Molecular Docking of Cryptoconcatones to α-Tubulin and Related Pironetin Analogues
Abstract
:1. Introduction
2. Results
3. Discussion
4. Materials and Methods
4.1. Molecular Structures and Software
4.2. In Silico Molecular Docking Procedure
- (1)
- Monte Carlo (MC) conformational search of the ligand using the BOSS (Biochemical and Organic Simulation System) software, freely available to academic users. The structure of the ligand was optimized using a classical MC conformational search procedure, as described in BOSS [52]. A conformational analysis was performed to define the best starting geometries for each compound. An energy minimization was carried out to identify all minimum-energy conformers, leading to the identification of a unique conformer for the free ligand. Within BOSS, MC simulations were performed in the constant-temperature and constant-pressure ensemble (NPT).
- (2)
- Evaluation of the free energy of hydration for the chosen structure of the ligand. The molecular mechanics/generalized Born surface area (MM/GBSA) procedure was used to evaluate the free energies of hydration (ΔG) (Jorgensen and Tirado-Rives, 2005) [53]. MC search and computation of ΔG were performed within BOSS using the xMCGB script according to procedures given in references [53,54]. The best ligand structure was then used in the docking procedure.
- (3)
- Definition of the α-tubulin-ligand site of interaction. The pironetin binding site was defined as the binding site for all α-pyrone derivatives tested. With the 5FNV structure, based on shape complementarity criteria, the flexible amino acids are Phe135, Phe202, Leu248, Leu252, Phe255, Gln256, Leu259, Cys316, Lys352, and Leu378. Shape complementarity and geometry considerations favor a docking grid centered in the volume defined by the central amino acid. Within the binding site, the side chains of the specific amino acids were considered fully flexible during docking.
- (4)
- Docking procedure using GOLD. In our typical docking process, 100 energetically reasonable poses (according to the ChemPLP scoring function) are retained while searching for the correct binding mode of the ligand. The decision to maintain a trial pose is based on ranked poses, using the PLP fitness scoring function (which is the default in GOLD version 5.3 used here) [55]. Six poses are kept. The empirical potential energy of the interaction ΔE for the ranked complexes was evaluated using the simple expression ΔE(interaction) = E(complex) − [E(protein) + E(ligand)]. Calculations of the final energy are performed on the basis of the SPASIBA spectroscopic force field. The corresponding parameters are derived from vibrational wavenumbers obtained in the infrared and Raman spectra of a large series of compounds including organic molecules, amino acids, saccharides, nucleic acids and lipids.
- (5)
- Validation using the SPASIBA force field. This last step is considered essential to define the best protein–ligand structure. The spectroscopic SPASIBA (Spectroscopic Potential Algorithm for Simulating Biomolecular conformational Adaptability) force field has been specifically developed to provide refined empirical molecular mechanics force field parameters [56]. SPASIBA empirical energies of interaction are calculated as described [57,58]. SPASIBA (integrated into CHARMM) [59] has been shown to be excellent in reproducing crystal phase infrared data. The same procedure was used to establish molecular models for the various drug–protein complexes.
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Compounds | ΔE (kcal/mol) | ΔG (kcal/mol) |
---|---|---|
Pironetin | −57.32 | −24.20 |
Cryptocontanone A | −67.80 | −25.00 |
Cryptocontanone B | −63.10 | −24.25 |
Cryptocontanone C | −70.30 | −26.25 |
Cryptocontanone D | −60.70 | −27.50 |
Cryptocontanone E | −65.40 | −22.00 |
Cryptocontanone F | −74.15 | −27.60 |
Cryptocontanone G | −66.00 | −24.40 |
Cryptocontanone H | −57.70 | −23.30 |
Cryptocontanone I | −66.65 | −29.10 |
Cryptocontanone J | −66.75 | −30.75 |
Cryptocontanone K | −52.30 | −22.85 |
Cryptocontanone L | −73.40 | −26.50 |
Cryptofolione | −56.20 | −21.75 |
Cryptoyunone B | −60.20 | −19.80 |
Obolactone | −52.50 | −18.50 |
Rugulactone | −59.50 | −16.80 |
Spicigerolide | −67.70 | −21.00 |
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Vergoten, G.; Bailly, C. Molecular Docking of Cryptoconcatones to α-Tubulin and Related Pironetin Analogues. Plants 2023, 12, 296. https://doi.org/10.3390/plants12020296
Vergoten G, Bailly C. Molecular Docking of Cryptoconcatones to α-Tubulin and Related Pironetin Analogues. Plants. 2023; 12(2):296. https://doi.org/10.3390/plants12020296
Chicago/Turabian StyleVergoten, Gérard, and Christian Bailly. 2023. "Molecular Docking of Cryptoconcatones to α-Tubulin and Related Pironetin Analogues" Plants 12, no. 2: 296. https://doi.org/10.3390/plants12020296
APA StyleVergoten, G., & Bailly, C. (2023). Molecular Docking of Cryptoconcatones to α-Tubulin and Related Pironetin Analogues. Plants, 12(2), 296. https://doi.org/10.3390/plants12020296