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HMQC

HMQC (Heteronuclear Multiple Quantum Coherence) is a powerful NMR spectroscopy technique used to investigate the chemical structure and dynamics of molecules.
It provides information about the coupling between proton and heteroatom (e.g., carbon, nitrogen) spins, enabling the analysis of complex molecular systems.
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Most cited protocols related to «HMQC»

1
Multidimensional NMR Experiments for Protein Structure
Cited 123 times
The 3D 15N dispersed NOESY experiment on the M50 protein was performed on a Bruker Avance 800 instrument at 298K. A total of 48 scans were recorded per increment. For the measurements the sweep width in the direct dimension was 11160.714 Hz, which was reduced to the HN area (11.0ppm – 5.5ppm) of 4403.250 Hz for the reconstruction. The sweep width in the indirect proton dimension was 9606.148 Hz ( 9.61 kHz), which was sampled in 400 increments of 0.104 ms and a maximum evolution time t-max of 41.62 ms. The sweep width in the indirect nitrogen dimension was 2000.000 Hz, which was sampled in 100 increments of 0.5ms and a maximum evolution time t-max of 50.00 ms. A total of 2400 increments out of the 40,000 point indirect Nyquist grid were measured resulting in a 6% sampling density.
The 4D methyl-methyl HMQC NOESY experiment on the MED25/VP16 complex was recorded on a Bruker Avance 750 instrument at 298K with the procedures described in (Hiller et al. 2009 (link)). The sampling schedule for the experiment on MED25/VP16 was generated with the MDD toolkit (Hiller et al. 2009 (link)). The sampling density was 14.5 %, with a maximum evolution time in the indirect dimensions of 17 ms in 1Hnoe, 13 ms in 13Cnoe, and 29 ms in 13Cdir. The numbers of complex indirect points in the Nyquist grid were 28 for 1Hnoe, 44 for 13Cnoe, and 96 for 13Cdir. The NOE mixing time was 150 ms. Spectral widths of the indirect dimensions were 1650 Hz in 1Hnoe, 3300 Hz in 13Cnoe and 13Cdir. The direct proton dimension was acquired for 77 ms with a spectral width of 10000 Hz. Four scans were recorded for each FID.
The 4D methyl-methyl HMQC NOESY experiment on GB1was recorded on a Bruker Avance 500 instrument at 303K using a methyl TROSY pulse sequence (Tugarinov et al. 2003 (link))(Hiller et al. 2009 (link)). The schedule for the 4D methyl-methyl NOESY experiment on GB1 was generated with the Poisson Gap sampling GUI described below. The sampling density was 0.8 % with maximum evolution times in the indirect dimensions of 118 ms in 1Hnoe, 118.4 ms in 13Cnoe, and 118.8 ms in 13Cdir. The numbers of complex indirect points in the Nyquist grid were 60 for 1Hnoe, 150 for 13Cnoe, and 150 for 13Cdir. The NOESY mixing time was 120 ms. Spectral widths of the indirect dimensions were 500.1 Hz in 1Hnoe, 1257.6 Hz in 13Cnoe and 13Cdir. The direct proton dimension was acquired for 154 ms with a spectral width of 6666.7 Hz. Four scans were recorded for each FID.
Hyberts S.G., Milbradt A.G., Wagner A.B., Arthanari H, & Wagner G. (2012). Application of Iterative Soft Thresholding for Fast Reconstruction of NMR Data Non-uniformly Sampled with Multidimensional Poisson Gap Scheduling. Journal of Biomolecular Nmr, 52(4), 315-327.
Publication 2012
Biological Evolution HMQC Nitrogen Proteins Protons Pulse Rate Radionuclide Imaging Reconstructive Surgical Procedures VP-16
2
Optimized Adiabatic HSQC NMR Characterization
Cited 19 times
NMR spectra from the gel-samples were acquired on a 750 MHz (DMX-750) Bruker Biospin (Rheinstetten, Germany) instrument equipped with an inverse (proton coils closest to the sample) gradient 5 mm TXI 1H/13C/15N cryoprobe. The central DMSO solvent peak was used as internal reference (δC 39.5, δH 2.49 ppm). The 13C–1H correlation experiment was an adiabatic HSQC experiment (Bruker standard pulse sequence ‘hsqcetgpsisp.2’; phase-sensitive gradient-edited-2D HSQC using adiabatic pulses for inversion and refocusing)109 (link) typically had the following parameters for the plant cell wall samples: spectra were acquired from 11 to −1 ppm in F2 (1H) using 1078 data points for an acquisition time (AQ) of 60 ms, an interscan delay (D1) of 750 ms, 196 to −23 ppm in F1 (13C) using 480 increments (F1 acquisition time 5.78 ms) of 16 scans, with a total acquisition time of 6 h. The same version of the adiabatic HSQC experiment (hsqcetgpsisp.2)was used on a Bruker 500 MHz (DMX-500) NMR with a cryogenically cooled 5 mm gradient cryoprobe with inverse geometry, and the parameter set was more effectively optimized for gel-samples: spectra were acquired from 10 to 0 ppm in F2 (1H) using 1000 data points for an acquisition time (AQ) of 100 ms, an interscan delay (D1) of 500 ms, 200 to 0 ppm in F1 (13C) using 320 increments (F1 acquisition time 6.36 ms) of 100 scans, with a total acquisition time of 5 h 34 m. The number of scans can, of course, be adjusted as usual depending on the signal-to-noise required from a sample. We also used a Bruker Avance 360 MHz instrument equipped with an inverse (proton coils closest to the sample) gradient 5 mm 1H/broadband gradient probe for structural elucidation and assignment authentication for the model compounds. The standard Bruker implementations of the traditional suite of 1D and 2D (gradient-selected, 1H-detected, e.g., COSY, HMQC/HSQC, HSQC-TOCSY, HMBC) NMR experiments were used. Normal HMQC (inv4gptp) experiments at 360 MHz were used for model compounds and had the following parameters: spectra were acquired from 10 to 0 ppm in F2 (1H) using 1400 data points for an acquisition time of ≤200 ms, 200 to 0 ppm in F1 (13C) using 128 (or 256) increments (F1 acquisition time 35.3 ms) of 32 scans, with a total acquisition time of 1 h 23 min. Processing used typical matched Gaussian apodization in F2 and a squared cosine-bell in F1. Interactive integrations of contours in 2D HSQC/HMQC plots were carried out using Bruker’s TopSpin 2.5 software, as was all data processing.
Kim H, & Ralph J. (2009). Solution-state 2D NMR of ball-milled plant cell wall gels in DMSO-d6/pyridine-d5. Organic & biomolecular chemistry, 8(3), 576-591.
Publication 2009
HMQC Inversion, Chromosome MS 32 Plant Cells Protons Pulse Rate Pulses Radionuclide Imaging Solvents Sulfoxide, Dimethyl
3
NESTA-NMR for Efficient 3D/4D NMR Data Processing
Cited 16 times
Experimental data were collected on three different proteins: (1) a 1 mM sample of the 8 kDa CUE domain containing residues 453–504 from human gp78 (Liu et al. 2012 (link)); (2) a 330 μM sample of the 15 kDa PH domain of ASAP1, which contains residues 339–451 (Luo et al. 2008 (link)); and (3) a 400 μM sample of the 32 kDa two domain construct (ZA) of ASAP1 containing residues 441–724 (Luo et al. 2008 (link)). Isotope labeling was performed by expressing and purifying the proteins from E. coli using standard techniques to produce either uniform 13C, 15N-labeled protein, uniform 2H, 13C, 15N-labeled protein (DCN), or uniform 2H, 13C, 15N, 13C1H3-methyl (Ileδ1, Leu, Val) labeled protein (DCN-ILV) or 2H, 15N, 13C1H3-methyl (Ileδ1, Leu, Val) labeled protein (DCmethylN-ILV).
NESTA-NMR has been used to process a wide range of 3D and 4D NMR experiments that were collected on these three samples, and the salient information of all of these experiments is listed in Supplemental Table 1. Data discussed explicitly in the manuscript consist of the following four data sets:

A 4D methyl-methyl HMQC-NOESY-HMQC experiment (4D CC-NOESY) utilizing mixed constant-time evolution (Ying et al. 2007 (link)) was recorded on 1 mM DCNILV gp78 CUE using a Bruker Avance 900 MHz instrument running TopSpin 2 with cryoprobe at 298K. The standard pulse sequence was modified to store all of the hypercomplex pairs adjacent to each other with quadrature modulations preceding time modulation and the delays in the indirect dimensions calculated according to a NUS sampling schedule. In order to compare reconstructions with those of different programs, the sampling schedule was produced by an in-house Python script according to the algorithm described by Mobli et al. (Mobli et al. 2010 (link)) which was additionally modified to ensure every index for a given dimension contained at least one sampling point. Sampling consisted of 7200 NUS points taken on a 48 13 C × 32 1H × 48 13C grid with a sampling density of 9.8%. In this report, the number of points of an indirect dimension is described in complex points—i.e. real and imaginary data are counted as one point. The maximum evolution times in the indirect dimensions were 11.5 ms for both 13C dimensions and 34.1 ms for the indirect 1H dimension. Spectral widths were 4098 Hz for both 13C dimensions and 909 Hz for the indirect 1H dimension. Each FID was recorded with 4 scans, and the NOE mixing period was 150 ms.

A variable (non-constant) time 4D methyl-methyl HMQC-NOESY-HMQC (Diercks et al. 1999 (link)) experiment was acquired on a 400 μM sample of DCmethylN-ILV ZA on a Bruker Avance III 600 MHz instrument with cryoprobe at 298K using TopSpin 3.2. The sampling schedule was designed with ScheduleTool, which is distributed with RNMRTK (Hoch and Stern 1996 ), and consisted of 12,000 NUS points taken on a 48 13 C × 64 1 H × 48 13C grid with a sampling density of 8.1%. The maximum evolution times in the indirect dimensions were 12.2 ms for both 13C dimensions and 19.0 ms for the indirect 1H dimension. Spectral widths were 3922 Hz for both 13C dimensions and 3360 Hz for the indirect 1H dimension. Each FID was recorded with 4 scans and the NOE mixing period was 200 ms.

Two 3D 15N-edited NOESY-HSQC experiments were acquired on a 330 μM 15N-labeled PH domain on a Bruker Avance III 600 MHz instrument with cryoprobe at 298 K using the Topspin 3.2 library pulse sequence nosesyhsqcf3gp193d (Sklenar et al. 1993 ). One data set was collected with uniform sampling (36 13 C × 180 1H) and serves as the reference. The other was collected with 1620 NUS points (25% sampling density) on a 36 × 180 grid. The sampling schedule was designed with ScheduleTool. For both experiments, the maximum evolution times in the indirect dimensions were 18.5 ms for 15N and 25 ms for 1H. Spectral widths were 1945 Hz for 15N and 7194 Hz for 1H. The NOE mixing period was 60 ms. Each FID contained 8 and 32 scans for the uniformly sampled and non-uniformly sampled data, respectively.

Data reconstruction was performed using in-house C programs for both the NESTA algorithm and alternative algorithms used for comparison. This was done to enable direct comparison of convergence rates since package-specific implementations may affect computing efficiency. Thus, all the algorithms utilized the same libraries and were compiled on the same computer. Mixed-radix FFT and IFFT routines from the GNU Scientific Library (GSL) (Galassi et al. 2009 ) capable of processing complex vectors of any length (not restricted to powers of 2) were used to construct multidimensional subroutines to transform hypercomplex data. Direct comparison of algorithms rather than a specific software package is enabled because the algorithms utilize the same libraries and the analysis of computational efficiency is measured by the number of iterations required to reach convergence.
The processing package NESTA-NMR was developed to apply NESTA minimization to 2D, 3D, and 4D NMR data. Data described in this manuscript were processed on a desktop computer running Centos 6 with a 2.13 GHz Intel Xeon processor containing 4 hyperthreaded cores (8 threads) or a Mac Pro with a 3.5 GHz Intel Xeon processor containing 6 hyperthreaded cores (12 threads). The software can also be run on a cluster to access even more threads; however, this is not generally necessary given the relatively short computational times of NESTA-NMR, even for 4D data (vide infra). After reconstructing the unsampled data points and merging them with experimentally sampled data, the indirect dimensions were processed with NMRPipe (Delaglio et al. 1995 (link)) using standard FFT methods for transformation and visualized using Sparky (Goddard and Kneller).
Sun S., Gill M., Li Y., Huang M, & Byrd R.A. (2015). Efficient and generalized processing of multidimensional NUS NMR data: the NESTA algorithm and comparison of regularization terms. Journal of biomolecular NMR, 62(1), 105-117.
Publication 2015
AMFR protein, human ASAP1 protein, human Biological Evolution cDNA Library Cloning Vectors Escherichia coli Proteins HMQC Homo sapiens Mac-3 Plant Roots Pleckstrin Homology Domains Proteins Pulse Rate Python Radionuclide Imaging Reconstructive Surgical Procedures
4
NMR Spectroscopy for Protein-Lipid Interactions
Cited 10 times

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Publication 2009
Amides Diffusion Epistropheus Extinction, Psychological HMQC Inversion, Chromosome Isoleucine Lipids Proteins Protons Pulse Rate Pulses Radionuclide Imaging Sodium Azide Valine Vibration
5
NMR-based Structural Characterization of Protein-RNA Complexes
Cited 8 times
NMR spectra were acquired at 25°C on an 850 MHz Bruker Avance spectrometer, equipped with a triple-resonance (15N/13C/1H) cryoprobe. The sample volume was either 0.16 or 0.35 mL, in SEC buffer, 5% D2O/90-95% H2O. A series of double- and triple-resonance spectra [25 (link),26 (link)] were recorded to obtain sequence-specific resonance assignment. We used the I-PINE assignment tool [27 (link)] implemented in NMRFAM-SPARKY [28 (link)] for initial automatic assignment. 1H-1H distance restraints were derived from 3D 15N/1H NOESY-HSQC and 13C/1H NOESY-HMQC, which were acquired using a NOE mixing time of 100 ms.
Structural calculation was carried out in CYANA [29 (link)] using NOESY data in combination with backbone torsion angle restraints, generated from assigned chemical shifts using the program TALOS+ [30 (link)]. First, the combined automated NOE assignment and structure determination protocol (CANDID) was used for automatic NOE cross-peak assignment. Subsequently, five cycles of simulated annealing combined with redundant dihedral angle restraints were used to calculate a set of converged structures with no significant restraint violations (distance and van der Waals violations < 0.5Å and dihedral angle constraint violations < 5°). The 40 structures with the least restraint violations were further refined in explicit solvent using the YASARA software with the YASARA forcefield [18 (link)] and subjected to further analysis using the Protein Structure Validation Software suite (www.nesg.org). The statistics for the resulting structure are summarized in Table 1. The structures, NMR restraints and resonance assignments were deposited in the Protein Data Bank (PDB, accession code: 6YI3) and BMRB (accession code: 34511).
To follow changes in the chemical shifts of a protein upon RNA binding, we calculated chemical shift perturbations (CSPs). The CSP of each assigned resonance in the 2D 15N/1H HSQC spectra of the protein in the free state was calculated as the geometrical distance in ppm to the peak in the 2D 15N/1H HSQC spectra acquired under different conditions using the formula: Δδ=ΔδH2+(ΔδN∙α)2 , where α is a weighing factor of 0.2 used to account for differences in the proton and nitrogen spectral widths [31 (link)].
Dinesh D.C., Chalupska D., Silhan J., Koutna E., Nencka R., Veverka V, & Boura E. (2020). Structural basis of RNA recognition by the SARS-CoV-2 nucleocapsid phosphoprotein. PLoS Pathogens, 16(12), e1009100.
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Publication 2020
A-factor (Streptomyces) Buffers factor A HMQC Nitrogen Pinus Post-Translational Protein Processing Proteins Protons Solvents Vertebral Column Vibration

Most recents protocols related to «HMQC»

1
NMR Analyses of Kinase Mutants
Intensity retention experiments were performed on ILV-labeled kinases using a Bruker AVANCE NEO NMR spectrometer operating at a 1H frequency of 800 MHz equipped with a TCI cryogenic probe. 1H/13C HMQC spectra were collected at 25 °C on 50 μM and 250 μM samples of WT0Y, V564I0Y, and V564E0Y in 25 mM HEPES pH 7.5, 150 mM NaCl, and 40 mM MgCl2 in the presence and absence of 20 mM ATP. Intensity retention values were calculated as the peak intensity in the ATP/Mg2+-bound state divided by the intensity in the absence of ATP. 1H/13C HMQC spectra for 50 μM samples in the absence of ATP were collected with eight scans, while spectra in the presence of 20 mM ATP were collected with 12 scans to account for the dilution upon nucleotide addition (50 μL nucleotide into 200 μL kinase sample). 1H/13C HMQC spectra for 250 μM samples in the presence and absence of ATP were each collected with four scans. To compensate for the dilution factor and/or scan difference in HMQC spectra, peak heights of kinase samples at 250 μM in the presence of ATP were multiplied by 1.25, while peak heights of kinase samples at 50 μM in the absence of ATP were multiplied by 1.2. The peak height multiplications were done in an identical manner for WT0Y, V564I0Y, and V564E0Y.
Besch A., Marsiglia W.M., Mohammadi M., Zhang Y, & Traaseth N.J. (2023). Gatekeeper mutations activate FGF receptor tyrosine kinases by destabilizing the autoinhibited state. Proceedings of the National Academy of Sciences of the United States of America, 120(8), e2213090120.
Publication 2023
HEPES HMQC Magnesium Chloride nucleotide phosphotransferase Nucleotides Phosphotransferases Radionuclide Imaging Retention (Psychology) Sodium Chloride Technique, Dilution
2
NMR Spectroscopy-Based ATP Binding Kinetics
ATP titrations were performed at 25 °C on WT0Y, V564I0Y, and V564E0Y using a Bruker AVANCE NEO NMR spectrometer operating at a 1H frequency of 800 MHz equipped with a TCI cryogenic probe. 1H/13C HMQC experiments were acquired on ILV-labeled kinases with 4 scans and 60 complex points in the indirect dimension to minimize the experiment time due to ATP hydrolysis. The entire titration was acquired in ~3 h. Titrations were carried out with 50 μM kinase in 25 mM HEPES pH 7.5, 150 mM NaCl, and 40 mM MgCl2. ATP was titrated at several concentrations ranging from low μM to mM, as displayed in the figure legends. The AMP-PCP titration was performed at 10 °C on FGFR2K using a Bruker AVANCE III NMR spectrometer operating at a 1H frequency of 600 MHz equipped with a TCI cryogenic probe. 1H/13C HMQC experiments were performed on 533 μM ILV-labeled kinases with two scans and 100 complex points in the indirect dimension. Binding constants were fit using a nonlinear least-squares regression as shown in Eq. 3. Δδobs = Δδmax[P]t+[L]t+Kd − ([P]t+[L]t+Kd)2 − 4PtLt2Pt
Besch A., Marsiglia W.M., Mohammadi M., Zhang Y, & Traaseth N.J. (2023). Gatekeeper mutations activate FGF receptor tyrosine kinases by destabilizing the autoinhibited state. Proceedings of the National Academy of Sciences of the United States of America, 120(8), e2213090120.
Publication 2023
5'-adenylyl (beta,gamma-methylene)diphosphonate HEPES HMQC Hydrolysis Magnesium Chloride Phosphotransferases Radionuclide Imaging Sodium Chloride Titrimetry
3
NMR Characterization of Mog-V and CUR/Mog-V Interactions
All NMR experiments were performed at 37 °C on a Bruker AVIII-500 NMR spectrometer (Bruker Corporation, Germany). The samples were prepared in D2O. As an external reference, 0.05% 3-(trimethylsilyl) propionic-2,2,3,3-d4 acid sodium salt (TSP) was used to calibrate the NMR chemical shifts. The spectra were analyzed with reference to the internal signal of TSP-d 4 protons at 0 ppm. Resonance assignments for Mog-V were made according to 2D 1H-1H COSY, 1H-13C HMBC, and 1H-13C HMQC NMR spectra and the reference data.24 (link) The chemical shifts of protons in Mog-V were recorded as a function of the concentrations (1, 2, 3, 4, 5, 8, 10, 15, 20, 30 and 50 mg/mL).
The 2D 1H-1H NOESY spectra for 1.0 and 50 mg/mL Mog-V solutions were measured to check the molecular conformation of Mog-V in the aqueous solution. Under similar conditions, 1H NMR spectra and 2D 1H-1H NOESY spectra of CUR/Mog-V SDP solutions (concentration equivalent to 50 mg/mL of Mog-V) were also recorded to validate the interaction positions between CUR and Mog-V molecules. The peaks of CUR were assigned based on prior reports.25 (link)
Zhang J., Zhang Y., Wang H., Chen W., Lu A., Li H., Kang L, & Wu C. (2023). Solubilisation and Enhanced Oral Absorption of Curcumin Using a Natural Non-Nutritive Sweetener Mogroside V. International Journal of Nanomedicine, 18, 1031-1045.
Publication 2023
1H NMR Acids HMQC Protons Sodium Sodium Chloride Vibration
4
Synthesis and Thermal Studies of Fused Azaisocytosine Congeners
Cited 2 times
Ethyl 2-[4-oxo-8-(R-phenyl)-4,6,7,8-tetrahydroimidazo[2,1-c][1,2,4]triazin-3-yl]acetates (1–6) belonging to fused azaisocytosine congeners have been synthesised for the purposes of thermal studies according to efficient synthetic approaches previously patented and published [2 ,3 (link)]. The structures of molecules 1–6 have been confirmed by 1H-NMR/13C-NMR spectra and elemental analysis, and established on the basis of the performed 13C, 1H HMBC and HMQC correlations for the ethyl ester of 2-(4-oxo-8-phenyl-4,6,7,8-tetrahydroimidazo[2,1-c][1,2,4]triazin-3-yl)acetic acid (1) [3 (link)]. The purity and homogeneity of all the compounds intended for thermal studies (1–6) have been previously evaluated under reaction and the purification conditions employed. All these ones have been obtained and described [3 (link)] as homogenous, pure, crystalline solids with sharp melting points and microanalyses within ±0.4 percent of the calculated values. They have been reported to reveal not only enhanced anticancer effects in malignant human multiple myeloma cells (MM1R, MM1S) but also antiproliferative activities against human tumours of the breast (T47D) and cervix (HeLa) [3 (link)]. In addition, their mode of anticancer action and very low toxicities towards normal human skin fibroblasts have been previously documented [3 (link)].
Ostasz A., Łyszczek R., Sztanke K, & Sztanke M. (2023). TG-DSC and TG-FTIR Studies of Annelated Triazinylacetic Acid Ethyl Esters—Potential Anticancer Agents. Molecules, 28(4), 1735.
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Publication 2023
1H NMR Acetates Acetic Acid Breast Neoplasm Carbon-13 Magnetic Resonance Spectroscopy Cells Cervix Uteri Esters Fibroblasts HeLa Cells HMQC Homo sapiens Homozygote Molecular Structure Plasma Cell Neoplasm Skin Triazines
5
NMR and Mass Spectrometry Analysis
On the AVANCE 500 MHz instrument (Bruker, Billerica, MA, USA), 1H and 13C/DEPT-NMR, two-dimensional homonuclear (i.e., COSY), and heteronuclear (i.e., HMQC and HMBC) analyses were carried out. Mass spectrometry was performed on a Waters ACQUITY H-Class UPLC system tandem a Waters Xevo TQ-S triple quadrupole time-of-flight mass spectrometer (Waters Corp., Milford, MA, USA).
Xu Q., Yang X., Zhang R., Li Y., Yan Z., Li X., Ma B., Liu Y., Lin A., Han S., Li K, & Chen L. (2023). Embryotoxicity and Teratogenicity of Steroidal Saponin Isolated from Ophiopholis mirabilis. Toxics, 11(2), 137.
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Publication 2023
Carbon-13 Magnetic Resonance Spectroscopy HMQC Mass Spectrometry

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More about "HMQC"

Heteronuclear Multiple Quantum Coherence (HMQC) is a powerful Nuclear Magnetic Resonance (NMR) spectroscopy technique used to investigate the chemical structure and dynamics of complex molecular systems.
This advanced method provides information about the coupling between proton (1H) and heteroatom (e.g., carbon, nitrogen) spins, enabling researchers to analyze intricate molecular structures with enhanced precision.
HMQC is widely employed in various fields, including organic chemistry, biochemistry, and materials science.
It complements other NMR techniques, such as HSQC (Heteronuclear Single Quantum Coherence) and HMBC (Heteronuclear Multiple Bond Correlation), to provide a comprehensive understanding of molecular properties.
The Bruker Avance III, Avance 500, and Avance III 600 MHz NMR spectrometers are commonly used platforms for HMQC experiments.
These advanced instruments, coupled with the powerful Topspin 3.2 and Topspin 4.0.6 software, enable researchers to acquire and analyze HMQC data with high accuracy and reproducibility.
To further streamline the HMQC workflow, PubCompare.ai's AI-powered platform can optimize your protocols, boost reproducibility, and enhance accuracy.
The platform helps you easily locate the best HMQC protocols from literature, pre-prints, and patents, and leverages AI-driven comparisons to identify the most effective products.
This takes the guesswork out of your HMQC experiments, ensuring you achieve reliable and informative results.
Whether you're working with small organic molecules, complex natural products, or macromolecular structures, HMQC is a versatile technique that can provide invaluable insights.
Coupled with the latest NMR instrumentation and the innovative tools offered by PubCompare.ai, you can unlock the full potential of this powerful analytical method and advance your research endeavors.