Synthesizing Amino Acids Modified with Reactive Carbonyls in Silico to Assess Structural Effects Using Molecular Dynamics Simulations
Summary
Here, we describe a protocol for the optimization and parameterization of amino acid residues modified with reactive carbonyl species, adaptable to protein systems. The protocol steps include structure design and optimization, charge assignments, parameter construction, and preparation of protein systems.
Abstract
Protein carbonylation by reactive aldehydes derived from lipid peroxidation leads to cross-linking, oligomerization, and aggregation of proteins, causing intracellular damage, impaired cell functions, and, ultimately, cell death. It has been described in aging and several age-related chronic conditions. However, the basis of structural changes related to the loss of function in protein targets is still not well understood. Hence, a route to the in silico construction of new parameters for amino acids carbonylated with reactive carbonyl species derived from fatty acid oxidation is described. The Michael adducts for Cys, His, and Lys with 4-hydroxy-2-nonenal (HNE), 4-hydroxy-2-hexenal (HHE), and a furan ring form for 4-Oxo-2-nonenal (ONE), were built, while malondialdehyde (MDA) was directly attached to each residue. The protocol describes details for the construction, geometry optimization, assignment of charges, missing bonds, angles, dihedral angles parameters, and its validation for each modified residue structure. As a result, structural effects induced by the carbonylation with these lipid derivatives have been measured by molecular dynamics simulations on different protein systems such as the thioredoxin enzyme, bovine serum albumin and the membrane Zu-5-ankyrin domain employing root-mean-square deviation (RMSD), root mean square fluctuation (RMSF), structural secondary prediction (DSSP) and the solvent-accessible surface area analysis (SASA), among others.
Introduction
In the constant pursuit of understanding the molecular behavior of proteins with oxidative modifications, computational chemistry has become a fundamental pillar in the broad field of scientific research. This relies on the use of theoretical models capable of interpreting physical phenomena in electronic systems, using mathematical equations to describe the atomic behavior of molecules. Within this landscape, computational simulations of proteins stand out as crucial tools to analyze the atomic behavior of molecular systems. Based on the evaluation of structural behavior, energetic calculations, and conformational states1, these methods become strategic allies to predict the behavior of biomolecular systems.
These simulations specialize in studying structural changes and assessing the loss or gain of biological functions in protein systems. However, computational approaches have shown significant limitations when applied to protein systems containing modified residues formed by covalent post-translational modifications in the sequence. This is because many available methods lack resources with parameters adaptable to force fields that are compatible with the most common packages of programs for molecular dynamics simulations of proteins2,3,4,5,6. Therefore, the standardization of computational software-compatible force-field adaptive parameters is essential to facilitate the precise coupling of topologies and atomic coordinates with the equation governing the potential energy of the system7.
In response to these challenges, a protocol adaptable to new modified amino acid residues with aldehydes derived from lipid peroxidation has been developed using ab initio methods. In that sense, the optimization of the structural geometry of the new residues allows the assignment of adaptive charges to new bond, angle, and dihedral parameters that can be run in general force fields such as AMBER. Subsequent validation of these parameters allows the determination of the consistency and robustness of the method applicable to molecular dynamics simulations.
One of the notable strengths of this method lies in its ability to adapt to diverse post-translational modifications, from carbonylation to phosphorylation, acetylation, and methylation, among others. This versatility is not only limited to protein systems but extends to macromolecular structures, allowing coupling with atomic topologies and coordinates. In contrast, previous studies reveal that the standard parameterization of post-translational modifications is only suited to a specific type of modification and can only be obtained from published repositories, lacking the ability to create new structures8.
Currently, challenges in protein structure prediction and design are becoming more evident when modeling structures with post-translational modifications. The scarcity of parameters describing alterations at specific amino acid sites underlines the urgent need to develop and apply computational methods that can be adjusted to standard parameterizations. The aim of this protocol is to provide a route for the in silico construction of new parameters for amino acids covalently modified with reactive carbonyl species derived from fatty acid oxidation. These modified amino acids are recognized by the general amber force field (GAFF) and can, therefore, be used to evaluate in silico the structural and functional effects that this kind of carbonylation has on their target proteins.
Protocol
Representative Results
Discussion
One of the critical steps in developing the AMBER parameterization protocol was the quantum optimization of the new amino acid residues modified with the lipid peroxidation derivatives, due to the energetic variability related to the minimization and the way of assigning RESP charges in the AMBER antechamber. For this, ab initio optimization methods with Hartree-Fock (HF/6-31G) and semiempirical density functional theory (DFT; B3LYP/6-31G and M062X/6-31G) were established to evaluate the response to the load ass…
Disclosures
The authors have nothing to disclose.
Acknowledgements
This work was supported by research grant code 1107-844-67943 from Ministerio de Ciencia, Tecnología e Innovación (Minciencias) and the University of Cartagena (Colombia) for grant to support the research groups 2021 and Acta 017-2022.
Materials
| AmberTools16 or Upper | The Amber Project | Amber is a suite of biomolecular simulation programs | |
| Gaussian 09 or Upper | Gaussian Inc | Draw and optimize structures | |
| Linux Ubuntu | GNU/Linux | Platform for AmberTools | |
| NVIDIA GPUs GTX 1080 or Upper | Nvidia | Compatible with PMEMD |
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