Abstract:In this study, a coarse-grained (CG) model for N,N-dimethylacetamide (DMA), which represents the polypeptoid backbone, is developed as a step towards establishing a CG model of the complex polypeptoid system. Polypeptoids or poly N-substituted glycines are a type of peptidomimetic polymers that are highly tunable, and hence an ideal model system to study self-assembly as a function of chemical groups in aqueous soft matter systems. The DMA CG model is parameterized to reproduce the structural properties of DMA… Show more
“…Du, Rick, and Kumar developed a CG model of polysarcosine (poly(N-methyl glycine), N,N-dimethylacetamide) as a prototypical model for the polypeptoid backbone. 26 The optimized potential for liquid simulations-united atom (OPLS-UA) model is adopted for the intramolecular peptoid interactions that explicitly models all atoms except hydrogens, which are eliminated. 29 The water solvent is modeled using Molinero and co-worker's model of water (mW) that models each water molecule as a single bead that interacts via a short-ranged Stillinger−Weber potential comprising two-and three-body terms.…”
Peptoids
(poly-N-substituted glycines) are a class of synthetic
polymers that are regioisomers of peptides (poly-C-substituted glycines),
in which the point of side-chain connectivity is shifted from the
backbone C to the N atom. Peptoids have found diverse applications
as peptidomimetic drugs, protein mimetic polymers, surfactants, and
catalysts. Computational modeling is valuable in the understanding
and design of peptoid-based nanomaterials. In this work, we report
the bottom-up parameterization of coarse-grained peptoid force fields
based on the MARTINI peptide force field against all-atom peptoid
simulation data. Our parameterization pipeline iteratively refits
coarse-grained bonded interactions using iterative Boltzmann inversion
and nonbonded interactions by matching the potential of mean force
for chain extension. We assure good sampling of the amide bond cis/trans
isomerizations in the all-atom simulation data using parallel bias
metadynamics. We develop coarse-grained models for two representative
peptoidspolysarcosine (poly(N-methyl glycine))
and poly(N-((4-bromophenyl)ethyl)glycine)and
show their structural and thermodynamic properties to be in excellent
accord with all-atom calculations but up to 25-fold more efficient
and compatible with MARTINI force fields. This work establishes a
new rigorously parameterized coarse-grained peptoid force field for
the understanding and design of peptoid nanomaterials at length and
time scales inaccessible to all-atom calculations.
“…Du, Rick, and Kumar developed a CG model of polysarcosine (poly(N-methyl glycine), N,N-dimethylacetamide) as a prototypical model for the polypeptoid backbone. 26 The optimized potential for liquid simulations-united atom (OPLS-UA) model is adopted for the intramolecular peptoid interactions that explicitly models all atoms except hydrogens, which are eliminated. 29 The water solvent is modeled using Molinero and co-worker's model of water (mW) that models each water molecule as a single bead that interacts via a short-ranged Stillinger−Weber potential comprising two-and three-body terms.…”
Peptoids
(poly-N-substituted glycines) are a class of synthetic
polymers that are regioisomers of peptides (poly-C-substituted glycines),
in which the point of side-chain connectivity is shifted from the
backbone C to the N atom. Peptoids have found diverse applications
as peptidomimetic drugs, protein mimetic polymers, surfactants, and
catalysts. Computational modeling is valuable in the understanding
and design of peptoid-based nanomaterials. In this work, we report
the bottom-up parameterization of coarse-grained peptoid force fields
based on the MARTINI peptide force field against all-atom peptoid
simulation data. Our parameterization pipeline iteratively refits
coarse-grained bonded interactions using iterative Boltzmann inversion
and nonbonded interactions by matching the potential of mean force
for chain extension. We assure good sampling of the amide bond cis/trans
isomerizations in the all-atom simulation data using parallel bias
metadynamics. We develop coarse-grained models for two representative
peptoidspolysarcosine (poly(N-methyl glycine))
and poly(N-((4-bromophenyl)ethyl)glycine)and
show their structural and thermodynamic properties to be in excellent
accord with all-atom calculations but up to 25-fold more efficient
and compatible with MARTINI force fields. This work establishes a
new rigorously parameterized coarse-grained peptoid force field for
the understanding and design of peptoid nanomaterials at length and
time scales inaccessible to all-atom calculations.
“…[ 50 ] A number of more computationally efficient coarse grained models have been developed to access these time and length scales. [ 31,51–53 ] The coarse‐grained peptoid models are developed in a bottom‐up way based on the atomistic peptoid simulations. However, one of the biggest shortcomings for the coarse‐grained models is nontransferable, which require huge effort in development of coarse‐grained models.…”
Polypeptoids (poly‐N‐substituent glycines) are a class of highly tailorable peptidomimetic polymers. Polypeptoids have identical backbones as polypeptides (poly‐C‐substituent glycines), but sidechains of polypeptoids are appended to backbone nitrogen rather than α‐carbon of polypeptides. As a result, peptoid backbone lacks of chirality and hydrogen bond donors. This unique structure gives polypeptoids a combined merit of both high stability as synthetic polymers and biocompatibility as biopolymers. In addition, peptoid sequences can be engineered precisely to assemble specific crystalline patterns such as spheres, fibers, ribbons, tubes, and sheets, which shows promising potentials of polypeptoids for different applications such as antimicrobials, catalysts, drug delivery, and templating inorganic materials. In this review, we summarize recent investigations into hierarchical self‐assembly pathways and molecular structures of peptoid crystals that are of interest as templates for fabricating functional materials for potential biomedical, biochemical, and bioengineering applications. This review provides a summary of recent experimental and computational studies of polypeptoid assembly in solution and solid‐liquid interfaces, current achievements in the field, and discusses future challenges and opportunities for the rational design of self‐assembled polypeptoid nanomaterials.
“…In this manuscript, we describe a new RE method for sampling the amide dihedral degrees of freedom and apply it to two different peptoid oligomers, as shown in Figure 1. N‐(methyl) glycine, or sarcosine, is the most commonly studied polypeptoid 12,13,18–20,22,24–26 . N‐ethyl glycine was chosen as a more hydrophobic polypeptoid.…”
Section: Introductionmentioning
confidence: 99%
“…N-(methyl) glycine, or sarcosine, is the most commonly studied polypeptoid. 12,13,[18][19][20]22,[24][25][26] N-ethyl glycine was chosen as a more hydrophobic polypeptoid.…”
Polypeptoids differ from polypeptides in that the amide bond can more frequently adopt both cis and trans conformations. The transition between the two conformations requires overcoming a large energy barrier, making it difficult for conventional molecular simulations to adequately visit the cis and trans structures. A replica-exchange method is presented that allows for easy rotations of the amide bond and also an efficient linking to a high temperature replica. The method allows for just three replicas (one at the temperature and Hamiltonian of interest, a second high temperature replica with a biased dihedral potential, and a third connecting them) to overcome the amide bond sampling problem and also enhance sampling for other coordinates. The results indicate that for short peptoid oligomers, the conformations can range from all cis to all trans with an average cis/trans ratio that depends on side chain and potential model.
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