1
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Fossat MJ, Posey AE, Pappu RV. Uncovering the Contributions of Charge Regulation to the Stability of Single Alpha Helices. Chemphyschem 2023; 24:e202200746. [PMID: 36599672 PMCID: PMC10734359 DOI: 10.1002/cphc.202200746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 12/07/2022] [Indexed: 01/06/2023]
Abstract
The single alpha helix (SAH) is a recurring motif in biology. The consensus sequence has a di-block architecture that includes repeats of four consecutive glutamate residues followed by four consecutive lysine residues. Measurements show that the overall helicity of sequences with consensus E4 K4 repeats is insensitive to a wide range of pH values. Here, we use the recently introduced q-canonical ensemble, which allows us to decouple measurements of charge state and conformation, to explain the observed insensitivity of SAH helicity to pH. We couple the outputs from separate measurements of charge and conformation with atomistic simulations to derive residue-specific quantifications of preferences for being in an alpha helix and for the ionizable residues to be charged vs. uncharged. We find a clear preference for accommodating uncharged Glu residues within internal positions of SAH-forming sequences. The stabilities of alpha helical conformations increase with the number of E4 K4 repeats and so do the numbers of accessible charge states that are compatible with forming conformations of high helical content. There is conformational buffering whereby charge state heterogeneity buffers against large-scale conformational changes thus making the overall helicity insensitive to large changes in pH. Further, the results clearly argue against a single, rod-like alpha helical conformation being the only or even dominant conformation in the ensembles of so-called SAH sequences.
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Affiliation(s)
| | | | - Rohit V. Pappu
- Department of Biomedical Engineering and the Center for Biomolecular Condensates, James McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO 63130
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2
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Mu J, Liu H, Zhang J, Luo R, Chen HF. Recent Force Field Strategies for Intrinsically Disordered Proteins. J Chem Inf Model 2021; 61:1037-1047. [PMID: 33591749 PMCID: PMC8256680 DOI: 10.1021/acs.jcim.0c01175] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.
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Affiliation(s)
- Junxi Mu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hao Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jian Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, School of Medicine, Shanghai Jiao Tong University, Shanghai 20025, China
| | - Ray Luo
- Departments of Molecular Biology and Biochemistry, Chemical and Molecular Engineering, Materials Science and Engineering, and Biomedical Engineering, University of California, Irvine, California 92697-3900, United States
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
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3
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Marchand JR, Knehans T, Caflisch A, Vitalis A. An ABSINTH-Based Protocol for Predicting Binding Affinities between Proteins and Small Molecules. J Chem Inf Model 2020; 60:5188-5202. [PMID: 32897071 DOI: 10.1021/acs.jcim.0c00558] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The core task in computational drug discovery is to accurately predict binding free energies in receptor-ligand systems for large libraries of putative binders. Here, the ABSINTH implicit solvent model and force field are extended to describe small, organic molecules and their interactions with proteins. We show that an automatic pipeline based on partitioning arbitrary molecules into substructures corresponding to model compounds with known free energies of solvation can be combined with the CHARMM general force field into a method that is successful at the two important challenges a scoring function faces in virtual screening work flows: it ranks known binders with correlation values rivaling that of comparable state-of-the-art methods and it enriches true binders in a set of decoys. Our protocol introduces innovative modifications to common virtual screening workflows, notably the use of explicit ions as competitors and the integration over multiple protein and ligand species differing in their protonation states. We demonstrate the value of modifications to both the protocol and ABSINTH itself. We conclude by discussing the limitations of high-throughput implicit methods such as the one proposed here.
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Affiliation(s)
- Jean-Rémy Marchand
- Department of Biochemistry, University of Zürich, CH 8057 Zürich, Switzerland
| | - Tim Knehans
- Department of Biochemistry, University of Zürich, CH 8057 Zürich, Switzerland
| | - Amedeo Caflisch
- Department of Biochemistry, University of Zürich, CH 8057 Zürich, Switzerland
| | - Andreas Vitalis
- Department of Biochemistry, University of Zürich, CH 8057 Zürich, Switzerland
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4
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Cohan MC, Ruff KM, Pappu RV. Information theoretic measures for quantifying sequence-ensemble relationships of intrinsically disordered proteins. Protein Eng Des Sel 2020; 32:191-202. [PMID: 31375817 PMCID: PMC7462041 DOI: 10.1093/protein/gzz014] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 06/19/2019] [Indexed: 01/26/2023] Open
Abstract
Intrinsically disordered proteins (IDPs) contribute to a multitude of functions. De novo design of IDPs should open the door to modulating functions and phenotypes controlled by these systems. Recent design efforts have focused on compositional biases and specific sequence patterns as the design features. Analysis of the impact of these designs on sequence-function relationships indicates that individual sequence/compositional parameters are insufficient for describing sequence-function relationships in IDPs. To remedy this problem, we have developed information theoretic measures for sequence–ensemble relationships (SERs) of IDPs. These measures rely on prior availability of statistically robust conformational ensembles derived from all atom simulations. We show that the measures we have developed are useful for comparing sequence-ensemble relationships even when sequence is poorly conserved. Based on our results, we propose that de novo designs of IDPs, guided by knowledge of their SERs, should provide improved insights into their sequence–ensemble–function relationships.
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Affiliation(s)
- Megan C Cohan
- Department of Biomedical Engineering and Center for Science & Engineering of Living Systems (CSELS) Washington University in St. Louis, One Brookings Drive, Campus Box 1097, St. Louis MO, USA
| | - Kiersten M Ruff
- Department of Biomedical Engineering and Center for Science & Engineering of Living Systems (CSELS) Washington University in St. Louis, One Brookings Drive, Campus Box 1097, St. Louis MO, USA
| | - Rohit V Pappu
- Department of Biomedical Engineering and Center for Science & Engineering of Living Systems (CSELS) Washington University in St. Louis, One Brookings Drive, Campus Box 1097, St. Louis MO, USA
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5
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Zhao Y, Cortes-Huerto R, Kremer K, Rudzinski JF. Investigating the Conformational Ensembles of Intrinsically Disordered Proteins with a Simple Physics-Based Model. J Phys Chem B 2020; 124:4097-4113. [PMID: 32345021 PMCID: PMC7246978 DOI: 10.1021/acs.jpcb.0c01949] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
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Intrinsically
disordered proteins (IDPs) play an important role
in an array of biological processes but present a number of fundamental
challenges for computational modeling. Recently, simple polymer models
have regained popularity for interpreting the experimental characterization
of IDPs. Homopolymer theory provides a strong foundation for understanding
generic features of phenomena ranging from single-chain conformational
dynamics to the properties of entangled polymer melts, but is difficult
to extend to the copolymer context. This challenge is magnified for
proteins due to the variety of competing interactions and large deviations
in side-chain properties. In this work, we apply a simple physics-based
coarse-grained model for describing largely disordered conformational
ensembles of peptides, based on the premise that sampling sterically
forbidden conformations can compromise the faithful description of
both static and dynamical properties. The Hamiltonian of the employed
model can be easily adjusted to investigate the impact of distinct
interactions and sequence specificity on the randomness of the resulting
conformational ensemble. In particular, starting with a bead–spring-like
model and then adding more detailed interactions one by one, we construct
a hierarchical set of models and perform a detailed comparison of
their properties. Our analysis clarifies the role of generic attractions,
electrostatics, and side-chain sterics, while providing a foundation
for developing efficient models for IDPs that retain an accurate description
of the hierarchy of conformational dynamics, which is nontrivially
influenced by interactions with surrounding proteins and solvent molecules.
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Affiliation(s)
- Yani Zhao
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany
| | | | - Kurt Kremer
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany
| | - Joseph F Rudzinski
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany
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6
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Choi JM, Pappu RV. Improvements to the ABSINTH Force Field for Proteins Based on Experimentally Derived Amino Acid Specific Backbone Conformational Statistics. J Chem Theory Comput 2019; 15:1367-1382. [PMID: 30633502 PMCID: PMC10749164 DOI: 10.1021/acs.jctc.8b00573] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
We present an improved version of the ABSINTH implicit solvation model and force field paradigm (termed ABSINTH-C) by incorporating a grid-based term that bootstraps against experimentally derived and computationally optimized conformational statistics for blocked amino acids. These statistics provide high-resolution descriptions of the intrinsic backbone dihedral angle preferences for all 20 amino acids. The original ABSINTH model generates Ramachandran plots that are too shallow in terms of the basin structures and too permissive in terms of dihedral angle preferences. We bootstrap against the reference optimized landscapes and incorporate CMAP-like residue-specific terms that help us reproduce the intrinsic dihedral angle preferences of individual amino acids. These corrections that lead to ABSINTH-C are achieved by balancing the incorporation of the new residue-specific terms with the accuracies inherent to the original ABSINTH model. We demonstrate the robustness of ABSINTH-C through a series of examples to highlight the preservation of accuracies as well as examples that demonstrate the improvements. Our efforts show how the recent experimentally derived and computationally optimized coil-library landscapes can be used as a touchstone for quantifying errors and making improvements to molecular mechanics force fields.
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Affiliation(s)
- Jeong-Mo Choi
- Department of Biomedical Engineering and Center for Biological Systems Engineering, Washington University in St. Louis, One Brookings Drive, Campus Box 1097, St. Louis, Missouri 63130
| | - Rohit V. Pappu
- Department of Biomedical Engineering and Center for Biological Systems Engineering, Washington University in St. Louis, One Brookings Drive, Campus Box 1097, St. Louis, Missouri 63130
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7
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Bacci M, Langini C, Vymětal J, Caflisch A, Vitalis A. Focused conformational sampling in proteins. J Chem Phys 2018; 147:195102. [PMID: 29166086 DOI: 10.1063/1.4996879] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
A detailed understanding of the conformational dynamics of biological molecules is difficult to obtain by experimental techniques due to resolution limitations in both time and space. Computer simulations avoid these in theory but are often too short to sample rare events reliably. Here we show that the progress index-guided sampling (PIGS) protocol can be used to enhance the sampling of rare events in selected parts of biomolecules without perturbing the remainder of the system. The method is very easy to use as it only requires as essential input a set of several features representing the parts of interest sufficiently. In this feature space, new states are discovered by spontaneous fluctuations alone and in unsupervised fashion. Because there are no energetic biases acting on phase space variables or projections thereof, the trajectories PIGS generates can be analyzed directly in the framework of transition networks. We demonstrate the possibility and usefulness of such focused explorations of biomolecules with two loops that are part of the binding sites of bromodomains, a family of epigenetic "reader" modules. This real-life application uncovers states that are structurally and kinetically far away from the initial crystallographic structures and are also metastable. Representative conformations are intended to be used in future high-throughput virtual screening campaigns.
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Affiliation(s)
- Marco Bacci
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Cassiano Langini
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Jiří Vymětal
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Amedeo Caflisch
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Andreas Vitalis
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
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8
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Rudzinski JF, Bereau T. Structural-kinetic-thermodynamic relationships identified from physics-based molecular simulation models. J Chem Phys 2018; 148:204111. [PMID: 29865838 DOI: 10.1063/1.5025125] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Coarse-grained molecular simulation models have provided immense, often general, insight into the complex behavior of condensed-phase systems but suffer from a lost connection to the true dynamical properties of the underlying system. In general, the physics that is built into a model shapes the free-energy landscape, restricting the attainable static and kinetic properties. In this work, we perform a detailed investigation into the property interrelationships resulting from these restrictions, for a representative system of the helix-coil transition. Inspired by high-throughput studies, we systematically vary force-field parameters and monitor their structural, kinetic, and thermodynamic properties. The focus of our investigation is a simple coarse-grained model, which accurately represents the underlying structural ensemble, i.e., effectively avoids sterically-forbidden configurations. As a result of this built-in physics, we observe a rather large restriction in the topology of the networks characterizing the simulation kinetics. When screening across force-field parameters, we find that structurally accurate models also best reproduce the kinetics, suggesting structural-kinetic relationships for these models. Additionally, an investigation into thermodynamic properties reveals a link between the cooperativity of the transition and the network topology at a single reference temperature.
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Affiliation(s)
| | - Tristan Bereau
- Max Planck Institute for Polymer Research, Mainz 55128, Germany
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9
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The Role of Conformational Entropy in the Determination of Structural-Kinetic Relationships for Helix-Coil Transitions. COMPUTATION 2018. [DOI: 10.3390/computation6010021] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Coarse-grained molecular simulation models can provide significant insight into the complex behavior of protein systems, but suffer from an inherently distorted description of dynamical properties. We recently demonstrated that, for a heptapeptide of alanine residues, the structural and kinetic properties of a simulation model are linked in a rather simple way, given a certain level of physics present in the model. In this work, we extend these findings to a longer peptide, for which the representation of configuration space in terms of a full enumeration of sequences of helical/coil states along the peptide backbone is impractical. We verify the structural-kinetic relationships by scanning the parameter space of a simple native-biased model and then employ a distinct transferable model to validate and generalize the conclusions. Our results further demonstrate the validity of the previous findings, while clarifying the role of conformational entropy in the determination of the structural-kinetic relationships. More specifically, while the global, long timescale kinetic properties of a particular class of models with varying energetic parameters but approximately fixed conformational entropy are determined by the overarching structural features of the ensemble, a shift in these kinetic observables occurs for models with a distinct representation of steric interactions. At the same time, the relationship between structure and more local, faster kinetic properties is not affected by varying the conformational entropy of the model.
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10
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Mukherjee S, Zhou G, Michel C, Voelz VA. Insights into Peptoid Helix Folding Cooperativity from an Improved Backbone Potential. J Phys Chem B 2015; 119:15407-17. [PMID: 26584227 DOI: 10.1021/acs.jpcb.5b09625] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Peptoids (N-substituted oligoglycines) are biomimetic polymers that can fold into a variety of unique structural scaffolds. Peptoid helices, which result from the incorporation of bulky chiral side chains, are a key peptoid structural motif whose formation has not yet been accurately modeled in molecular simulations. Here, we report that a simple modification of the backbone φ-angle potential in GAFF is able to produce well-folded cis-amide helices of (S)-N-(1-phenylethyl)glycine (Nspe), consistent with experiment. We validate our results against both QM calculations and NMR experiments. For this latter task, we make quantitative comparisons to sparse NOE data using the Bayesian Inference of Conformational Populations (BICePs) algorithm, a method we have recently developed for this purpose. We then performed extensive REMD simulations of Nspe oligomers as a function of chain length and temperature to probe the molecular forces driving cooperative helix formation. Analysis of simulation data by Lifson-Roig helix-coil theory show that the modified potential predicts much more cooperative folding for Nspe helices. Unlike peptides, per-residue entropy changes for helix nucleation and extension are mostly positive, suggesting that steric bulk provides the main driving force for folding. We expect these results to inform future work aimed at predicting and designing peptoid peptidomimetics and tertiary assemblies of peptoid helices.
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Affiliation(s)
- Sudipto Mukherjee
- Department of Chemistry, Temple University , Philadelphia, Pennsylvania 19122, United States
| | - Guangfeng Zhou
- Department of Chemistry, Temple University , Philadelphia, Pennsylvania 19122, United States
| | - Chris Michel
- Department of Chemistry, Temple University , Philadelphia, Pennsylvania 19122, United States
| | - Vincent A Voelz
- Department of Chemistry, Temple University , Philadelphia, Pennsylvania 19122, United States
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11
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Bacci M, Vitalis A, Caflisch A. A molecular simulation protocol to avoid sampling redundancy and discover new states. Biochim Biophys Acta Gen Subj 2014; 1850:889-902. [PMID: 25193737 DOI: 10.1016/j.bbagen.2014.08.013] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2014] [Revised: 08/21/2014] [Accepted: 08/25/2014] [Indexed: 10/24/2022]
Abstract
BACKGROUND For biomacromolecules or their assemblies, experimental knowledge is often restricted to specific states. Ambiguity pervades simulations of these complex systems because there is no prior knowledge of relevant phase space domains, and sampling recurrence is difficult to achieve. In molecular dynamics methods, ruggedness of the free energy surface exacerbates this problem by slowing down the unbiased exploration of phase space. Sampling is inefficient if dwell times in metastable states are large. METHODS We suggest a heuristic algorithm to terminate and reseed trajectories run in multiple copies in parallel. It uses a recent method to order snapshots, which provides notions of "interesting" and "unique" for individual simulations. We define criteria to guide the reseeding of runs from more "interesting" points if they sample overlapping regions of phase space. RESULTS Using a pedagogical example and an α-helical peptide, the approach is demonstrated to amplify the rate of exploration of phase space and to discover metastable states not found by conventional sampling schemes. Evidence is provided that accurate kinetics and pathways can be extracted from the simulations. CONCLUSIONS The method, termed PIGS for Progress Index Guided Sampling, proceeds in unsupervised fashion, is scalable, and benefits synergistically from larger numbers of replicas. Results confirm that the underlying ideas are appropriate and sufficient to enhance sampling. GENERAL SIGNIFICANCE In molecular simulations, errors caused by not exploring relevant domains in phase space are always unquantifiable and can be arbitrarily large. Our protocol adds to the toolkit available to researchers in reducing these types of errors. This article is part of a Special Issue entitled "Recent developments of molecular dynamics".
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Affiliation(s)
- Marco Bacci
- University of Zurich, Department of Biochemistry, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Andreas Vitalis
- University of Zurich, Department of Biochemistry, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.
| | - Amedeo Caflisch
- University of Zurich, Department of Biochemistry, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.
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12
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Vitalis A, Pappu RV. A simple molecular mechanics integrator in mixed rigid body and dihedral angle space. J Chem Phys 2014; 141:034105. [PMID: 25053299 PMCID: PMC4103982 DOI: 10.1063/1.4887339] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2014] [Accepted: 06/25/2014] [Indexed: 11/14/2022] Open
Abstract
We propose a numerical scheme to integrate equations of motion in a mixed space of rigid-body and dihedral angle coordinates. The focus of the presentation is biomolecular systems and the framework is applicable to polymers with tree-like topology. By approximating the effective mass matrix as diagonal and lumping all bias torques into the time dependencies of the diagonal elements, we take advantage of the formal decoupling of individual equations of motion. We impose energy conservation independently for every degree of freedom and this is used to derive a numerical integration scheme. The cost of all auxiliary operations is linear in the number of atoms. By coupling the scheme to one of two popular thermostats, we extend the method to sample constant temperature ensembles. We demonstrate that the integrator of choice yields satisfactory stability and is free of mass-metric tensor artifacts, which is expected by construction of the algorithm. Two fundamentally different systems, viz., liquid water and an α-helical peptide in a continuum solvent are used to establish the applicability of our method to a wide range of problems. The resultant constant temperature ensembles are shown to be thermodynamically accurate. The latter relies on detailed, quantitative comparisons to data from reference sampling schemes operating on exactly the same sets of degrees of freedom.
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Affiliation(s)
- Andreas Vitalis
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Rohit V Pappu
- Department of Biomedical Engineering and Center for Biological Systems Engineering, Washington University in St. Louis, One Brookings Drive, Campus Box 1097, St. Louis, Missouri 63130, USA
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13
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Ioannou F, Leontidis E, Archontis G. Helix Formation by Alanine-Based Peptides in Pure Water and Electrolyte Solutions: Insights from Molecular Dynamics Simulations. J Phys Chem B 2013; 117:9866-76. [DOI: 10.1021/jp406231g] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Filippos Ioannou
- Department
of Chemistry, and ‡Deparment of Physics, University of Cyprus, PO20537, CY1678, Nicosia, Cyprus
| | - Epameinondas Leontidis
- Department
of Chemistry, and ‡Deparment of Physics, University of Cyprus, PO20537, CY1678, Nicosia, Cyprus
| | - Georgios Archontis
- Department
of Chemistry, and ‡Deparment of Physics, University of Cyprus, PO20537, CY1678, Nicosia, Cyprus
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14
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Chen Y, Ding J. Construction of an intermediate-resolution lattice model and re-examination of the helix-coil transition: a dynamic Monte Carlo simulation. J Biomol Struct Dyn 2013; 32:792-803. [PMID: 23746129 DOI: 10.1080/07391102.2013.791645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
In protein modeling, spatial resolution and computational efficiency are always incompatible. As a compromise, an intermediate-resolution lattice model has been constructed in the present work. Each residue is decomposed into four basic units, i.e. the α-carbon group, the carboxyl group, the imino group, and the side-chain group, and each basic coarse-grained unit is represented by a minimum cubic box with eight lattice sites. The spacing of the lattice is about 0.56 Å, holding the highest spatial resolution for the present lattice protein models. As the first report of this new model, the helix-coil transition of a polyalanine chain was examined via dynamic Monte Carlo simulation. The period of formed α-helix was about 3.68 residues, close to that of a natural α-helix. The resultant backbone motion was found to be in the realistic regions of the conformational space in the Ramachandran plot. Helix propagation constant and nucleation constant were further determined through the dynamic hydrogen bonding process and torsional angle variation, and the results were used to make comparison between classical Zimm-Bragg theory and Lifson-Roig theory based on the Qian-Schellman relationship. The simulation results confirmed that our lattice model can reproduce the helix-coil transition of polypeptide and construct a moderately fine α-helix conformation without significantly weakening the priority in efficiency for a lattice model.
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Affiliation(s)
- Yantao Chen
- a State Key Laboratory of Molecular Engineering of Polymers, Shenzhen Key Laboratory of Functional Polymer , College of Chemistry and Chemical Engineering, Shenzhen University , Shenzhen , 518060 , China
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15
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Qin Z, Fabre A, Buehler MJ. Structure and mechanism of maximum stability of isolated alpha-helical protein domains at a critical length scale. THE EUROPEAN PHYSICAL JOURNAL. E, SOFT MATTER 2013; 36:53. [PMID: 23708839 DOI: 10.1140/epje/i2013-13053-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2012] [Accepted: 04/05/2013] [Indexed: 06/02/2023]
Abstract
The stability of alpha helices is important in protein folding, bioinspired materials design, and controls many biological properties under physiological and disease conditions. Here we show that a naturally favored alpha helix length of 9 to 17 amino acids exists at which the propensity towards the formation of this secondary structure is maximized. We use a combination of thermodynamical analysis, well-tempered metadynamics molecular simulation and statistical analyses of experimental alpha helix length distributions and find that the favored alpha helix length is caused by a competition between alpha helix folding, unfolding into a random coil and formation of higher-order tertiary structures. The theoretical result is suggested to be used to explain the statistical distribution of the length of alpha helices observed in natural protein structures. Our study provides mechanistic insight into fundamental controlling parameters in alpha helix structure formation and potentially other biopolymers or synthetic materials. The result advances our fundamental understanding of size effects in the stability of protein structures and may enable the design of de novo alpha-helical protein materials.
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Affiliation(s)
- Zhao Qin
- Laboratory for Atomistic and Molecular Mechanics, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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16
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