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@article{Dudley:2024,
	author = {Joshua A. Dudley and Sojeong Park and Oliver Cho and Nicholas G. M. Wells and Meagan E. MacDonald and Katerina M. Blejec and Emmanuel Fetene and Eric Zanderigo and Scott Houliston and Jennifer C. Liddle and Chad M. Dashnaw and T. Michael Sabo and Bryan F. Shaw and Jeremy L. Balsbaugh and Gabriel J. Rocklin and Colin A. Smith},
	date-added = {2024-03-28 16:48:28 -0400},
	date-modified = {2024-03-28 16:50:31 -0400},
	journal = {Protein Sci},
	title = {Heat-induced structural and chemical changes to a computationally designed miniprotein},
	year = {2024}}

@book{Wuthrich:1986aa,
	address = {New York},
	annote = {Includes bibliographical references (pages 271-285) and index.},
	author = {W{\"u}thrich, Kurt},
	date-added = {2024-03-28 16:32:08 -0400},
	date-modified = {2024-03-28 16:35:04 -0400},
	id = {alma99493953903768},
	isbn = {0471828939},
	keywords = {35.25 spectrochemical analysis; Nuclear magnetic resonance spectroscopy; Nucleic acids -- Analysis; Proteins -- Analysis; Nucleic acids -- Spectra; Proteins -- Spectra},
	n2 = {This title provides an introduction to underlying principles and experimental procedures using the newest strategies and techniques for obtaining extensive NMR assignments in biopolymers based on NMR data and the primary structure.},
	publisher = {Wiley},
	title = {NMR of proteins and nucleic acids},
	year = {1986}}

@inbook{Inagaki:2013aa,
	address = {Berlin, Heidelberg},
	author = {Inagaki, Fuyuhiko},
	booktitle = {Encyclopedia of Biophysics},
	date = {2013//},
	date-added = {2024-03-28 16:30:32 -0400},
	date-modified = {2024-03-28 16:30:32 -0400},
	doi = {10.1007/978-3-642-16712-6{\_}312},
	editor = {Roberts, Gordon C.  K. },
	id = {Inagaki2013},
	isbn = {978-3-642-16712-6},
	pages = {2033--2037},
	publisher = {Springer Berlin Heidelberg},
	title = {Protein NMR Resonance Assignment},
	url = {https://doi.org/10.1007/978-3-642-16712-6_312},
	year = {2013},
	bdsk-url-1 = {https://doi.org/10.1007/978-3-642-16712-6_312},
	bdsk-url-2 = {https://doi.org/10.1007/978-3-642-16712-6%7B%5C_%7D312}}

@article{Cao:2022aa,
	abstract = {The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains a challenge1--5. Here we describe a general solution to this problem that starts with a broad exploration of the vast space of possible binding modes to a selected region of a protein surface, and then intensifies the search in the vicinity of the most promising binding modes. We demonstrate the broad applicability of this approach through the de novo design of binding proteins to 12 diverse protein targets with different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and, following experimental optimization, bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of five of the binder--target complexes, and all five closely match the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein--protein interactions, and should guide improvements of both. Our approach enables the targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.},
	author = {Cao, Longxing and Coventry, Brian and Goreshnik, Inna and Huang, Buwei and Sheffler, William and Park, Joon Sung and Jude, Kevin M. and Markovi{\'c}, Iva and Kadam, Rameshwar U. and Verschueren, Koen H. G. and Verstraete, Kenneth and Walsh, Scott Thomas Russell and Bennett, Nathaniel and Phal, Ashish and Yang, Aerin and Kozodoy, Lisa and DeWitt, Michelle and Picton, Lora and Miller, Lauren and Strauch, Eva-Maria and DeBouver, Nicholas D. and Pires, Allison and Bera, Asim K. and Halabiya, Samer and Hammerson, Bradley and Yang, Wei and Bernard, Steffen and Stewart, Lance and Wilson, Ian A. and Ruohola-Baker, Hannele and Schlessinger, Joseph and Lee, Sangwon and Savvides, Savvas N. and Garcia, K. Christopher and Baker, David},
	date = {2022/05/01},
	date-added = {2024-03-28 16:08:49 -0400},
	date-modified = {2024-03-28 16:08:49 -0400},
	doi = {10.1038/s41586-022-04654-9},
	id = {Cao2022},
	isbn = {1476-4687},
	journal = {Nature},
	number = {7910},
	pages = {551--560},
	title = {Design of protein-binding proteins from the target structure alone},
	url = {https://doi.org/10.1038/s41586-022-04654-9},
	volume = {605},
	year = {2022},
	bdsk-url-1 = {https://doi.org/10.1038/s41586-022-04654-9}}

@article{Castillo:2011aa,
	abstract = {The computational cost for the simulation of NMR spectra grows exponentially with the number of nuclei. Today, the memory available to store the Hamiltonian limits the size of the system that can be studied. Modern computers enable to tackle systems containing up to 13 spins {$[$}1{$]$}, which obviously does not allow to study most molecules of interest in research. This issue can be addressed by identifying groups of spins or fragments that are not or only weakly interacting together, i.e., that only share weakly coupled spin pairs. Such a fragmentation is only permitted in the weak coupling regime, i.e., when the coupling interaction is weak compared to the difference in chemical shift of the coupled spins. Here, we propose a procedure that removes weak coupling interactions in order to split the spin system efficiently and to correct a posteriori for the effect of the neglected couplings. This approach yields accurate spectra when the adequate interactions are removed, i.e., between spins only involved in weak coupling interactions, but fails otherwise. As a result, the computational time for the simulation of 1D spectra grows linearly with the size of the spin system.},
	author = {Castillo, Andr{\'e}s M. and Patiny, Luc and Wist, Julien},
	date = {2011/04/01/},
	date-added = {2024-03-28 13:57:58 -0400},
	date-modified = {2024-03-30 20:03:48 -0400},
	doi = {10.1016/j.jmr.2010.12.008},
	isbn = {1090-7807},
	journal = {Journal of Magnetic Resonance},
	keywords = {Quantum spin dynamics; Spectra Simulation; NMR; Scalar coupling; Clustering},
	number = {2},
	pages = {123--130},
	title = {Fast and accurate algorithm for the simulation of NMR spectra of large spin systems},
	url = {https://www.sciencedirect.com/science/article/pii/S1090780710004003},
	volume = {209},
	year = {2011},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S1090780710004003},
	bdsk-url-2 = {https://doi.org/10.1016/j.jmr.2010.12.008}}

@article{Li:2023aa,
	author = {Li, D.-W. and Bruschweiler-Li, L. and Hansen, A. L. and Br\"uschweiler, R.},
	date-added = {2024-03-28 13:53:18 -0400},
	date-modified = {2024-03-28 13:53:31 -0400},
	doi = {10.5194/mr-4-19-2023},
	journal = {Magnetic Resonance},
	number = {1},
	pages = {19--26},
	title = {DEEP Picker1D and Voigt Fitter1D: a versatile tool set for the automated quantitative spectral deconvolution of complex 1D-NMR spectra},
	url = {https://mr.copernicus.org/articles/4/19/2023/},
	volume = {4},
	year = {2023},
	bdsk-url-1 = {https://mr.copernicus.org/articles/4/19/2023/},
	bdsk-url-2 = {https://doi.org/10.5194/mr-4-19-2023}}

@article{Tiainen:2014aa,
	abstract = {The quantitative interpretation of 1H NMR spectra of mixtures like the biofluids is a demanding task due to spectral complexity and overlap. Complications may arise also from water suppression, T2-editing, protein interactions, relaxation differences of the species, experimental artifacts and, furthermore, the spectra may contain unknown components and macromolecular background which cannot be easily separated from baseline. In this work, tools and strategies for quantitative Quantum Mechanical Spectral Analysis (qQMSA) of 1H NMR spectra from complex mixtures were developed and systematically assessed. In the present approach, the signals of well-defined, stoichiometric components are described by a QM model, while the background is described by a multiterm baseline function and the unknown signals using optimizable and adjustable lines, regular multiplets or any spectral structures which can be composed from spectral lines. Any prior knowledge available from the spectrum can also be added to the model. Fitting strategies for weak and strongly overlapping spectral systems were developed and assessed using two basic model systems, the metabolite mixtures without and with macromolecular (serum) background. The analyses show that if the spectra are measured in high-throughput manner, the consistent absolute quantification demands some calibration to compensate the different response factors of the protons and compounds. On the other hand, the results show that also the T2-edited spectra can be measured so that they obey well the QM rules. In general, qQMSA exploits and interprets the spectral information in maximal way taking full advantage from the QM properties of the spectra and, at the same time, offers chemical confidence which means that individual components can be identified with high confidence on the basis of their accurate spectral parameters.},
	author = {Tiainen, Mika and Soininen, Pasi and Laatikainen, Reino},
	date = {2014/05/01/},
	date-added = {2024-03-27 18:17:50 -0400},
	date-modified = {2024-03-30 20:05:27 -0400},
	doi = {10.1016/j.jmr.2014.02.008},
	isbn = {1090-7807},
	journal = {Journal of Magnetic Resonance},
	keywords = {Quantum mechanical; Quantitative NMR; Spectral analysis; QMSA; Serum; Mixtures; Biofluids},
	pages = {67--78},
	title = {Quantitative Quantum Mechanical Spectral Analysis (qQMSA) of 1H NMR spectra of complex mixtures and biofluids},
	url = {https://www.sciencedirect.com/science/article/pii/S1090780714000469},
	volume = {242},
	year = {2014},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S1090780714000469},
	bdsk-url-2 = {https://doi.org/10.1016/j.jmr.2014.02.008}}

@article{Cheshkov:2018aa,
	author = {Cheshkov, D. A. and Sheberstov, K. F. and Sinitsyn, D. O. and Chertkov, V. A.},
	date = {2018/06/01},
	date-added = {2024-03-27 18:01:02 -0400},
	date-modified = {2024-03-30 20:04:28 -0400},
	doi = {10.1002/mrc.4689},
	isbn = {0749-1581},
	journal = {Magnetic Resonance in Chemistry},
	journal1 = {Magnetic Resonance in Chemistry},
	journal2 = {Magnetic Resonance in Chemistry},
	journal3 = {Magn Reson Chem},
	keywords = {1D NMR simulation; broadening approach; multiplet structure elucidation; total lineshape analysis},
	month = {2024/03/27},
	n2 = {In this paper we present a new fast and free open-source software package ANATOLIA for the total lineshape analysis of NMR spectra. It performs fitting of experimental 1D NMR spectra based on quantum mechanical formalism. The program serves for the determination of J-coupling constants and elucidation of complicated multiplet structures including strongly coupled systems. The program utilizes the Lorentzian broadening approach for local minima suppression. It is developed in the C++ language for standard personal computers. ANATOLIA is adapted to work with the Bruker NMR spectral format and could be conveniently integrated into the TopSpin software package. This tutorial contains a program description, 2 demonstration examples, and general recommendations for NMR spectra analysis.},
	number = {6},
	pages = {449--457},
	publisher = {John Wiley \& Sons, Ltd},
	title = {ANATOLIA: NMR software for spectral analysis of total lineshape},
	url = {https://doi.org/10.1002/mrc.4689},
	volume = {56},
	year = {2018},
	year1 = {2018},
	bdsk-url-1 = {https://doi.org/10.1002/mrc.4689}}

@inbook{Cheshkov:2020aa,
	abstract = {Analysis of high-resolution NMR spectra consist in determining the parameters of the spin system that provide the best correspondence between the theoretical and experimental spectra. This review is devoted to modern approaches to the total line shape analysis of high-resolution NMR spectra; discussion of difficulties and pitfalls associated with both the fundamental features of high-resolution NMR spectra and the optimization of parameters values. The question of the accuracy of determining values of spin systems parameters is discussed. Practical examples of the spectra analysis are considered, as well as recommendations for obtaining experimental NMR spectra of high quality.},
	author = {Cheshkov, Dmitry A. and Sinitsyn, Dmitry O.},
	booktitle = {Annual Reports on NMR Spectroscopy},
	date = {2020/01/01/},
	date-added = {2024-03-27 18:01:02 -0400},
	date-modified = {2024-03-30 20:04:16 -0400},
	doi = {10.1016/bs.arnmr.2019.11.001},
	editor = {Webb, Graham A. },
	isbn = {0066-4103},
	keywords = {Total line shape analysis; Spin-spin coupling constants; Multiplet structure elucidation; Broadening approach; Simulated annealing},
	pages = {61--96},
	publisher = {Academic Press},
	title = {Chapter Two - Total line shape analysis of high-resolution NMR spectra},
	url = {https://www.sciencedirect.com/science/article/pii/S0066410319300419},
	volume = {100},
	year = {2020},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S0066410319300419},
	bdsk-url-2 = {https://doi.org/10.1016/bs.arnmr.2019.11.001}}

@article{Heinzer:1977aa,
	abstract = {A iterative least-squares procedure for the lineshape fitting of high-resolution NMR spectra making use of symmetry and magnetic equivalence factorization is outlined. Parameter refinements of large spin systems are speeded up substantially by the aid of first-order perturbation theory. The program NMRCON handling up to six different chemical shifts is described. Three examples illustrate the application of the program.},
	author = {Heinzer, J},
	date = {1977/05/01/},
	date-added = {2024-03-27 18:00:41 -0400},
	date-modified = {2024-03-30 20:05:04 -0400},
	doi = {10.1016/0022-2364(77)90176-7},
	isbn = {0022-2364},
	journal = {Journal of Magnetic Resonance (1969)},
	number = {2},
	pages = {301--316},
	title = {Iterative least-squares nmr lineshape fitting with use of symmetry and magnetic equivalence factorization},
	url = {https://www.sciencedirect.com/science/article/pii/0022236477901767},
	volume = {26},
	year = {1977},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/0022236477901767},
	bdsk-url-2 = {https://doi.org/10.1016/0022-2364(77)90176-7}}

@article{Castellano:1964aa,
	abstract = {An iterative method for the least‐squares analysis of an observed high‐resolution NMR spectrum is described. The method is applicable even if not all lines are assignable, is not affected by symmetry in the Hamiltonian, yields an estimate of the ellipsoid of error, and converges relatively rapidly to a predetermined assignment. A computer program based on this method is described. Effectively infinite chemical shift may be introduced permitting the analysis of ABXY, etc., spectra. An illustration of its application to the analysis of the proton spectrum of 2‐benzoylpyridine is given.},
	author = {Castellano, S. and Bothner‐By, A. A.},
	date-added = {2024-03-27 18:00:14 -0400},
	date-modified = {2024-03-27 18:00:14 -0400},
	doi = {10.1063/1.1725826},
	isbn = {0021-9606},
	journal = {The Journal of Chemical Physics},
	journal1 = {J. Chem. Phys.},
	month = {3/27/2024},
	number = {12},
	pages = {3863--3869},
	title = {Analysis of NMR Spectra by Least Squares},
	url = {https://doi.org/10.1063/1.1725826},
	volume = {41},
	year = {1964},
	year1 = {1964/12/15},
	bdsk-url-1 = {https://doi.org/10.1063/1.1725826}}

@article{Achanta:2021aa,
	abstract = {Issues related to pharmaceutical quality are arising at an alarming rate. Pharmaceutical quality concerns both the Active Pharmaceutical Ingredients (APIs) and the Finished Drug Product/ Formulation. Recently, there has been a significant increase in the number of reports of harmful impurities in marketed drug formulations. Impurities range from solvents, reactants, adulterants, and catalysts to synthetic byproducts. Quality concerns in commercial preparations may also arise due to shelf life stability. Furthermore, a number of falsified and substandard drug cases have been reported. Most of the techniques which are currently in place can, at best, detect the impurities, but cannot identify them unless they are already known and can be compared to a standard. On the other hand, 1H NMR spectroscopy detects all the hydrogen containing species, typically provides information to elucidate structures partially or even completely, and through its absolute quantitative capabilities even can detect the presence hydrogen-free species indirectly. The structural properties that produce 1H NMR signals as characteristic representations of a given molecule are the chemical shifts (δin ppm) and coupling constants (J in Hz). Along with the line widths (ω1/2 in Hz), these parameters are bound to both the molecule and the NMR experimental conditions by quantum mechanical (QM) principles. This means that the 1H NMR spectra of APIs can be precisely calculated and compared to the experimental data. This review explains how 1H NMR spectroscopy coupled with Full Spin Analysis can contribute towards the quality control of pharmaceuticals by improving structural dereplication and achieving simultaneous quantification of both APIs and their contaminants.},
	author = {Achanta, Prabhakar S. and Jaki, Birgit U. and McAlpine, James B. and Friesen, J. Brent and Niemitz, Matthias and Chen, Shao-Nong and Pauli, Guido F.},
	date = {2021/01/05/},
	date-added = {2024-03-27 17:59:46 -0400},
	date-modified = {2024-03-30 20:03:31 -0400},
	doi = {10.1016/j.jpba.2020.113601},
	isbn = {0731-7085},
	journal = {Journal of Pharmaceutical and Biomedical Analysis},
	keywords = {H NMR spectroscopy (HNMR); Quantum mechanics; Signal multiplicity; Calculated NMR spectra; Simulated NMR spectra},
	pages = {113601},
	title = {Quantum mechanical NMR full spin analysis in pharmaceutical identity testing and quality control},
	url = {https://www.sciencedirect.com/science/article/pii/S0731708520314874},
	volume = {192},
	year = {2021},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S0731708520314874},
	bdsk-url-2 = {https://doi.org/10.1016/j.jpba.2020.113601}}

@article{Smith:2017aa,
	abstract = {Software for fitting of NMR spectra in MATLAB is presented. Spectra are fitted in the frequency domain, using Fourier transformed lineshapes, which are derived using the experimental acquisition and processing parameters. This yields more accurate fits compared to common fitting methods that use Lorentzian or Gaussian functions. Furthermore, a very time-efficient algorithm for calculating and fitting spectra has been developed. The software also performs initial peak picking, followed by subsequent fitting and refinement of the peak list, by iteratively adding and removing peaks to improve the overall fit. Estimation of error on fitting parameters is performed using a Monte-Carlo approach. Many fitting options allow the software to be flexible enough for a wide array of applications, while still being straightforward to set up with minimal user input.},
	author = {Smith, Albert A. },
	date = {2017/02/01},
	date-added = {2024-03-27 09:56:42 -0400},
	date-modified = {2024-03-27 09:56:42 -0400},
	doi = {10.1007/s10858-016-0085-2},
	id = {Smith2017},
	isbn = {1573-5001},
	journal = {Journal of Biomolecular NMR},
	number = {2},
	pages = {77--94},
	title = {INFOS: spectrum fitting software for NMR analysis},
	url = {https://doi.org/10.1007/s10858-016-0085-2},
	volume = {67},
	year = {2017},
	bdsk-url-1 = {https://doi.org/10.1007/s10858-016-0085-2}}

@article{Niklasson:2017aa,
	abstract = {NMR spectroscopy is uniquely suited for atomic resolution studies of biomolecules such as proteins, nucleic acids and metabolites, since detailed information on structure and dynamics are encoded in positions and line shapes of peaks in NMR spectra. Unfortunately, accurate determination of these parameters is often complicated and time consuming, in part due to the need for different software at the various analysis steps and for validating the results. Here, we present an integrated, cross-platform and open-source software that is significantly more versatile than the typical line shape fitting application. The software is a completely redesigned version of PINT (https://pint-nmr.github.io/PINT/). It features a graphical user interface and includes functionality for peak picking, editing of peak lists and line shape fitting. In addition, the obtained peak intensities can be used directly to extract, for instance, relaxation rates, heteronuclear NOE values and exchange parameters. In contrast to most available software the entire process from spectral visualization to preparation of publication-ready figures is done solely using PINT and often within minutes, thereby, increasing productivity for users of all experience levels. Unique to the software are also the outstanding tools for evaluating the quality of the fitting results and extensive, but easy-to-use, customization of the fitting protocol and graphical output. In this communication, we describe the features of the new version of PINT and benchmark its performance.},
	author = {Niklasson, Markus and Otten, Renee and Ahlner, Alexandra and Andresen, Cecilia and Schlagnitweit, Judith and Petzold, Katja and Lundstr{\"o}m, Patrik},
	date = {2017/10/01},
	date-added = {2024-03-27 09:55:09 -0400},
	date-modified = {2024-03-27 09:55:09 -0400},
	doi = {10.1007/s10858-017-0141-6},
	id = {Niklasson2017},
	isbn = {1573-5001},
	journal = {Journal of Biomolecular NMR},
	number = {2},
	pages = {93--99},
	title = {Comprehensive analysis of NMR data using advanced line shape fitting},
	url = {https://doi.org/10.1007/s10858-017-0141-6},
	volume = {69},
	year = {2017},
	bdsk-url-1 = {https://doi.org/10.1007/s10858-017-0141-6}}

@article{Ahlner:2013aa,
	abstract = {We present the software Peak INTegration (PINT), designed to perform integration of peaks in NMR spectra. The program is very simple to run, yet powerful enough to handle complicated spectra. Peaks are integrated by fitting predefined line shapes to experimental data and the fitting can be customized to deal with, for instance, heavily overlapped peaks. The results can be inspected visually, which facilitates systematic optimization of the line shape fitting. Finally, integrated peak volumes can be used to extract parameters such as relaxation rates and information about low populated states. The utility of PINT is demonstrated by applications to the 59 residue SH3 domain of the yeast protein Abp1p and the 289 residue kinase domain of murine EphB2.},
	author = {Ahlner, Alexandra and Carlsson, Mats and Jonsson, Bengt-Harald and Lundstr{\"o}m, Patrik},
	date = {2013/07/01},
	date-added = {2024-03-27 09:54:45 -0400},
	date-modified = {2024-03-27 09:54:45 -0400},
	doi = {10.1007/s10858-013-9737-7},
	id = {Ahlner2013},
	isbn = {1573-5001},
	journal = {Journal of Biomolecular NMR},
	number = {3},
	pages = {191--202},
	title = {PINT: a software for integration of peak volumes and extraction of relaxation rates},
	url = {https://doi.org/10.1007/s10858-013-9737-7},
	volume = {56},
	year = {2013},
	bdsk-url-1 = {https://doi.org/10.1007/s10858-013-9737-7}}

@article{Bernstein:2013aa,
	abstract = {NMR is routinely used to quantitate chemical species. The necessary experimental procedures to acquire quantitative data are well-known, but relatively little attention has been applied to data processing and analysis. We describe here a robust expert system that can be used to automatically choose the best signals in a sample for overall concentration determination and determine analyte concentration using all accepted methods. The algorithm is based on the complete deconvolution of the spectrum which makes it tolerant of cases where signals are very close to one another and includes robust methods for the automatic classification of NMR resonances and molecule-to-spectrum multiplets assignments. With the functionality in place and optimized, it is then a relatively simple matter to apply the same workflow to data in a fully automatic way. The procedure is desirable for both its inherent performance and applicability to NMR data acquired for very large sample sets.},
	annote = {doi: 10.1021/ac400411q},
	author = {Bernstein, Michael A. and S{\'y}kora, Stan and Peng, Chen and Barba, Agust{\'\i}n and Cobas, Carlos},
	date = {2013/06/18},
	date-added = {2024-03-26 17:12:44 -0400},
	date-modified = {2024-03-26 17:12:44 -0400},
	doi = {10.1021/ac400411q},
	isbn = {0003-2700},
	journal = {Analytical Chemistry},
	journal1 = {Analytical Chemistry},
	journal2 = {Anal. Chem.},
	month = {06},
	n2 = {NMR is routinely used to quantitate chemical species. The necessary experimental procedures to acquire quantitative data are well-known, but relatively little attention has been applied to data processing and analysis. We describe here a robust expert system that can be used to automatically choose the best signals in a sample for overall concentration determination and determine analyte concentration using all accepted methods. The algorithm is based on the complete deconvolution of the spectrum which makes it tolerant of cases where signals are very close to one another and includes robust methods for the automatic classification of NMR resonances and molecule-to-spectrum multiplets assignments. With the functionality in place and optimized, it is then a relatively simple matter to apply the same workflow to data in a fully automatic way. The procedure is desirable for both its inherent performance and applicability to NMR data acquired for very large sample sets.},
	number = {12},
	pages = {5778--5786},
	publisher = {American Chemical Society},
	title = {Optimization and Automation of Quantitative NMR Data Extraction},
	type = {doi: 10.1021/ac400411q},
	url = {https://doi.org/10.1021/ac400411q},
	volume = {85},
	year = {2013},
	year1 = {2013},
	bdsk-url-1 = {https://doi.org/10.1021/ac400411q}}

@article{Hogben:2011aa,
	abstract = {We introduce a software library incorporating our recent research into efficient simulation algorithms for large spin systems. Liouville space simulations (including symmetry, relaxation and chemical kinetics) of most liquid-state NMR experiments on 40+ spin systems can now be performed without effort on a desktop workstation. Much progress has also been made with improving the efficiency of ESR, solid state NMR and Spin Chemistry simulations. Spinach is available for download at http://spindynamics.org.},
	author = {Hogben, H. J. and Krzystyniak, M. and Charnock, G. T. P. and Hore, P. J. and Kuprov, Ilya},
	date = {2011/02/01/},
	date-added = {2024-03-26 16:56:04 -0400},
	date-modified = {2024-03-27 10:38:28 -0400},
	doi = {10.1016/j.jmr.2010.11.008},
	isbn = {1090-7807},
	journal = {Journal of Magnetic Resonance},
	keywords = {NMR; ESR; Simulation; Spin dynamics; },
	number = {2},
	pages = {179--194},
	title = {Spinach --A software library for simulation of spin dynamics in large spin systems},
	url = {https://www.sciencedirect.com/science/article/pii/S1090780710003575},
	volume = {208},
	year = {2011},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S1090780710003575},
	bdsk-url-2 = {https://doi.org/10.1016/j.jmr.2010.11.008}}

@article{Veshtort:2006aa,
	abstract = {Exact numerical simulations of NMR experiments are often required for the development of new techniques and for the extraction of structural and dynamic information from the spectra. Simulations of solid-state magic angle spinning (MAS) experiments can be particularly demanding both computationally and in terms of the programming required to carry them out, even if special simulation software is used. We recently developed a number of approaches that dramatically improve the efficiency and allow a high degree of automation of these computations. In the present paper, we describe SPINEVOLUTION, a highly optimized computer program that implements the new methodology. The algorithms used in the program will be described separately. Although particularly efficient for the simulation of experiments with complex pulse sequences and multi-spin systems in solids, SPINEVOLUTION is a versatile and easy to use tool for the simulation and optimization of virtually any NMR experiment. The performance of SPINEVOLUTION was compared with that of another recently developed NMR simulation package, SIMPSON. Benchmarked on a series of examples, SPINEVOLUTION was consistently found to be orders of magnitude faster. At the time of publication, the program is available gratis for non-commercial use.},
	author = {Veshtort, Mikhail and Griffin, Robert G.},
	date = {2006/02/01/},
	date-added = {2024-03-26 16:22:28 -0400},
	date-modified = {2024-03-27 10:39:11 -0400},
	doi = {10.1016/j.jmr.2005.07.018},
	isbn = {1090-7807},
	journal = {Journal of Magnetic Resonance},
	keywords = {NMR simulations; Virtual NMR spectrometer; Software; Parameter optimization; Data fitting},
	number = {2},
	pages = {248--282},
	title = {SPINEVOLUTION: A powerful tool for the simulation of solid and liquid state NMR experiments},
	url = {https://www.sciencedirect.com/science/article/pii/S1090780705002442},
	volume = {178},
	year = {2006},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S1090780705002442},
	bdsk-url-2 = {https://doi.org/10.1016/j.jmr.2005.07.018}}

@article{Kessler:1985aa,
	author = {Kessler, H. and M{\"u}ller, A. and Oschkinat, H.},
	date = {1985/10/01},
	date-added = {2024-03-26 14:53:04 -0400},
	date-modified = {2024-03-27 10:38:41 -0400},
	doi = {10.1002/mrc.1260231012},
	isbn = {0749-1581},
	journal = {Magnetic Resonance in Chemistry},
	journal1 = {Magnetic Resonance in Chemistry},
	journal2 = {Magnetic Resonance in Chemistry},
	journal3 = {Magn. Reson. Chem.},
	month = {2024/03/26},
	n2 = {Abstract A procedure is proposed for obtaining coupling constants from phase-sensitive H,H-COSY spectra. For this purpose, firstly pseudo-one-dimensional spectra are created by co-addition of individual traces of cross-peaks, and by a similar addition of diagonal peaks in a spectrum which is phase corrected to pure-absorption line shapes. The sum and difference of the pseudo-one-dimensional spectra of a cross-peak and its diagonal peak give two spectra, with a pattern in which the active coupling ceases to exist (?spin decoupling?) but is shifted by half the value of the same. If diagonal peaks are not available owing to overlapping signals, sums and differences of the pseudo-one-dimensional spectra of two cross-peaks can be applied to simplify spectral patterns for the evaluation of J values. The procedure is demonstrated with the example of the AMXY spin system of a tyrosine, and the complex pattern of the Pro8 spin system of the cyclic decapeptide antamanide. The conformation of the Pro8 ring, derived from the coupling constants thus obtained, is of the ?E type.},
	number = {10},
	pages = {844--852},
	publisher = {John Wiley \& Sons, Ltd},
	title = {Differences and sums of traces within, COSY spectra (DISCO) for the extraction of coupling constants: `Decoupling'after the measurement},
	url = {https://doi.org/10.1002/mrc.1260231012},
	volume = {23},
	year = {1985},
	year1 = {1985},
	bdsk-url-1 = {https://doi.org/10.1002/mrc.1260231012}}

@article{Delaglio:2001aa,
	abstract = {An interactive computer procedure is described which determines 1H--1H couplings from fitting the cross-peak multiplets in regular phase-sensitive COSY spectra. The robustness and simplicity of the method rely on the fact that a given cross-peak intensity is not an independent variable in the fitting procedure, making it possible to measure couplings accurately even from individual cross peaks with unresolved multiplet structure.},
	author = {Delaglio, Frank and Wu, Zhengrong and Bax, Ad},
	date = {2001/04/01/},
	date-added = {2024-03-26 14:51:29 -0400},
	date-modified = {2024-03-30 20:04:47 -0400},
	doi = {10.1006/jmre.2001.2297},
	isbn = {1090-7807},
	journal = {Journal of Magnetic Resonance},
	number = {2},
	pages = {276--281},
	title = {Measurement of Homonuclear Proton Couplings from Regular 2D COSY Spectra},
	url = {https://www.sciencedirect.com/science/article/pii/S1090780701922979},
	volume = {149},
	year = {2001},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S1090780701922979},
	bdsk-url-2 = {https://doi.org/10.1006/jmre.2001.2297}}

@article{Vuister:1993aa,
	annote = {doi: 10.1021/ja00070a024},
	author = {Vuister, Geerten W. and Bax, Ad},
	date = {1993/08/01},
	date-added = {2024-03-20 10:38:08 -0400},
	date-modified = {2024-03-20 10:38:08 -0400},
	doi = {10.1021/ja00070a024},
	isbn = {0002-7863},
	journal = {Journal of the American Chemical Society},
	journal1 = {Journal of the American Chemical Society},
	journal2 = {J. Am. Chem. Soc.},
	month = {08},
	number = {17},
	pages = {7772--7777},
	publisher = {American Chemical Society},
	title = {Quantitative J correlation: a new approach for measuring homonuclear three-bond J(HNH.alpha.) coupling constants in 15N-enriched proteins},
	type = {doi: 10.1021/ja00070a024},
	url = {https://doi.org/10.1021/ja00070a024},
	volume = {115},
	year = {1993},
	year1 = {1993},
	bdsk-url-1 = {https://doi.org/10.1021/ja00070a024}}

@article{Grzesiek:1995aa,
	annote = {doi: 10.1021/ja00124a014},
	author = {Grzesiek, Stephan and Kuboniwa, Hitoshi and Hinck, Andrew P. and Bax, Ad},
	date = {1995/05/01},
	date-added = {2024-03-20 10:28:44 -0400},
	date-modified = {2024-03-20 10:28:44 -0400},
	doi = {10.1021/ja00124a014},
	isbn = {0002-7863},
	journal = {Journal of the American Chemical Society},
	journal1 = {Journal of the American Chemical Society},
	journal2 = {J. Am. Chem. Soc.},
	month = {05},
	number = {19},
	pages = {5312--5315},
	publisher = {American Chemical Society},
	title = {Multiple-Quantum Line Narrowing for Measurement of H.alpha.-H.beta. J Couplings in Isotopically Enriched Proteins},
	type = {doi: 10.1021/ja00124a014},
	url = {https://doi.org/10.1021/ja00124a014},
	volume = {117},
	year = {1995},
	year1 = {1995},
	bdsk-url-1 = {https://doi.org/10.1021/ja00124a014}}

@article{Tessari:1995aa,
	author = {Tessari, M. and Mariani, M. and Boelens, R. and Kaptein, R.},
	date = {1995/07/01/},
	date-added = {2024-03-20 10:27:14 -0400},
	date-modified = {2024-03-27 10:38:55 -0400},
	doi = {10.1006/jmrb.1995.1108},
	isbn = {1064-1866},
	journal = {Journal of Magnetic Resonance, Series B},
	number = {1},
	pages = {89--93},
	title = {(H)XYH-COSY and (H)XYH-E.COSY Experiments for Backbone and Side-Chain Assignment and Determination of 3JHH′Coupling Constants in (13C, 15N)-Labeled Proteins},
	url = {https://www.sciencedirect.com/science/article/pii/S1064186685711089},
	volume = {108},
	year = {1995},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S1064186685711089},
	bdsk-url-2 = {https://doi.org/10.1006/jmrb.1995.1108}}

@article{Emerson:1992aa,
	author = {Emerson, S. Donald and Montelione, Gaetano T.},
	date = {1992/09/01/},
	date-added = {2024-03-20 09:44:57 -0400},
	date-modified = {2024-03-27 10:37:31 -0400},
	doi = {10.1016/0022-2364(92)90196-E},
	isbn = {0022-2364},
	journal = {Journal of Magnetic Resonance (1969)},
	number = {2},
	pages = {413--420},
	title = {2D and 3D HCCH TOCSY experiments for determining 3J(HαHβ) coupling constants of amino acid residues},
	url = {https://www.sciencedirect.com/science/article/pii/002223649290196E},
	volume = {99},
	year = {1992},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/002223649290196E},
	bdsk-url-2 = {https://doi.org/10.1016/0022-2364(92)90196-E}}

@article{Griesinger:1992aa,
	author = {Griesinger, C and Eggenberger, U},
	date = {1992/04/01/},
	date-added = {2024-03-20 09:42:41 -0400},
	date-modified = {2024-03-27 10:38:09 -0400},
	doi = {10.1016/0022-2364(92)90328-5},
	isbn = {0022-2364},
	journal = {Journal of Magnetic Resonance (1969)},
	number = {2},
	pages = {426--434},
	title = {Determination of proton-proton coupling constants in 13C-labeled molecules},
	url = {https://www.sciencedirect.com/science/article/pii/0022236492903285},
	volume = {97},
	year = {1992},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/0022236492903285},
	bdsk-url-2 = {https://doi.org/10.1016/0022-2364(92)90328-5}}

@article{Gemmecker:1991aa,
	author = {Gemmecker, Gerd and Fesik, Stephen W},
	date = {1991/10/15/},
	date-added = {2024-03-20 09:42:20 -0400},
	date-modified = {2024-03-27 10:37:48 -0400},
	doi = {10.1016/0022-2364(91)90340-Y},
	isbn = {0022-2364},
	journal = {Journal of Magnetic Resonance (1969)},
	number = {1},
	pages = {208--213},
	title = {A method for measuring 1H-1H coupling constants in 13C-labeled molecules},
	url = {https://www.sciencedirect.com/science/article/pii/002223649190340Y},
	volume = {95},
	year = {1991},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/002223649190340Y},
	bdsk-url-2 = {https://doi.org/10.1016/0022-2364(91)90340-Y}}

@inbook{Vuister:2002aa,
	address = {Boston, MA},
	author = {Vuister, Geerten W. and Tessari, Marco and Karimi-Nejad, Yasmin and Whitehead, Brian},
	booktitle = {Modern Techniques in Protein NMR},
	date-added = {2024-03-19 16:49:14 -0400},
	date-modified = {2024-03-19 16:49:38 -0400},
	doi = {10.1007/0-306-47083-7_6},
	editor = {Krishna, N. Rama and Berliner, Lawrence J.},
	isbn = {978-0-306-47083-7},
	pages = {195--257},
	publisher = {Springer US},
	title = {Pulse Sequences for Measuring Coupling Constants},
	url = {https://doi.org/10.1007/0-306-47083-7_6},
	year = {2002},
	bdsk-url-1 = {https://doi.org/10.1007/0-306-47083-7_6}}

@article{Prasch:1998aa,
	author = {Prasch, Thomas and Gr{\"o}schke, Peter and Glaser, Steffen J.},
	date = {1998/04/03},
	date-added = {2024-03-19 12:05:17 -0400},
	date-modified = {2024-03-19 12:05:26 -0400},
	doi = {10.1002/(SICI)1521-3773(19980403)37:6<802::AID-ANIE802>3.0.CO;2-M},
	isbn = {1433-7851},
	journal = {Angewandte Chemie International Edition},
	journal1 = {Angewandte Chemie International Edition},
	journal2 = {Angewandte Chemie International Edition},
	journal3 = {Angewandte Chemie International Edition},
	keywords = {NMR spectroscopy; Peptides; Proteins; Structure elucidation},
	month = {2024/03/19},
	n2 = {Abstract The simultaneous acquisition of in-phase and antiphase multiplets with high sensitivity and minimum overlap (see section of 2D spectra on the right) is possible in a novel NMR experiment. Based on this method, homonuclear coupling constants such as the 3J(HN,Hα) couplings in peptides and proteins can be determined quantitatively without isotope labeling.},
	number = {6},
	pages = {802--806},
	publisher = {John Wiley \& Sons, Ltd},
	title = {SIAM, a Novel NMR Experiment for the Determination of Homonuclear Coupling Constants},
	url = {https://doi.org/10.1002/(SICI)1521-3773(19980403)37:6<802::AID-ANIE802>3.0.CO;2-M},
	volume = {37},
	year = {1998},
	year1 = {1998},
	bdsk-url-1 = {https://doi.org/10.1002/(SICI)1521-3773(19980403)37:6%3C802::AID-ANIE802%3E3.0.CO;2-M}}

@article{Oschkinat:1984aa,
	author = {Oschkinat, Hartmut and Freeman, Ray},
	date = {1984/10/15/},
	date-added = {2024-03-19 11:52:41 -0400},
	date-modified = {2024-03-19 11:59:57 -0400},
	doi = {10.1016/0022-2364(84)90044-1},
	isbn = {0022-2364},
	journal = {Journal of Magnetic Resonance (1969)},
	number = {1},
	pages = {164--169},
	title = {Fine structure in two-dimensional NMR correlation spectroscopy},
	url = {https://www.sciencedirect.com/science/article/pii/0022236484900441},
	volume = {60},
	year = {1984},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/0022236484900441},
	bdsk-url-2 = {https://doi.org/10.1016/0022-2364(84)90044-1}}

@article{Huber:1993aa,
	author = {Huber, P. and Zwahlen, C. and Vincent, S. J. F. and Bodenhausen, G.},
	date = {1993/06/01/},
	date-added = {2024-03-19 11:42:40 -0400},
	date-modified = {2024-03-19 12:00:13 -0400},
	doi = {10.1006/jmra.1993.1142},
	isbn = {1064-1858},
	journal = {Journal of Magnetic Resonance, Series A},
	number = {1},
	pages = {118--121},
	title = {Accurate Determination of Scalar Couplings by Convolution of Complementary Two-Dimensional Multiplets},
	url = {https://www.sciencedirect.com/science/article/pii/S1064185883711423},
	volume = {103},
	year = {1993},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S1064185883711423},
	bdsk-url-2 = {https://doi.org/10.1006/jmra.1993.1142}}

@article{Titman:1990aa,
	author = {Titman, Jeremy J and Keeler, James},
	date = {1990/10/01/},
	date-added = {2024-03-19 11:41:20 -0400},
	date-modified = {2024-03-19 12:00:29 -0400},
	doi = {10.1016/0022-2364(90)90351-9},
	isbn = {0022-2364},
	journal = {Journal of Magnetic Resonance (1969)},
	number = {3},
	pages = {640--646},
	title = {Measurement of homonuclear coupling constants from NMR correlation spectra},
	url = {https://www.sciencedirect.com/science/article/pii/0022236490903519},
	volume = {89},
	year = {1990},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/0022236490903519},
	bdsk-url-2 = {https://doi.org/10.1016/0022-2364(90)90351-9}}

@article{Lohr:1999aa,
	annote = {doi: 10.1021/ja991356h},
	author = {L{\"o}hr, Frank and Schmidt, J{\"u}rgen M. and R{\"u}terjans, Heinz},
	date = {1999/12/01},
	date-added = {2024-03-19 11:28:02 -0400},
	date-modified = {2024-03-19 11:28:02 -0400},
	doi = {10.1021/ja991356h},
	isbn = {0002-7863},
	journal = {Journal of the American Chemical Society},
	journal1 = {Journal of the American Chemical Society},
	journal2 = {J. Am. Chem. Soc.},
	month = {12},
	number = {50},
	pages = {11821--11826},
	publisher = {American Chemical Society},
	title = {Simultaneous Measurement of 3JHN,Hαand 3JHα,HβCoupling Constants in 13C,15N-Labeled Proteins},
	type = {doi: 10.1021/ja991356h},
	url = {https://doi.org/10.1021/ja991356h},
	volume = {121},
	year = {1999},
	year1 = {1999},
	bdsk-url-1 = {https://doi.org/10.1021/ja991356h}}

@article{Delaglio:1995aa,
	abstract = {The NMRPipe system is a UNIX software environment of processing, graphics, and analysis tools designed to meet current routine and research-oriented multidimensional processing requirements, and to anticipate and accommodate future demands and developments. The system is based on UNIX pipes, which allow programs running simultaneously to exchange streams of data under user control. In an NMRPipe processing scheme, a stream of spectral data flows through a pipeline of processing programs, each of which performs one component of the overall scheme, such as Fourier transformation or linear prediction. Complete multidimensional processing schemes are constructed as simple UNIX shell scripts. The processing modules themselves maintain and exploit accurate records of data sizes, detection modes, and calibration information in all dimensions, so that schemes can be constructed without the need to explicitly define or anticipate data sizes or storage details of real and imaginary channels during processing. The asynchronous pipeline scheme provides other substantial advantages, including high flexibility, favorable processing speeds, choice of both all-in-memory and disk-bound processing, easy adaptation to different data formats, simpler software development and maintenance, and the ability to distribute processing tasks on multi-CPU computers and computer networks.},
	author = {Delaglio, Frank and Grzesiek, Stephan and Vuister, Geerten W. and Zhu, Guang and Pfeifer, John and Bax, Ad},
	date = {1995/11/01},
	date-added = {2024-03-19 11:14:51 -0400},
	date-modified = {2024-03-19 11:14:51 -0400},
	doi = {10.1007/BF00197809},
	id = {Delaglio1995},
	isbn = {1573-5001},
	journal = {Journal of Biomolecular NMR},
	number = {3},
	pages = {277--293},
	title = {NMRPipe: A multidimensional spectral processing system based on UNIX pipes},
	url = {https://doi.org/10.1007/BF00197809},
	volume = {6},
	year = {1995},
	bdsk-url-1 = {https://doi.org/10.1007/BF00197809}}

@article{Griesinger:1986aa,
	abstract = {A novel and general concept of restricting coherence transfer in nuclear spin systems is described. It opens new possibilities for editing one‐and two‐dimensional NMR spectra. For example, the widely applied two‐dimensional correlation experiment COSY can be modified such as to restrict coherence transfer to take place exclusively between connected transitions in the energy level diagram. Such two‐dimensional spectra possess ideal features for assignment of complex scalar coupling networks and for computer assisted analysis. Experimental 1H spectra of a cyclic decapeptide are presented. Other applications of the general filtering concept are briefly discussed.},
	author = {Griesinger, C. and S{\o}rensen, O. W. and Ernst, R. R.},
	date-added = {2024-03-19 11:07:29 -0400},
	date-modified = {2024-03-19 11:16:08 -0400},
	doi = {10.1063/1.451421},
	isbn = {0021-9606},
	journal = {The Journal of Chemical Physics},
	journal1 = {J. Chem. Phys.},
	month = {3/19/2024},
	number = {12},
	pages = {6837--6852},
	title = {Correlation of connected transitions by two‐dimensional NMR spectroscopy},
	url = {https://doi.org/10.1063/1.451421},
	volume = {85},
	year = {1986},
	year1 = {1986/12/15},
	bdsk-url-1 = {https://doi.org/10.1063/1.451421}}

@article{Griesinger:1985aa,
	annote = {doi: 10.1021/ja00308a042},
	author = {Griesinger, C. and S{\o}rensen, O. W. and Ernst, R. R.},
	date = {1985/10/01},
	date-added = {2024-03-19 11:06:34 -0400},
	date-modified = {2024-03-19 11:16:20 -0400},
	doi = {10.1021/ja00308a042},
	isbn = {0002-7863},
	journal = {Journal of the American Chemical Society},
	journal1 = {Journal of the American Chemical Society},
	journal2 = {J. Am. Chem. Soc.},
	month = {10},
	number = {22},
	pages = {6394--6396},
	publisher = {American Chemical Society},
	title = {Two-dimensional correlation of connected NMR transitions},
	type = {doi: 10.1021/ja00308a042},
	url = {https://doi.org/10.1021/ja00308a042},
	volume = {107},
	year = {1985},
	year1 = {1985},
	bdsk-url-1 = {https://doi.org/10.1021/ja00308a042}}

@article{Griesinger:1987aa,
	abstract = {Practical aspects of the E.COSY technique for measurement of coupling constants are discussed. Guidelines are presented for the experimental setup and for spectral assignments. The features of E.COSY cross-peak multiplet patterns are illustrated by experimental spectra of valine, phenylalanine, and proline residues in the decapeptide antamanide.},
	author = {Griesinger, C and S{\o}rensen, O. W and Ernst, R. R},
	date = {1987/12/01/},
	date-added = {2024-03-19 10:55:29 -0400},
	date-modified = {2024-03-19 11:13:21 -0400},
	doi = {10.1016/0022-2364(87)90102-8},
	isbn = {0022-2364},
	journal = {Journal of Magnetic Resonance (1969)},
	number = {3},
	pages = {474--492},
	title = {Practical aspects of the E.COSY technique. Measurement of scalar spin-spin coupling constants in peptides},
	url = {https://www.sciencedirect.com/science/article/pii/0022236487901028},
	volume = {75},
	year = {1987},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/0022236487901028},
	bdsk-url-2 = {https://doi.org/10.1016/0022-2364(87)90102-8}}

@article{Shapovalov:2011aa,
	abstract = {Summary Rotamer libraries are used in protein structure determination, prediction, and design. The backbone-dependent rotamer library consists of rotamer frequencies, mean dihedral angles, and variances as a function of the backbone dihedral angles. Structure prediction and design methods that employ backbone flexibility would strongly benefit from smoothly varying probabilities and angles. A new version of the backbone-dependent rotamer library has been developed using adaptive kernel density estimates for the rotamer frequencies and adaptive kernel regression for the mean dihedral angles and variances. This formulation allows for evaluation of the rotamer probabilities, mean angles, and variances as a smooth and continuous function of phi and psi. Continuous probability density estimates for the nonrotameric degrees of freedom of amides, carboxylates, and aromatic side chains have been modeled as a function of the backbone dihedrals and rotamers of the remaining degrees of freedom. New backbone-dependent rotamer libraries at varying levels of smoothing are available from http://dunbrack.fccc.edu.},
	author = {Shapovalov, Maxim V. and Dunbrack, Roland L.},
	date = {2011/06/08/},
	date-added = {2024-03-12 16:49:43 -0400},
	date-modified = {2024-03-19 11:13:56 -0400},
	doi = {10.1016/j.str.2011.03.019},
	isbn = {0969-2126},
	journal = {Structure},
	number = {6},
	pages = {844--858},
	title = {A Smoothed Backbone-Dependent Rotamer Library for Proteins Derived from Adaptive Kernel Density Estimates and Regressions},
	url = {https://www.sciencedirect.com/science/article/pii/S0969212611001444},
	volume = {19},
	year = {2011},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S0969212611001444},
	bdsk-url-2 = {https://doi.org/10.1016/j.str.2011.03.019}}

@article{Westbrook:2015aa,
	abstract = {Summary: The Chemical Component Dictionary (CCD) is a chemical reference data resource that describes all residue and small molecule components found in Protein Data Bank (PDB) entries. The CCD contains detailed chemical descriptions for standard and modified amino acids/nucleotides, small molecule ligands and solvent molecules. Each chemical definition includes descriptions of chemical properties such as stereochemical assignments, chemical descriptors, systematic chemical names and idealized coordinates. The content, preparation, validation and distribution of this CCD chemical reference dataset are described.Availability and implementation: The CCD is updated regularly in conjunction with the scheduled weekly release of new PDB structure data. The CCD and amino acid variant reference datasets are hosted in the public PDB ftp repository at ftp://ftp.wwpdb.org/pub/pdb/data/monomers/components.cif.gz, ftp://ftp.wwpdb.org/pub/pdb/data/monomers/aa-variants-v1.cif.gz, and its mirror sites, and can be accessed from http://wwpdb.org.Contact:  jwest{\char64}rcsb.rutgers.edu.Supplementary information:  Supplementary data are available at Bioinformatics online.},
	author = {Westbrook, John D. and Shao, Chenghua and Feng, Zukang and Zhuravleva, Marina and Velankar, Sameer and Young, Jasmine},
	date-added = {2024-03-12 14:59:10 -0400},
	date-modified = {2024-03-12 14:59:10 -0400},
	doi = {10.1093/bioinformatics/btu789},
	isbn = {1367-4803},
	journal = {Bioinformatics},
	journal1 = {Bioinformatics},
	month = {3/12/2024},
	number = {8},
	pages = {1274--1278},
	title = {The chemical component dictionary: complete descriptions of constituent molecules in experimentally determined 3D macromolecules in the Protein Data Bank},
	url = {https://doi.org/10.1093/bioinformatics/btu789},
	volume = {31},
	year = {2015},
	year1 = {2015/04/01},
	bdsk-url-1 = {https://doi.org/10.1093/bioinformatics/btu789}}

@article{Schmidt:1999aa,
	abstract = {The concept of self-consistent J coupling evaluation exploits redundant structure information inherent in large sets of 3J coupling constants. Application to the protein Desulfovibrio vulgaris flavodoxin demonstrates the simultaneous refinement of torsion-angle values and related Karplus coefficients. The experimental basis includes quantitative coupling constants related to the polypeptide backbone φtorsion originating from a variety of heteronuclear 2D and 3D NMR correlation experiments, totalling 124 3J(HN,Hα), 129 3J(HN,C′), 121 3J(HN,Cβ), 128 3J(C′i−1,Hαi), 121 3J(C′i−1,C′i), and 122 3J(C′i−1,Cβi). Without prior knowledge from either X-ray crystallography or NMR data, such as NOE distance constraints, accurate φdihedral angles are specified for 122 non-glycine and non-proline residues out of a total of 147 amino acids. Different models of molecular internal mobility are considered. The Karplus coefficients obtained are applicable to the conformational analysis of φtorsions in other polypeptides.},
	author = {Schmidt, J{\"u}rgen M. and Bl{\"u}mel, Markus and L{\"o}hr, Frank and R{\"u}terjans, Heinz},
	date = {1999/05/01},
	date-added = {2024-03-12 14:44:15 -0400},
	date-modified = {2024-03-12 14:44:15 -0400},
	doi = {10.1023/A:1008345303942},
	id = {Schmidt1999},
	isbn = {1573-5001},
	journal = {Journal of Biomolecular NMR},
	number = {1},
	pages = {1--12},
	title = {Self-consistent 3J coupling analysis for the joint calibration of Karplus coefficients and evaluation of torsion angles},
	url = {https://doi.org/10.1023/A:1008345303942},
	volume = {14},
	year = {1999},
	bdsk-url-1 = {https://doi.org/10.1023/A:1008345303942}}

@article{Karplus:1963aa,
	annote = {doi: 10.1021/ja00901a059},
	author = {Karplus, Martin.},
	date = {1963/09/01},
	date-added = {2024-03-12 14:19:39 -0400},
	date-modified = {2024-03-12 14:19:39 -0400},
	doi = {10.1021/ja00901a059},
	isbn = {0002-7863},
	journal = {Journal of the American Chemical Society},
	journal1 = {Journal of the American Chemical Society},
	journal2 = {J. Am. Chem. Soc.},
	month = {09},
	number = {18},
	pages = {2870--2871},
	publisher = {American Chemical Society},
	title = {Vicinal Proton Coupling in Nuclear Magnetic Resonance},
	type = {doi: 10.1021/ja00901a059},
	url = {https://doi.org/10.1021/ja00901a059},
	volume = {85},
	year = {1963},
	year1 = {1963},
	bdsk-url-1 = {https://doi.org/10.1021/ja00901a059}}

@article{Perez:2001aa,
	abstract = {Recently proposed self-consistent 3J coupling analysis (Schmidt, J. M.; Bl{\"u}mel, M.; L{\"o}hr, F.; R{\"u}terjans, H. J. Biomol. NMR 1999, 14, 1-12) has been carried out to calibrate Karplus parameters constituting the empirical dependence of 3J coupling constants on the chi1 dihedral angle in amino acid side chains. The procedure involves simultaneous least-squares optimization of six sets of three Karplus coefficients related to all six 3J coupling types accessible in 15N,13C-labeled proteins. A simple concept of fundamental and incremental component couplings is proposed to account for substituent effects, eventually yielding amino acid topology-specific Karplus parameters. The method is exemplified with recombinant Desulfovibrio vulgaris flavodoxin (147 amino acids, 16 kDa) with reference to a total of 749 experimental 3JHalpha,Hbeta, 3JN',Hbeta, 3JC',Hbeta, 3JHalpha,Cgamma, 3JN',Cgamma, and 3JC',Cgamma coupling constants. Unlike other parametrizations, the present method does not make reference to X-ray coordinates, so that the Karplus coefficients obtained are not influenced by differences between solution and crystal states. Cross validation using X-ray torsion angles demonstrates the improvement relative to previous parametrizations. The Karplus coefficients derived are applicable to other proteins, too. Parameter refinement also yields a series of chi1 torsion angles, providing valuable constraints for protein structure determination, as well as optional parameters of local angular mobility in the contexts of Gaussian random fluctuation or a three-site jump model. The procedure permits automatic stereospecific assignments of Hbeta and Cgamma chemical shifts. The majority of the flavodoxin side-chain conformations agrees with high-resolution X-ray structures of the protein. Marked deviations between NMR and X-ray datasets are attributed to different rotameric states due to crystal-packing effects and to conformational equilibria between multiple chi1 rotamers.},
	address = {Institut f{\"u}r Biophysikalische Chemie, Johann Wolfgang Goethe-Universit{\"a}t, Biozentrum N230, Marie-Curie-Strasse 9, D-60439 Frankfurt am Main, Germany.},
	author = {P{\'e}rez, C and L{\"o}hr, F and R{\"u}terjans, H and Schmidt, J M},
	crdt = {2001/07/19 10:00},
	date = {2001 Jul 25},
	date-added = {2024-01-17 12:54:52 -0500},
	date-modified = {2024-01-17 12:54:52 -0500},
	dcom = {20011204},
	doi = {10.1021/ja003724j},
	edat = {2001/07/19 10:00},
	issn = {0002-7863 (Print); 0002-7863 (Linking)},
	jid = {7503056},
	journal = {J Am Chem Soc},
	jt = {Journal of the American Chemical Society},
	language = {eng},
	lr = {20190708},
	mh = {Flavodoxin/chemistry; Magnetics; Models, Molecular; Molecular Structure; Nuclear Magnetic Resonance, Biomolecular/*methods; Peptides/*chemistry; Torsion Abnormality},
	mhda = {2002/01/05 10:01},
	month = {Jul},
	number = {29},
	own = {NLM},
	pages = {7081--7093},
	phst = {2001/07/19 10:00 {$[$}pubmed{$]$}; 2002/01/05 10:01 {$[$}medline{$]$}; 2001/07/19 10:00 {$[$}entrez{$]$}},
	pii = {ja003724j},
	pl = {United States},
	pmid = {11459487},
	pst = {ppublish},
	pt = {Journal Article; Research Support, Non-U.S. Gov't},
	rn = {0 (Flavodoxin); 0 (Peptides)},
	sb = {IM},
	status = {MEDLINE},
	title = {Self-consistent Karplus parametrization of 3J couplings depending on the polypeptide side-chain torsion chi1.},
	volume = {123},
	year = {2001},
	bdsk-url-1 = {https://doi.org/10.1021/ja003724j}}

@article{Hoch:2023aa,
	abstract = {The Biological Magnetic Resonance Data Bank (BMRB, https://bmrb.io) is the international open data repository for biomolecular nuclear magnetic resonance (NMR) data. Comprised of both empirical and derived data, BMRB has applications in the study of biomacromolecular structure and dynamics, biomolecular interactions, drug discovery, intrinsically disordered proteins, natural products, biomarkers, and metabolomics. Advances including GHz-class NMR instruments, national and trans-national NMR cyberinfrastructure, hybrid structural biology methods and machine learning are driving increases in the amount, type, and applications of NMR data in the biosciences. BMRB is a Core Archive and member of the World-wide Protein Data Bank (wwPDB).},
	address = {Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871. Japan.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871. Japan.; Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871. Japan.; Graduate School of Engineering Science, Yokohama National University, Yokohama 240-8501, Japan.; Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871. Japan.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871. Japan.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA.; Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871. Japan.},
	auid = {ORCID: 0000-0002-9230-2019; ORCID: 0000-0002-5073-1819; ORCID: 0000-0002-5354-0807},
	author = {Hoch, Jeffrey C and Baskaran, Kumaran and Burr, Harrison and Chin, John and Eghbalnia, Hamid R and Fujiwara, Toshimichi and Gryk, Michael R and Iwata, Takeshi and Kojima, Chojiro and Kurisu, Genji and Maziuk, Dmitri and Miyanoiri, Yohei and Wedell, Jonathan R and Wilburn, Colin and Yao, Hongyang and Yokochi, Masashi},
	copyright = {{\copyright}The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.},
	crdt = {2022/12/08 12:35},
	date = {2023 Jan 6},
	date-added = {2024-01-17 11:14:13 -0500},
	date-modified = {2024-01-17 11:14:34 -0500},
	dcom = {20230119},
	doi = {10.1093/nar/gkac1050},
	edat = {2022/12/09 06:00},
	gr = {R01 GM109046/GM/NIGMS NIH HHS/United States},
	issn = {1362-4962 (Electronic); 0305-1048 (Print); 0305-1048 (Linking)},
	jid = {0411011},
	journal = {Nucleic Acids Res},
	jt = {Nucleic acids research},
	language = {eng},
	lid = {10.1093/nar/gkac1050 {$[$}doi{$]$}},
	lr = {20230128},
	mh = {Databases, Protein; *Magnetic Resonance Spectroscopy; Nuclear Magnetic Resonance, Biomolecular; Protein Conformation; *Databases, Chemical},
	mhda = {2023/01/12 06:00},
	month = {Jan},
	number = {D1},
	own = {NLM},
	pages = {D368-D376},
	phst = {2022/10/23 00:00 {$[$}accepted{$]$}; 2022/10/20 00:00 {$[$}revised{$]$}; 2022/10/04 00:00 {$[$}received{$]$}; 2022/12/09 06:00 {$[$}pubmed{$]$}; 2023/01/12 06:00 {$[$}medline{$]$}; 2022/12/08 12:35 {$[$}entrez{$]$}},
	pii = {6880708; gkac1050},
	pl = {England},
	pmc = {PMC9825541},
	pmid = {36478084},
	pst = {ppublish},
	pt = {Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't},
	sb = {IM},
	status = {MEDLINE},
	title = {Biological Magnetic Resonance Data Bank},
	volume = {51},
	year = {2023},
	bdsk-url-1 = {https://doi.org/10.1093/nar/gkac1050}}

@article{Dashti:2018aa,
	abstract = {We have developed technology for producing accurate spectral fingerprints of small molecules through modeling of NMR spin system matrices to encapsulate their chemical shifts and scalar couplings. We describe here how libraries of these spin systems utilizing unique and reproducible atom numbering can be used to improve NMR-based ligand screening and metabolomics studies. We introduce new Web services that facilitate the analysis of NMR spectra of mixtures of small molecules to yield their identification and quantification. The library of parametrized compounds has been expanded to cover simulations of (1)H NMR spectra at a variety of magnetic fields of more than 1100 compounds, included are many common metabolites and a library of drug-like molecular fragments used in ligand screening. The compound library and related Web services are freely available from http://gissmo.nmrfam.wisc.edu/ .},
	address = {Department of Pathology and Immunology , Washington University School of Medicine , St. Louis , Missouri 63110 , United States.},
	auid = {ORCID: 0000-0002-0418-9707; ORCID: 0000-0002-5073-1819},
	author = {Dashti, Hesam and Wedell, Jonathan R and Westler, William M and Tonelli, Marco and Aceti, David and Amarasinghe, Gaya K and Markley, John L and Eghbalnia, Hamid R},
	cois = {The authors declare no competing financial interest.},
	crdt = {2018/08/21 06:00},
	date = {2018 Sep 18},
	date-added = {2024-01-17 09:42:55 -0500},
	date-modified = {2024-01-17 09:42:55 -0500},
	dcom = {20190408},
	dep = {20180824},
	doi = {10.1021/acs.analchem.8b02660},
	edat = {2018/08/21 06:00},
	gr = {R01 GM109046/GM/NIGMS NIH HHS/United States; R01 AI123926/AI/NIAID NIH HHS/United States; P01 AI120943/AI/NIAID NIH HHS/United States; P41 GM111135/GM/NIGMS NIH HHS/United States; P41 GM103399/GM/NIGMS NIH HHS/United States; U19 AI109664/AI/NIAID NIH HHS/United States},
	issn = {1520-6882 (Electronic); 0003-2700 (Print); 0003-2700 (Linking)},
	jid = {0370536},
	journal = {Anal Chem},
	jt = {Analytical chemistry},
	language = {eng},
	lid = {10.1021/acs.analchem.8b02660 {$[$}doi{$]$}},
	lr = {20190408},
	mhda = {2018/08/21 06:01},
	mid = {NIHMS993026},
	month = {Sep},
	number = {18},
	own = {NLM},
	pages = {10646--10649},
	phst = {2018/08/21 06:00 {$[$}pubmed{$]$}; 2018/08/21 06:01 {$[$}medline{$]$}; 2018/08/21 06:00 {$[$}entrez{$]$}},
	pl = {United States},
	pmc = {PMC6201686},
	pmid = {30125102},
	pst = {ppublish},
	pt = {Journal Article; Research Support, Non-U.S. Gov't},
	status = {PubMed-not-MEDLINE},
	title = {Applications of Parametrized NMR Spin Systems of Small Molecules.},
	volume = {90},
	year = {2018},
	bdsk-url-1 = {https://doi.org/10.1021/acs.analchem.8b02660}}

@article{Dashti:2017aa,
	abstract = {The exceptionally rich information content of nuclear magnetic resonance (NMR) spectra is routinely used to identify and characterize molecules and molecular interactions in a wide range of applications, including clinical biomarker discovery, drug discovery, environmental chemistry, and metabolomics. The set of peak positions and intensities from a reference NMR spectrum generally serves as the identifying signature for a compound. Reference spectra normally are collected under specific conditions of pH, temperature, and magnetic field strength, because changes in conditions can distort the identifying signatures of compounds. A spin system matrix that parametrizes chemical shifts and coupling constants among spins provides a much richer feature set for a compound than a spectral signature based on peak positions and intensities. Spin system matrices expand the applicability of NMR spectral libraries beyond the specific conditions under which data were collected. In addition to being able to simulate spectra at any field strength, spin parameters can be adjusted to systematically explore alterations in chemical shift patterns due to variations in other experimental conditions, such as compound concentration, pH, or temperature. We present methodology and software for efficient interactive optimization of spin parameters against experimental 1D-(1)H NMR spectra of small molecules. We have used the software to generate spin system matrices for a set of key mammalian metabolites and are also using the software to parametrize spectra of small molecules used in NMR-based ligand screening. The software, along with optimized spin system matrix data for a growing number of compounds, is available from http://gissmo.nmrfam.wisc.edu/ .},
	address = {National Magnetic Resonance Facility at Madison and BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.; National Magnetic Resonance Facility at Madison and BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.; National Magnetic Resonance Facility at Madison and BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.; National Magnetic Resonance Facility at Madison and BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.; National Magnetic Resonance Facility at Madison and BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.; National Magnetic Resonance Facility at Madison and BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.},
	auid = {ORCID: 0000-0003-1799-6134},
	author = {Dashti, Hesam and Westler, William M and Tonelli, Marco and Wedell, Jonathan R and Markley, John L and Eghbalnia, Hamid R},
	cois = {Notes The authors declare no competing financial interest.},
	crdt = {2017/10/24 06:00},
	date = {2017 Nov 21},
	date-added = {2024-01-17 09:42:55 -0500},
	date-modified = {2024-01-17 09:42:55 -0500},
	dcom = {20190416},
	dep = {20171107},
	doi = {10.1021/acs.analchem.7b02884},
	edat = {2017/10/24 06:00},
	gr = {P41 GM103399/GM/NIGMS NIH HHS/United States; P41 GM111135/GM/NIGMS NIH HHS/United States; R01 GM109046/GM/NIGMS NIH HHS/United States},
	issn = {1520-6882 (Electronic); 0003-2700 (Print); 0003-2700 (Linking)},
	jid = {0370536},
	journal = {Anal Chem},
	jt = {Analytical chemistry},
	language = {eng},
	lid = {10.1021/acs.analchem.7b02884 {$[$}doi{$]$}},
	lr = {20190416},
	mh = {Hydrogen-Ion Concentration; Ligands; *Magnetic Resonance Spectroscopy; Metabolomics/*methods; Small Molecule Libraries/*analysis/metabolism; Software; Temperature},
	mhda = {2019/04/17 06:00},
	mid = {NIHMS919584},
	month = {Nov},
	number = {22},
	own = {NLM},
	pages = {12201--12208},
	phst = {2017/10/24 06:00 {$[$}pubmed{$]$}; 2019/04/17 06:00 {$[$}medline{$]$}; 2017/10/24 06:00 {$[$}entrez{$]$}},
	pl = {United States},
	pmc = {PMC5705194},
	pmid = {29058410},
	pst = {ppublish},
	pt = {Journal Article; Research Support, N.I.H., Extramural},
	rn = {0 (Ligands); 0 (Small Molecule Libraries)},
	sb = {IM},
	status = {MEDLINE},
	title = {Spin System Modeling of Nuclear Magnetic Resonance Spectra for Applications in Metabolomics and Small Molecule Screening.},
	volume = {89},
	year = {2017},
	bdsk-url-1 = {https://doi.org/10.1021/acs.analchem.7b02884}}

@article{Dudley:2020,
	abstract = {Nuclear magnetic resonance (NMR) is a valuable tool for determining the structures of molecules and probing their dynamics. A longstanding problem facing both small-molecule and macromolecular NMR is overlapped signals in crowded spectra. To address this, we have developed a method that extracts peak features by fitting analytically derived models of NMR lineshapes. The approach takes into account the effects of truncation, apodization, and the resulting artifacts, while avoiding systematic errors that have affected other models. Even severely overlapped peaks, beyond the point of coalescence, can be distinguished in both simulated and experimental data. We show that the method can measure unresolved backbone scalar couplings directly from a 2D proton-nitrogen spectrum of a de novo designed mini protein. The algorithm is implemented in the FitNMR open-source R package and can be used to analyze nearly any type of single or multidimensional data from small molecules or biomolecules.},
	author = {Joshua A Dudley and Sojeong Park and Meagan E MacDonald and Emanual Fetene and Colin A Smith},
	date-added = {2024-01-17 09:36:41 -0500},
	date-modified = {2024-01-17 09:36:41 -0500},
	doi = {10.1016/j.jmr.2020.106773},
	journal = {J Magn Reson},
	month = {Sep},
	pages = {106773},
	title = {Resolving overlapped signals with automated FitNMR analytical peak modeling},
	volume = {318},
	year = {2020},
	bdsk-url-1 = {https://doi.org/10.1016/j.jmr.2020.106773}}

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