There is a need to develop robust computational models for mesoscale simulation of the structure of peptides over large length scales toward the discovery of novel peptides for medical applications to address the issues of peptide aggregation, enzymatic degradation, and short half-life. The primary objective was to predict the structure and conformation of peptides whose native structures are not known. This work presents a new model for computation of interaction parameters between the beads in coarse-grained dissipative particle dynamics (DPD) simulation that is properly calibrated for amino acids, supports compressibility requirement of water molecules, and accounts for subtle differences in the structure of amino acids and the charge in the side chain of charged amino acids. This new model is referred to as Structure Independent Molecular Fragment Interfuse Model, abbreviated as SIMFIM, because it accounts for specific interactions between different beads, which represent molecular fragments of the amino acids, in calculating nonbonded interaction parameters in the absence of knowing the actual peptide structure. The electrostatic interactions are incorporated in this model by using a normal distribution of charges around the center of the beads to prevent the collapse of oppositely charged soft beads. The uniquely parameterized DPD force field in the SIMFIM model is optimized for a given peptide with respect to the degree of coarse-grained graining for simulating the peptide over long times and length scales. The SIMFIM model was tested in this work using four peptides, namely, TrpZip2, Rubrivinodin, Lihuanodin, and IC3-CB1/Gai peptides, whose structures were sourced from the Protein Data Bank. The SIMFIM model predicted radius of gyration (R(g)) values for the peptides closer to the actual structures as compared to the conventional model, and there was less deviation between the predicted and actual structures of the peptides.
A Structure Independent Molecular Fragment Interfuse Model for Mesoscale Dissipative Particle Dynamics Simulation of Peptides.
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作者:Dash Ricky Anshuman, Jabbari Esmaiel
| 期刊: | ACS Omega | 影响因子: | 4.300 |
| 时间: | 2024 | 起止号: | 2024 Apr 12; 9(16):18001-18022 |
| doi: | 10.1021/acsomega.3c09534 | ||
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