Improved Polarizable Dipole–Dipole Interaction Model for Hydrogen Bonding, Stacking, T-Shaped, and X–H···π Interactions

Computational Methods for Modeling Lipid-Mediated Active Pharmaceutical Ingredient Delivery

Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.

From bonds to interactions: comprehensive molecular characterization via polarizable bond-dipole approach

Accurately characterizing molecular interactions stands as a pivotal requirement for ensuring the reliability of molecular dynamics simulations. In line with our bond-dipole-based interaction model proposed by Gao et al. [X.-C. Gao, Q. Hao and C.-S. Wang, J. Chem. Theory Comput., 2017, 13, 2730-2741.], we have implemented an efficient and concise approach to compute electrostatic potential. This methodology capitalizes on the polarizable nature of chemical bond dipoles, resulting in a model of remarkable simplicity. In this study, we have revised the polarizable bond-dipole-based force field (PBFF) through the meticulous curation of quantum chemical data sets. These data sets encompass a comprehensive collection of 40 000 conformations, including those of water, methylamine, methanol, and N-methylacetamide. Additionally, we incorporate 520 hydrogen-bonded dimers into our data sets. In pursuit of enhanced accuracy in molecular dynamics simulations and a more faithful representation of potential energy landscapes, we undertook the re-optimization of the nonbonded parameters within the PBFF framework. Concurrently, we intricately fine-tuned the bonded parameters. The results of our comprehensive evaluation denote that this newly optimized force field method adeptly and efficiently computes structural characteristics, harmonic frequencies, and interaction energies. Overall, this study provides further validation for the applicability of PBFF in molecular dynamics simulations.

A scheme for rapid evaluation of the intermolecular three-body polarization effect in water clusters

The ability to accurately and rapidly evaluate the intermolecular many-body polarization effect of the water system is very important for computer simulations of biomolecule in aqueous. In this paper, a scheme is proposed based on the polarizable dipole-dipole interaction model and used to rapidly estimate the intermolecular many-body polarization effect in water clusters. We use a bond-dipole-based polarization function to evaluate the polarization energy. We regard two OH bonds of a water molecule as two bond-dipoles and set the permanent OH bond-dipole moment of a water molecule to be 1.51 Debye. We estimate the induced OH bond-dipole moment via a simple formula in which only one correction factor is needed. This scheme is then applied to tens of water clusters to calculate the three- and four-body interaction energies. The three-body interaction energies of 93 water clusters produced by our scheme are compared with those produced by the counterpoise-corrected CCSD(T)/aug-cc-pVDZ, MP2/aug-cc-pVDZ, M06-2X/jul-cc-pVTZ methods, by the AMOEBApro13, iAMOEBA, AMOEBA+, AMOEBA+(CF) methods, and by the MB-pol method. The four-body interaction energies of 47 water clusters yielded by our scheme are compared with those yielded by the counterpoise-corrected MP2/aug-cc-pVDZ and M06-2X/ jul-cc-pVTZ methods, by the AMOEBApro13, AMOEBA+, AMOEBA+(CF) methods, and by the MB-pol method. The comparison results show that the scheme proposed in this paper can reproduce the counterpoise-corrected CCSD(T)/aug-cc-pVDZ three-body interaction energies and reproduce the counterpoise-corrected MP2/aug-cc-pVDZ four-body interaction energies both accurately and efficiently. We anticipate the scheme proposed here can be useful for computer simulations of liquid water and aqueous solutions.

Insight into pyrolysis mechanism of 1,2-propylene glycol: Based on density functional theory and wavefunction analysis

The multiple thermal decomposition mechanisms of 1,2-propylene glycol are studied through theoretical calculation and experiment, including carbon chain break, dehydrogenation and dehydration mechanism. The wavefunction is employed to analyze the decomposition process from a micro perspective. DLPNO-CCSD(T)/CBS method is engaged in establishing potential energy surface. The results reveal that the dehydration and carbon chain break mechanism are the primary pyrolysis paths, and the former is the dominant pyrolysis mechanism at low temperature, while the latter is applicable at the high temperature. The pyrolysis products are mainly acetaldehyde, propanal and acetone, which is consistent with experimental results. Besides, the comparison results of 1,2-propylene glycol and glycerol pyrolysis products indicate that the increment of hydroxyls are conducive to the generation of carbonyl compounds during the polyol thermal decomposition. This work is aimed to comprehensively investigate the pyrolysis mechanism of 1,2-propylene glycol and provide the valuable thermodynamics and kinetic data for developing efficient polyol pyrolysis technology. Furthermore, it provides a reference for choosing low-toxic tobacco humectant.

Non-Covalent Interaction on the Self-Healing of Mechanical Properties in Supramolecular Polymers

Supramolecular polymers are widely utilized and applied in self-assembly or self-healing materials, which can be repaired when damaged. Normally, the healing process is classified into two types, including extrinsic and intrinsic self-healable materials. Therefore, the aim of this work is to review the intrinsic self-healing strategy based on supramolecular interaction or non-covalent interaction and molecular recognition to obtain the improvement of mechanical properties. In this review, we introduce the main background of non-covalent interaction, which consists of the metal–ligand coordination, hydrogen bonding, π–π interaction, electrostatic interaction, dipole–dipole interaction, and host–guest interactions, respectively. From the perspective of mechanical properties, these interactions act as transient crosslinking points to both prevent and repair the broken polymer chains. For material utilization in terms of self-healing products, this knowledge can be applied and developed to increase the lifetime of the products, causing rapid healing and reducing accidents and maintenance costs. Therefore, the self-healing materials using supramolecular polymers or non-covalent interaction provides a novel strategy to enhance the mechanical properties of materials causing the extended cycling lifetime of products before replacement with a new one.

Development and Testing of Force Field Parameters for Phenylalanine and Tyrosine Derivatives

Theoretical analyses are valuable for the exploration of the effects of unnatural amino acids on enzyme functions; however, many necessary parameters for unnatural amino acids remain lacking. In this study, we developed and tested force field parameters compatible with Amber ff14SB for 18 phenylalanine and tyrosine derivatives. The charge parameters were derived from ab initio calculations using the RESP fitting approach and then adjusted to reproduce the benchmark relative energies (at the MP2/TZ level) of the α- and β-backbones for each unnatural amino acid dipeptide. The structures optimized under the proposed force field parameters for the 18 unnatural amino acid dipeptides in both the α- and β-backbone forms were in good agreement with their QM structures, as the average RMSD was as small as 0.1 Å. The force field parameters were then tested in their application to seven proteins containing unnatural amino acids. The RMSDs of the simulated configurations of these unnatural amino acids were approximately 1.0 Å compared with those of the crystal structures. The vital interactions between proteins and unnatural amino acids in five protein–ligand complexes were also predicted using MM/PBSA analysis, and they were largely consistent with experimental observations. This work will provide theoretical aid for drug design involving unnatural amino acids.

Polarizable Force Fields for Biomolecular Simulations: Recent Advances and Applications

Realistic modeling of biomolecular systems requires an accurate treatment of electrostatics, including electronic polarization. Due to recent advances in physical models, simulation algorithms, and computing hardware, biomolecular simulations with advanced force fields at biologically relevant timescales are becoming increasingly promising. These advancements have not only led to new biophysical insights but also afforded opportunities to advance our understanding of fundamental intermolecular forces. This article describes the recent advances and applications, as well as future directions, of polarizable force fields in biomolecular simulations.