Hydration free energies calculated using the AMBER ff03 charge model for natural and unnatural amino acids and multiple water models

Investigating the molecular mechanism of vitexin targeting CDK1 to inhibit colon cancer cell proliferation via GEO chip data mining, computer simulation, and biological activity verification

The objective of this study is to explore the antiproliferative activity of the traditional Chinese medicine monomer vitexin on colon cancer HCT-116 cells and its underlying mechanism. The in vitro antiproliferative activity of vitexin on colon cancer HCT-116 cells was evaluated using the CCK-8 assay. Potential drug targets for colon cancer were identified through GEO chip data mining, and molecular docking using Schrödinger software was conducted. Molecular dynamics simulations were employed to deeply analyze the interaction between candidate compounds and target proteins. Flow cytometry was employed to examine the cell cycle. The impact of vitexin on the expression of CDK1/cyclinB proteins in HCT-116 cells was assessed through Western blot analysis, immunofluorescence, and CDK inhibition assay. Vitexin exhibited inhibitory effects on colon cancer HCT-116 cells, with a half inhibitory concentration (IC50) value of 203.27 ± 9.85 μmol/L. The analysis of differential gene expression in GEO and TCGA datasets, along with the GENECARD dataset of related disease genes, identified 91 disease targets, including "CDK1." Vitexin induced cell cycle arrest in the G2/M phase of HCT-116 cells. Molecular docking revealed a strong interaction between Vitexin and CDK1 (Docking score - 9.497), with molecular dynamics simulations confirming the stability of the Vitexin-CDK1 complex and comparable inhibitory effects to Flavopiridol. Vitexin can inhibit the expression of CDK1/cyclin B proteins in HCT-116 cells, with an IC50 of 58.06 ± 3.07 μmol/L. Vitexin may inhibit colon cancer HCT-116 cell proliferation by suppressing CDK1/cyclin B expression, leading to cell cycle arrest in the G2/M phase.

Analysis of the binding selectivity and inhibiting mechanism of chlorogenic acid isomers and their interaction with grass carp endogenous lipase using multi-spectroscopic, inhibition kinetics and modeling methods

Polyphenols are inhibitors for lipase, but the binding selectivity and mechanism of polyphenol isomers and how they interact with lipase are not clear. Here, chlorogenic acid (CGA) isomers, neochlorogenic acid (NCGA) and cryptochlorogenic acid (CCGA) were used to explore the binding selectivity and mechanism of lipase. An inhibition assay indicated that both CGA isomers had dose-dependent inhibitory effects on lipase; however, the inhibitory effect of NCGA was better (IC₅₀: 0.647 mg/mL) than that of CCGA (IC₅₀: 0.677 mg/mL). NCGA and CCGA formed complexes with lipase at a molar ratio of 1:1, and the electrostatic interaction force plays a major role in the lipase-CCGA system. Molecular dynamics studies demonstrated that NCGA had a greater impact on the structure of lipase. The multi-spectroscopic and modeling results explained the effects of micro-structural changes on the binding site, the interaction force and the inhibition rate of the isomers when they combined with lipase.

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.

Data-driven analysis of the number of Lennard-Jones types needed in a force field

Force fields used in molecular simulations contain numerical parameters, such as Lennard-Jones (LJ) parameters, which are assigned to the atoms in a molecule based on a classification of their chemical environments. The number of classes, or types, should be no more than needed to maximize agreement with experiment, as parsimony avoids overfitting and simplifies parameter optimization. However, types have historically been crafted based largely on chemical intuition, so current force fields may contain more types than needed. In this study, we seek the minimum number of LJ parameter types needed to represent key properties of organic liquids. We find that highly competitive force field accuracy is obtained with minimalist sets of LJ types; e.g. two H types and one type apiece for C, O, and N atoms. We also find that the fitness surface has multiple minima, which can lead to local trapping of the optimizer.

Enthalpic and Entropic Contributions to Hydrophobicity

Hydrophobic hydration plays a key role in a vast variety of biological processes, ranging from the formation of cells to protein folding and ligand binding. Hydrophobicity scales simplify the complex process of hydration by assigning a value describing the averaged hydrophobic character to each amino acid. Previously published scales were not able to calculate the enthalpic and entropic contributions to the hydrophobicity directly. We present a new method, based on Molecular Dynamics simulations and Grid Inhomogeneous Solvation Theory, that calculates hydrophobicity from enthalpic and entropic contributions. Instead of deriving these quantities from the temperature dependence of the free energy of hydration or as residual of the free energy and the enthalpy, we directly obtain these values from the phase space occupied by water molecules. Additionally, our method is able to identify regions with specific enthalpic and entropic properties, allowing to identify so-called "unhappy water" molecules, which are characterized by weak enthalpic interactions and unfavorable entropic constraints.

Osmotic Pressure Simulations of Amino Acids and Peptides Highlight Potential Routes to Protein Force Field Parameterization

Recent molecular dynamics (MD) simulations of proteins have suggested that common force fields overestimate the strength of amino acid interactions in aqueous solution. In an attempt to determine the causes of these effects, we have measured the osmotic coefficients of a number of amino acids using the AMBER ff99SB-ILDN force field with two popular water models, and compared the results with available experimental data. With TIP4P-Ew water, interactions between aliphatic residues agree well with experiment, but interactions of the polar residues serine and threonine are found to be excessively attractive. For all tested amino acids, the osmotic coefficients are lower when the TIP3P water model is used. Additional simulations performed on charged amino acids indicate that the osmotic coefficients are strongly dependent on the parameters assigned to the salt ions, with a reparameterization of the sodium/carboxylate interaction reported by the Aksimentiev group significantly improving description of the osmotic coefficient for glutamate. For five neutral amino acids, we also demonstrate a decrease in solute-solute attractions using the recently reported TIP4P-D water model and using the KBFF force field. Finally, we show that for four two-residue peptides improved agreement with experiment can be achieved by rederiving the partial charges for each peptide.