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Meshach Paul D, Rajasekaran R. In silico approach to explore the disruption in the molecular mechanism of human hyaluronidase 1 by mutant E268K that directs Natowicz syndrome. EUROPEAN BIOPHYSICS JOURNAL: EBJ 2016; 46:157-169. [PMID: 27424109 DOI: 10.1007/s00249-016-1151-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Revised: 06/02/2016] [Accepted: 07/01/2016] [Indexed: 01/27/2023]
Abstract
Natowicz syndrome (mucopolysaccharidoses type 9) is a lysosomal storage disorder caused by deficient or defective human hyaluronidase 1. The disorder is not well studied at the molecular level. Therefore, a new in silico approach was proposed to study the molecular basis on which one clinically observed mutation, Glu268Lys, results in a defective enzyme. The native and mutant structures were subjected to comparative analyses using a conformational sampling approach for geometrical variables viz, RMSF, RMSD, and Ramachandran plot. In addition, the strength of a Cys207-Cys221 disulfide bond and electrostatic interaction between Arg265 and Asp206 were studied, as they are known to be involved in the catalytic activity of the enzyme. Native and mutant E268K showed statistically significant variations with p < 0.05 in RMSD, Ramachandran plot, strengths of disulfide bond, and electrostatic interactions. Further, single model analysis showed variations between native and mutant structures in terms of intra-protein interactions, hydrogen bond dilution, secondary structure, and dihedral angles. Docking analysis predicted the mutant to have a less favorable substrate binding energy compared to the native protein. Additionally, steered MD analysis indicated that the substrate should have more affinity to the native than mutant enzymes. The observed changes theoretically explain the less favorable binding energy of substrate towards mutant E268K, thereby providing a structural basis for its reduced catalytic activity. Hence, our study provides a basis for understanding the disruption in the molecular mechanism of human hyaluronidase 1 by mutation E268K, which may prove useful for the development of synthetic chaperones as a treatment option for Natowicz syndrome.
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Affiliation(s)
- D Meshach Paul
- Computational Biology Lab, Department of Biotechnology, School of Bio Sciences and Technology, VIT University, Vellore, 632014, Tamil Nadu, India
| | - R Rajasekaran
- Computational Biology Lab, Department of Biotechnology, School of Bio Sciences and Technology, VIT University, Vellore, 632014, Tamil Nadu, India.
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2
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Abstract
Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect intrinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein. Results: We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displacements and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts’ intuitive assessment of computational models and provides information of practical usefulness of models. Availability and implementation:https://bitbucket.org/mjamroz/flexscore Contact:dkihara@purdue.edu Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Michal Jamroz
- Department of Chemistry, University of Warsaw, Warsaw, 02-093, Poland
| | - Andrzej Kolinski
- Department of Chemistry, University of Warsaw, Warsaw, 02-093, Poland
| | - Daisuke Kihara
- Department of Biological Sciences Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
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Measuring and modeling diffuse scattering in protein X-ray crystallography. Proc Natl Acad Sci U S A 2016; 113:4069-74. [PMID: 27035972 DOI: 10.1073/pnas.1524048113] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
X-ray diffraction has the potential to provide rich information about the structural dynamics of macromolecules. To realize this potential, both Bragg scattering, which is currently used to derive macromolecular structures, and diffuse scattering, which reports on correlations in charge density variations, must be measured. Until now, measurement of diffuse scattering from protein crystals has been scarce because of the extra effort of collecting diffuse data. Here, we present 3D measurements of diffuse intensity collected from crystals of the enzymes cyclophilin A and trypsin. The measurements were obtained from the same X-ray diffraction images as the Bragg data, using best practices for standard data collection. To model the underlying dynamics in a practical way that could be used during structure refinement, we tested translation-libration-screw (TLS), liquid-like motions (LLM), and coarse-grained normal-modes (NM) models of protein motions. The LLM model provides a global picture of motions and was refined against the diffuse data, whereas the TLS and NM models provide more detailed and distinct descriptions of atom displacements, and only used information from the Bragg data. Whereas different TLS groupings yielded similar Bragg intensities, they yielded different diffuse intensities, none of which agreed well with the data. In contrast, both the LLM and NM models agreed substantially with the diffuse data. These results demonstrate a realistic path to increase the number of diffuse datasets available to the wider biosciences community and indicate that dynamics-inspired NM structural models can simultaneously agree with both Bragg and diffuse scattering.
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Senthilkumar B, Kumar P, Rajasekaran R. In-Silico Template Selection of In-Vitro Evolved Kalata B1 ofOldenlandia Affinisfor Scaffolding Peptide-Based Drug Design. J Cell Biochem 2015; 117:66-73. [DOI: 10.1002/jcb.25248] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 05/29/2015] [Indexed: 12/20/2022]
Affiliation(s)
- B. Senthilkumar
- Bioinformatics Division; School of Bio Sciences and Technology; Vellore Institute of Technology University; Vellore 632014 Tamil Nadu India
| | - Prakash Kumar
- Bioinformatics Division; School of Bio Sciences and Technology; Vellore Institute of Technology University; Vellore 632014 Tamil Nadu India
| | - R. Rajasekaran
- Bioinformatics Division; School of Bio Sciences and Technology; Vellore Institute of Technology University; Vellore 632014 Tamil Nadu India
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Kuzmanic A, Pannu NS, Zagrovic B. X-ray refinement significantly underestimates the level of microscopic heterogeneity in biomolecular crystals. Nat Commun 2015; 5:3220. [PMID: 24504120 PMCID: PMC3926004 DOI: 10.1038/ncomms4220] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2013] [Accepted: 01/07/2014] [Indexed: 11/09/2022] Open
Abstract
Biomolecular X-ray structures typically provide a static, time- and ensemble-averaged view of molecular ensembles in crystals. In the absence of rigid-body motions and lattice defects, B-factors are thought to accurately reflect the structural heterogeneity of such ensembles. In order to study the effects of averaging on B-factors, we employ molecular dynamics simulations to controllably manipulate microscopic heterogeneity of a crystal containing 216 copies of villin headpiece. Using average structure factors derived from simulation, we analyse how well this heterogeneity is captured by high-resolution molecular-replacement-based model refinement. We find that both isotropic and anisotropic refined B-factors often significantly deviate from their actual values known from simulation: even at high 1.0 Å resolution and Rfree of 5.9%, B-factors of some well-resolved atoms underestimate their actual values even sixfold. Our results suggest that conformational averaging and inadequate treatment of correlated motion considerably influence estimation of microscopic heterogeneity via B-factors, and invite caution in their interpretation.
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Affiliation(s)
- Antonija Kuzmanic
- Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna, Campus Vienna Biocenter 5, A-1030 Vienna, Austria
| | - Navraj S Pannu
- Biophysical Structural Chemistry, Leiden University, PO Box 9502, 2300 RA Leiden, The Netherlands
| | - Bojan Zagrovic
- Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna, Campus Vienna Biocenter 5, A-1030 Vienna, Austria
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Van Benschoten AH, Afonine PV, Terwilliger TC, Wall ME, Jackson CJ, Sauter NK, Adams PD, Urzhumtsev A, Fraser JS. Predicting X-ray diffuse scattering from translation-libration-screw structural ensembles. ACTA CRYSTALLOGRAPHICA. SECTION D, BIOLOGICAL CRYSTALLOGRAPHY 2015; 71:1657-67. [PMID: 26249347 PMCID: PMC4528799 DOI: 10.1107/s1399004715007415] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Accepted: 04/15/2015] [Indexed: 01/01/2023]
Abstract
Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling and validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier's equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation-libration-screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls_as_xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophosphodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. These methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis.
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Affiliation(s)
- Andrew H. Van Benschoten
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Pavel V. Afonine
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | | | - Michael E. Wall
- Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
| | - Colin J. Jackson
- Research School of Chemistry, Australian National University, Canberra, ACT 2601, Australia
| | - Nicholas K. Sauter
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Paul D. Adams
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, USA
| | - Alexandre Urzhumtsev
- Centre for Integrative Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS–INSERM–UdS, 1 Rue Laurent Fries, BP 10142, 67404 Illkirch, France
- Faculté des Sciences et Technologies, Université de Lorraine, BP 239, 54506 Vandoeuvre-les-Nancy, France
| | - James S. Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
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Ardèvol A, Rovira C. Reaction Mechanisms in Carbohydrate-Active Enzymes: Glycoside Hydrolases and Glycosyltransferases. Insights from ab Initio Quantum Mechanics/Molecular Mechanics Dynamic Simulations. J Am Chem Soc 2015; 137:7528-47. [DOI: 10.1021/jacs.5b01156] [Citation(s) in RCA: 151] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Albert Ardèvol
- Departament
de Química Orgànica and Institut de Química Teòrica
i Computacional (IQTCUB), Universitat de Barcelona, Martí
i Franquès 1, 08028 Barcelona, Spain
| | - Carme Rovira
- Departament
de Química Orgànica and Institut de Química Teòrica
i Computacional (IQTCUB), Universitat de Barcelona, Martí
i Franquès 1, 08028 Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys, 23, 08018 Barcelona, Spain
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E pluribus unum, no more: from one crystal, many conformations. Curr Opin Struct Biol 2014; 28:56-62. [PMID: 25113271 DOI: 10.1016/j.sbi.2014.07.005] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2014] [Revised: 07/10/2014] [Accepted: 07/18/2014] [Indexed: 11/22/2022]
Abstract
Several distinct computational approaches have recently been implemented to represent conformational heterogeneity from X-ray crystallography datasets that are averaged in time and space. As these modeling methods mature, newly discovered alternative conformations are being used to derive functional protein mechanisms. Room temperature X-ray data collection is emerging as a key variable for sampling functionally relevant conformations also observed in solution studies. Although concerns about radiation damage are warranted with higher temperature data collection, 'diffract and destroy' strategies on X-ray free electron lasers may permit radiation damage-free data collection. X-ray crystallography need not be confined to 'static unique snapshots'; these experimental and computational advances are revealing how the many conformations populated within a single crystal are used in biological mechanisms.
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Affiliation(s)
- Riccardo Baron
- Department of Medicinal Chemistry, College of Pharmacy, and The Henry Eyring Center for Theoretical Chemistry, The University of Utah, Salt Lake City, Utah 84112-5820;
| | - J. Andrew McCammon
- Howard Hughes Medical Institute, Department of Chemistry and Biochemistry, Department of Pharmacology, and Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, California 92093-0365;
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Polyansky AA, Kuzmanic A, Hlevnjak M, Zagrovic B. On the Contribution of Linear Correlations to Quasi-harmonic Conformational Entropy in Proteins. J Chem Theory Comput 2012; 8:3820-9. [PMID: 26593023 DOI: 10.1021/ct300082q] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We study the contribution of linear, pairwise atom-positional correlations (covariances) to absolute and relative conformational entropy as calculated by quasi-harmonic analysis of molecular dynamics (MD) trajectories (SQH and ΔSQH). By analyzing a total of 25 μs of MD simulations of ubiquitin and six of its binding partners in bound and unbound states, and 2.4 μs of simulations of eight different proteins in phosphorylated and unphosphorylated states, we show that ΔSQH represents a remarkably constant fraction of a quasi-harmonic entropy change obtained if one ignores the contribution of covariance terms and uses mass-weighted atom-positional variances only (ΔSVAR). In other words, the relative contribution of linear correlations to conformational entropy change for different proteins and in different biomolecular processes appears to be largely constant. Based on this, we establish an empirical relationship between relative quasi-harmonic conformational entropy and changes in crystallographic B-factors induced by different processes, and we use it to estimate conformational-entropic contribution to the free energy of binding for a large set of protein complexes based on their X-ray structures. Our results suggest a simple way for relating other types of dynamical observables with conformational entropy in the absence of information on correlated motions, such as in the case of NMR order parameters.
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Affiliation(s)
- Anton A Polyansky
- Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna , Campus Vienna Biocenter 5, Vienna, AT-1030, Austria
| | - Antonija Kuzmanic
- Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna , Campus Vienna Biocenter 5, Vienna, AT-1030, Austria
| | - Mario Hlevnjak
- Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna , Campus Vienna Biocenter 5, Vienna, AT-1030, Austria
| | - Bojan Zagrovic
- Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna , Campus Vienna Biocenter 5, Vienna, AT-1030, Austria
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