1. Quantum Chemical Studies of Energetics of RNA-Drug Interactions
Anubhooti, Purshotam Sharma, Gopalakrishnan Bulusu and Abhijit Mitra
Center for Computational Natural Sciences and Bioinformatics (CCNSB),
International Institute of Information Technology, Hyderabad
Introduction
Results & Discussion
Base Pair
∆E (RIMP2)
ΔEcor
MOROKUMA decomposition of interaction energy
EDFT-D
Eelec
Eex
Epol
Ect
Ehoc
∆E (BSSE)
Cytosine:Theophylline (cis WRNA:HDRUG)
(-11.04)
-3.99 (-2.76)
(-9.62)
26.56 (3.35)
-7.62 (-1.8)
-8.15 (-2.34)
0.3 (-0.07)
(-8.74)
(-11.43)
Uracil:Theophylline (cis WRNA:SDRUG)
(-6.98)
-4.32 (-3.32)
(-6.94)
14.86 (4.50)
-2.73 (-0.84)
-4.91 (-2.61)
0.32 (0.03)
-7.90 (-4.06)
(-7.51)
Guanine:Blasticidin (cis WRNA:WDRUG)
(-20.38)
-3.82 (-5.15)
(-32.71)
32.87 (28.77)
-9.16 (-7.64)
-9.47 (-8.00)
-1.15 (-0.11)
(-16.58)
(-22.67)
Guanine:Puromycin (trans SRNA:SDRUG)
(-17.17)
(-12.13)
(-34.45)
26.20 (39.26)
-4.80 (-5.97)
-9.37 (-11.33)
0.36 (1.95)
(-6.69)
(-21.71)
Uracil:Linezolid (WRNA:Drug)
-8.78 (7.90)
-3.48 (6.45)
(-7.13)
11.62 (26.5)
-1.88 (-2.94)
-4.04 (-5.4)
-0.19 (2.58)
-9.68 (15.91)
-9.68 (6.25)
Adenine:Clindamycin (WRNA:Drug)
(-9.24)
-6.27 (-8.02)
(-29.16)
21.92 (39.09)
-3.76 (-6.19)
-6.59 (-12.54)
0.11 (2.77)
-9.47 (-3.13)
(-12.60)
Adenine:Paromomycin (WRNA:Drug)
(-3.54)
-6.06 (-6.83)
(-12.62)
19.22 (19.16)
-3.23 (-1.98)
-5.75 (-4.85)
0.2 (0.79)
-7.99 (2.8)
(-5.39)
Table 1: Interaction Energies (Kcal/mol) of RNA-Drug Base Pairs and Pseudo pairs after Full optimization and Hydrogen optimization, as seen within parenthesis.
Fig 1. Ribosome targeted by different drugs at different stages of translation.
Interaction energy range in fully optimized geometry: Kcal/mol to Kcal/mol. It correlates with RNA base pairs.
Highest ΔEcor (53.84%) contribution to interaction energy by Guanine-Puromycin model pair.
Attractive component of total interaction energy is significantly larger than other components; Range: Kcal/mol to Kcal/mol.
Due to its wide functional importance and structural flexibility, RNA is a potential drug target (e.g. Ribosomes, Aptamers).
Drugs interact with nucleotides of binding pocket in the target RNA, forming base pairs and pseudo pairs based on the presence or absence of nucleobase moiety, respectively, in the drugs.
In addition to the structural aspects of the RNA-Drug interactions, molecular level understanding of their role in RNA functions require the analysis of their stabilities and interaction energies.
Objective
To investigate the intrinsic stability of base pairs and pseudo pairs observed in crystal structure of RNA-Drug complexes, by studying the geometries & interaction energies associated with them.
Conclusions
Base pairs tend to achieve planarity and are more stabilized in their minimum energy isolated gas-phase geometries – indicates influence of other stabilising forces which results in the formation of intrinsic geometries observed in the complex.
Strength of the interaction between the drug and its target RNA depend on the number of interacting donor-acceptor pairs in the molecules.
The interaction between the RNA-Drug pairs is further stabilized due to dispersion as shown from the DFT-D results.
Base pairs including sugar-edge interaction are dominated by dispersion forces.
Fig 2. Theophylline bound to Theophylline aptamer.
Theophylline with its Aptamer
Model Generation:
Initial coordinates of pairs extracted from available RNA-Drug complexes’ PDB data (Hydrogen atoms added using default mode Gaussian 03).
Geometry Optimization:
Full and “Hydrogen-only” optimization in gas phase performed at B3LYP/6-31G(d,p) level using Gaussian 03.
Interaction Energy:
Calculated at RIMP2/aug-cc-pVDZ – using TURBOMOLE v6.2
Morokuma – Contribution of interaction energy components at HF/6-31G(d,p)
Dispersion Effects:
DFT calculations with dispersion correction (DFT-D) performed.
Fig 3 (A,B,C) on the left:
Superimposition of Hydrogen optimized (in CPK) and Fully Optimized Geometries (in orange) of xanthine triplets.
Computational Methods
Fig 4 below:
Graphical representation of the percentage contribution of the pairwise interaction energy of individual bases interacting with the drug.
Kcal/mol;
RMSD: 0.84Å
(B) Kcal/mol;
RMSD: 1.45Å
(C) Kcal/mol;
RMSD: 1.46Å
Interaction energy results correlate to binding affinity of Theophylline aptamer
Theophylline >> Theobromine > Caffeine
C22 is a discriminating factor
Percentage pairwise contribution of C22 is more than U24 in theophylline bound state.
C22 has moved farther from Theobromine or caffeine than in the case when theophylline was bound. 
Negligible cooperative effect between bases of the binding pocket and the drug (Theophylline=0.82Kcal/mol, Theobromine=0.22 Kcal/mol and Caffeine=0.26 Kcal/mol).
Models Considered
Base Pairs
Pseudo Pairs
Cytosine-Theophylline
Cytosine-Linezolid
Uracil-Theophylline
Adenine-Clindamycin
References
[1] J. Kondo and E. Westhof, J. Mol. Recogn. 2, 23 (2009).
[2] Q. Vicens and E. Westhof, ChemBioChem 2003, 4, 1018 ± 1023.
[3] P. Sharma, A. Mitra, S. Sharma, H. Singh, D. Bhattacharyya, J. Biomol. Struct. Dyn, 25,709 (2008)
[4] P. Sharma, S. Sharma, A. Mitra and H. Singh, J. Chem. Sci. 119, 525 (2007)
[5] G. R. Zimmermann, R.D. Jenison, C. L. Wick, J. P. Simore, A. Pardi, Nat.Struct.Biol., 1997,4: (1997)
[6] I. M. Johnson, S. G. B. Kumar, R. Malathi, 2003, J. Biomol. Struct. Dyn,20,
Guanine-Blasticidin
Guanine-Puromycin
Adenine-Paromomycin