1
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Banayan NE, Hsu A, Hunt JF, Palmer AG, Friesner RA. Parsing Dynamics of Protein Backbone NH and Side-Chain Methyl Groups using Molecular Dynamics Simulations. J Chem Theory Comput 2024; 20:6316-6327. [PMID: 38957960 DOI: 10.1021/acs.jctc.4c00378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2024]
Abstract
Experimental NMR spectroscopy and theoretical molecular dynamics (MD) simulations provide complementary insights into protein conformational dynamics and hence into biological function. The present work describes an extensive set of backbone NH and side-chain methyl group generalized order parameters for the Escherichia coli ribonuclease HI (RNH) enzyme derived from 2-μs microsecond MD simulations using the OPLS4 and AMBER-FF19SB force fields. The simulated generalized order parameters are compared with values derived from NMR 15N and 13CH2D spin relaxation measurements. The squares of the generalized order parameters, S2 for the N-H bond vector and Saxis2 for the methyl group symmetry axis, characterize the equilibrium distribution of vector orientations in a molecular frame of reference. Optimal agreement between simulated and experimental results was obtained by averaging S2 or Saxis2 calculated by dividing the simulated trajectories into 50 ns blocks (∼five times the rotational diffusion correlation time for RNH). With this procedure, the median absolute deviations (MAD) between experimental and simulated values of S2 and Saxis2 are 0.030 (NH) and 0.061 (CH3) for OPLS4 and 0.041 (NH) and 0.078 (CH3) for AMBER-FF19SB. The MAD between OPLS4 and AMBER-FF19SB are 0.021 (NH) and 0.072 (CH3). The generalized order parameters for the methyl group symmetry axis can be decomposed into contributions from backbone fluctuations, between-rotamer dihedral angle transitions, and within-rotamer dihedral angle fluctuations. Analysis of the simulation trajectories shows that (i) backbone and side chain conformational fluctuations exhibit little correlation and that (ii) fluctuations within rotamers are limited and highly uniform with values that depend on the number of dihedral angles considered. Low values of Saxis2, indicative of enhanced side-chain flexibility, result from between-rotamer transitions that can be enhanced by increased local backbone flexibility.
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Affiliation(s)
- Nooriel E Banayan
- Department of Biological Sciences, Columbia University, 3000 Broadway, New York, New York 10027, United States
| | - Andrew Hsu
- Department of Chemistry, Columbia University, 3000 Broadway, New York, New York 10027, United States
| | - John F Hunt
- Department of Biological Sciences, Columbia University, 3000 Broadway, New York, New York 10027, United States
| | - Arthur G Palmer
- Department of Biochemistry and Molecular Biophysics, Columbia University, 701 West 168th Street, New York, New York 10032, United States
| | - Richard A Friesner
- Department of Chemistry, Columbia University, 3000 Broadway, New York, New York 10027, United States
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2
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Maiti S, Singh A, Maji T, Saibo NV, De S. Experimental methods to study the structure and dynamics of intrinsically disordered regions in proteins. Curr Res Struct Biol 2024; 7:100138. [PMID: 38707546 PMCID: PMC11068507 DOI: 10.1016/j.crstbi.2024.100138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 03/12/2024] [Accepted: 03/15/2024] [Indexed: 05/07/2024] Open
Abstract
Eukaryotic proteins often feature long stretches of amino acids that lack a well-defined three-dimensional structure and are referred to as intrinsically disordered proteins (IDPs) or regions (IDRs). Although these proteins challenge conventional structure-function paradigms, they play vital roles in cellular processes. Recent progress in experimental techniques, such as NMR spectroscopy, single molecule FRET, high speed AFM and SAXS, have provided valuable insights into the biophysical basis of IDP function. This review discusses the advancements made in these techniques particularly for the study of disordered regions in proteins. In NMR spectroscopy new strategies such as 13C detection, non-uniform sampling, segmental isotope labeling, and rapid data acquisition methods address the challenges posed by spectral overcrowding and low stability of IDPs. The importance of various NMR parameters, including chemical shifts, hydrogen exchange rates, and relaxation measurements, to reveal transient secondary structures within IDRs and IDPs are presented. Given the high flexibility of IDPs, the review outlines NMR methods for assessing their dynamics at both fast (ps-ns) and slow (μs-ms) timescales. IDPs exert their functions through interactions with other molecules such as proteins, DNA, or RNA. NMR-based titration experiments yield insights into the thermodynamics and kinetics of these interactions. Detailed study of IDPs requires multiple experimental techniques, and thus, several methods are described for studying disordered proteins, highlighting their respective advantages and limitations. The potential for integrating these complementary techniques, each offering unique perspectives, is explored to achieve a comprehensive understanding of IDPs.
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Affiliation(s)
| | - Aakanksha Singh
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, WB, 721302, India
| | - Tanisha Maji
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, WB, 721302, India
| | - Nikita V. Saibo
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, WB, 721302, India
| | - Soumya De
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, WB, 721302, India
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3
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Champion C, Lehner M, Smith AA, Ferrage F, Bolik-Coulon N, Riniker S. Unraveling motion in proteins by combining NMR relaxometry and molecular dynamics simulations: A case study on ubiquitin. J Chem Phys 2024; 160:104105. [PMID: 38465679 DOI: 10.1063/5.0188416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 02/20/2024] [Indexed: 03/12/2024] Open
Abstract
Nuclear magnetic resonance (NMR) relaxation experiments shine light onto the dynamics of molecular systems in the picosecond to millisecond timescales. As these methods cannot provide an atomically resolved view of the motion of atoms, functional groups, or domains giving rise to such signals, relaxation techniques have been combined with molecular dynamics (MD) simulations to obtain mechanistic descriptions and gain insights into the functional role of side chain or domain motion. In this work, we present a comparison of five computational methods that permit the joint analysis of MD simulations and NMR relaxation experiments. We discuss their relative strengths and areas of applicability and demonstrate how they may be utilized to interpret the dynamics in MD simulations with the small protein ubiquitin as a test system. We focus on the aliphatic side chains given the rigidity of the backbone of this protein. We find encouraging agreement between experiment, Markov state models built in the χ1/χ2 rotamer space of isoleucine residues, explicit rotamer jump models, and a decomposition of the motion using ROMANCE. These methods allow us to ascribe the dynamics to specific rotamer jumps. Simulations with eight different combinations of force field and water model highlight how the different metrics may be employed to pinpoint force field deficiencies. Furthermore, the presented comparison offers a perspective on the utility of NMR relaxation to serve as validation data for the prediction of kinetics by state-of-the-art biomolecular force fields.
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Affiliation(s)
- Candide Champion
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Marc Lehner
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Albert A Smith
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstrasse 16-18, 04107 Leipzig, Germany
| | - Fabien Ferrage
- Laboratoire des Biomolécules, LBM, Département de Chimie, École normale supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| | - Nicolas Bolik-Coulon
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada
| | - Sereina Riniker
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
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4
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Saravanan V, Ahammed I, Bhattacharya A, Bhattacharya S. Uncovering allostery and regulation in SORCIN through molecular dynamics simulations. J Biomol Struct Dyn 2024; 42:1812-1825. [PMID: 37098805 DOI: 10.1080/07391102.2023.2202772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 04/08/2023] [Indexed: 04/27/2023]
Abstract
Soluble resistance-related calcium-binding protein or Sorcin is an allosteric, calcium-binding Penta-EF hand (PEF) family protein implicated in multi-drug resistant cancers. Sorcin is known to bind chemotherapeutic molecules such as Doxorubicin. This study uses in-silico molecular dynamics simulations to explore the dynamics and allosteric behavior of Sorcin in the context of Ca2+ uptake and Doxorubicin binding. The results show that Ca2+ binding induces large, but reversible conformational changes in the Sorcin structure which manifest as rigid body reorientations that preserve the local secondary structure. A reciprocal allosteric handshake centered around the EF5 hand is found to be key in Sorcin dimer formation and stabilization. Binding of Doxorubicin results in rearrangement of allosteric communities which disrupts long-range allosteric information transfer from the N-terminal domain to the middle lobe. However, this binding does not result in secondary structure destabilization. Sorcin does not appear to have a distinct Ca2+ activated mode of Doxorubicin binding.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Vinnarasi Saravanan
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Ijas Ahammed
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Akash Bhattacharya
- Visiting Assistant Professor of Physics, St. Mary's University, San Antonio, Texas, USA
| | - Swati Bhattacharya
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India
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5
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Kamski-Hennekam ER, Huang J, Ahmed R, Melacini G. Toward a molecular mechanism for the interaction of ATP with alpha-synuclein. Chem Sci 2023; 14:9933-9942. [PMID: 37736631 PMCID: PMC10510630 DOI: 10.1039/d3sc03612j] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 08/19/2023] [Indexed: 09/23/2023] Open
Abstract
The ability of Adenosine Triphosphate (ATP) to modulate protein solubility establishes a critical link between ATP homeostasis and proteinopathies, such as Parkinson's (PD). The most significant risk factor for PD is aging, and ATP levels decline dramatically with age. However, the mechanism by which ATP interacts with alpha-synuclein (αS), whose aggregation is characteristic of PD, is currently not fully understood, as is ATP's effect on αS aggregation. Here, we use nuclear magnetic resonance spectroscopy as well as fluorescence, dynamic light scattering and microscopy to show that ATP affects multiple species in the αS self-association cascade. The triphosphate moiety of ATP disrupts long-range electrostatic intramolecular contacts in αS monomers to enhance initial aggregation, while also inhibiting the formation of late-stage β-sheet fibrils by disrupting monomer-fibril interactions. These effects are modulated by magnesium ions and early onset PD-related αS mutations, suggesting that loss of the ATP hydrotropic function on αS fibrillization may play a role in PD etiology.
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Affiliation(s)
| | - Jinfeng Huang
- Department of Chemistry and Chemical Biology, McMaster University Hamilton ON L8S 4M1 Canada
| | - Rashik Ahmed
- Department of Biochemistry and Biomedical Sciences, McMaster University Hamilton ON L8S 4M1 Canada
| | - Giuseppe Melacini
- Department of Chemistry and Chemical Biology, McMaster University Hamilton ON L8S 4M1 Canada
- Department of Biochemistry and Biomedical Sciences, McMaster University Hamilton ON L8S 4M1 Canada
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6
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Smith IN, Dawson JE, Krieger J, Thacker S, Bahar I, Eng C. Structural and Dynamic Effects of PTEN C-Terminal Tail Phosphorylation. J Chem Inf Model 2022; 62:4175-4190. [PMID: 36001481 PMCID: PMC9472802 DOI: 10.1021/acs.jcim.2c00441] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Indexed: 11/28/2022]
Abstract
The phosphatase and tensin homologue deleted on chromosome 10 (PTEN) tumor suppressor gene encodes a tightly regulated dual-specificity phosphatase that serves as the master regulator of PI3K/AKT/mTOR signaling. The carboxy-terminal tail (CTT) is key to regulation and harbors multiple phosphorylation sites (Ser/Thr residues 380-385). CTT phosphorylation suppresses the phosphatase activity by inducing a stable, closed conformation. However, little is known about the mechanisms of phosphorylation-induced CTT-deactivation dynamics. Using explicit solvent microsecond molecular dynamics simulations, we show that CTT phosphorylation leads to a partially collapsed conformation, which alters the secondary structure of PTEN and induces long-range conformational rearrangements that encompass the active site. The active site rearrangements prevent localization of PTEN to the membrane, precluding lipid phosphatase activity. Notably, we have identified phosphorylation-induced allosteric coupling between the interdomain region and a hydrophobic site neighboring the active site in the phosphatase domain. Collectively, the results provide a mechanistic understanding of CTT phosphorylation dynamics and reveal potential druggable allosteric sites in a previously believed clinically undruggable protein.
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Affiliation(s)
- Iris N. Smith
- Genomic
Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, Ohio 44195, United States
| | - Jennifer E. Dawson
- Genomic
Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, Ohio 44195, United States
| | - James Krieger
- Department
of Computational and Systems Biology, University
of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, Pennsylvania 15260, United States
| | - Stetson Thacker
- Genomic
Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, Ohio 44195, United States
- Cleveland
Clinic Lerner College of Medicine, Case
Western Reserve University, 9500 Euclid Avenue, Cleveland, Ohio 44195, United
States
| | - Ivet Bahar
- Department
of Computational and Systems Biology, University
of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, Pennsylvania 15260, United States
| | - Charis Eng
- Genomic
Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, Ohio 44195, United States
- Cleveland
Clinic Lerner College of Medicine, Case
Western Reserve University, 9500 Euclid Avenue, Cleveland, Ohio 44195, United
States
- Case
Comprehensive Cancer Center, Case Western
Reserve University School of Medicine, 10900 Euclid Avenue, Cleveland, Ohio 44106, United States
- Taussig
Cancer Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, Ohio 44195, United States
- Department
of Genetics and Genome Sciences, Case Western
Reserve University School of Medicine, 10900 Euclid Avenue, Cleveland, Ohio 44106, United States
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7
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In Search of a Dynamical Vocabulary: A Pipeline to Construct a Basis of Shared Traits in Large-Scale Motions of Proteins. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12147157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The paradigmatic sequence–structure–dynamics–function relation in proteins is currently well established in the scientific community; in particular, a large effort has been made to probe the first connection, indeed providing convincing evidence of its strength and rationalizing it in a quantitative and general framework. In contrast, however, the role of dynamics as a link between structure and function has eluded a similarly clear-cut verification and description. In this work, we propose a pipeline aimed at building a basis for the quantitative characterization of the large-scale dynamics of a set of proteins, starting from the sole knowledge of their native structures. The method hinges on a dynamics-based clusterization, which allows a straightforward comparison with structural and functional protein classifications. The resulting basis set, obtained through the application to a group of related proteins, is shown to reproduce the salient large-scale dynamical features of the dataset. Most interestingly, the basis set is shown to encode the fluctuation patterns of homologous proteins not belonging to the initial dataset, thus highlighting the general applicability of the pipeline used to build it.
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8
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Kozak F, Kurzbach D. How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations. Comput Struct Biotechnol J 2021; 19:2097-2105. [PMID: 33995905 PMCID: PMC8085671 DOI: 10.1016/j.csbj.2021.04.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 04/07/2021] [Accepted: 04/07/2021] [Indexed: 12/12/2022] Open
Abstract
We review recent advances in modeling structural ensembles of transcription factors from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopic data, integrated with molecular dynamics (MD) simulations. We focus on approaches that confirm computed conformational ensembles by sparse constraints obtained from magnetic resonance. This combination enables the deduction of functional and structural protein models even if nuclear Overhauser effects (NOEs) are too scarce for conventional structure determination. We highlight recent insights into the folding-upon-DNA binding transitions of intrinsically disordered transcription factors that could be assessed using such integrative approaches.
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Affiliation(s)
- Fanny Kozak
- University Vienna, Faculty of Chemistry, Institute of Biological Chemistry, Waehringer Str. 38, 1090 Vienna, Austria
| | - Dennis Kurzbach
- University Vienna, Faculty of Chemistry, Institute of Biological Chemistry, Waehringer Str. 38, 1090 Vienna, Austria
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9
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Khago D, Fucci IJ, Byrd RA. The Role of Conformational Dynamics in the Recognition and Regulation of Ubiquitination. Molecules 2020; 25:E5933. [PMID: 33333809 PMCID: PMC7765195 DOI: 10.3390/molecules25245933] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 12/07/2020] [Accepted: 12/09/2020] [Indexed: 11/23/2022] Open
Abstract
The ubiquitination pathway is central to many cell signaling and regulatory events. One of the intriguing aspects of the pathway is the combinatorial sophistication of substrate recognition and ubiquitin chain building determinations. The abundant structural and biological data portray several characteristic protein folds among E2 and E3 proteins, and the understanding of the combinatorial complexity that enables interaction with much of the human proteome is a major goal to developing targeted and selective manipulation of the pathway. With the commonality of some folds, there are likely other aspects that can provide differentiation and recognition. These aspects involve allosteric effects and conformational dynamics that can direct recognition and chain building processes. In this review, we will describe the current state of the knowledge for conformational dynamics across a wide timescale, address the limitations of present approaches, and illustrate the potential to make new advances in connecting dynamics with ubiquitination regulation.
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Affiliation(s)
| | | | - Robert Andrew Byrd
- Structural Biophysics Laboratory, Center for Cancer Research, National Cancer Institute, P.O. Box B, Building 538, Frederick, MD 21702-1201, USA; (D.K.); (I.J.F.)
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10
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Cárdenas R, Martínez-Seoane J, Amero C. Combining Experimental Data and Computational Methods for the Non-Computer Specialist. Molecules 2020; 25:E4783. [PMID: 33081072 PMCID: PMC7594097 DOI: 10.3390/molecules25204783] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 08/25/2020] [Accepted: 08/28/2020] [Indexed: 01/01/2023] Open
Abstract
Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretation of the results is often a very challenging task. While experimental and computational methods are often considered as two different and separate approaches, the power and utility of combining both is undeniable. The integration of the experimental data with computational techniques can assist and enrich the interpretation, providing new detailed molecular understanding of the systems. Here, we briefly describe the basic principles of how experimental data can be combined with computational methods to obtain insights into the molecular mechanism and expand the interpretation through the generation of detailed models.
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Affiliation(s)
| | | | - Carlos Amero
- Laboratorio de Bioquímica y Resonancia Magnética Nuclear, Centro de Investigaciones Químicas, Instituto de Investigación en Ciencias Básicas y Aplicadas, Universidad Autónoma del Estado de Morelos, Cuernavaca, Morelos 62209, Mexico; (R.C.); (J.M.-S.)
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11
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Agarwal PK, Bernard DN, Bafna K, Doucet N. Enzyme dynamics: Looking beyond a single structure. ChemCatChem 2020; 12:4704-4720. [PMID: 33897908 PMCID: PMC8064270 DOI: 10.1002/cctc.202000665] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Indexed: 12/23/2022]
Abstract
Conventional understanding of how enzymes function strongly emphasizes the role of structure. However, increasing evidence clearly indicates that enzymes do not remain fixed or operate exclusively in or close to their native structure. Different parts of the enzyme (from individual residues to full domains) undergo concerted motions on a wide range of time-scales, including that of the catalyzed reaction. Information obtained on these internal motions and conformational fluctuations has so far uncovered and explained many aspects of enzyme mechanisms, which could not have been understood from a single structure alone. Although there is wide interest in understanding enzyme dynamics and its role in catalysis, several challenges remain. In addition to technical difficulties, the vast majority of investigations are performed in dilute aqueous solutions, where conditions are significantly different than the cellular milieu where a large number of enzymes operate. In this review, we discuss recent developments, several challenges as well as opportunities related to this topic. The benefits of considering dynamics as an integral part of the enzyme function can also enable new means of biocatalysis, engineering enzymes for industrial and medicinal applications.
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Affiliation(s)
- Pratul K. Agarwal
- Department of Physiological Sciences and High-Performance Computing Center, Oklahoma State University, Stillwater, Oklahoma 74078
- Arium BioLabs, 2519 Caspian Drive, Knoxville, Tennessee 37932
| | - David N. Bernard
- Centre Armand-Frappier Santé Biotechnologie, Institut national de la recherche scientifique (INRS), Université du Québec, 531 Boulevard des Prairies, Laval, Quebec, H7V 1B7, Canada
| | - Khushboo Bafna
- Department of Chemistry and Chemical Biology, and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New York 12180
| | - Nicolas Doucet
- Centre Armand-Frappier Santé Biotechnologie, Institut national de la recherche scientifique (INRS), Université du Québec, 531 Boulevard des Prairies, Laval, Quebec, H7V 1B7, Canada
- PROTEO, the Quebec Network for Research on Protein Function, Structure, and Engineering, 1045 Avenue de la Médecine, Université Laval, Québec, QC, G1V 0A6, Canada
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12
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Verkhivker GM, Agajanian S, Hu G, Tao P. Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning. Front Mol Biosci 2020; 7:136. [PMID: 32733918 PMCID: PMC7363947 DOI: 10.3389/fmolb.2020.00136] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022] Open
Abstract
Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.
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Affiliation(s)
- Gennady M. Verkhivker
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, United States
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA, United States
| | - Steve Agajanian
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, United States
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Peng Tao
- Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, TX, United States
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13
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Liao Q. Enhanced sampling and free energy calculations for protein simulations. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 170:177-213. [PMID: 32145945 DOI: 10.1016/bs.pmbts.2020.01.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Molecular dynamics simulation is a powerful computational technique to study biomolecular systems, which complements experiments by providing insights into the structural dynamics relevant to biological functions at atomic scale. It can also be used to calculate the free energy landscapes of the conformational transitions to better understand the functions of the biomolecules. However, the sampling of biomolecular configurations is limited by the free energy barriers that need to be overcome, leading to considerable gaps between the timescales reached by MD simulation and those governing biological processes. To address this issue, many enhanced sampling methodologies have been developed to increase the sampling efficiency of molecular dynamics simulations and free energy calculations. Usually, enhanced sampling algorithms can be classified into methods based on collective variables (CV-based) and approaches which do not require predefined CVs (CV-free). In this chapter, the theoretical basis of free energy estimation is briefly reviewed first, followed by the reviews of the most common CV-based and CV-free methods including the presentation of some examples and recent developments. Finally, the combination of different enhanced sampling methods is discussed.
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Affiliation(s)
- Qinghua Liao
- Science for Life Laboratory, Department of Chemistry-BMC, Uppsala University, Uppsala, Sweden.
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14
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Sheik Amamuddy O, Veldman W, Manyumwa C, Khairallah A, Agajanian S, Oluyemi O, Verkhivker GM, Tastan Bishop Ö. Integrated Computational Approaches and Tools forAllosteric Drug Discovery. Int J Mol Sci 2020; 21:E847. [PMID: 32013012 PMCID: PMC7036869 DOI: 10.3390/ijms21030847] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Revised: 01/20/2020] [Accepted: 01/21/2020] [Indexed: 12/16/2022] Open
Abstract
Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.
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Affiliation(s)
- Olivier Sheik Amamuddy
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Wayde Veldman
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Colleen Manyumwa
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Afrah Khairallah
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
| | - Steve Agajanian
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
| | - Odeyemi Oluyemi
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
| | - Gennady M. Verkhivker
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA; (S.A.); (O.O.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
| | - Özlem Tastan Bishop
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown 6140, South Africa; (O.S.A.); (W.V.); (C.M.); (A.K.)
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15
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Transient multimers modulate conformer abundances of prion protein monomer through conformational selection. Sci Rep 2019; 9:12159. [PMID: 31434938 PMCID: PMC6704068 DOI: 10.1038/s41598-019-48377-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 08/01/2019] [Indexed: 01/15/2023] Open
Abstract
Prions are known to be involved in neurodegenerative pathologies such as Creutzfeld-Jakob disease. Current models point to a molecular event which rely on a transmissible structural change that leads to the production of β-sheet-rich prion conformer (PrPSc). PrPSc itself has the capability to trigger the structural rearrangement of the ubiquitously present prion (PrPc) substrate in a self-perpetuating cascade. In this article, we demonstrate that recombinant PrPc exists in a conformational equilibrium. The conformers’ abundances were shown to be dependent on PrPc concentration through the formation of transient multimers leading to conformational selection. The study of PrPc mutants that follow dedicated oligomerization pathways demonstrated that the conformers’ relative abundances are modified, thus reinforcing the assertion that the nature of conformers’ interactions orient the oligomerization pathways. Further this result can be viewed as the “signature” of an aborted oligomerization process. This discovery sheds a new light on the possible origin of prion protein diseases, namely that a change in prion protein structure could be transmitted through the formation of transient multimers having different conformer compositions. This could explain the selection of a transient multimeric type that could be viewed as the precursor of PrPSc responsible for structural information transmission, and strain apparition.
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16
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Sacquin-Mora S. Coarse-grain simulations on NMR conformational ensembles highlight functional residues in proteins. J R Soc Interface 2019; 16:20190075. [PMID: 31288649 DOI: 10.1098/rsif.2019.0075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Dynamics are a key feature of protein function, and this is especially true of gating residues, which occupy cavity or tunnel lining positions in the protein structure, and will reversibly switch between open and closed conformations in order to control the diffusion of small molecules within a protein's internal matrix. Earlier work on globins and hydrogenases have shown that these gating residues can be detected using a multiscale scheme combining all-atom classic molecular dynamics simulations and coarse-grain calculations of the resulting conformational ensemble mechanical properties. Here, we show that the structural variations observed in the conformational ensembles produced by NMR spectroscopy experiments are sufficient to induce noticeable mechanical changes in a protein, which in turn can be used to identify residues important for function and forming a mechanical nucleus in the protein core. This new approach, which combines experimental data and rapid coarse-grain calculations and no longer needs to resort to time-consuming all-atom simulations, was successfully applied to five different protein families.
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Affiliation(s)
- Sophie Sacquin-Mora
- Laboratoire de Biochimie Théorique, CNRS UPR9080, Institut de Biologie Physico-Chimique , 13 rue Pierre et Marie Curie, 75005 Paris , France
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17
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Maiti S, Acharya B, Boorla VS, Manna B, Ghosh A, De S. Dynamic Studies on Intrinsically Disordered Regions of Two Paralogous Transcription Factors Reveal Rigid Segments with Important Biological Functions. J Mol Biol 2019; 431:1353-1369. [PMID: 30802457 DOI: 10.1016/j.jmb.2019.02.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Revised: 01/31/2019] [Accepted: 02/15/2019] [Indexed: 10/27/2022]
Abstract
Long stretches of intrinsically disordered regions (IDRs) are abundantly present in eukaryotic transcription factors. Although their biological significance is well appreciated, the underlying structural and dynamic mechanisms of their function are still not clear. Using solution NMR spectroscopy, we have studied the structural and dynamic features of two paralogous HOX transcription factors, SCR and DFD, from Drosophila. Both proteins have a conserved DNA-binding homeodomain and a long stretch of functionally important IDR. Using NMR dynamics, we determined flexibility of each residue in these proteins. The flexibility of the residues in the disordered region is not uniform. In both proteins, the IDRs have short stretches of consecutive residues with relatively less flexibility, that is, higher rigidity. We show that one such rigid segment is specifically recognized by another co-transcription factor, thus highlighting the importance of these rigid segments in IDR-mediated protein-protein interactions. Using molecular dynamics simulation, we further show that the rigid segments sample less conformations compared to the rest of the residues in the disordered region. The restrained conformational sampling of these rigid residues should lower the loss in conformational entropy during their interactions with binding partners resulting in sequence specific binding. This work provides experimental evidence of a "rigid-segment" model of IDRs, where functionally important rigid segments are connected by highly flexible linkers. Furthermore, a comparative study of IDRs in paralogous proteins reveals that in spite of low-sequence conservation, the rigid and flexible segments are sequentially maintained to preserve related functions and regulations of these proteins.
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Affiliation(s)
- Snigdha Maiti
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Bidisha Acharya
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Veda Sheersh Boorla
- Department of Chemical Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Bharat Manna
- School of Energy Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Amit Ghosh
- School of Energy Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Soumya De
- School of Bioscience, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India.
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18
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Hsu A, Ferrage F, Palmer AG. Analysis of NMR Spin-Relaxation Data Using an Inverse Gaussian Distribution Function. Biophys J 2018; 115:2301-2309. [PMID: 30503534 DOI: 10.1016/j.bpj.2018.10.030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 08/28/2018] [Accepted: 10/24/2018] [Indexed: 02/08/2023] Open
Abstract
Spin relaxation in solution-state NMR spectroscopy is a powerful approach to explore the conformational dynamics of biological macromolecules. Probability distribution functions for overall or internal correlation times have been used previously to model spectral density functions central to spin-relaxation theory. Applications to biological macromolecules rely on transverse relaxation rate constants, and when studying nanosecond timescale motions, sampling at ultralow frequencies is often necessary. Consequently, appropriate distribution functions necessitate spectral density functions that are accurate and convergent as frequencies approach zero. In this work, the inverse Gaussian probability distribution function is derived from general properties of spectral density functions at low and high frequencies for macromolecules in solution, using the principle of maximal entropy. This normalized distribution function is first used to calculate the correlation function, followed by the spectral density function. The resulting model-free spectral density functions are finite at a frequency of zero and can be used to describe distributions of either overall or internal correlation times using the model-free ansatz. To validate the approach, 15N spin-relaxation data for the bZip transcription factor domain of the Saccharomyces cerevisiae protein GCN4, in the absence of cognate DNA, were analyzed using the inverse Gaussian probability distribution for intramolecular correlation times. The results extend previous models for the conformational dynamics of the intrinsically disordered, DNA-binding region of the bZip transcription factor domain.
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Affiliation(s)
- Andrew Hsu
- Department of Chemistry, Columbia University, New York, New York
| | - Fabien Ferrage
- Laboratoire des Biomolécules, Département de Chimie, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, Paris, France
| | - Arthur G Palmer
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York.
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19
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Mechanical variations in proteins with large-scale motions highlight the formation of structural locks. J Struct Biol 2018; 203:195-204. [DOI: 10.1016/j.jsb.2018.05.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Revised: 05/18/2018] [Accepted: 05/22/2018] [Indexed: 12/18/2022]
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20
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Enhanced spectral density mapping through combined multiple-field deuterium 13CH 2D methyl spin relaxation NMR spectroscopy. Methods 2017; 138-139:76-84. [PMID: 29288801 DOI: 10.1016/j.ymeth.2017.12.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 12/23/2017] [Accepted: 12/24/2017] [Indexed: 11/23/2022] Open
Abstract
Quadrupolar relaxation of 2H (D) nuclear spins is a powerful probe of conformational dynamics in biological macromolecules. Deuterium relaxation rate constants are determined by the spectral density function for reorientation of the C-D bond vector at zero, single-quantum, and double-quantum 2H frequencies. In the present work, 2H relaxation rate constants were measured for an E. coli ribonuclease H [U-2H, 15N] ILV-[13CH2D] sample using 400, 500, 800, and 900 MHz NMR spectrometers and analyzed by three approaches to determine spectral density values. First, data recorded at each static magnetic field were analyzed independently. Second, data recorded at 400 and 800 MHz were analyzed jointly and data recorded at other fields were analyzed independently. Third, data recorded at 400 and 500 MHz were interpolated to 450 MHz, and the resulting two pairs of data, corresponding to 400 MHz/800 MHz and 450 MHz/900 MHz, were analyzed jointly. The second and third approaches rely on the identity between the double quantum frequency at the lower field and the single quantum frequency at the higher field. Spectral density values for 32 of the 48 resolvable ILV methyl resonances were fit by the Lipari-Szabo model-free formalism and used to validate the three methods. The three spectral density mapping methods performed equally well in cross validation with data recorded at 700 MHz. However, the third method yielded approximately 10-15% more precise estimates of model-free parameters and consequently provides a general strategy for analysis of 2H spin relaxation data in biological macromolecules.
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21
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Kim DN, Sanbonmatsu KY. Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model. Biosci Rep 2017; 37:BSR20170072. [PMID: 28963369 PMCID: PMC5715128 DOI: 10.1042/bsr20170072] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Revised: 09/26/2017] [Accepted: 09/27/2017] [Indexed: 12/16/2022] Open
Abstract
As cryo-electron microscopy (cryo-EM) enters mainstream structural biology, the demand for fitting methods is high. Here, we review existing flexible fitting methods for cryo-EM. We discuss their importance, potential concerns and assessment strategies. We aim to give readers concrete descriptions of cryo-EM flexible fitting methods with corresponding examples.
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Affiliation(s)
- Doo Nam Kim
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, U.S.A
| | - Karissa Y Sanbonmatsu
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, U.S.A.
- New Mexico Consortium, Los Alamos, U.S.A
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22
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Howard RJ, Carnevale V, Delemotte L, Hellmich UA, Rothberg BS. Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport. BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES 2017; 1860:927-942. [PMID: 29258839 DOI: 10.1016/j.bbamem.2017.12.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2017] [Revised: 12/08/2017] [Accepted: 12/14/2017] [Indexed: 11/20/2022]
Abstract
Ion translocation across biological barriers is a fundamental requirement for life. In many cases, controlling this process-for example with neuroactive drugs-demands an understanding of rapid and reversible structural changes in membrane-embedded proteins, including ion channels and transporters. Classical approaches to electrophysiology and structural biology have provided valuable insights into several such proteins over macroscopic, often discontinuous scales of space and time. Integrating these observations into meaningful mechanistic models now relies increasingly on computational methods, particularly molecular dynamics simulations, while surfacing important challenges in data management and conceptual alignment. Here, we seek to provide contemporary context, concrete examples, and a look to the future for bridging disciplinary gaps in biological ion transport. This article is part of a Special Issue entitled: Beyond the Structure-Function Horizon of Membrane Proteins edited by Ute Hellmich, Rupak Doshi and Benjamin McIlwain.
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Affiliation(s)
- Rebecca J Howard
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Box 1031, 17121 Solna, Sweden.
| | - Vincenzo Carnevale
- Institute for Computational Molecular Science, Department of Chemistry, Temple University, Philadelphia, PA 19122, USA.
| | - Lucie Delemotte
- Science for Life Laboratory, Department of Theoretical Physics, KTH Royal Institute of Technology, Box 1031, 17121 Solna, Sweden.
| | - Ute A Hellmich
- Johannes Gutenberg University Mainz, Institute for Pharmacy and Biochemistry, Johann-Joachim-Becherweg 30, 55128 Mainz, Germany; Centre for Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue Str. 9, 60438 Frankfurt, Germany.
| | - Brad S Rothberg
- Department of Medical Genetics and Molecular Biochemistry, Temple University Lewis Katz School of Medicine, Philadelphia, PA 19140, USA.
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23
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Koehler Leman J, D'Avino AR, Bhatnagar Y, Gray JJ. Comparison of NMR and crystal structures of membrane proteins and computational refinement to improve model quality. Proteins 2017; 86:57-74. [PMID: 29044728 DOI: 10.1002/prot.25402] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Revised: 09/27/2017] [Accepted: 10/11/2017] [Indexed: 12/29/2022]
Abstract
Membrane proteins are challenging to study and restraints for structure determination are typically sparse or of low resolution because the membrane environment that surrounds them leads to a variety of experimental challenges. When membrane protein structures are determined by different techniques in different environments, a natural question is "which structure is most biologically relevant?" Towards answering this question, we compiled a dataset of membrane proteins with known structures determined by both solution NMR and X-ray crystallography. By investigating differences between the structures, we found that RMSDs between crystal and NMR structures are below 5 Å in the membrane region, NMR ensembles have a higher convergence in the membrane region, crystal structures typically have a straighter transmembrane region, have higher stereo-chemical correctness, and are more tightly packed. After quantifying these differences, we used high-resolution refinement of the NMR structures to mitigate them, which paves the way for identifying and improving the structural quality of membrane proteins.
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Affiliation(s)
- Julia Koehler Leman
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland.,Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, New York
| | - Andrew R D'Avino
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland.,Department of Biology, Johns Hopkins University, Baltimore, Maryland
| | - Yash Bhatnagar
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Jeffrey J Gray
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland
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24
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Hinck AP, Neira JL. An introduction to the special issue on biomolecular NMR. Arch Biochem Biophys 2017; 628:1-2. [PMID: 28666741 DOI: 10.1016/j.abb.2017.06.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Andrew P Hinck
- Department of Structural Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
| | - Jose L Neira
- Instituto de Biología Molecular y Celular, Universidad Miguel Hernández de Elche, Elche, Alicante 03202, Spain.
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