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Fiorucci L, Schiavina M, Felli IC, Pierattelli R, Ravera E. Are Protein Conformational Ensembles in Agreement with Experimental Data? A Geometrical Interpretation of the Problem. J Chem Inf Model 2024. [PMID: 38959217 DOI: 10.1021/acs.jcim.4c00582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2024]
Abstract
The conformational variability of biological macromolecules can play an important role in their biological function. Therefore, understanding conformational variability is expected to be key for predicting the behavior of a particular molecule in the context of organism-wide studies. Several experimental methods have been developed and deployed for accessing this information, and computational methods are continuously updated for the profitable integration of different experimental sources. The outcome of this endeavor is conformational ensembles, which may vary significantly in properties and composition when different ensemble reconstruction methods are used, and this raises the issue of comparing the predicted ensembles against experimental data. In this article, we discuss a geometrical formulation to provide a framework for understanding the agreement of an ensemble prediction to the experimental observations.
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Affiliation(s)
- Letizia Fiorucci
- Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
| | - Marco Schiavina
- Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
| | - Isabella C Felli
- Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
| | - Roberta Pierattelli
- Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
| | - Enrico Ravera
- Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy
- Florence Data Science, University of Florence, Viale G.B. Morgagni 59, 50134 Florence, Italy
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2
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Roy R, Geng A, Shi H, Merriman DK, Dethoff EA, Salmon L, Al-Hashimi HM. Kinetic Resolution of the Atomic 3D Structures Formed by Ground and Excited Conformational States in an RNA Dynamic Ensemble. J Am Chem Soc 2023; 145:22964-22978. [PMID: 37831584 DOI: 10.1021/jacs.3c04614] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Abstract
Knowing the 3D structures formed by the various conformations populating the RNA free-energy landscape, their relative abundance, and kinetic interconversion rates is required to obtain a quantitative and predictive understanding of how RNAs fold and function at the atomic level. While methods integrating ensemble-averaged experimental data with computational modeling are helping define the most abundant conformations in RNA ensembles, elucidating their kinetic rates of interconversion and determining the 3D structures of sparsely populated short-lived RNA excited conformational states (ESs) remains challenging. Here, we developed an approach integrating Rosetta-FARFAR RNA structure prediction with NMR residual dipolar couplings and relaxation dispersion that simultaneously determines the 3D structures formed by the ground-state (GS) and ES subensembles, their relative abundance, and kinetic rates of interconversion. The approach is demonstrated on HIV-1 TAR, whose six-nucleotide apical loop was previously shown to form a sparsely populated (∼13%) short-lived (lifetime ∼ 45 μs) ES. In the GS, the apical loop forms a broad distribution of open conformations interconverting on the pico-to-nanosecond time scale. Most residues are unpaired and preorganized to bind the Tat-superelongation protein complex. The apical loop zips up in the ES, forming a narrow distribution of closed conformations, which sequester critical residues required for protein recognition. Our work introduces an approach for determining the 3D ensemble models formed by sparsely populated RNA conformational states, provides a rare atomic view of an RNA ES, and kinetically resolves the atomic 3D structures of RNA conformational substates, interchanging on time scales spanning 6 orders of magnitude, from picoseconds to microseconds.
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Affiliation(s)
- Rohit Roy
- Center for Genomic and Computational Biology, Duke University School of Medicine, Durham, North Carolina 27710, United States
| | - Ainan Geng
- Department of Biochemistry, Duke University School of Medicine, Durham, North Carolina 27710, United States
| | - Honglue Shi
- Department of Chemistry, Duke University, Durham, North Carolina 27708, United States
| | - Dawn K Merriman
- Department of Chemistry, Duke University, Durham, North Carolina 27708, United States
| | - Elizabeth A Dethoff
- Department of Chemistry and Biophysics, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Loïc Salmon
- Department of Chemistry and Biophysics, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Hashim M Al-Hashimi
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032, United States
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3
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Kovács D, Bodor A. The influence of random-coil chemical shifts on the assessment of structural propensities in folded proteins and IDPs. RSC Adv 2023; 13:10182-10203. [PMID: 37006359 PMCID: PMC10065145 DOI: 10.1039/d3ra00977g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 03/15/2023] [Indexed: 04/03/2023] Open
Abstract
In studying secondary structural propensities of proteins by nuclear magnetic resonance (NMR) spectroscopy, secondary chemical shifts (SCSs) serve as the primary atomic scale observables. For SCS calculation, the selection of an appropriate random coil chemical shift (RCCS) dataset is a crucial step, especially when investigating intrinsically disordered proteins (IDPs). The scientific literature is abundant in such datasets, however, the effect of choosing one over all the others in a concrete application has not yet been studied thoroughly and systematically. Hereby, we review the available RCCS prediction methods and to compare them, we conduct statistical inference by means of the nonparametric sum of ranking differences and comparison of ranks to random numbers (SRD-CRRN) method. We try to find the RCCS predictors best representing the general consensus regarding secondary structural propensities. The existence and the magnitude of resulting differences on secondary structure determination under varying sample conditions (temperature, pH) are demonstrated and discussed for globular proteins and especially IDPs.
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Affiliation(s)
- Dániel Kovács
- ELTE, Eötvös Loránd University, Institute of Chemistry, Analytical and BioNMR Laboratory Pázmány Péter sétány 1/A Budapest 1117 Hungary
- Eötvös Loránd University, Hevesy György PhD School of Chemistry Pázmány Péter sétány 1/A Budapest 1117 Hungary
| | - Andrea Bodor
- ELTE, Eötvös Loránd University, Institute of Chemistry, Analytical and BioNMR Laboratory Pázmány Péter sétány 1/A Budapest 1117 Hungary
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4
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Sethio D, Poongavanam V, Xiong R, Tyagi M, Duy Vo D, Lindh R, Kihlberg J. Simulation Reveals the Chameleonic Behavior of Macrocycles. J Chem Inf Model 2023; 63:138-146. [PMID: 36563083 PMCID: PMC9832480 DOI: 10.1021/acs.jcim.2c01093] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Conformational analysis is central to the design of bioactive molecules. It is particularly challenging for macrocycles due to noncovalent transannular interactions, steric interactions, and ring strain that are often coupled. Herein, we simulated the conformations of five macrocycles designed to express a progression of increasing complexity in environment-dependent intramolecular interactions and verified the results against NMR measurements in chloroform and dimethyl sulfoxide. Molecular dynamics using an explicit solvent model, but not the Monte Carlo method with implicit solvation, handled both solvents correctly. Refinement of conformations at the ab initio level was fundamental to reproducing the experimental observations─standard state-of-the-art molecular mechanics force fields were insufficient. Our simulations correctly predicted the intramolecular interactions between side chains and the macrocycle and revealed an unprecedented solvent-induced conformational switch of the macrocyclic ring. Our results provide a platform for the rational, prospective design of molecular chameleons that adapt to the properties of the environment.
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5
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Bakker MJ, Mládek A, Semrád H, Zapletal V, Pavlíková Přecechtělová J. Improving IDP theoretical chemical shift accuracy and efficiency through a combined MD/ADMA/DFT and machine learning approach. Phys Chem Chem Phys 2022; 24:27678-27692. [PMID: 36373847 DOI: 10.1039/d2cp01638a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
This work extends the multi-scale computational scheme for the quantum mechanics (QM) calculations of Nuclear Magnetic Resonance (NMR) chemical shifts (CSs) in proteins that lack a well-defined 3D structure. The scheme couples the sampling of an intrinsically disordered protein (IDP) by classical molecular dynamics (MD) with protein fragmentation using the adjustable density matrix assembler (ADMA) and density functional theory (DFT) calculations. In contrast to our early investigation on IDPs (Pavlíková Přecechtělová et al., J. Chem. Theory Comput., 2019, 15, 5642-5658) and the state-of-the art NMR calculations for structured proteins, a partial re-optimization was implemented on the raw MD geometries in vibrational normal mode coordinates to enhance the accuracy of the MD/ADMA/DFT computational scheme. In addition, machine-learning based cluster analysis was performed on the scheme to explore its potential in producing protein structure ensembles (CLUSTER ensembles) that yield accurate CSs at a reduced computational cost. The performance of the cluster-based calculations is validated against results obtained with conventional structural ensembles consisting of MD snapshots extracted from the MD trajectory at regular time intervals (REGULAR ensembles). CS calculations performed with the refined MD/ADMA/DFT framework employed the 6-311++G(d,p) basis set that outperformed IGLO-III calculations with the same density functional approximation (B3LYP) and both explicit and implicit solvation. The partial geometry optimization did not universally improve the agreement of computed CSs with the experiment but substantially decreased errors associated with the ensemble averaging. A CLUSTER ensemble with 50 structures yielded ensemble averages close to those obtained with a REGULAR ensemble consisting of 500 MD frames. The cluster based calculations thus required only a fraction of the computational time.
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Affiliation(s)
- Michael J Bakker
- Faculty of Pharmacy in Hradec Králové, Charles University, Akademika Heyrovského 1203/8, 500 05 Hradec Králové, Czech Republic.
| | - Arnošt Mládek
- Faculty of Pharmacy in Hradec Králové, Charles University, Akademika Heyrovského 1203/8, 500 05 Hradec Králové, Czech Republic.
| | - Hugo Semrád
- Faculty of Pharmacy in Hradec Králové, Charles University, Akademika Heyrovského 1203/8, 500 05 Hradec Králové, Czech Republic. .,Department of Chemistry, Faculty of Science, Masaryk University, Kotlářská 267/2, 611 37 Brno, Czech Republic
| | - Vojtěch Zapletal
- Faculty of Pharmacy in Hradec Králové, Charles University, Akademika Heyrovského 1203/8, 500 05 Hradec Králové, Czech Republic.
| | - Jana Pavlíková Přecechtělová
- Faculty of Pharmacy in Hradec Králové, Charles University, Akademika Heyrovského 1203/8, 500 05 Hradec Králové, Czech Republic.
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Abstract
In-cell structural biology aims at extracting structural information about proteins or nucleic acids in their native, cellular environment. This emerging field holds great promise and is already providing new facts and outlooks of interest at both fundamental and applied levels. NMR spectroscopy has important contributions on this stage: It brings information on a broad variety of nuclei at the atomic scale, which ensures its great versatility and uniqueness. Here, we detail the methods, the fundamental knowledge, and the applications in biomedical engineering related to in-cell structural biology by NMR. We finally propose a brief overview of the main other techniques in the field (EPR, smFRET, cryo-ET, etc.) to draw some advisable developments for in-cell NMR. In the era of large-scale screenings and deep learning, both accurate and qualitative experimental evidence are as essential as ever to understand the interior life of cells. In-cell structural biology by NMR spectroscopy can generate such a knowledge, and it does so at the atomic scale. This review is meant to deliver comprehensive but accessible information, with advanced technical details and reflections on the methods, the nature of the results, and the future of the field.
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Affiliation(s)
- Francois-Xavier Theillet
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France
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7
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Rapid and accurate determination of atomistic RNA dynamic ensemble models using NMR and structure prediction. Nat Commun 2020; 11:5531. [PMID: 33139729 PMCID: PMC7608651 DOI: 10.1038/s41467-020-19371-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Accepted: 10/07/2020] [Indexed: 11/08/2022] Open
Abstract
Biomolecules form dynamic ensembles of many inter-converting conformations which are key for understanding how they fold and function. However, determining ensembles is challenging because the information required to specify atomic structures for thousands of conformations far exceeds that of experimental measurements. We addressed this data gap and dramatically simplified and accelerated RNA ensemble determination by using structure prediction tools that leverage the growing database of RNA structures to generate a conformation library. Refinement of this library with NMR residual dipolar couplings provided an atomistic ensemble model for HIV-1 TAR, and the model accuracy was independently supported by comparisons to quantum-mechanical calculations of NMR chemical shifts, comparison to a crystal structure of a substate, and through designed ensemble redistribution via atomic mutagenesis. Applications to TAR bulge variants and more complex tertiary RNAs support the generality of this approach and the potential to make the determination of atomic-resolution RNA ensembles routine. Determining dynamic ensembles of biomolecules is still challenging. Here the authors present an approach for rapid RNA ensemble determination that combines RNA structure prediction tools and NMR residual dipolar coupling data and use it to determine atomistic ensemble models for a variety of RNAs.
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8
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Bernetti M, Bertazzo M, Masetti M. Data-Driven Molecular Dynamics: A Multifaceted Challenge. Pharmaceuticals (Basel) 2020; 13:E253. [PMID: 32961909 PMCID: PMC7557855 DOI: 10.3390/ph13090253] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 09/14/2020] [Accepted: 09/16/2020] [Indexed: 12/18/2022] Open
Abstract
The big data concept is currently revolutionizing several fields of science including drug discovery and development. While opening up new perspectives for better drug design and related strategies, big data analysis strongly challenges our current ability to manage and exploit an extraordinarily large and possibly diverse amount of information. The recent renewal of machine learning (ML)-based algorithms is key in providing the proper framework for addressing this issue. In this respect, the impact on the exploitation of molecular dynamics (MD) simulations, which have recently reached mainstream status in computational drug discovery, can be remarkable. Here, we review the recent progress in the use of ML methods coupled to biomolecular simulations with potentially relevant implications for drug design. Specifically, we show how different ML-based strategies can be applied to the outcome of MD simulations for gaining knowledge and enhancing sampling. Finally, we discuss how intrinsic limitations of MD in accurately modeling biomolecular systems can be alleviated by including information coming from experimental data.
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Affiliation(s)
- Mattia Bernetti
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), via Bonomea 265, I-34136 Trieste, Italy;
| | - Martina Bertazzo
- Computational Sciences, Istituto Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy;
| | - Matteo Masetti
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum—Università di Bologna, via Belmeloro 6, I-40126 Bologna, Italy
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9
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Li J, Bennett KC, Liu Y, Martin MV, Head-Gordon T. Accurate prediction of chemical shifts for aqueous protein structure on "Real World" data. Chem Sci 2020; 11:3180-3191. [PMID: 34122823 PMCID: PMC8152569 DOI: 10.1039/c9sc06561j] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Accepted: 03/02/2020] [Indexed: 02/04/2023] Open
Abstract
Here we report a new machine learning algorithm for protein chemical shift prediction that outperforms existing chemical shift calculators on realistic data that is not heavily curated, nor eliminates test predictions ad hoc. Our UCBShift predictor implements two modules: a transfer prediction module that employs both sequence and structural alignment to select reference candidates for experimental chemical shift replication, and a redesigned machine learning module based on random forest regression which utilizes more, and more carefully curated, feature extracted data. When combined together, this new predictor achieves state-of-the-art accuracy for predicting chemical shifts on a randomly selected dataset without careful curation, with root-mean-square errors of 0.31 ppm for amide hydrogens, 0.19 ppm for Hα, 0.84 ppm for C', 0.81 ppm for Cα, 1.00 ppm for Cβ, and 1.81 ppm for N. When similar sequences or structurally related proteins are available, UCBShift shows superior native state selection from misfolded decoy sets compared to SPARTA+ and SHIFTX2, and even without homology we exceed current prediction accuracy of all other popular chemical shift predictors.
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Affiliation(s)
- Jie Li
- Pitzer Center for Theoretical Chemistry, University of California Berkeley CA 94720 USA
- Department of Chemistry, University of California Berkeley CA 94720 USA
| | - Kochise C Bennett
- Pitzer Center for Theoretical Chemistry, University of California Berkeley CA 94720 USA
- Department of Chemistry, University of California Berkeley CA 94720 USA
| | - Yuchen Liu
- Pitzer Center for Theoretical Chemistry, University of California Berkeley CA 94720 USA
- Department of Chemistry, University of California Berkeley CA 94720 USA
| | - Michael V Martin
- Department of Bioengineering, University of California Berkeley CA 94720 USA
| | - Teresa Head-Gordon
- Pitzer Center for Theoretical Chemistry, University of California Berkeley CA 94720 USA
- Department of Chemistry, University of California Berkeley CA 94720 USA
- Department of Bioengineering, University of California Berkeley CA 94720 USA
- Department of Chemical and Biomolecular Engineering, University of California Berkeley CA 94720 USA
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10
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Pavlíková Přecechtělová J, Mládek A, Zapletal V, Hritz J. Quantum Chemical Calculations of NMR Chemical Shifts in Phosphorylated Intrinsically Disordered Proteins. J Chem Theory Comput 2019; 15:5642-5658. [DOI: 10.1021/acs.jctc.8b00257] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Jana Pavlíková Přecechtělová
- Faculty of Pharmacy in Hradec Králové, Charles University, Akademika Heyrovského 1203, 500 05 Hradec Králové, Czech Republic
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11
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Zhou H, Sathyamoorthy B, Stelling A, Xu Y, Xue Y, Pigli YZ, Case DA, Rice PA, Al-Hashimi HM. Characterizing Watson-Crick versus Hoogsteen Base Pairing in a DNA-Protein Complex Using Nuclear Magnetic Resonance and Site-Specifically 13C- and 15N-Labeled DNA. Biochemistry 2019; 58:1963-1974. [PMID: 30950607 DOI: 10.1021/acs.biochem.9b00027] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
A( syn)-T and G( syn)-C+ Hoogsteen base pairs in protein-bound DNA duplexes can be difficult to resolve by X-ray crystallography due to ambiguous electron density and by nuclear magnetic resonance (NMR) spectroscopy due to poor chemical shift dispersion and size limitations with solution-state NMR spectroscopy. Here we describe an NMR strategy for characterizing Hoogsteen base pairs in protein-DNA complexes, which relies on site-specifically incorporating 13C- and 15N-labeled nucleotides into DNA duplexes for unambiguous resonance assignment and to improve spectral resolution. The approach was used to resolve the conformation of an A-T base pair in a crystal structure of an ∼43 kDa complex between a 34 bp duplex DNA and the integration host factor (IHF) protein. In the crystal structure (Protein Data Bank entry 1IHF ), this base pair adopts an unusual Hoogsteen conformation with a distorted sugar backbone that is accommodated by a nearby nick used to aid in crystallization. The NMR chemical shifts and interproton nuclear Overhauser effects indicate that this base pair predominantly adopts a Watson-Crick conformation in the intact DNA-IHF complex under solution conditions. Consistent with these NMR findings, substitution of 7-deazaadenine at this base pair resulted in only a small (∼2-fold) decrease in the IHF-DNA binding affinity. The NMR strategy provides a new approach for resolving crystallographic ambiguity and more generally for studying the structure and dynamics of protein-DNA complexes in solution.
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Affiliation(s)
- Huiqing Zhou
- Department of Biochemistry , Duke University School of Medicine , Durham , North Carolina 27710 , United States
| | - Bharathwaj Sathyamoorthy
- Department of Chemistry , Indian Institute of Science Education and Research Bhopal , Bhopal 462066 , India
| | - Allison Stelling
- Department of Biochemistry , Duke University School of Medicine , Durham , North Carolina 27710 , United States
| | - Yu Xu
- Department of Chemistry , Duke University , Durham , North Carolina 27708 , United States
| | - Yi Xue
- Tsinghua-Peking Center for Life Sciences, School of Life Sciences , Tsinghua University , Beijing 100084 , China
| | - Ying Zhang Pigli
- Biochemistry and Molecular Biology , The University of Chicago , Chicago , Illinois 60637 , United States
| | - David A Case
- Department of Chemistry and Chemical Biology , Rutgers University , Piscataway , New Jersey 08854 , United States
| | - Phoebe A Rice
- Biochemistry and Molecular Biology , The University of Chicago , Chicago , Illinois 60637 , United States
| | - Hashim M Al-Hashimi
- Department of Biochemistry , Duke University School of Medicine , Durham , North Carolina 27710 , United States.,Department of Chemistry , Duke University , Durham , North Carolina 27708 , United States
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12
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Kumari P, Frey L, Sobol A, Lakomek NA, Riek R. 15N transverse relaxation measurements for the characterization of µs-ms dynamics are deteriorated by the deuterium isotope effect on 15N resulting from solvent exchange. JOURNAL OF BIOMOLECULAR NMR 2018; 72:125-137. [PMID: 30306288 DOI: 10.1007/s10858-018-0211-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Accepted: 10/03/2018] [Indexed: 06/08/2023]
Abstract
15N R2 relaxation measurements are key for the elucidation of the dynamics of both folded and intrinsically disordered proteins (IDPs). Here we show, on the example of the intrinsically disordered protein α-synuclein and the folded domain PDZ2, that at physiological pH and near physiological temperatures amide-water exchange can severely skew Hahn-echo based 15N R2 relaxation measurements as well as low frequency data points in CPMG relaxation dispersion experiments. The nature thereof is the solvent exchange with deuterium in the sample buffer, which modulates the 15N chemical shift tensor via the deuterium isotope effect, adding to the apparent relaxation decay which leads to systematic errors in the relaxation data. This results in an artificial increase of the measured apparent 15N R2 rate constants-which should not be mistaken with protein inherent chemical exchange contributions, Rex, to 15N R2. For measurements of 15N R2 rate constants of IDPs and folded proteins at physiological temperatures and pH, we recommend therefore the use of a very low D2O molar fraction in the sample buffer, as low as 1%, or the use of an external D2O reference along with a modified 15N R2 Hahn-echo based experiment. This combination allows for the measurement of Rex contributions to 15N R2 originating from conformational exchange in a time window from µs to ms.
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Affiliation(s)
- Pratibha Kumari
- Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland
| | - Lukas Frey
- Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland
| | - Alexander Sobol
- Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland
| | - Nils-Alexander Lakomek
- Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland.
| | - Roland Riek
- Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland.
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13
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Fritz M, Quinn CM, Wang M, Hou G, Lu X, Koharudin LMI, Struppe J, Case DA, Polenova T, Gronenborn AM. Determination of accurate backbone chemical shift tensors in microcrystalline proteins by integrating MAS NMR and QM/MM. Phys Chem Chem Phys 2018; 20:9543-9553. [PMID: 29577158 PMCID: PMC5892194 DOI: 10.1039/c8cp00647d] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Chemical shifts are highly sensitive probes of local conformation and overall structure. Both isotropic shifts and chemical shift tensors are readily accessible from NMR experiments but their quantum mechanical calculations remain challenging. In this work, we report and compare accurately measured and calculated 15NH and 13Cα chemical shift tensors in proteins, using the microcrystalline agglutinin from Oscillatoria agardhii (OAA). Experimental 13Cα and 15NH chemical tensors were obtained by solid-state NMR spectroscopy, employing tailored recoupling sequences, and for their quantum mechanics/molecular mechanics (QM/MM) calculations different sets of functionals were evaluated. We show that 13Cα chemical shift tensors are primarily determined by backbone dihedral angles and dynamics, while 15NH tensors mainly depend on local electrostatic contributions from solvation and hydrogen bonding. In addition, the influence of including crystallographic waters, the molecular mechanics geometry optimization protocol, and the level of theory on the accuracy of the calculated chemical shift tensors is discussed. Specifically, the power of QM/MM calculations in accurately predicting the unusually upfield shifted 1HN G26 and G93 resonances is highlighted. Our integrated approach is expected to benefit structure refinement of proteins and protein assemblies.
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Affiliation(s)
- Matthew Fritz
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, United States
- Pittsburgh Center for HIV Protein Interactions, University of Pittsburgh School of Medicine, 1051 Biomedical Science Tower 3, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
| | - Caitlin M. Quinn
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, United States
- Pittsburgh Center for HIV Protein Interactions, University of Pittsburgh School of Medicine, 1051 Biomedical Science Tower 3, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
| | - Mingzhang Wang
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, United States
- Pittsburgh Center for HIV Protein Interactions, University of Pittsburgh School of Medicine, 1051 Biomedical Science Tower 3, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
| | - Guangjin Hou
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, United States
| | - Xingyu Lu
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, United States
- Pittsburgh Center for HIV Protein Interactions, University of Pittsburgh School of Medicine, 1051 Biomedical Science Tower 3, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
| | - Leonardus M. I. Koharudin
- Pittsburgh Center for HIV Protein Interactions, University of Pittsburgh School of Medicine, 1051 Biomedical Science Tower 3, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
- Department of Structural Biology, University of Pittsburgh School of Medicine, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
| | - Jochem Struppe
- Bruker Biospin Corporation, 15 Fortune Drive, Billerica, MA, United States
| | - David A. Case
- Department of Chemistry and Chemical Biology, Rutgers University, 174 Frelinghuysen Road, Piscataway, NJ 08854-8087, United States
| | - Tatyana Polenova
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, United States
- Pittsburgh Center for HIV Protein Interactions, University of Pittsburgh School of Medicine, 1051 Biomedical Science Tower 3, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
| | - Angela M. Gronenborn
- Pittsburgh Center for HIV Protein Interactions, University of Pittsburgh School of Medicine, 1051 Biomedical Science Tower 3, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
- Department of Structural Biology, University of Pittsburgh School of Medicine, 3501 Fifth Ave., Pittsburgh, PA 15261, United States
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14
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Shi H, Clay MC, Rangadurai A, Sathyamoorthy B, Case DA, Al-Hashimi HM. Atomic structures of excited state A-T Hoogsteen base pairs in duplex DNA by combining NMR relaxation dispersion, mutagenesis, and chemical shift calculations. JOURNAL OF BIOMOLECULAR NMR 2018; 70:229-244. [PMID: 29675775 PMCID: PMC6048961 DOI: 10.1007/s10858-018-0177-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 03/29/2018] [Indexed: 05/20/2023]
Abstract
NMR relaxation dispersion studies indicate that in canonical duplex DNA, Watson-Crick base pairs (bps) exist in dynamic equilibrium with short-lived low abundance excited state Hoogsteen bps. N1-methylated adenine (m1A) and guanine (m1G) are naturally occurring forms of damage that stabilize Hoogsteen bps in duplex DNA. NMR dynamic ensembles of DNA duplexes with m1A-T Hoogsteen bps reveal significant changes in sugar pucker and backbone angles in and around the Hoogsteen bp, as well as kinking of the duplex towards the major groove. Whether these structural changes also occur upon forming excited state Hoogsteen bps in unmodified duplexes remains to be established because prior relaxation dispersion probes provided limited information regarding the sugar-backbone conformation. Here, we demonstrate measurements of C3' and C4' spin relaxation in the rotating frame (R1ρ) in uniformly 13C/15N labeled DNA as sensitive probes of the sugar-backbone conformation in DNA excited states. The chemical shifts, combined with structure-based predictions using an automated fragmentation quantum mechanics/molecular mechanics method, show that the dynamic ensemble of DNA duplexes containing m1A-T Hoogsteen bps accurately model the excited state Hoogsteen conformation in two different sequence contexts. Formation of excited state A-T Hoogsteen bps is accompanied by changes in sugar-backbone conformation that allow the flipped syn adenine to form hydrogen-bonds with its partner thymine and this in turn results in overall kinking of the DNA toward the major groove. Results support the assignment of Hoogsteen bps as the excited state observed in canonical duplex DNA, provide an atomic view of DNA dynamics linked to formation of Hoogsteen bps, and lay the groundwork for a potentially general strategy for solving structures of nucleic acid excited states.
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Affiliation(s)
- Honglue Shi
- Department of Chemistry, Duke University, Durham, NC 27710, USA
| | - Mary C. Clay
- Department of Biochemistry, Duke University School of Medicine, Durham, NC 27710, USA
| | - Atul Rangadurai
- Department of Biochemistry, Duke University School of Medicine, Durham, NC 27710, USA
| | - Bharathwaj Sathyamoorthy
- Department of Chemistry, Duke University, Durham, NC 27710, USA
- Department of Biochemistry, Duke University School of Medicine, Durham, NC 27710, USA
| | - David A. Case
- Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
- To whom correspondence should be addressed. Telephone: (919) 660-1113, or
| | - Hashim M. Al-Hashimi
- Department of Chemistry, Duke University, Durham, NC 27710, USA
- Department of Biochemistry, Duke University School of Medicine, Durham, NC 27710, USA
- To whom correspondence should be addressed. Telephone: (919) 660-1113, or
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15
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Using the Maximum Entropy Principle to Combine Simulations and Solution Experiments. COMPUTATION 2018. [DOI: 10.3390/computation6010015] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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16
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Ikeya T, Ban D, Lee D, Ito Y, Kato K, Griesinger C. Solution NMR views of dynamical ordering of biomacromolecules. Biochim Biophys Acta Gen Subj 2017; 1862:287-306. [PMID: 28847507 DOI: 10.1016/j.bbagen.2017.08.020] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 08/22/2017] [Accepted: 08/24/2017] [Indexed: 01/01/2023]
Abstract
BACKGROUND To understand the mechanisms related to the 'dynamical ordering' of macromolecules and biological systems, it is crucial to monitor, in detail, molecular interactions and their dynamics across multiple timescales. Solution nuclear magnetic resonance (NMR) spectroscopy is an ideal tool that can investigate biophysical events at the atomic level, in near-physiological buffer solutions, or even inside cells. SCOPE OF REVIEW In the past several decades, progress in solution NMR has significantly contributed to the elucidation of three-dimensional structures, the understanding of conformational motions, and the underlying thermodynamic and kinetic properties of biomacromolecules. This review discusses recent methodological development of NMR, their applications and some of the remaining challenges. MAJOR CONCLUSIONS Although a major drawback of NMR is its difficulty in studying the dynamical ordering of larger biomolecular systems, current technologies have achieved considerable success in the structural analysis of substantially large proteins and biomolecular complexes over 1MDa and have characterised a wide range of timescales across which biomolecular motion exists. While NMR is well suited to obtain local structure information in detail, it contributes valuable and unique information within hybrid approaches that combine complementary methodologies, including solution scattering and microscopic techniques. GENERAL SIGNIFICANCE For living systems, the dynamic assembly and disassembly of macromolecular complexes is of utmost importance for cellular homeostasis and, if dysregulated, implied in human disease. It is thus instructive for the advancement of the study of the dynamical ordering to discuss the potential possibilities of solution NMR spectroscopy and its applications. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato.
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Affiliation(s)
- Teppei Ikeya
- Department of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, 1-1 Minamiosawa, Hachioji, Tokyo 192-0373, Japan; CREST, Japan Science and Technology Agency (JST), 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan.
| | - David Ban
- Department of Medicine, James Graham Brown Cancer Center, University of Louisville, 505 S. Hancock St., Louisville, KY 40202, USA
| | - Donghan Lee
- Department of Medicine, James Graham Brown Cancer Center, University of Louisville, 505 S. Hancock St., Louisville, KY 40202, USA
| | - Yutaka Ito
- Department of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, 1-1 Minamiosawa, Hachioji, Tokyo 192-0373, Japan; CREST, Japan Science and Technology Agency (JST), 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan
| | - Koichi Kato
- Okazaki Institute for Integrative Bioscience and Institute for Molecular Science, National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan; Graduate School of Pharmaceutical Sciences, Nagoya City University, Tanabe-dori 3-1, Mizuho-ku, Nagoya 467-8603, Japan
| | - Christian Griesinger
- Department of Structural Biology, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, Göttingen 37077, Germany.
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17
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Jose KVJ, Raghavachari K. Fragment-Based Approach for the Evaluation of NMR Chemical Shifts for Large Biomolecules Incorporating the Effects of the Solvent Environment. J Chem Theory Comput 2017; 13:1147-1158. [DOI: 10.1021/acs.jctc.6b00922] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- K. V. Jovan Jose
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Krishnan Raghavachari
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
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18
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Olsson S, Noé F. Mechanistic Models of Chemical Exchange Induced Relaxation in Protein NMR. J Am Chem Soc 2016; 139:200-210. [DOI: 10.1021/jacs.6b09460] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Simon Olsson
- Computational Molecular
Biology,
FB Mathematik und Informatik, Freie Universität Berlin, Berlin 14195, Germany
| | - Frank Noé
- Computational Molecular
Biology,
FB Mathematik und Informatik, Freie Universität Berlin, Berlin 14195, Germany
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19
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Nygaard M, Terkelsen T, Vidas Olsen A, Sora V, Salamanca Viloria J, Rizza F, Bergstrand-Poulsen S, Di Marco M, Vistesen M, Tiberti M, Lambrughi M, Jäättelä M, Kallunki T, Papaleo E. The Mutational Landscape of the Oncogenic MZF1 SCAN Domain in Cancer. Front Mol Biosci 2016; 3:78. [PMID: 28018905 PMCID: PMC5156680 DOI: 10.3389/fmolb.2016.00078] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Accepted: 11/17/2016] [Indexed: 11/24/2022] Open
Abstract
SCAN domains in zinc-finger transcription factors are crucial mediators of protein-protein interactions. Up to 240 SCAN-domain encoding genes have been identified throughout the human genome. These include cancer-related genes, such as the myeloid zinc finger 1 (MZF1), an oncogenic transcription factor involved in the progression of many solid cancers. The mechanisms by which SCAN homo- and heterodimers assemble and how they alter the transcriptional activity of zinc-finger transcription factors in cancer and other diseases remain to be investigated. Here, we provide the first description of the conformational ensemble of the MZF1 SCAN domain cross-validated against NMR experimental data, which are probes of structure and dynamics on different timescales. We investigated the protein-protein interaction network of MZF1 and how it is perturbed in different cancer types by the analyses of high-throughput proteomics and RNASeq data. Collectively, we integrated many computational approaches, ranging from simple empirical energy functions to all-atom microsecond molecular dynamics simulations and network analyses to unravel the effects of cancer-related substitutions in relation to MZF1 structure and interactions.
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Affiliation(s)
- Mads Nygaard
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Thilde Terkelsen
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - André Vidas Olsen
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Valentina Sora
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Juan Salamanca Viloria
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Fabio Rizza
- Department of Biomedical Sciences, University of Padua Padua, Italy
| | - Sanne Bergstrand-Poulsen
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Miriam Di Marco
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Mette Vistesen
- Cell Stress and Survival Unit and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Matteo Tiberti
- Department of Chemistry and Biochemistry, School of Biological and Chemical Sciences, Queen Mary University of London London, UK
| | - Matteo Lambrughi
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Marja Jäättelä
- Unit of Cell Death and Metabolism and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Tuula Kallunki
- Unit of Cell Death and Metabolism and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
| | - Elena Papaleo
- Computational Biology Laboratory and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center Copenhagen, Denmark
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20
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Bratholm LA, Jensen JH. Protein structure refinement using a quantum mechanics-based chemical shielding predictor. Chem Sci 2016; 8:2061-2072. [PMID: 28451325 PMCID: PMC5399634 DOI: 10.1039/c6sc04344e] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Accepted: 11/15/2016] [Indexed: 11/21/2022] Open
Abstract
We show that a QM-based predictor of a protein backbone and CB chemical shifts is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors (errors in chemical shifts shown in red).
The accurate prediction of protein chemical shifts using a quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor of a protein backbone and CB chemical shifts (ProCS15, PeerJ, 2016, 3, e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic chemical shielding values (ProCS15) can be used to refine protein structures using Markov Chain Monte Carlo (MCMC) simulations, relating the chemical shielding values to the experimental chemical shifts probabilistically. Two kinds of MCMC structural refinement simulations were performed using force field geometry optimized X-ray structures as starting points: simulated annealing of the starting structure and constant temperature MCMC simulation followed by simulated annealing of a representative ensemble structure. Annealing of the CHARMM structure changes the CA-RMSD by an average of 0.4 Å but lowers the chemical shift RMSD by 1.0 and 0.7 ppm for CA and N. Conformational averaging has a relatively small effect (0.1–0.2 ppm) on the overall agreement with carbon chemical shifts but lowers the error for nitrogen chemical shifts by 0.4 ppm. If an amino acid specific offset is included the ProCS15 predicted chemical shifts have RMSD values relative to experiments that are comparable to popular empirical chemical shift predictors. The annealed representative ensemble structures differ in CA-RMSD relative to the initial structures by an average of 2.0 Å, with >2.0 Å difference for six proteins. In four of the cases, the largest structural differences arise in structurally flexible regions of the protein as determined by NMR, and in the remaining two cases, the large structural change may be due to force field deficiencies. The overall accuracy of the empirical methods are slightly improved by annealing the CHARMM structure with ProCS15, which may suggest that the minor structural changes introduced by ProCS15-based annealing improves the accuracy of the protein structures. Having established that QM-based chemical shift prediction can deliver the same accuracy as empirical shift predictors we hope this can help increase the accuracy of related approaches such as QM/MM or linear scaling approaches or interpreting protein structural dynamics from QM-derived chemical shift.
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Affiliation(s)
- Lars A Bratholm
- Department of Chemistry , University of Copenhagen , Copenhagen , Denmark . ; ; http://www.twitter.com/janhjensen
| | - Jan H Jensen
- Department of Chemistry , University of Copenhagen , Copenhagen , Denmark . ; ; http://www.twitter.com/janhjensen
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21
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van Gunsteren WF, Allison JR, Daura X, Dolenc J, Hansen N, Mark AE, Oostenbrink C, Rusu VH, Smith LJ. Bestimmung von Strukturinformation aus experimentellen Messdaten für Biomoleküle. Angew Chem Int Ed Engl 2016. [DOI: 10.1002/ange.201601828] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Wilfred F. van Gunsteren
- Laboratorium für Physikalische Chemie; Eidgenössische Technische Hochschule Zürich; 8093 Zürich Schweiz
| | - Jane R. Allison
- Centre for Theor. Chem. and Phys. & Institute of Natural and Mathematical Sciences; Massey Univ.; Auckland Neuseeland
- Biomolecular Interaction Centre; University of Canterbury, Christchurch; Neuseeland
- Maurice Wilkins Centre for Molecular Biodiscovery; Neuseeland
| | - Xavier Daura
- Institute of Biotechnology and Biomedicine; Universitat Autònoma de Barcelona (UAB); 08193 Barcelona Spanien
- Catalan Institution for Research and Advanced Studies (ICREA); 08010 Barcelona Spanien
| | - Jožica Dolenc
- Laboratorium für Physikalische Chemie; Eidgenössische Technische Hochschule Zürich; 8093 Zürich Schweiz
| | - Niels Hansen
- Institut für Technische Thermodynamik und Thermische Verfahrenstechnik; Universität Stuttgart; Pfaffenwaldring 9 70569 Stuttgart Deutschland
| | - Alan E. Mark
- School of Chemistry and Molecular Biosciences; University of Queensland; St. Lucia QLD 4072 Australien
| | - Chris Oostenbrink
- Institut für Molekulare Modellierung und Simulation; Universität für Bodenkultur Wien; Wien Österreich
| | - Victor H. Rusu
- Laboratorium für Physikalische Chemie; Eidgenössische Technische Hochschule Zürich; 8093 Zürich Schweiz
| | - Lorna J. Smith
- Department of Chemistry; University of Oxford, Inorganic Chemistry Laboratory; South Parks Road Oxford OX1 3QR Großbritannien
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22
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van Gunsteren WF, Allison JR, Daura X, Dolenc J, Hansen N, Mark AE, Oostenbrink C, Rusu VH, Smith LJ. Deriving Structural Information from Experimentally Measured Data on Biomolecules. Angew Chem Int Ed Engl 2016; 55:15990-16010. [PMID: 27862777 DOI: 10.1002/anie.201601828] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Revised: 07/08/2016] [Indexed: 12/27/2022]
Abstract
During the past half century, the number and accuracy of experimental techniques that can deliver values of observables for biomolecular systems have been steadily increasing. The conversion of a measured value Qexp of an observable quantity Q into structural information is, however, a task beset with theoretical and practical problems: 1) insufficient or inaccurate values of Qexp , 2) inaccuracies in the function Q(r→) used to relate the quantity Q to structure r→ , 3) how to account for the averaging inherent in the measurement of Qexp , 4) how to handle the possible multiple-valuedness of the inverse r→(Q) of the function Q(r→) , to mention a few. These apply to a variety of observable quantities Q and measurement techniques such as X-ray and neutron diffraction, small-angle and wide-angle X-ray scattering, free-electron laser imaging, cryo-electron microscopy, nuclear magnetic resonance, electron paramagnetic resonance, infrared and Raman spectroscopy, circular dichroism, Förster resonance energy transfer, atomic force microscopy and ion-mobility mass spectrometry. The process of deriving structural information from measured data is reviewed with an eye to non-experts and newcomers in the field using examples from the literature of the effect of the various choices and approximations involved in the process. A list of choices to be avoided is provided.
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Affiliation(s)
- Wilfred F van Gunsteren
- Laboratory of Physical Chemistry, Swiss Federal Institute of Technology, ETH, 8093, Zurich, Switzerland
| | - Jane R Allison
- Centre for Theor. Chem. and Phys. & Institute of Natural and Mathematical Sciences, Massey Univ., Auckland, New Zealand.,Biomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand.,Maurice Wilkins Centre for Molecular Biodiscovery, New Zealand
| | - Xavier Daura
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona (UAB), 08193, Barcelona, Spain.,Catalan Institution for Research and Advanced Studies (ICREA), 08010, Barcelona, Spain
| | - Jožica Dolenc
- Laboratory of Physical Chemistry, Swiss Federal Institute of Technology, ETH, 8093, Zurich, Switzerland
| | - Niels Hansen
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569, Stuttgart, Germany
| | - Alan E Mark
- School of Chemistry and Molecular Biosciences, University of Queensland, St. Lucia, QLD 4072, Australia
| | - Chris Oostenbrink
- Institute of Molecular Modeling and Simulation, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Victor H Rusu
- Laboratory of Physical Chemistry, Swiss Federal Institute of Technology, ETH, 8093, Zurich, Switzerland
| | - Lorna J Smith
- Department of Chemistry, University of Oxford, Inorganic Chemistry Laboratory, South Parks Road, Oxford, OX1 3QR, UK
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23
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Bhowmick A, Brookes DH, Yost SR, Dyson HJ, Forman-Kay JD, Gunter D, Head-Gordon M, Hura GL, Pande VS, Wemmer DE, Wright PE, Head-Gordon T. Finding Our Way in the Dark Proteome. J Am Chem Soc 2016; 138:9730-42. [PMID: 27387657 PMCID: PMC5051545 DOI: 10.1021/jacs.6b06543] [Citation(s) in RCA: 99] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The traditional structure-function paradigm has provided significant insights for well-folded proteins in which structures can be easily and rapidly revealed by X-ray crystallography beamlines. However, approximately one-third of the human proteome is comprised of intrinsically disordered proteins and regions (IDPs/IDRs) that do not adopt a dominant well-folded structure, and therefore remain "unseen" by traditional structural biology methods. This Perspective considers the challenges raised by the "Dark Proteome", in which determining the diverse conformational substates of IDPs in their free states, in encounter complexes of bound states, and in complexes retaining significant disorder requires an unprecedented level of integration of multiple and complementary solution-based experiments that are analyzed with state-of-the art molecular simulation, Bayesian probabilistic models, and high-throughput computation. We envision how these diverse experimental and computational tools can work together through formation of a "computational beamline" that will allow key functional features to be identified in IDP structural ensembles.
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Affiliation(s)
- Asmit Bhowmick
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720
| | - David H. Brookes
- Department of Chemistry, University of California, Berkeley, CA 94720
| | - Shane R. Yost
- Department of Chemistry, University of California, Berkeley, CA 94720
| | - H. Jane Dyson
- Department of Integrative Structural and Computational Biology, Scripps Research Institute, La Jolla, California 92037
| | - Julie D. Forman-Kay
- Molecular Structure and Function Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Daniel Gunter
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley CA, 94720
| | | | - Gregory L. Hura
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley CA, 94720
| | - Vijay S. Pande
- Department of Chemistry, Stanford University, Stanford, CA 94305
| | - David E. Wemmer
- Department of Chemistry, University of California, Berkeley, CA 94720
| | - Peter E. Wright
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Teresa Head-Gordon
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720
- Department of Chemistry, University of California, Berkeley, CA 94720
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley CA, 94720
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24
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Shaghaghi H, Ebrahimi HP, Fathi F, Bahrami Panah N, Jalali-Heravi M, Tafazzoli M. A simple graphical approach to predict local residue conformation using NMR chemical shifts and density functional theory. J Comput Chem 2016; 37:1296-305. [DOI: 10.1002/jcc.24323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Revised: 11/25/2015] [Accepted: 01/17/2016] [Indexed: 11/08/2022]
Affiliation(s)
- Hoora Shaghaghi
- Department of Radiology; University of Pennsylvania; Philadelphia Pennsylvania 19104
| | - Hossein Pasha Ebrahimi
- Department of Biochemistry and National Magnetic Resonance Facility at Madison; University of Wisconsin-Madison; Wisconsin
| | - Fariba Fathi
- Department of Chemistry; Sharif University of Technology; Tehran Iran
| | | | - Mehdi Jalali-Heravi
- Department of Chemistry and Biochemistry; California State University; Los Angeles California
| | - Mohsen Tafazzoli
- Department of Chemistry; Sharif University of Technology; Tehran Iran
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25
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Vícha J, Babinský M, Demo G, Otrusinová O, Jansen S, Pekárová B, Žídek L, Munzarová ML. The influence of Mg2+ coordination on 13C and 15N chemical shifts in CKI1RD protein domain from experiment and molecular dynamics/density functional theory calculations. Proteins 2016; 84:686-99. [PMID: 26879585 DOI: 10.1002/prot.25019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Revised: 01/29/2016] [Accepted: 02/10/2016] [Indexed: 11/09/2022]
Abstract
Sequence dependence of (13) C and (15) N chemical shifts in the receiver domain of CKI1 protein from Arabidopsis thaliana, CKI1RD , and its complexed form, CKI1RD •Mg(2+), was studied by means of MD/DFT calculations. MD simulations of a 20-ns production run length were performed. Nine explicitly hydrated structures of increasing complexity were explored, up to a 40-amino-acid structure. The size of the model necessary depended on the type of nucleus, the type of amino acid and its sequence neighbors, other spatially close amino acids, and the orientation of amino acid NH groups and their surface/interior position. Using models covering a 10 and a 15 Å environment of Mg(2+), a semi-quantitative agreement has been obtained between experiment and theory for the V67-I73 sequence. The influence of Mg(2+) binding was described better by the 15 Å as compared to the 10 Å model. Thirteen chemical shifts were analyzed in terms of the effect of Mg(2+) insertion and geometry preparation. The effect of geometry was significant and opposite in sign to the effect of Mg(2+) binding. The strongest individual effects were found for (15) N of D70, S74, and V68, where the electrostatics dominated; for (13) Cβ of D69 and (15) N of K76, where the influences were equal, and for (13) Cα of F72 and (13) Cβ of K76, where the geometry adjustment dominated. A partial correlation between dominant geometry influence and torsion angle shifts upon the coordination has been observed.
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Affiliation(s)
- Jan Vícha
- Central European Institute of Technology, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic
| | - Martin Babinský
- Central European Institute of Technology, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic
| | - Gabriel Demo
- Central European Institute of Technology, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic
| | - Olga Otrusinová
- Central European Institute of Technology, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic.,Faculty of Science, National Centre for Biomolecular Research, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic
| | - Séverine Jansen
- Central European Institute of Technology, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic
| | - Blanka Pekárová
- Central European Institute of Technology, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic
| | - Lukáš Žídek
- Central European Institute of Technology, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic.,Faculty of Science, National Centre for Biomolecular Research, Masaryk University, Kamenice 5, Brno, 62500, Czech Republic
| | - Markéta L Munzarová
- Faculty of Science, Department of Chemistry, Masaryk University, Kotlářská 2, Brno, 61137, Czech Republic
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26
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Doyle CM, Rumfeldt JA, Broom HR, Sekhar A, Kay LE, Meiering EM. Concurrent Increases and Decreases in Local Stability and Conformational Heterogeneity in Cu, Zn Superoxide Dismutase Variants Revealed by Temperature-Dependence of Amide Chemical Shifts. Biochemistry 2016; 55:1346-61. [PMID: 26849066 DOI: 10.1021/acs.biochem.5b01133] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The chemical shifts of backbone amide protons in proteins are sensitive reporters of local structural stability and conformational heterogeneity, which can be determined from their readily measured linear and nonlinear temperature-dependences, respectively. Here we report analyses of amide proton temperature-dependences for native dimeric Cu, Zn superoxide dismutase (holo pWT SOD1) and structurally diverse mutant SOD1s associated with amyotrophic lateral sclerosis (ALS). Holo pWT SOD1 loses structure with temperature first at its periphery and, while having extremely high global stability, nevertheless exhibits extensive conformational heterogeneity, with ∼1 in 5 residues showing evidence for population of low energy alternative states. The holo G93A and E100G ALS mutants have moderately decreased global stability, whereas V148I is slightly stabilized. Comparison of the holo mutants as well as the marginally stable immature monomeric unmetalated and disulfide-reduced (apo(2SH)) pWT with holo pWT shows that changes in the local structural stability of individual amides vary greatly, with average changes corresponding to differences in global protein stability measured by differential scanning calorimetry. Mutants also exhibit altered conformational heterogeneity compared to pWT. Strikingly, substantial increases as well as decreases in local stability and conformational heterogeneity occur, in particular upon maturation and for G93A. Thus, the temperature-dependence of amide shifts for SOD1 variants is a rich source of information on the location and extent of perturbation of structure upon covalent changes and ligand binding. The implications for potential mechanisms of toxic misfolding of SOD1 in disease and for general aspects of protein energetics, including entropy-enthalpy compensation, are discussed.
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Affiliation(s)
| | | | | | | | - Lewis E Kay
- Program in Molecular Structure and Function, Hospital for Sick Children , Toronto, Canada
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Fu I, Case DA, Baum J. Dynamic Water-Mediated Hydrogen Bonding in a Collagen Model Peptide. Biochemistry 2016; 54:6029-37. [PMID: 26339765 DOI: 10.1021/acs.biochem.5b00622] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
In the canonical (G-X-Y)(n) sequence of the fibrillar collagen triple helix, stabilizing direct interchain hydrogen bonding connects neighboring chains. Mutations of G can disrupt these interactions and are linked to connective tissue diseases. Here we integrate computational approaches with nuclear magnetic resonance (NMR) to obtain a dynamic view of hydrogen bonding distributions in the (POG)(4)(-)(POA)-(POG)(5) peptide, showing that the solution conformation, dynamics, and hydrogen bonding deviate from the reported X-ray crystal structure in many aspects. The simulations and NMR data provide clear evidence of inequivalent environments in the three chains. Molecular dynamics (MD) simulations indicate direct interchain hydrogen bonds in the leading chain, water bridges in the middle chain, and nonbridging waters in the trailing chain at the G → A substitution site. Theoretical calculations of NMR chemical shifts using a quantum fragmentation procedure can account for the unusual downfield NMR chemical shifts at the substitution sites and are used to assign the resonances to the individual chains. The NMR and MD data highlight the sensitivity of amide shifts to changes in the acceptor group from peptide carbonyls to water. The results are used to interpret solution NMR data for a variety of glycine substitutions and other sequence triplet interruptions to provide new connections between collagen sequences, their associated structures, dynamical behavior, and their ability to recognize collagen receptors.
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Affiliation(s)
- Iwen Fu
- Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University , Piscataway, New Jersey 08854, United States
| | - David A Case
- Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University , Piscataway, New Jersey 08854, United States
| | - Jean Baum
- Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University , Piscataway, New Jersey 08854, United States
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28
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Swails J, Zhu T, He X, Case DA. AFNMR: automated fragmentation quantum mechanical calculation of NMR chemical shifts for biomolecules. JOURNAL OF BIOMOLECULAR NMR 2015; 63:125-39. [PMID: 26232926 PMCID: PMC6556433 DOI: 10.1007/s10858-015-9970-3] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2015] [Accepted: 07/20/2015] [Indexed: 05/08/2023]
Abstract
We evaluate the performance of the automated fragmentation quantum mechanics/molecular mechanics approach (AF-QM/MM) on the calculation of protein and nucleic acid NMR chemical shifts. The AF-QM/MM approach models solvent effects implicitly through a set of surface charges computed using the Poisson-Boltzmann equation, and it can also be combined with an explicit solvent model through the placement of water molecules in the first solvation shell around the solute; the latter substantially improves the accuracy of chemical shift prediction of protons involved in hydrogen bonding with solvent. We also compare the performance of AF-QM/MM on proteins and nucleic acids with two leading empirical chemical shift prediction programs SHIFTS and SHIFTX2. Although the empirical programs outperform AF-QM/MM in predicting chemical shifts, the differences are in some cases small, and the latter can be applied to chemical shifts on biomolecules which are outside the training set employed by the empirical programs, such as structures containing ligands, metal centers, and non-standard residues. The AF-QM/MM described here is implemented in version 5 of the SHIFTS software, and is fully automated, so that only a structure in PDB format is required as input.
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Affiliation(s)
- Jason Swails
- Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University, Piscataway, NJ, 08854, USA
| | - Tong Zhu
- State Key Laboratory of Precision Spectroscopy, Institute of Theoretical and Computational Science, East China Normal University, Shanghai, 200062, China
| | - Xiao He
- State Key Laboratory of Precision Spectroscopy, Institute of Theoretical and Computational Science, East China Normal University, Shanghai, 200062, China.
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China.
| | - David A Case
- Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University, Piscataway, NJ, 08854, USA.
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29
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Jee JG. Comparison of NMR structures refined under implicit and explicit solvents. JOURNAL OF THE KOREAN MAGNETIC RESONANCE SOCIETY 2015. [DOI: 10.6564/jkmrs.2015.19.1.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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30
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Sturlese M, Bellanda M, Moro S. NMR-Assisted Molecular Docking Methodologies. Mol Inform 2015; 34:513-25. [DOI: 10.1002/minf.201500012] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Accepted: 04/24/2015] [Indexed: 11/11/2022]
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31
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Pastor N, Amero C. Information flow and protein dynamics: the interplay between nuclear magnetic resonance spectroscopy and molecular dynamics simulations. FRONTIERS IN PLANT SCIENCE 2015; 6:306. [PMID: 25999971 PMCID: PMC4419604 DOI: 10.3389/fpls.2015.00306] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2015] [Accepted: 04/17/2015] [Indexed: 06/04/2023]
Abstract
Proteins participate in information pathways in cells, both as links in the chain of signals, and as the ultimate effectors. Upon ligand binding, proteins undergo conformation and motion changes, which can be sensed by the following link in the chain of information. Nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations represent powerful tools for examining the time-dependent function of biological molecules. The recent advances in NMR and the availability of faster computers have opened the door to more detailed analyses of structure, dynamics, and interactions. Here we briefly describe the recent applications that allow NMR spectroscopy and MD simulations to offer unique insight into the basic motions that underlie information transfer within and between cells.
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Affiliation(s)
- Nina Pastor
- Laboratorio de Dinámica de Proteínas y Ácidos Nucleicos, Centro de Investigación en Dinámica Celular, Universidad Autónoma del Estado de Morelos, Cuernavaca, Mexico
| | - Carlos Amero
- Laboratorio de Bioquímica y Resonancia Magnética Nuclear, Centro de Investigaciones Químicas, Universidad Autónoma del Estado de Morelos, Cuernavaca, Mexico
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32
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He X, Zhu T, Wang X, Liu J, Zhang JZH. Fragment quantum mechanical calculation of proteins and its applications. Acc Chem Res 2014; 47:2748-57. [PMID: 24851673 DOI: 10.1021/ar500077t] [Citation(s) in RCA: 145] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Conspectus The desire to study molecular systems that are much larger than what the current state-of-the-art ab initio or density functional theory methods could handle has naturally led to the development of novel approximate methods, including semiempirical approaches, reduced-scaling methods, and fragmentation methods. The major computational limitation of ab initio methods is the scaling problem, because the cost of ab initio calculation scales nth power or worse with system size. In the past decade, the fragmentation approach based on chemical locality has opened a new door for developing linear-scaling quantum mechanical (QM) methods for large systems and for applications to large molecular systems such as biomolecules. The fragmentation approach is highly attractive from a computational standpoint. First, the ab initio calculation of individual fragments can be conducted almost independently, which makes it suitable for massively parallel computations. Second, the electron properties, such as density and energy, are typically combined in a linear fashion to reproduce those for the entire molecular system, which makes the overall computation scale linearly with the size of the system. In this Account, two fragmentation methods and their applications to macromolecules are described. They are the electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method and the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) approach. The EE-GMFCC method is developed from the MFCC approach, which was initially used to obtain accurate protein-ligand QM interaction energies. The main idea of the MFCC approach is that a pair of conjugate caps (concaps) is inserted at the location where the subsystem is divided by cutting the chemical bond. In addition, the pair of concaps is fused to form molecular species such that the overcounted effect from added concaps can be properly removed. By introducing the electrostatic embedding field in each fragment calculation and two-body interaction energy correction on top of the MFCC approach, the EE-GMFCC method is capable of accurately reproducing the QM molecular properties (such as the dipole moment, electron density, and electrostatic potential), the total energy, and the electrostatic solvation energy from full system calculations for proteins. On the other hand, the AF-QM/MM method was used for the efficient QM calculation of protein nuclear magnetic resonance (NMR) parameters, including the chemical shift, chemical shift anisotropy tensor, and spin-spin coupling constant. In the AF-QM/MM approach, each amino acid and all the residues in its vicinity are automatically assigned as the QM region through a distance cutoff for each residue-centric QM/MM calculation. Local chemical properties of the central residue can be obtained from individual QM/MM calculations. The AF-QM/MM approach precisely reproduces the NMR chemical shifts of proteins in the gas phase from full system QM calculations. Furthermore, via the incorporation of implicit and explicit solvent models, the protein NMR chemical shifts calculated by the AF-QM/MM method are in excellent agreement with experimental values. The applications of the AF-QM/MM method may also be extended to more general biological systems such as DNA/RNA and protein-ligand complexes.
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Affiliation(s)
- Xiao He
- State
Key Laboratory of Precision Spectroscopy, Institute of Theoretical
and Computational Science, East China Normal University, Shanghai 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - Tong Zhu
- State
Key Laboratory of Precision Spectroscopy, Institute of Theoretical
and Computational Science, East China Normal University, Shanghai 200062, China
| | - Xianwei Wang
- State
Key Laboratory of Precision Spectroscopy, Institute of Theoretical
and Computational Science, East China Normal University, Shanghai 200062, China
| | - Jinfeng Liu
- State
Key Laboratory of Precision Spectroscopy, Institute of Theoretical
and Computational Science, East China Normal University, Shanghai 200062, China
| | - John Z. H. Zhang
- State
Key Laboratory of Precision Spectroscopy, Institute of Theoretical
and Computational Science, East China Normal University, Shanghai 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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Camilloni C, Vendruscolo M. Statistical mechanics of the denatured state of a protein using replica-averaged metadynamics. J Am Chem Soc 2014; 136:8982-91. [PMID: 24884637 DOI: 10.1021/ja5027584] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The characterization of denatured states of proteins is challenging because the lack of permanent structure in these states makes it difficult to apply to them standard methods of structural biology. In this work we use all-atom replica-averaged metadynamics (RAM) simulations with NMR chemical shift restraints to determine an ensemble of structures representing an acid-denatured state of the 86-residue protein ACBP. This approach has enabled us to reach convergence in the free energy landscape calculations, obtaining an ensemble of structures in relatively accurate agreement with independent experimental data used for validation. By observing at atomistic resolution the transient formation of native and non-native structures in this acid-denatured state of ACBP, we rationalize the effects of single-point mutations on the folding rate, stability, and transition-state structures of this protein, thus characterizing the role of the unfolded state in determining the folding process.
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Affiliation(s)
- Carlo Camilloni
- Department of Chemistry, University of Cambridge , Cambridge CB2 1EW, United Kingdom
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34
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Jensen MR, Zweckstetter M, Huang JR, Blackledge M. Exploring free-energy landscapes of intrinsically disordered proteins at atomic resolution using NMR spectroscopy. Chem Rev 2014; 114:6632-60. [PMID: 24725176 DOI: 10.1021/cr400688u] [Citation(s) in RCA: 213] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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35
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Christensen AS, Linnet TE, Borg M, Boomsma W, Lindorff-Larsen K, Hamelryck T, Jensen JH. Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics. PLoS One 2013; 8:e84123. [PMID: 24391900 PMCID: PMC3877219 DOI: 10.1371/journal.pone.0084123] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2013] [Accepted: 11/11/2013] [Indexed: 11/18/2022] Open
Abstract
We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts--sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond ((h3)J(NC')) spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to obtain this agreement. The ProCS method thus offers a powerful new tool for refining the structures of hydrogen bonding networks to high accuracy with many potential applications such as protein flexibility in ligand binding.
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Affiliation(s)
| | - Troels E. Linnet
- Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Mikael Borg
- Structural Bioinformatics Group, Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Wouter Boomsma
- Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Hamelryck
- Structural Bioinformatics Group, Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Jan H. Jensen
- Department of Chemistry, University of Copenhagen, Copenhagen, Denmark
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36
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Frank AT, Bae SH, Stelzer AC. Prediction of RNA 1H and 13C chemical shifts: a structure based approach. J Phys Chem B 2013; 117:13497-506. [PMID: 24033307 DOI: 10.1021/jp407254m] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The use of NMR-derived chemical shifts in protein structure determination and prediction has received much attention, and, as such, many methods have been developed to predict protein chemical shifts from three-dimensional (3D) coordinates. In contrast, little attention has been paid to predicting chemical shifts from RNA coordinates. Using the random forest machine learning approach, we developed RAMSEY, which is capable of predicting both (1)H and protonated (13)C chemical shifts from RNA coordinates. In this report, we introduce RAMSEY, assess its accuracy, and demonstrate the sensitivity of RAMSEY-predicted chemical shifts to RNA 3D structure.
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Affiliation(s)
- Aaron T Frank
- Nymirum , 3510 West Liberty Road, Ann Arbor, Michigan 48103, United States
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37
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Wang B, He X, Merz KM. Quantum Mechanical Study of Vicinal J Spin-Spin Coupling Constants for the Protein Backbone. J Chem Theory Comput 2013; 9:4653-9. [PMID: 26589175 DOI: 10.1021/ct400631b] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
We have performed densisty functional theory (DFT) calculations of vicinal J coupling constants involving the backbone torsional angle for the protein GB3 using our recently developed automatic fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) approach (Xiao He et al. J. Phys. Chem. B 2009, 113, 10380-10388). Interestingly, the calculated values based on an NMR structure are more accurate than those based on a high-resolution X-ray strucure because the NMR structure was refined using a large number of residual dipolar couplings (RDCs) whereas the hydrogen atoms were added into the X-ray structure in idealized positions, confirming that the postioning of the hydrogen atoms relative to the backbone atoms is important to the accuracy of J coupling constant prediction. By comparing three Karplus equations, our results have demonstrated that hydrogen bonding, substituent and electrostatic effects could have significant impacts on vicinal J couplings even though they depend mostly on the intervening dihedral angles. The root-mean-square deviations (RMSDs) of the calculated (3)J(H(N),H(α)), (3)J(H(N),C(β)), (3)J(H(N),C') values based on the NMR structure are 0.52, 0.25, and 0.35 Hz, respectively, after taking the dynamic effect into consideration. The excellent accuracy demonstrates that our AF-QM/MM approach is a useful tool to study the relationship between J coupling constants and the structure and dynamics of proteins.
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Affiliation(s)
- Bing Wang
- Department of Chemistry and the Quantum Theory Project, University of Florida , Gainesville, Florida, 32611, United States
| | - Xiao He
- State Key Laboratory of Precision Spectroscopy and Department of Physics, Institute of Theoretical and Computational Science, East China Normal University , Shanghai 200062, China
| | - Kenneth M Merz
- Department of Chemistry and the Quantum Theory Project, University of Florida , Gainesville, Florida, 32611, United States
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38
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Kragelj J, Ozenne V, Blackledge M, Jensen MR. Conformational Propensities of Intrinsically Disordered Proteins from NMR Chemical Shifts. Chemphyschem 2013; 14:3034-45. [DOI: 10.1002/cphc.201300387] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2013] [Indexed: 12/22/2022]
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