enhanced molecular dynamics simulations
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Since its early days in the 19th century, medicinal chemistry has concentrated its efforts on the treatment of diseases, using tools from areas such as chemistry, pharmacology, and molecular biology. The understanding of biological mechanisms and signaling pathways is crucial information for the development of potential agents for the treatment of diseases mainly because they are such complex processes. Given the limitations that the experimental approach presents, computational chemistry is a valuable alternative for the study of these systems and their behavior. Thus, classical molecular dynamics, based on Newton's laws, is considered a technique of great accuracy, when appropriated force fields are used, and provides satisfactory contributions to the scientific community. However, as many configurations are generated in a large MD simulation, methods such as Statistical Inefficiency and Optimal Wavelet Signal Compression Algorithm are great tools that can reduce the number of subsequent QM calculations. Accordingly, this review aims to briefly discuss the importance and relevance of medicinal chemistry allied to computational chemistry as well as to present a case study where, through a molecular dynamics simulation of AMPK protein (50 ns) and explicit solvent (TIP3P model), a minimum number of snapshots necessary to describe the oscillation profile of the protein behavior was proposed. For this purpose, the RMSD calculation, together with the sophisticated OWSCA method was used to propose the minimum number of snapshots.
- MeSH
- algoritmy MeSH
- farmaceutická chemie MeSH
- kvantová teorie MeSH
- lidé MeSH
- proteinkinasy aktivované AMP metabolismus chemie MeSH
- simulace molekulární dynamiky * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
There is increasing pharmaceutical interest in deep eutectic solvents not only as a green alternative to organic solvents in drug manufacturing, but also as liquid formulation for drug delivery. The present work introduces a hydrophobic deep eutectic solvent (HDES) to the field of lipid-based formulations (LBF). Phase behavior of a mixture with 2:1 M ratio of decanoic- to dodecanoic acid was studied experimentally and described by thermodynamic modelling. Venetoclax was selected as a hydrophobic model drug and studied by atomistic molecular dynamics simulations of the mixtures. As a result, valuable molecular insights were gained into the interaction networks between the different components. Moreover, experimentally the HDES showed greatly enhanced drug solubilization compared to conventional glyceride-based vehicles, but aqueous dispersion behavior was limited. Hence surfactants were studied for their ability to improve aqueous dispersion and addition of Tween 80 resulted in lowest droplet sizes and high in vitro drug release. In conclusion, the combination of HDES with surfactant(s) provides a novel LBF with high pharmaceutical potential. However, the components must be finely balanced to keep the integrity of the solubilizing HDES, while enabling sufficient dispersion and drug release.
- MeSH
- farmaceutická chemie metody MeSH
- hydrofobní a hydrofilní interakce * MeSH
- kyseliny laurové chemie MeSH
- lipidy * chemie MeSH
- oleje chemie MeSH
- polysorbáty chemie MeSH
- povrchově aktivní látky * chemie MeSH
- příprava léků * metody MeSH
- rozpouštědla * chemie MeSH
- rozpustnost * MeSH
- simulace molekulární dynamiky * MeSH
- sulfonamidy chemie aplikace a dávkování MeSH
- uvolňování léčiv * MeSH
- Publikační typ
- časopisecké články MeSH
Hyaluronan is a natural carbohydrate polymer with a negative charge that fosters gel-like conditions crucial for its cellular functions and industrial applications. As a recognized ligand for proteins, understanding their mutual interactions provides solid ground to tune hyaluronan's gel properties using biocompatible peptides. This work employs NMR and molecular dynamics simulations to identify molecular motifs relevant to hyaluronan-peptide interactions using arginine, lysine, and glycine oligopeptides. Arginine-rich peptides exhibit the strongest binding to hyaluronan according to chemical shift perturbation measurements, followed distantly by the similarly charged lysine. This difference highlights the significance of electrostatics and the peculiarities of the guanidinium side chain in arginine, capable of non-polar interactions that further stabilize the binding. Additional nuclear Overhauser effect measurements do not show stable interaction partners, precluding strong and well-defined complexes. Finally, molecular simulations support our findings and show an extended but significant interaction region, especially for arginine, responsible for the observed enhanced binding, which can also promote cross-linking of hyaluronan polymers. Our findings pave the way for optimizing biocompatible peptides to alter hyaluronan gels' properties efficiently and also explain why hyaluronan-protein interaction typically involves positively charged arginine-rich regions also capable of forming hydrogen bonds and non-polar interactions.
Herbal medications have an extensive history of use in treating various diseases, attributed to their perceived efficacy and safety. Traditional medicine practitioners and contemporary healthcare providers have shown particular interest in herbal syrups, especially for respiratory illnesses associated with the SARS-CoV-2 virus. However, the current understanding of the pharmacokinetic and toxicological properties of phytochemicals in these herbal mixtures is limited. This study presents a comprehensive computational analysis utilizing novel approach methodologies (NAMs) to investigate the pharmacokinetic and toxicological profiles of phytochemicals in herbal syrup, leveraging in-silico techniques and prediction tools such as PubChem, SwissADME, and Molsoft's database. Although molecular dynamics, docking, and broader system-wide analyses were not considered, future studies hold potential for further investigation in these areas. By combining drug-likeness with molecular simulation, researchers identify diverse phytochemicals suitable for complex medication development examining their pharmacokinetic-toxicological profiles in phytopharmaceutical syrup. The study focuses on herbal solutions for respiratory infections, with the goal of adding to the pool of all-natural treatments for such ailments. This research has the potential to revolutionize environmental and alternative medicine by leveraging in-silico models and innovative analytical techniques to identify novel phytochemicals with enhanced therapeutic benefits and explore network-based and systems biology approaches for a deeper understanding of their interactions with biological systems. Overall, our study offers valuable insights into the computational analysis of the pharmacokinetic and toxicological profiles of herbal concoction. This paves the way for advancements in environmental and alternative medicine. However, we acknowledge the need for future studies to address the aforementioned topics that were not adequately covered in this research.
- Publikační typ
- časopisecké články MeSH
Atomic characterization of large nonfibrillar aggregates of amyloid polypeptides cannot be determined by experimental means. Starting from β-rich aggregates of Y and elongated topologies predicted by coarse-grained simulations and consisting of more than 100 Aβ16-22 peptides, we performed atomistic molecular dynamics (MD), replica exchange with solute scaling (REST2), and umbrella sampling simulations using the CHARMM36m force field in explicit solvent. Here, we explored the dynamics within 3 μs, the free energy landscape, and the potential of mean force associated with either the unbinding of one single peptide in different configurations within the aggregate or fragmentation events of a large number of peptides. Within the time scale of MD and REST2, we find that the aggregates experience slow global conformational plasticity, and remain essentially random coil though we observe slow beta-strand structuring with a dominance of antiparallel beta-sheets over parallel beta-sheets. Enhanced REST2 simulation is able to capture fragmentation events, and the free energy of fragmentation of a large block of peptides is found to be similar to the free energy associated with fibril depolymerization by one chain for longer Aβ sequences.
Phosphate···π, also called anion···π, contacts occur between nucleobases and anionic phosphate oxygens (OP2) in r(GNRA) and r(UNNN) U-turn motifs (N = A,G,C,U; R = A,G). These contacts were investigated using state-of-the-art quantum-chemical methods (QM) to characterize their physicochemical properties and to serve as a reference to evaluate AMBER force field (AFF) performance. We found that phosphate···π interaction energies calculated with the AFF for dimethyl phosphate···nucleobase model systems are less stabilizing in comparison with double-hybrid DFT and that minimum contact distances are larger for all nucleobases. These distance stretches are also observed in large-scale AFF vs QM/MM computations and classical molecular dynamics (MD) simulations on several r(gcGNRAgc) tetraloop hairpins when compared to experimental data extracted from X-ray/cryo-EM structures (res. ≤ 2.5 Å) using the WebFR3D bioinformatic tool. MD simulations further revealed shifted OP2/nucleobase positions. We propose that discrepancies between the QM and AFF result from a combination of missing polarization in the AFF combined with too large AFF Lennard-Jones (LJ) radii of nucleobase carbon atoms in addition to an exaggerated short-range repulsion of the r-12 LJ repulsive term. We compared these results with earlier data gathered on lone pair···π contacts in CpG Z-steps occurring in r(UNCG) tetraloops. In both instances, charge transfer calculations do not support any significant n → π* donation effects. We also investigated thiophosphate···π contacts that showed reduced stabilizing interaction energies when compared to phosphate···π contacts. Thus, we challenge suggestions that the experimentally observed enhanced thermodynamic stability of phosphorothioated r(GNRA) tetraloops can be explained by larger London dispersion.
- MeSH
- fosfáty MeSH
- RNA * chemie MeSH
- simulace molekulární dynamiky * MeSH
- termodynamika MeSH
- výpočetní biologie MeSH
- Publikační typ
- časopisecké články MeSH
This work extends the multi-scale computational scheme for the quantum mechanics (QM) calculations of Nuclear Magnetic Resonance (NMR) chemical shifts (CSs) in proteins that lack a well-defined 3D structure. The scheme couples the sampling of an intrinsically disordered protein (IDP) by classical molecular dynamics (MD) with protein fragmentation using the adjustable density matrix assembler (ADMA) and density functional theory (DFT) calculations. In contrast to our early investigation on IDPs (Pavlíková Přecechtělová et al., J. Chem. Theory Comput., 2019, 15, 5642-5658) and the state-of-the art NMR calculations for structured proteins, a partial re-optimization was implemented on the raw MD geometries in vibrational normal mode coordinates to enhance the accuracy of the MD/ADMA/DFT computational scheme. In addition, machine-learning based cluster analysis was performed on the scheme to explore its potential in producing protein structure ensembles (CLUSTER ensembles) that yield accurate CSs at a reduced computational cost. The performance of the cluster-based calculations is validated against results obtained with conventional structural ensembles consisting of MD snapshots extracted from the MD trajectory at regular time intervals (REGULAR ensembles). CS calculations performed with the refined MD/ADMA/DFT framework employed the 6-311++G(d,p) basis set that outperformed IGLO-III calculations with the same density functional approximation (B3LYP) and both explicit and implicit solvation. The partial geometry optimization did not universally improve the agreement of computed CSs with the experiment but substantially decreased errors associated with the ensemble averaging. A CLUSTER ensemble with 50 structures yielded ensemble averages close to those obtained with a REGULAR ensemble consisting of 500 MD frames. The cluster based calculations thus required only a fraction of the computational time.
FGF2 is a cell survival factor involved in tumor-induced angiogenesis that is secreted through an unconventional secretory pathway based upon direct protein translocation across the plasma membrane. Here, we demonstrate that both PI(4,5)P2-dependent FGF2 recruitment at the inner plasma membrane leaflet and FGF2 membrane translocation into the extracellular space are positively modulated by cholesterol in living cells. We further revealed cholesterol to enhance FGF2 binding to PI(4,5)P2-containing lipid bilayers. Based on extensive atomistic molecular dynamics (MD) simulations and membrane tension experiments, we proposed cholesterol to modulate FGF2 binding to PI(4,5)P2 by (i) increasing head group visibility of PI(4,5)P2 on the membrane surface, (ii) increasing avidity by cholesterol-induced clustering of PI(4,5)P2 molecules triggering FGF2 oligomerization, and (iii) increasing membrane tension facilitating the formation of lipidic membrane pores. Our findings have general implications for phosphoinositide-dependent protein recruitment to membranes and explain the highly selective targeting of FGF2 toward the plasma membrane, the subcellular site of FGF2 membrane translocation during unconventional secretion of FGF2.
The effect of aqueous solutions of selected ionic liquids solutions on Ideonella sakaiensis PETase with bis(2-hydroxyethyl) terephthalate (BHET) substrate were studied by means of molecular dynamics simulations in order to identify the possible effect of ionic liquids on the structure and dynamics of enzymatic Polyethylene terephthalate (PET) hydrolysis. The use of specific ionic liquids can potentially enhance the enzymatic hydrolyses of PET where these ionic liquids are known to partially dissolve PET. The aqueous solution of cholinium phosphate were found to have the smallest effect of the structure of PETase, and its interaction with (BHET) as substrate was comparable to that with the pure water. Thus, the cholinium phosphate was identified as possible candidate as ionic liquid co-solvent to study the enzymatic hydrolyses of PET.
- MeSH
- Burkholderiales enzymologie MeSH
- hydrofobní a hydrofilní interakce MeSH
- hydrolasy metabolismus MeSH
- hydrolýza MeSH
- iontové kapaliny chemie MeSH
- konformace proteinů MeSH
- kyseliny ftalové chemie MeSH
- polyethylentereftaláty chemie MeSH
- rozpouštědla chemie MeSH
- simulace molekulární dynamiky MeSH
- vodíková vazba MeSH
- Publikační typ
- časopisecké články MeSH
Oxidative stress can lead to various derivatives of the tyrosine residue in peptides and proteins. A typical product is 3-nitro-L-tyrosine residue (Nit), which can affect protein behavior during neurodegenerative processes, such as those associated with Alzheimer's and Parkinson's diseases. Surface enhanced Raman spectroscopy (SERS) is a technique with potential for detecting peptides and their metabolic products at very low concentrations. To explore the applicability to Nit, we use SERS to monitor tyrosine nitration in Met-Enkephalin, rev-Prion protein, and α-synuclein models. Useful nitration indicators were the intensity ratio of two tyrosine marker bands at 825 and 870 cm-1 and a bending vibration of the nitro group. During the SERS measurement, a conversion of nitrotyrosine to azobenzene containing peptides was observed. The interpretation of the spectra has been based on density functional theory (DFT) simulations. The CAM-B3LYP and ωB97XD functionals were found to be most suitable for modeling the measured data. The secondary structure of the α-synuclein models was monitored by electronic and vibrational circular dichroism (ECD and VCD) spectroscopies and modeled by molecular dynamics (MD) simulations. The results suggest that the nitration in these peptides has a limited effect on the secondary structure, but may trigger their aggregation.
- MeSH
- azosloučeniny chemie MeSH
- cirkulární dichroismus MeSH
- peptidy chemická syntéza chemie MeSH
- Ramanova spektroskopie metody MeSH
- sekundární struktura proteinů MeSH
- simulace molekulární dynamiky MeSH
- teorie funkcionálu hustoty MeSH
- tyrosin analogy a deriváty analýza MeSH
- Publikační typ
- časopisecké články MeSH
