Understanding Protein Folding with Energy Landscape Theory Part I: Basic Concepts
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NIH Public Access Author Manuscript Proteins
NIH Public Access Author Manuscript Proteins. Author manuscript; available in PMC 2015 February 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Proteins. 2014 February ; 82(0 2): 208–218. doi:10.1002/prot.24374. One contact for every twelve residues allows robust and accurate topology-level protein structure modeling David E. Kim, Frank DiMaio, Ray Yu-Ruei Wang, Yifan Song, and David Baker* Department of Biochemistry, University of Washington, Seattle 98195, Washington Abstract A number of methods have been described for identifying pairs of contacting residues in protein three-dimensional structures, but it is unclear how many contacts are required for accurate structure modeling. The CASP10 assisted contact experiment provided a blind test of contact guided protein structure modeling. We describe the models generated for these contact guided prediction challenges using the Rosetta structure modeling methodology. For nearly all cases, the submitted models had the correct overall topology, and in some cases, they had near atomic-level accuracy; for example the model of the 384 residue homo-oligomeric tetramer (Tc680o) had only 2.9 Å root-mean-square deviation (RMSD) from the crystal structure. Our results suggest that experimental and bioinformatic methods for obtaining contact information may need to generate only one correct contact for every 12 residues in the protein to allow accurate topology level modeling. Keywords protein structure prediction; rosetta; comparative modeling; homology modeling; ab initio prediction; contact prediction INTRODUCTION Predicting the three-dimensional structure of a protein given just the amino acid sequence with atomic-level accuracy has been limited to small (<100 residues), single domain proteins. -
Molecular Mechanisms of Protein Thermal Stability
University of Denver Digital Commons @ DU Electronic Theses and Dissertations Graduate Studies 1-1-2016 Molecular Mechanisms of Protein Thermal Stability Lucas Sawle University of Denver Follow this and additional works at: https://digitalcommons.du.edu/etd Part of the Biological and Chemical Physics Commons Recommended Citation Sawle, Lucas, "Molecular Mechanisms of Protein Thermal Stability" (2016). Electronic Theses and Dissertations. 1137. https://digitalcommons.du.edu/etd/1137 This Dissertation is brought to you for free and open access by the Graduate Studies at Digital Commons @ DU. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of Digital Commons @ DU. For more information, please contact [email protected],[email protected]. Molecular Mechanisms of Protein Thermal Stability A Dissertation Presented to the Faculty of Natural Sciences and Mathematics University of Denver in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Lucas Sawle June 2016 Advisor: Dr. Kingshuk Ghosh c Copyright by Lucas Sawle, 2016. All Rights Reserved Author: Lucas Sawle Title: Molecular Mechanisms of Protein Thermal Stability Advisor: Dr. Kingshuk Ghosh Degree Date: June 2016 Abstract Organisms that thrive under extreme conditions, such as high salt concentra- tion, low pH, or high temperature, provide an opportunity to investigate the molec- ular and cellular strategies these organisms have adapted to survive in their harsh environments. Thermophilic proteins, those extracted from organisms that live at high temperature, maintain their structure and function at much higher tempera- tures compared to their mesophilic counterparts, found in organisms that live near room temperature. -
DNA Energy Landscapes Via Calorimetric Detection of Microstate Ensembles of Metastable Macrostates and Triplet Repeat Diseases
DNA energy landscapes via calorimetric detection of microstate ensembles of metastable macrostates and triplet repeat diseases Jens Vo¨ lkera, Horst H. Klumpb, and Kenneth J. Breslauera,c,1 aDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Rd, Piscataway, NJ 08854; bDepartment of Molecular and Cell Biology, University of Cape Town, Private Bag, Rondebosch 7800, South Africa; and cCancer Institute of New Jersey, New Brunswick, NJ 08901 Communicated by I. M. Gelfand, Rutgers, The State University of New Jersey, Piscataway, NJ, October 15, 2008 (received for review September 8, 2008) Biopolymers exhibit rough energy landscapes, thereby allowing biological role(s), if any, of kinetically stable (metastable) mi- biological processes to access a broad range of kinetic and ther- crostates that make up the time-averaged, native state ensembles modynamic states. In contrast to proteins, the energy landscapes of macroscopic nucleic acid states remains to be determined. of nucleic acids have been the subject of relatively few experimen- As part of an effort to address this deficiency, we report here tal investigations. In this study, we use calorimetric and spectro- experimental evidence for the presence of discrete microstates scopic observables to detect, resolve, and selectively enrich ener- in metastable triplet repeat bulge looped ⍀-DNAs of potential getically discrete ensembles of microstates within metastable DNA biological significance. The specific triplet repeat bulge looped structures. Our results are consistent with metastable, ‘‘native’’ ⍀-DNA species investigated mimic slipped DNA structures DNA states being composed of an ensemble of discrete and corresponding to intermediates in the processes that lead to kinetically stable microstates of differential stabilities, rather than DNA expansion in triplet repeat diseases (36). -
The Role of Conformational Entropy in the Determination of Structural-Kinetic Relationships for Helix-Coil Transitions
computation Article The Role of Conformational Entropy in the Determination of Structural-Kinetic Relationships for Helix-Coil Transitions Joseph F. Rudzinski * ID and Tristan Bereau ID Max Planck Institute for Polymer Research, Mainz 55128, Germany; [email protected] * Correspondence: [email protected]; Tel.: +49-6131-3790 Received: 21 December 2017; Accepted: 16 February 2018; Published: 26 February 2018 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. -
Ruggedness in the Free Energy Landscape Dictates Misfolding of the Prion Protein
Article Ruggedness in the Free Energy Landscape Dictates Misfolding of the Prion Protein Roumita Moulick 1, Rama Reddy Goluguri 1 and Jayant B. Udgaonkar 1,2 1 - National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India 2 - Indian Institute of Science Education and Research, Pashan, Pune 411008, India Correspondence to Jayant B. Udgaonkar: Indian Institute of Science Education and Research, Pashan, Pune 411008, India. [email protected] https://doi.org/10.1016/j.jmb.2018.12.009 Edited by Sheena Radford Abstract Experimental determination of the key features of the free energy landscapes of proteins, which dictate their adeptness to fold correctly, or propensity to misfold and aggregate and which are modulated upon a change from physiological to aggregation-prone conditions, is a difficult challenge. In this study, sub-millisecond kinetic measurements of the folding and unfolding of the mouse prion protein reveal how the free energy landscape becomes more complex upon a shift from physiological (pH 7) to aggregation-prone (pH 4) conditions. Folding and unfolding utilize the same single pathway at pH 7, but at pH 4, folding occurs on a pathway distinct from the unfolding pathway. Moreover, the kinetics of both folding and unfolding at pH 4 depend not only on the final conditions but also on the conditions under which the processes are initiated. Unfolding can be made to switch to occur on the folding pathway by varying the initial conditions. Folding and unfolding pathways appear to occupy different regions of the free energy landscape, which are separated by large free energy barriers that change with a change in the initial conditions. -
Introducing the Levinthal's Protein Folding Paradox and Its Solution
Article pubs.acs.org/jchemeduc Introducing the Levinthal’s Protein Folding Paradox and Its Solution Leandro Martínez* Department of Physical Chemistry, Institute of Chemistry, University of Campinas, Campinas, Saõ Paulo 13083-970, Brazil *S Supporting Information ABSTRACT: The protein folding (Levinthal’s) paradox states that it would not be possible in a physically meaningful time to a protein to reach the native (functional) conformation by a random search of the enormously large number of possible structures. This paradox has been solved: it was shown that small biases toward the native conformation result in realistic folding times of realistic-length sequences. This solution of the paradox is, however, not amenable to most chemistry or biology students due to the demanding mathematics. Here, a simplification of the study of the paradox and its solution is provided so that it is accessible to chemists and biologists at an undergraduate or graduate level. Despite its simplicity, the model captures some fundamental aspects of the protein folding mechanism and allows students to grasp the actual significance of the popular folding funnel representation of the protein energy landscape. The analysis of the folding model provides a rich basis for a discussion of the relationships between kinetics and thermodynamics on a fundamental level and on student perception of the time-scales of molecular phenomena. KEYWORDS: Upper-Division Undergraduate, Graduate Education, Biochemistry, Biophysical Chemistry, Molecular Biology, Proteins/Peptides, -
CHAPTER 4 Proteins: Structure, Function, Folding
Recitation #2 Proteins: Structure, Function, Folding CHAPTER 4 Proteins: Structure, Function, Folding Learning goals: – Structure and properties of the peptide bond – Structural hierarchy in proteins – Structure and function of fibrous proteins – Structure analysis of globular proteins – Protein folding and denaturation Structure of Proteins • Unlike most organic polymers, protein molecules adopt a specific three-dimensional conformation. • This structure is able to fulfill a specific biological function • This structure is called the native fold • The native fold has a large number of favorable interactions within the protein • There is a cost in conformational entropy of folding the protein into one specific native fold Favorable Interactions in Proteins • Hydrophobic effect – Release of water molecules from the structured solvation layer around the molecule as protein folds increases the net entropy • Hydrogen bonds – Interaction of N-H and C=O of the peptide bond leads to local regular structures such as -helices and -sheets • London dispersion – Medium-range weak attraction between all atoms contributes significantly to the stability in the interior of the protein • Electrostatic interactions – Long-range strong interactions between permanently charged groups – Salt-bridges, esp. buried in the hydrophobic environment strongly stabilize the protein • Levels of structure in proteins. The primary structure consists of a sequence of amino acids linked together by peptide bonds • and includes any disulfide bonds. The resulting polypeptide can be arranged into units of secondary structure, such as an α-helix. The helix is a part of the tertiary structure of the folded polypeptide, which is itself one of the subunits that make up the quaternary structure of the multi-subunit protein, in this case hemoglobin. -
Complex Energy Landscapes” (IPAM Program, Fall 2017)
Whitepaper: “Complex Energy Landscapes” (IPAM program, fall 2017) Authors list (alphabetically) Nestor F. Aguirre, Chris Anderson, Lorenzo Boninsegna, Gábor Csányi, Mauricio del Razo Sarmina, Marco Di Gennaro, Florent Hédin, Graeme Henkelman, Richard G. Hennig, Jan Janßen, Tony Lelièvre, Hao Li, Mitchell Luskin, Noa Marom, Jörg Neugebauer, Feliks Nüske, Joshua Paul, Danny Perez, Giovanni Pinamonti, Petr Plechac, Biswas Rijal, Gideon Simpson, Justin C. Smith, Thomas Swinburne, Anne Marie Z. Tan, Mira Todorova, Dallas R. Trinkle, Stephen Xie, Ping Yang Abstract Recent advances in computational resources and the development of high-throughput frameworks enable the efficient sampling of complicated multivariate functions. This includes energy and electronic property landscapes of inorganic, organic, biomolecular, and hybrid materials and functional nanostructures. Combined with new developments in data science, this leads to a rapidly growing need for numerical methods and a fundamental mathematical understanding of efficient sampling approaches, optimization techniques, hierarchical surrogate models, coarse-graining techniques, and methods for uncertainty quantification. The complexity of these energy and property landscapes originates from their simultaneous dependence on discrete degrees of freedom – i.e., number of atoms and species types – and continuous ones – i.e., the position of atoms. Moreover, dynamical behavior governed by complex landscapes involves a rich hierarchy of timescales and is characterized by rare events -
Protein Functional Landscapes, Dynamics, Allostery 297
Quarterly Reviews of Biophysics 43, 3 (2010), pp. 295–332. f Cambridge University Press 2010 295 doi:10.1017/S0033583510000119 Printed in the United States of America Protein functional landscapes,dynamics, allostery: a tortuouspathtowards a universal theoretical framework Pavel I. Zhuravlev and Garegin A. Papoian* Department of Chemistry and Biochemistry, Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, USA Abstract. Energy landscape theories have provided a common ground for understanding the protein folding problem, which once seemed to be overwhelmingly complicated. At the same time, the native state was found to be an ensemble of interconverting states with frustration playing a more important role compared to the folding problem. The landscape of the folded protein – the native landscape – is glassier than the folding landscape; hence, a general description analogous to the folding theories is difficult to achieve. On the other hand, the native basin phase volume is much smaller, allowing a protein to fully sample its native energy landscape on the biological timescales. Current computational resources may also be used to perform this sampling for smaller proteins, to build a ‘topographical map’ of the native landscape that can be used for subsequent analysis. Several major approaches to representing this topographical map are highlighted in this review, including the construction of kinetic networks, hierarchical trees and free energy surfaces with subsequent structural and kinetic analyses. In this review, we extensively discuss the important question of choosing proper collective coordinates characterizing functional motions. In many cases, the substates on the native energy landscape, which represent different functional states, can be used to obtain variables that are well suited for building free energy surfaces and analyzing the protein’s functional dynamics. -
Evolution, Energy Landscapes and the Paradoxes of Protein Folding
Biochimie 119 (2015) 218e230 Contents lists available at ScienceDirect Biochimie journal homepage: www.elsevier.com/locate/biochi Review Evolution, energy landscapes and the paradoxes of protein folding Peter G. Wolynes Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA article info abstract Article history: Protein folding has been viewed as a difficult problem of molecular self-organization. The search problem Received 15 September 2014 involved in folding however has been simplified through the evolution of folding energy landscapes that are Accepted 11 December 2014 funneled. The funnel hypothesis can be quantified using energy landscape theory based on the minimal Available online 18 December 2014 frustration principle. Strong quantitative predictions that follow from energy landscape theory have been widely confirmed both through laboratory folding experiments and from detailed simulations. Energy Keywords: landscape ideas also have allowed successful protein structure prediction algorithms to be developed. Folding landscape The selection constraint of having funneled folding landscapes has left its imprint on the sequences of Natural selection Structure prediction existing protein structural families. Quantitative analysis of co-evolution patterns allows us to infer the statistical characteristics of the folding landscape. These turn out to be consistent with what has been obtained from laboratory physicochemical folding experiments signaling a beautiful confluence of ge- nomics and chemical physics. © 2014 Elsevier B.V. and Societ e française de biochimie et biologie Moleculaire (SFBBM). All rights reserved. Contents 1. Introduction . ....................... 218 2. General evidence that folding landscapes are funneled . ....................... 221 3. How rugged is the folding landscape e physicochemical approach . ....................... 222 4. -
Spectrin SH3 Domain Xavier Periole,1* Michele Vendruscolo,2 and Alan E
proteins STRUCTURE O FUNCTION O BIOINFORMATICS Molecular dynamics simulations from putative transition states of a-spectrin SH3 domain Xavier Periole,1* Michele Vendruscolo,2 and Alan E. Mark1,3,4* 1 Department of Biophysical Chemistry, Groningen Biomolecular Sciences and Biotechnology Institute (GBB), University of Groningen, 9747 AG Groningen, The Netherlands 2 Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom 3 School of Molecular and Microbial Sciences, University of Queensland, St Lucia, 4072, Queensland, Australia 4 Institute for Molecular Biosciences, University of Queensland, St Lucia, 4072, Queensland, Australia INTRODUCTION ABSTRACT Understanding of the process of protein folding is one of the grand challenges in A series of molecular dynam- molecular biology. Ever since it was shown that the information contained in the ics simulations in explicit sol- sequence of amino acids is sufficient for a protein to find the structure of its native vent were started from nine state,1 experimentalists and theoreticians have tried to understand the mechanisms of structural models of the tran- this important biological process.2–5 sition state of the SH3 do- 5 main of a-spectrin, which Much effort has been focused on proteins that undergo two-state folding. The pri- were generated by Lindorff- mary advantage of two-state proteins is the lack of detectable intermediate states, so Larsen et al. (Nat Struct Mol their folding process can be considered as involving a transition from a broad ensem- Biol 2004;11:443–449) using ble of configurations representing the unfolded state to a narrow ensemble of configu- molecular dynamics simula- rations making up the native state, via a specific transition state. -
Thermodynamics of Denaturation of Barstar: Evidence for Cold Denaturation and Evaluation of the Interaction with Guanidine Hydrochloride+
3286 Biochemistry 1995, 34, 3286-3299 Thermodynamics of Denaturation of Barstar: Evidence for Cold Denaturation and Evaluation of the Interaction with Guanidine Hydrochloride+ Vishwas R. Agashe and Jayant B. Udgaonkar* National Centre for Biological Sciences, TIFR Centre, P.O. Box 1234, Indian Institute of Science Campus, Bangalore 56001 2, India Received October 17, 1994; Revised Manuscript Received December 19, 1994@ ABSTRACT:Isothermal guanidine hydrochloride (GdnHC1)-induced denaturation curves obtained at 14 different temperatures in the range 273-323 K have been used in conjunction with thermally-induced denaturation curves obtained in the presence of 15 different concentrations of GdnHCl to characterize the thermodynamics of cold and heat denaturation of barstar. The linear free energy model has been used to determine the excess changes in free energy, enthalpy, entropy, and heat capacity that occur on denaturation. The stability of barstar in water decreases as the temperature is decreased from 300 to 273 K. This decrease in stability is not accompanied by a change in structure as monitored by measurement of the mean residue ellipticities at both 222 and 275 nm. When GdnHCl is present at concentrations between 1.2 and 2.0 M, the decrease in stability with decrease in temperature is however so large that the protein undergoes cold denaturation. The structural transition accompanying the cold denaturation process has been monitored by measuring the mean residue ellipticity at 222 nm. The temperature dependence of the change in free energy, obtained in the presence of 10 different concentrations of GdnHCl in the range 0.2-2.0 M, shows a decrease in stability with a decrease as well as an increase in temperature from 300 K.