1021/acs.jctc.5b00869	journal	February 2016
Protein storytelling through physics Brini, Emiliano; Simmerling, Carlos; Dill, Ken Science, Vol. 370, Issue 6520 https://doi.org/10.1126/science.aaz3041	journal	November 2020
The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design Alford, Rebecca F.; Leaver-Fay, Andrew; Jeliazkov, Jeliazko R. Journal of Chemical Theory and Computation, Vol. 13, Issue 6 https://doi.org/10.1021/acs.jctc.7b00125	journal	May 2017
Deep learning methods in protein structure prediction Torrisi, Mirko; Pollastri, Gianluca; Le, Quan Computational and Structural Biotechnology Journal, Vol. 18 https://doi.org/10.1016/j.csbj.2019.12.011	journal	January 2020
New developments in force fields for biomolecular simulations Nerenberg, Paul S.; Head-Gordon, Teresa Current Opinion in Structural Biology, Vol. 49 https://doi.org/10.1016/j.sbi.2018.02.002	journal	April 2018
Minimalist models for proteins: a comparative analysis Tozzini, Valentina Quarterly Reviews of Biophysics, Vol. 43, Issue 3 https://doi.org/10.1017/s0033583510000132	journal	August 2010
Coarse-Grained Protein Models and Their Applications Kmiecik, Sebastian; Gront, Dominik; Kolinski, Michal Chemical Reviews, Vol. 116, Issue 14 https://doi.org/10.1021/acs.chemrev.6b00163	journal	June 2016
Insights from Coarse-Grained Gō Models for Protein Folding and Dynamics Hills, Ronald; Brooks, Charles International Journal of Molecular Sciences, Vol. 10, Issue 3 https://doi.org/10.3390/ijms10030889	journal	March 2009
Deriving effective mesoscale potentials from atomistic simulations: Mesoscale Potentials from Atomistic Simulations Reith, Dirk; Pütz, Mathias; Müller-Plathe, Florian Journal of Computational Chemistry, Vol. 24, Issue 13 https://doi.org/10.1002/jcc.10307	journal	August 2003
A Multiscale Coarse-Graining Method for Biomolecular Systems Izvekov, Sergei; Voth, Gregory A. The Journal of Physical Chemistry B, Vol. 109, Issue 7 https://doi.org/10.1021/jp044629q	journal	February 2005
Ensemble learning of coarse-grained molecular dynamics force fields with a kernel approach Wang, Jiang; Chmiela, Stefan; Müller, Klaus-Robert The Journal of Chemical Physics, Vol. 152, Issue 19 https://doi.org/10.1063/5.0007276	journal	May 2020
Computer simulation of protein folding Levitt, Michael; Warshel, Arieh Nature, Vol. 253, Issue 5494 https://doi.org/10.1038/253694a0	journal	February 1975
Principles of protein folding - A perspective from simple exact models Dill, Ken A.; Bromberg, Sarina; Yue, Kaizhi Protein Science, Vol. 4, Issue 4 https://doi.org/10.1002/pro.5560040401	journal	April 1995
Protein Folding Thermodynamics and Dynamics: Where Physics, Chemistry, and Biology Meet Shakhnovich, Eugene Chemical Reviews, Vol. 106, Issue 5 https://doi.org/10.1021/cr040425u	journal	May 2006
Mapping All-Atom Models onto One-Bead Coarse-Grained Models: General Properties and Applications to a Minimal Polypeptide Model Tozzini, Valentina; Rocchia, Walter; McCammon, J. Andrew Journal of Chemical Theory and Computation, Vol. 2, Issue 3 https://doi.org/10.1021/ct050294k	journal	April 2006
Coarse-Grained Peptide Modeling Using a Systematic Multiscale Approach Zhou, Jian; Thorpe, Ian F.; Izvekov, Sergey Biophysical Journal, Vol. 92, Issue 12 https://doi.org/10.1529/biophysj.106.094425	journal	June 2007
OpenMM 7: Rapid development of high performance algorithms for molecular dynamics Eastman, Peter; Swails, Jason; Chodera, John D. PLOS Computational Biology, Vol. 13, Issue 7 https://doi.org/10.1371/journal.pcbi.1005659	journal	July 2017
Replica-exchange molecular dynamics method for protein folding Sugita, Yuji; Okamoto, Yuko Chemical Physics Letters, Vol. 314, Issue 1-2 https://doi.org/10.1016/s0009-2614(99)01123-9	journal	November 1999
Convergence and sampling efficiency in replica exchange simulations of peptide folding in explicit solvent Periole, Xavier; Mark, Alan E. The Journal of Chemical Physics, Vol. 126, Issue 1 https://doi.org/10.1063/1.2404954	journal	January 2007
Foldamer Architectures of Triazine-Based Sequence-Defined Polymers Investigated with Molecular Dynamics Simulations and Enhanced Sampling Methods Ahn, Surl-Hee; Grate, Jay W. The Journal of Physical Chemistry B, Vol. 123, Issue 44 https://doi.org/10.1021/acs.jpcb.9b06067	journal	October 2019
Ensuring Mixing Efficiency of Replica-Exchange Molecular Dynamics Simulations Abraham, Mark J.; Gready, Jill E. Journal of Chemical Theory and Computation, Vol. 4, Issue 7 https://doi.org/10.1021/ct800016r	journal	May 2008
Exchange frequency in replica exchange molecular dynamics Sindhikara, Daniel; Meng, Yilin; Roitberg, Adrian E. The Journal of Chemical Physics, Vol. 128, Issue 2 https://doi.org/10.1063/1.2816560	journal	January 2008
On the acceptance probability of replica-exchange Monte Carlo trials Kofke, David A. The Journal of Chemical Physics, Vol. 117, Issue 15 https://doi.org/10.1063/1.1507776	journal	October 2002
Optimal allocation of replicas in parallel tempering simulations Rathore, Nitin; Chopra, Manan; de Pablo, Juan J. The Journal of Chemical Physics, Vol. 122, Issue 2 https://doi.org/10.1063/1.1831273	journal	January 2005
A constant entropy increase model for the selection of parallel tempering ensembles Sabo, Dubravko; Meuwly, Markus; Freeman, David L. The Journal of Chemical Physics, Vol. 128, Issue 17 https://doi.org/10.1063/1.2907846	journal	May 2008
Optimized parallel tempering simulations of proteins Trebst, Simon; Troyer, Matthias; Hansmann, Ulrich H. E. The Journal of Chemical Physics, Vol. 124, Issue 17 https://doi.org/10.1063/1.2186639	journal	May 2006
On the Efficiency of Exchange in Parallel Tempering Monte Carlo Simulations Predescu, Cristian; Predescu, Mihaela; Ciobanu, Cristian V. The Journal of Physical Chemistry B, Vol. 109, Issue 9 https://doi.org/10.1021/jp045073+	journal	February 2005
Replica exchange and expanded ensemble simulations as Gibbs sampling: Simple improvements for enhanced mixing Chodera, John D.; Shirts, Michael R. The Journal of Chemical Physics, Vol. 135, Issue 19 https://doi.org/10.1063/1.3660669	journal	November 2011
Accelerating molecular dynamic simulation on graphics processing units Friedrichs, Mark S.; Eastman, Peter; Vaidyanathan, Vishal Journal of Computational Chemistry, Vol. 30, Issue 6 https://doi.org/10.1002/jcc.21209	journal	April 2009
Efficient nonbonded interactions for molecular dynamics on a graphics processing unit Eastman, Peter; Pande, Vijay S. Journal of Computational Chemistry https://doi.org/10.1002/jcc.21413	journal	January 2009
SciPy 1.0: fundamental algorithms for scientific computing in Python Virtanen, Pauli; Gommers, Ralf; Oliphant, Travis E. Nature Methods https://doi.org/10.1038/s41592-019-0686-2	journal	February 2020
Simple Quantitative Tests to Validate Sampling from Thermodynamic Ensembles Shirts, Michael R. Journal of Chemical Theory and Computation, Vol. 9, Issue 2 https://doi.org/10.1021/ct300688p	journal	December 2012
Testing for physical validity in molecular simulations Merz, Pascal T.; Shirts, Michael R. PLOS ONE, Vol. 13, Issue 9 https://doi.org/10.1371/journal.pone.0202764	journal	September 2018
An Introduction to the Bootstrap Efron, Bradley; Tibshirani, Robert J. Chapman and Hall/CRC https://doi.org/10.1007/978-1-4899-4541-9	book	January 1993
Clustering algorithms to analyze molecular dynamics simulation trajectories for complex chemical and biological systems Peng, Jun-hui; Wang, Wei; Yu, Ye-qing Chinese Journal of Chemical Physics, Vol. 31, Issue 4 https://doi.org/10.1063/1674-0068/31/cjcp1806147	journal	August 2018
MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories McGibbon, Robert T.; Beauchamp, Kyle A.; Harrigan, Matthew P. Biophysical Journal, Vol. 109, Issue 8 https://doi.org/10.1016/j.bpj.2015.08.015	journal	October 2015
DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN Schubert, Erich; Sander, Jörg; Ester, Martin ACM Transactions on Database Systems, Vol. 42, Issue 3 https://doi.org/10.1145/3068335	journal	August 2017
Identifying ligand binding sites and poses using GPU-accelerated Hamiltonian replica exchange molecular dynamics Wang, Kai; Chodera, John D.; Yang, Yanzhi Journal of Computer-Aided Molecular Design, Vol. 27, Issue 12 https://doi.org/10.1007/s10822-013-9689-8	journal	December 2013
Simple data and workflow management with the signac framework Adorf, Carl S.; Dodd, Paul M.; Ramasubramani, Vyas Computational Materials Science, Vol. 146 https://doi.org/10.1016/j.commatsci.2018.01.035	journal	April 2018
Going Backward: A Flexible Geometric Approach to Reverse Transformation from Coarse Grained to Atomistic Models Wassenaar, Tsjerk A.; Pluhackova, Kristyna; Böckmann, Rainer A. Journal of Chemical Theory and Computation, Vol. 10, Issue 2 https://doi.org/10.1021/ct400617g	journal	January 2014
Backmapping from Multiresolution Coarse-Grained Models to Atomic Structures of Large Biomolecules by Restrained Molecular Dynamics Simulations Using Bayesian Inference Peng, Junhui; Yuan, Chuang; Ma, Rongsheng Journal of Chemical Theory and Computation, Vol. 15, Issue 5 https://doi.org/10.1021/acs.jctc.9b00062	journal	March 2019

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Title: Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure

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