Spin System Modeling of Nuclear Magnetic Resonance Spectra for Applications in Metabolomics and Small Molecule Screening

被引:31
作者
Dashti, Hesam [1 ]
Westler, William M. [1 ]
Tonelli, Marco [1 ]
Wedell, Jonathan R. [1 ]
Markley, John L. [1 ]
Eghbalnia, Hamid R. [1 ]
机构
[1] Univ Wisconsin, Dept Biochem, Madison & BioMagResBank, Natl Magnet Resonance Facil, Madison, WI 53706 USA
基金
美国国家卫生研究院;
关键词
RESOLUTION NMR-SPECTRA; COUPLING-CONSTANTS; CHEMICAL-SHIFTS; SPECTROSCOPY; METABOLITES; SIMULATION; PREDICTION; TISSUE; SERUM;
D O I
10.1021/acs.analchem.7b02884
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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-1H 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/.
引用
收藏
页码:12201 / 12208
页数:8
相关论文
共 56 条
[1]   ANALYSIS OF HIGH-RESOLUTION NMR SPECTRA [J].
ANDERSON, W ;
MCCONNELL, HM .
JOURNAL OF CHEMICAL PHYSICS, 1957, 26 (06) :1496-1504
[2]  
[Anonymous], 2003, HDB CHEM PHYS
[3]   Liouvillians in NMR: The direct method revisited [J].
Bain, Alex D. ;
Berno, Bob .
PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY, 2011, 59 (03) :223-244
[4]   Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts [J].
Beckonert, Olaf ;
Keun, Hector C. ;
Ebbels, Timothy M. D. ;
Bundy, Jacob G. ;
Holmes, Elaine ;
Lindon, John C. ;
Nicholson, Jeremy K. .
NATURE PROTOCOLS, 2007, 2 (11) :2692-2703
[5]   The impact of available experimental data on the prediction of 1H NMR chemical shifts by neural networks [J].
Binev, Y ;
Corvo, M ;
Aires-De-Sousa, J .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2004, 44 (03) :946-949
[6]   Prediction of 1H NMR coupling constants with associative neural networks trained for chemical shifts [J].
Binev, Yuri ;
Marques, Maria M. B. ;
Aires-de-Sousa, Joao .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2007, 47 (06) :2089-2097
[7]   Ligand-Orientation Based Fragment Selection in STD NMR Screening [J].
Cala, Olivier ;
Krimm, Isabelle .
JOURNAL OF MEDICINAL CHEMISTRY, 2015, 58 (21) :8739-8742
[8]   NMR-based analysis of protein-ligand interactions [J].
Cala, Olivier ;
Guilliere, Florence ;
Krimm, Isabelle .
ANALYTICAL AND BIOANALYTICAL CHEMISTRY, 2014, 406 (04) :943-956
[9]   NMR Screening and Hit Validation in Fragment Based Drug Discovery [J].
Campos-Olivas, Ramon .
CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2011, 11 (01) :43-67
[10]   A normalized root-mean-square distance for comparing protein three-dimensional structures [J].
Carugo, O ;
Pongor, S .
PROTEIN SCIENCE, 2001, 10 (07) :1470-1473