Structure of DNA sequence d-TGATCA by two-dimensional nuclear magnetic resonance spectroscopy and restrained molecular dynamics

Barthwal, Ritu; Awasthi, Pamita; Mônica, Mônica; Kaur, Manpreet; Sharma, Uma; Srivastava, Nandana; Barthwal, S. K.; Govil, Girjesh

doi:10.1016/j.jsb.2004.05.005

Cited by 8 publications

(3 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The identification of the cross-peaks were done on the basis of proton assignments using DQF COSY and 2D NOESY spectra. [20] Two of the H4 signals (A3 and T4) are separated from the H5 overlapped regions and their connectivities through the four-bond couplings with G2pA3 and A3pT4 phosphates confirm the assignments. The 31 P signals shift on varying the temperature but no line broadening is observed (Supporting Information, S1).…”

Section: Resultssupporting

confidence: 53%

Studies on drug–DNA complexes, adriamycin–d‐(TGATCA)₂ and 4′‐epiadriamycin–d‐(CGATCG)₂, by phosphorus‐31 nuclear magnetic resonance spectroscopy

Agrawal¹,

Govil²,

Barthwal³

2009

Magnetic Reson in Chemistry

Self Cite

View full text Add to dashboard Cite

The complexes of adriamycin-d-(TGATCA)(2) and 4'-epiadriamycin-d-(CGATCG)(2) are studied by one- and two-dimensional (31)P nuclear magnetic resonance spectroscopy (NMR) at 500 MHz in the temperature range 275-328 K and as a function of drug to DNA ratio (0.0-2.0). The binding of drug to DNA is clearly evident in (31)P-(31)P exchange NOESY spectra that shows two sets of resonances in slow chemical exchange. The phosphate resonances at the intercalating steps, T1pG2/C1pG2 and C5pA6/C5pG6, shift downfield up to 1.7 ppm and that at the adjacent step shift downfield up to 0.7 ppm, whereas the central phosphate A3pT4 is relatively unaffected. The variations of chemical shift with drug to DNA ratio and temperature as well as linewidths are different in each of the two complexes. These observations reflect change in population of B(I)/B(II) conformation, stretching of backbone torsional angle zeta, and distortions in O-P-O bond angles that occur on binding of drug to DNA. To the best of our knowledge, there are no solution studies on 4'-epiadriamycin, a better tolerated drug, and binding of daunomycin or its analogue to d-(TGATCA)(2) hexamer sequence. The studies report the use of (31)P NMR as a tool to differentiate various complexes. The specific differences may well be the reasons that are responsible for different antitumor action of these drugs due to different binding ability and distortions in DNA.

show abstract

Section: Resultssupporting

confidence: 53%

Studies on drug–DNA complexes, adriamycin–d‐(TGATCA)₂ and 4′‐epiadriamycin–d‐(CGATCG)₂, by phosphorus‐31 nuclear magnetic resonance spectroscopy

Agrawal¹,

Govil²,

Barthwal³

2009

Magnetic Reson in Chemistry

Self Cite

View full text Add to dashboard Cite

show abstract

“…In our previous publication, we used the MIM microsolvation (formerly referred to as MIM explicit–implicit constraint ) method to calculate the NMR chemical shifts of 10 nucleic acids with PDB ID’s 1SY8, 1K2K, 1KR8, 2N5P, 6XAH, 2LIB, 1N2W, 2LFX, 7NBK, and 2LAR . The calculated chemical shifts for all 1 H and 13 C nuclei of these nucleic acids were compared to experimentally available shifts, and the results are depicted in Figure .…”

Section: Resultsmentioning

confidence: 99%

MIM-ML: A Novel Quantum Chemical Fragment-Based Random Forest Model for Accurate Prediction of NMR Chemical Shifts of Nucleic Acids

Chandy,

Raghavachari

2023

J. Chem. Theory Comput.

View full text Add to dashboard Cite

We developed a random forest machine learning (ML) model for the prediction of 1 H and 13 C NMR chemical shifts of nucleic acids. Our ML model is trained entirely on reproducing computed chemical shifts obtained previously on 10 nucleic acids using a Molecules-in-Molecules (MIM) fragment-based density functional theory (DFT) protocol including microsolvation effects. Our ML model includes structural descriptors as well as electronic descriptors from an inexpensive low-level semiempirical calculation (GFN2-xTB) and trained on a relatively small number of DFT chemical shifts (2080 1 H chemical shifts and 1780 13 C chemical shifts on the 10 nucleic acids). The ML model is then used to make chemical shift predictions on 8 new nucleic acids ranging in size from 600 to 900 atoms and compared directly to experimental data. Though no experimental data was used in the training, the performance of our model is excellent (mean absolute deviation of 0.34 ppm for 1 H chemical shifts and 2.52 ppm for 13 C chemical shifts for the test set), despite having some nonstandard structures. A simple analysis suggests that both structural and electronic descriptors are critical for achieving reliable predictions. This is the first attempt to combine ML from fragment-based DFT calculations to predict experimental chemical shifts accurately, making the MIM-ML model a valuable tool for NMR predictions of nucleic acids.

show abstract

“…First, we calibrate the performance of MIM for obtaining accurate energy ordering of multiple conformers of nucleic acids, and then, we calibrate one-layer and two-layer MIM-NMR methods on the lowest energy conformer for the prediction of NMR chemical shifts. To calibrate the MIM methods, we have obtained the structure and experimental chemical shifts of three DNA molecules 1SY8 (BMRB ID 6186), 1K2K (BMRB ID 5339), and 1KR8 (BMRB ID 5282) from the Protein Data Bank (PDB), as shown in Figure . 1SY8 and 1K2K DNA molecules are used for regulation of gene expressions and intercalation site for several anticancer drugs, whereas 1KR8 is an extraordinarily stable mini-hairpin d(GCGAAGC) heptamer.…”

Section: Determination Of Fragmentation Protocols For Mim-nmr Of Nucl...mentioning

confidence: 99%

Accurate and Cost-Effective NMR Chemical Shift Predictions for Nucleic Acids Using a Molecules-in-Molecules Fragmentation-Based Method

Chandy

Raghavachari

2023

J. Chem. Theory Comput.

View full text Add to dashboard Cite

We have developed, implemented, and assessed an efficient protocol for the prediction of NMR chemical shifts of large nucleic acids using our molecules-in-molecules (MIM) fragment-based quantum chemical approach. To assess the performance of our approach, MIM-NMR calculations are calibrated on a test set of three nucleic acids, where the structure is derived from solution-phase NMR studies. For DNA systems with multiple conformers, the one-layer MIM method with trimer fragments (MIM1trimer) is benchmarked to get the lowest energy structure, with an average error of only 0.80 kcal/mol with respect to unfragmented full molecule calculations. The MIMI-NMRdimer calibration with respect to unfragmented full molecule calculations shows a mean absolute deviation (MAD) of 0.06 and 0.11 ppm, respectively, for 1H and 13C nuclei, but the performance with respect to experimental NMR chemical shifts is comparable to the more expensive MIM1-NMR and MIM2-NMR methods with trimer subsystems. To compare with the experimental chemical shifts, a standard protocol is derived using DNA systems with Protein Data Bank (PDB) IDs 1SY8, 1K2K, and 1KR8. The effect of structural minimizations is employed using a hybrid mechanics/semiempirical approach and used for computations in solution with implicit and explicit–implicit solvation models in our MIM1-NMRdimer methodology. To demonstrate the applicability of our protocol, we tested it on seven nucleic acids, including structures with nonstandard residues, heteroatom substitutions (F and B atoms), and side chain mutations with a size ranging from ∼300 to 1100 atoms. The major improvement for predicted MIM1-NMRdimer calculations is obtained from structural minimizations and implicit solvation effects. A significant improvement with the explicit–implicit solvation model is observed only for two smaller nucleic acid systems (1KR8 and 7NBK), where the expensive first solvation shell is replaced by the microsolvation model, in which a single water molecule is added for each solvent-exposed amino and imino protons, along with the implicit solvation. Overall, our target accuracy of ∼0.2–0.3 ppm for 1H and ∼2–3 ppm for 13C has been achieved for large nucleic acids. The proposed MIM-NMR approach is accurate and cost-effective (linear scaling with system size), and it can aid in the structural assignments of a wide range of complex biomolecules.

show abstract

Structure of DNA sequence d-TGATCA by two-dimensional nuclear magnetic resonance spectroscopy and restrained molecular dynamics

Cited by 8 publications

References 59 publications

Studies on drug–DNA complexes, adriamycin–d‐(TGATCA)₂ and 4′‐epiadriamycin–d‐(CGATCG)₂, by phosphorus‐31 nuclear magnetic resonance spectroscopy

Studies on drug–DNA complexes, adriamycin–d‐(TGATCA)₂ and 4′‐epiadriamycin–d‐(CGATCG)₂, by phosphorus‐31 nuclear magnetic resonance spectroscopy

MIM-ML: A Novel Quantum Chemical Fragment-Based Random Forest Model for Accurate Prediction of NMR Chemical Shifts of Nucleic Acids

Accurate and Cost-Effective NMR Chemical Shift Predictions for Nucleic Acids Using a Molecules-in-Molecules Fragmentation-Based Method

Contact Info

Product

Resources

About

Structure of DNA sequence d-TGATCA by two-dimensional nuclear magnetic resonance spectroscopy and restrained molecular dynamics

Cited by 8 publications

References 59 publications

Studies on drug–DNA complexes, adriamycin–d‐(TGATCA)2 and 4′‐epiadriamycin–d‐(CGATCG)2, by phosphorus‐31 nuclear magnetic resonance spectroscopy

Studies on drug–DNA complexes, adriamycin–d‐(TGATCA)2 and 4′‐epiadriamycin–d‐(CGATCG)2, by phosphorus‐31 nuclear magnetic resonance spectroscopy

MIM-ML: A Novel Quantum Chemical Fragment-Based Random Forest Model for Accurate Prediction of NMR Chemical Shifts of Nucleic Acids

Accurate and Cost-Effective NMR Chemical Shift Predictions for Nucleic Acids Using a Molecules-in-Molecules Fragmentation-Based Method

Contact Info

Product

Resources

About

Studies on drug–DNA complexes, adriamycin–d‐(TGATCA)₂ and 4′‐epiadriamycin–d‐(CGATCG)₂, by phosphorus‐31 nuclear magnetic resonance spectroscopy

Studies on drug–DNA complexes, adriamycin–d‐(TGATCA)₂ and 4′‐epiadriamycin–d‐(CGATCG)₂, by phosphorus‐31 nuclear magnetic resonance spectroscopy