Benchmark of a functional-group database for distributed polarizability and dipole moment in biomolecules

• Published in: Physical chemistry chemical physics : PCCP 2022-12, Vol.24 (48), p.29495-2954
• Main Authors: Ligorio, Raphael F, Rodrigues, Jose L, Zuev, Anatoly, Dos Santos, Leonardo H. R, Krawczuk, Anna
• Format: Article
• Language: English
• Subjects: Amino acids; Anisotropy; Benchmarks; Biomedical materials; Biomolecules; Density functional theory; Dipole moments; Functional groups; Optical properties; Peptides; Polypeptides; Solvent effect; Tensors
• ISSN: 1463-9076; 1463-9084
• DOI: 10.1039/d2cp04052b

The extraction of functional-group properties in condensed phases is very useful for predicting material behaviors, including those of biomaterials. For this reason, computational approaches based on partitioning schemes have been developed aiming at rapidly and accurately estimating properties from chemically meaningful building blocks. A comprehensive database of group polarizabilities and dipole moments is useful not only to predict the optical properties of biomacromolecules but also to improve molecular force fields focused on simulating biochemical processes. In this work we benchmark a database of distributed polarizabilities and dipole moments for functional groups extracted from a series of polypeptides. This allows reconstruction of a variety of relevant chemical environments. The accuracy of our database was tested to predict the electro-optical properties of larger peptides and also simpler amino acids for which density functional theory calculations at the M06-HF/aug-cc-pVDZ level of theory was chosen as the reference. This approach is reasonably accurate for the diagonal components of the polarizability tensor, with errors not larger than 15-20%. The anisotropy of the polarizability is predicted with smaller efficacy though. Solvent effects were included explicitly by surrounding the database entries by a box of water molecules whose distribution was optimized using the CHARMM force field. Application of group polarizability database towards better prediction of electric moments and electrostatic properties of biomolecules.