The dielectric spectra of complex biomolecules reflect the molecular heterogeneity of the proteins and are particularly important for the calculations of electrostatic (Coulomb) and electrodynamic (van der Waals) interactions in protein physics. The dielectric response of the proteins can be decomposed into different components depending on the size, structure, composition, locality, and environment of the protein in general. We present a new robust simulation method anchored in rigorous ab initio quantum mechanical calculations of explicit atomistic models, without any indeterminate parameters to compute and gain insight into the dielectric spectra of small proteins under different conditions. We implement this methodology to a polypeptide RGD-4C (1FUV) in different environments, and the SD1 domain in the spike protein of SARS-COV-2. Two peaks at 5.2–5.7 eV and 14.4–15.2 eV in the dielectric absorption spectra are observed for 1FUV and SD1 in vacuum as well as in their solvated and salted models.
more »
« less
Solvent Effect on the Structure and Properties of RGD Peptide (1FUV) at Body Temperature (310 K) Using Ab Initio Molecular Dynamics
The structure and properties of the arginine-glycine-aspartate (RGD) sequence of the 1FUV peptide at 0 K and body temperature (310 K) are systematically investigated in a dry and aqueous environment using more accurate ab initio molecular dynamics and density functional theory calculations. The fundamental properties, such as electronic structure, interatomic bonding, partial charge distribution, and dielectric response function at 0 and 310 K are analyzed, comparing them in dry and solvated models. These accurate microscopic parameters determined from highly reliable quantum mechanical calculations are useful to define the range and strength of complex molecular interactions occurring between the RGD peptide and the integrin receptor. The in-depth bonding picture analyzed using a novel quantum mechanical metric, the total bond order (TBO), quantifies the role played by hydrogen bonds in the internal cohesion of the simulated structures. The TBO at 310 K decreases in the dry model but increases in the solvated model. These differences are small but extremely important in the context of conditions prevalent in the human body and relevant for health issues. Our results provide a new level of understanding of the structure and properties of the 1FUV peptide and help in advancing the study of RGD containing other peptides.
more »
« less
- Award ID(s):
- 2028803
- PAR ID:
- 10321674
- Date Published:
- Journal Name:
- Polymers
- Volume:
- 13
- Issue:
- 19
- ISSN:
- 2073-4360
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Non-covalent complexes of the short amyloid peptide motif Gly-Asn-Asn-Gln-Gln-Asn-Tyr (GNNQQNY) with peptide counterparts that were tagged with a diazirine ring at the N-termini (*GNNQQNY) were generated as singly charged ions in the gas phase. Specific laser photodissociation (UVPD) of the diazirine tag in the gas-phase complexes at 355 nm generated transient carbene intermediates that underwent covalent cross-linking with the target GNNQQNY peptide. The crosslinking yields ranged between 0.8 and 4.5%, depending on the combinations of peptide C-terminal amides and carboxylates. The covalent complexes were analyzed by collision-induced dissociation tandem mass spectrometry (CID-MS 3 ), providing distributions of cross-links at the target peptide amino acid residues. A general preference for cross-linking at the target peptide Gln-4-Gln-5-Asn-6-Tyr-7 segment was observed. Born–Oppenheimer molecular dynamics calculations were used to obtain 100 ps trajectories for nine lowest free-energy conformers identified by ωB97X-D/6-31+G(d,p) gradient geometry optimizations. The trajectories were analyzed for close contacts between the incipient carbene atom and the X–H bonds in the target peptide. The close-contact analysis pointed to the Gln-5 and Tyr-7 residues as the most likely sites of cross-linking, consistent with the experimental CID-MS 3 results. Non-covalent binding in the amide complexes was evaluated by DFT calculations of structures and energies. Although antiparallel arrangements of the GNNQQNY and *GNNQQNY peptides were favored in low-energy gas-phase and solvated complexes, the conformations and peptide–peptide interface surfaces were found to differ from the secondary structure of the dry interface in GNNQQNY motifs of amyloid aggregates.more » « less
-
Gas-evolving photochemical reactions use light and mild conditions to access strained organic compounds irreversibly. Cyclopropenones are a class of light-responsive molecules used in bioorthogonal photoclick reactions; their excited-state decarbonylation reaction mechanisms are misunderstood due to their ultrafast (<100 femtosecond) lifetimes. We have combined multiconfigurational quantum mechanical (QM) calculations and non-adiabatic molecular dynamics (NAMD) simulations to uncover the excited-state mechanism of cyclopropenone and a photoprotected cyclooctyne-(COT)-precursor in gaseous and explicit aqueous environments. We explore the role of H-bonding with fully quantum mechanical explicitly solvated NAMD simulations for the decarbonylation reaction. The cyclopropenones pass through asynchronous conical intersections and have dynamically concerted photodecarbonylation mechanisms. The COT-precursor has a higher quantum yield of 55% than cyclopropenone (28%) because these trajectories prefer to break a σCC bond to avoid the strained trans-cyclooctene geometries. Our solvated simulations show an increased quantum yield (58%) for the systems studied here.more » « less
-
Inspired by spider silk's hierarchical diversity, we leveraged peptide motifs with the capability to tune structural arrangement for controlling the mechanical properties of a conventional polymer framework. The addition of nanofiller with hydrogen bonding sites was used as another pathway towards hierarchical tuning via matrix–filler interactions. Specifically, peptide–polyurea hybrids (PPUs) were combined with cellulose nanocrystals (CNCs) to develop mechanically-tunable nanocomposites via tailored matrix–filler interactions (or peptide–cellulose interactions). In this material platform, we explored the effect of these matrix–filler interactions on the secondary structure, hierarchical ordering, and mechanical properties of the peptide hybrid nanocomposites. Interactions between the peptide matrix and CNCs occur in all of the PPU/CNC nanocomposites, preventing α-helical ordering, but promoting inter-molecular hydrogen bonded β-sheet formation. Depending on peptide and CNC content, the Young's modulus varies from 10 to 150 MPa. Unlike conventional cellulose-reinforced polymer nanocomposites, the mechanical properties of these composite materials are dictated by a balance of CNC reinforcement, peptidic ordering, and microphase-separated morphology. This research highlights that leveraging peptide–cellulose interactions is a strategy to create materials with targeted mechanical properties for a specific application using a limited selection of building blocks.more » « less
-
UV absorption is widely used for characterizing proteins structures. The mapping of UV spectra to atomic structure of proteins relies on expensive theoretical simulations, circumventing the heavy computational cost which involves repeated quantum-mechanical simulations of excited-state properties of many fluctuating protein geometries, which has been a long-time challenge. Here we show that a neural network machine-learning technique can predict electronic absorption spectra of N -methylacetamide (NMA), which is a widely used model system for the peptide bond. Using ground-state geometric parameters and charge information as descriptors, we employed a neural network to predict transition energies, ground-state, and transition dipole moments of many molecular-dynamics conformations at different temperatures, in agreement with time-dependent density-functional theory calculations. The neural network simulations are nearly 3,000× faster than comparable quantum calculations. Machine learning should provide a cost-effective tool for simulating optical properties of proteins.more » « less
An official website of the United States government

