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67,616 result(s) for "Molecular modelling"
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Thermal Degradation Kinetics of Anthocyanins Extracted from Purple Maize Flour Extract and the Effect of Heating on Selected Biological Functionality
The thermal degradation of the anthocyanins and antioxidant activity in purple maize extracts was determined between 80 and 180 °C. The anthocyanins were found to be thermostable in the temperature range of 80 to 120 °C, whereas at higher temperatures the thermal degradation of both anthocyanins and antioxidant activity followed a first-order kinetic model. The z-values started from 61.72 ± 2.28 °C for anthocyanins and 75.75 ± 2.87 °C for antioxidant activity. The conformational space of pairs of model anthocyanin molecules at 25 and 180 °C was explored through a molecular dynamics test, and results indicated the occurrence of intermolecular self-association reactions and intramolecular co-pigmentation events, which might help explaining the findings of the degradation kinetics. The relationship between thermal degradation of anthocyanins and antioxidant activity and the in vitro release was further studied. The unheated extracts showed a high stability under gastric environment, whereas after heating at 180 °C, the digestion ended quickly after 60 min. After simulated intestinal digestion, the anthocyanins were slowly decreased to a maximum of 12% for the unheated extracts, whereas an 83% decrease was found after preliminary heating at 180 °C. The thermal degradation of anthocyanins was positively correlated with the in vitro decrease of antioxidant activity.
Molecular Modeling Methods in the Development of Affine and Specific Protein-Binding Agents
High-affinity and specific agents are widely applied in various areas, including diagnostics, scientific research, and disease therapy (as drugs and drug delivery systems). It takes significant time to develop them. For this reason, development of high-affinity agents extensively utilizes computer methods at various stages for the analysis and modeling of these molecules. The review describes the main affinity and specific agents, such as monoclonal antibodies and their fragments, antibody mimetics, aptamers, and molecularly imprinted polymers. The methods of their obtaining as well as their main advantages and disadvantages are briefly described, with special attention focused on the molecular modeling methods used for their analysis and development.
Mechanism of PARP1 Elongation Reaction Revealed by Molecular Modeling
Poly(ADP-ribose) polymerase 1 (PARP1) plays a major role in the DNA damage repair and transcriptional regulation, and is targeted by a number of clinical inhibitors. Despite this, catalytic mechanism of PARP1 remains largely underexplored because of the complex substrate/product structure. Using molecular modeling and metadynamics simulations we have described in detail elongation of poly(ADP-ribose) chain in the PARP1 active site. It was shown that elongation reaction proceeds via the SN1-like mechanism involving formation of the intermediate furanosyl oxocarbenium ion. Intriguingly, nucleophilic 2′A-OH group of the acceptor substrate can be activated by the general base Glu988 not directly but through the proton relay system including the adjacent 3′A-OH group.
Exploring protein structural ensembles: Integration of sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling methods
Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure–function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.
In Silico Prediction of Diffusion Interaction Parameter (kD), a Key Indicator of Antibody Solution Behaviors
PurposeTo develop resource-sparing in silico approaches that aim to reduce experimental effort and material required by developability assessments (DA) of monoclonal antibody (mAb) drug candidates.MethodsA battery of standardized biophysical experiments was performed on high concentration formulations of 16 drug product development stage mAbs using a platform buffer. Full-length molecular models of these mAbs were also generated via molecular modeling. These models were used to computationally estimate molecular descriptors of these 16 mAbs. Pairwise and multi-parameter correlations among experimentally measured biophysical attributes and calculated molecular descriptors were obtained via statistical analyses.ResultsDiffusion interaction parameter (kD) showed statistically significant pairwise correlations (p-values <0.005) with thermal stability, viscosity, isoelectric point, and apparent solubility of the antibodies in our dataset. kD also showed statistically significant pairwise correlations (p-values <0.005) with several computationally calculated molecular descriptors (pI, net charge, charge on the Fv region, and zeta potential.) These pairwise correlations were further refined by multivariate analyses. These analyses yielded several useful equations for prediction of kD from antibody sequences, structural models, and experimentally measured biophysical attributes.ConclusionsDiffusion interaction parameter (kD) was found to be a key biophysical property for the mAbs in our dataset. It connects conformational heterogeneity of an antibody with its colloidal and rheological behaviors. The equations derived in this work shall enable rapid, resource-sparing, and cost-effective DAs of biologic drug candidates.
Molecular Modeling of Signal Peptide Recognition by Eukaryotic Sec Complexes
Here, we review recent molecular modelling and simulation studies of the Sec translocon, the primary component/channel of protein translocation into the endoplasmic reticulum (ER) and bacterial periplasm, respectively. Our focus is placed on the eukaryotic Sec61, but we also mention modelling studies on prokaryotic SecY since both systems operate in related ways. Cryo-EM structures are now available for different conformational states of the Sec61 complex, ranging from the idle or closed state over an inhibited state with the inhibitor mycolactone bound near the lateral gate, up to a translocating state with bound substrate peptide in the translocation pore. For all these states, computational studies have addressed the conformational dynamics of the translocon with respect to the pore ring, the plug region, and the lateral gate. Also, molecular simulations are addressing mechanistic issues of insertion into the ER membrane vs. translocation into the ER, how signal-peptides are recognised at all in the translocation pore, and how accessory proteins affect the Sec61 conformation in the co- and post-translational pathways.
Bicalutamide Anticancer Activity Enhancement by Formulation of Soluble Inclusion Complexes with Cyclodextrins
Bicalutamide (BCL) is a nonsteroidal antiandrogen drug that represents an alternative to castration in the treatment of prostate cancer, due to its relatively long half-life and tolerable side effects. However, it possesses a very low water solubility that can affect its oral bioavailability. In this work, we developed inclusion complexes of BCL with the highly soluble hydroxypropyl-β-cyclodextrin (HP-β-CyD) and sulfobutylether-β-cyclodextrin (SBE-β-CyD) to increase the water solubility and anticancer activity of BCL. The inclusion complexes were prepared using the freeze-drying method and were then characterized in a solid state via differential scanning calorimetry and X-ray analysis and in solution via phase-solubility studies and UV-vis and NMR spectroscopy. The BCL/HP-β-CyD and BCL/SBE-β-CyD inclusion complexes were amorphous and rapidly dissolved in water. Both the 1H-NMR spectra and molecular modeling studies confirmed the penetration of the 2-(trifluoromethyl)benzonitrile ring of BCL within the cavity of both cyclodextrins (CyDs). Due to the consistent improvement of the water solubility of BCL, the inclusion complexes showed higher antiproliferative activity toward the human prostate androgen-independent cell lines, DU-145 and PC-3, with respect to free BCL. These results demonstrate the ability of HP-β-CyD and SBE-β-CyD to complex BCL, permitting the realization of liquid formulations with potentially high oral bioavailability and/or possible parenteral administration.
Synthesis, α-mannosidase inhibition studies and molecular modeling of 1,4-imino-ᴅ-lyxitols and their C-5-altered N -arylalkyl derivatives
A synthesis of 1,4-imino-ᴅ-lyxitols and their N -arylalkyl derivatives altered at C-5 is reported. Their inhibitory activity and selectivity toward four GH38 α-mannosidases (two Golgi types: GMIIb from Drosophila melanogaster and AMAN-2 from Caenorhabditis elegans , and two lysosomal types: LManII from Drosophila melanogaster and JBMan from Canavalia ensiformis ) were investigated. 6-Deoxy-DIM was found to be the most potent inhibitor of AMAN-2 ( K i = 0.19 μM), whose amino acid sequence and 3D structure of the active site are almost identical to the human α-mannosidase II (GMII). Although 6-deoxy-DIM was 3.5 times more potent toward AMAN-2 than DIM, their selectivity profiles were almost the same. N -Arylalkylation of 6-deoxy-DIM resulted only in a partial improvement as the selectivity was enhanced at the expense of potency. Structural and physicochemical properties of the corresponding inhibitor:enzyme complexes were analyzed by molecular modeling.
Synthesis, Characterization, Optical Properties, Molecular Modeling and Urease Inhibition Analysis of Organic Ligands and Their Metal Complexes
Recently, screening of efficient urease inhibitors by employing organic small molecules metalloderivatives interests the scientific community due to their efficacy for treatment of urease triggered health complications. This study comprises the synthesis, urease inhibition activity, optical analysis and molecular modeling of hydrazinecarbothioamide and hydrazinecarboxamide metalloderivatives. Characterization of synthesized materials was done by UV-visible, fluorescence, NMR and FTIR spectroscopic analysis. Metalloderivatization of ligands induce increment in urease inhibition potential and effect was prominent for copper complexes with 10-fold enhancement, cobalt complex with 3.5 fold’s enhancement and palladium with 2-fold increment in the inhibition efficacy toward urease when it was compared with reference urease inhibitor. Zinc and iron complexes cause declined urease inhibition activity of the bare ligand. The overall activity of hydrazinecarbothioamide slightly exceeds than that of hydrazinecarboxamide, possibly due to larger complexation ability of sulfur-based ligand in comparison to oxygenated derivatives i.e., hydrazinecarboxamide. The enzyme inhibition kinetics for the most active complexes represent the mixed type urease inhibition for 3a and competitive urease inhibition for 5a , as determined by Lineweaver–Burk plots. The docked scoring values for both the ligands were calculated to be 61.34, 64.72, 56.68, 62.94, 64.98 and 58.98. Three active hydrogen bonds were observed in docking complex upon computational analysis of most potent metallodrug 3a inside active region of targeted protein.
(+)-Usnic Acid and Its Derivatives as Inhibitors of a Wide Spectrum of SARS-CoV-2 Viruses
In order to test the antiviral activity, a series of usnic acid derivatives were synthesized, including new, previously undescribed compounds. The activity of the derivatives against three strains of SARS-CoV-2 virus was studied. To understand the mechanism of antiviral action, the inhibitory activity of the main protease of SARS-CoV-2 virus was studied using the developed model as well as the antiviral activity against the pseudoviral system with glycoprotein S of SARS-CoV-2 virus on its surface. It was shown that usnic acid exhibits activity against three strains of SARS-CoV-2 virus: Wuhan, Delta, and Omicron. Compounds 10 and 13 also showed high activity against the three strains. The performed biological studies and molecular modeling allowed us to assume that the derivatives of usnic acid bind in the N-terminal domain of the surface glycoprotein S at the binding site of the hemoglobin decay metabolite.