Modeling of peptides containing D-amino acids: implications on cyclization
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Cyclic peptides are therapeutically attractive due to their high bioavailability, potential selectivity, and scaffold novelty. Furthermore, the presence of D-residues induces conformational preferences not followed by peptides consisting of naturally abundant L-residues. Therefore, comprehending how amino acids induce turns in peptides, subsequently facilitating cyclization, is significant in peptide design. Here, we performed 20-ns explicit-solvent molecular dynamics simulations for three diastereomeric peptides with stereochemistries: LLLLL, LLLDL, and LDLDL. Experimentally LLLLL and LDLDL readily cyclize, whereas LLLDL cyclizes in low yield. Simulations at 310 K produced conformations with inter-terminal hydrogen bonds that correlated qualitatively with the experimental cyclization trend. Energies obtained for representative structures from quantum chemical (B3LYP/PCM/cc-pVTZ//HF/6-31G*) calculations predicted pseudo-cyclic and extended conformations as the most stable for LLLLL and LLLDL, respectively, in agreement with the experimental data. In contrast, the most stable conformer predicted for peptide LDLDL was not a pseudo-cyclic structure. Moreover, D-residues preferred the experimentally less populated αL rotamers even when simulations were performed at a higher temperature and with strategically selected starting conformations. Energies calculated with molecular mechanics were consistent only with peptide LLLLL. Thus, the conformational preferences obtained for the all L-amino acid peptide were in agreement with the experimental observations. Moreover, refinement of the force field is expected to provide far-reaching conformational sampling of peptides containing D-residues to further develop force field-based conformational-searching methods.
KeywordsPeptide conformation Force field Quantum mechanics Molecular dynamics simulations
This work was supported by the State of Florida, Executive Officer of the Governor’s Office of Tourism, Trade and Economic Development, and by the National Science Foundation (CHE0455072 to R. A. H.). Authors thank the University Of Georgia Research Computing Center for supercomputing time, and the Theoretical and Computational Biophysics Group UIUC for providing VMD and NAMD programs. We are thankful to the referees for helpful criticisms of this manuscript.
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