Quantum mechanical simulation
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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 a lack of experimental electron ionization high-resolution mass spectra available to assist compound identification. The in silico generation of mass spectra by quantum chemistry can aid annotation workflows, in particular to support the identification of compounds that lack experimental reference spectra, such as environmental chemicals. We present an open-source, semiautomated workflow for the in silico prediction of electron ionization high-resolution mass spectra at 70 eV based on the QCxMS software. The workflow was applied to predict the spectra of 367 environmental chemicals, and the accuracy was evaluated by comparison to experimental reference spectra acquired. The molecular flexibility, number of rotatable bonds, and number of electronegative atoms of a compound were negatively correlated with prediction accuracy. Few analytes are predicted to sufficient accuracy for the direct application of predicted spectra in spectral matching workflows (overall average score 428). The m/z values of the top 5 most abundant ions of predicted spectra rarely match ions in experimental spectra, evidencing the disconnect between simulated fragmentation pathways and empirical reaction mechanisms.
- Publikační typ
- časopisecké články MeSH
CONTEXT: Chlordecone (CLD) and β-hexachlorocyclohexane (β-HCH) are chlorinated pesticides that coexist as persistent organic pollutants in the groundwater of several countries in the Caribbean, being an environmental issue. This work evaluates theoretically the competitive formation of host-guest complexes pesticides@cyclodextrines (CDs) as an alternative for water purification and selective separation of pesticides. METHODS: Quantum mechanical calculations based on density functional theory (DFT) and classical molecular dynamics (MD) simulations were used to achieve information on geometries, energies, structure, and dynamics of guest-host complexes in the gas phase, implicit solvent medium, and in aqueous solutions. RESULTS: DFT studies showed that interactions of both pesticides with CDs are mediated by steric factors and guided by maximization of the hydrophobic interactions either with the other pesticide or with the CD cavity's inner atoms. MD results corroborate the formation of stable complexes of both pesticides with the studied CDs. α-CD exhibited a preference for the smaller β-HCH molecule over the CLD that could not perturb the formed complex. CONCLUSIONS: The simulation of competitive formation with γ-CD illustrated that this molecule could accommodate both pesticides inside its cavity. These results suggest that CDs with smaller cavity sizes such as α-CD could be used for selective separation of β-HCH from CLD in water bodies, while γ-CD could be used for methods that aim to remove both pesticides at the same time.
- Publikační typ
- časopisecké články MeSH
PURPOSE: While the recommended analysis method for magnetic resonance spectroscopy data is linear combination model (LCM) fitting, the supervised deep learning (DL) approach for quantification of MR spectroscopy (MRS) and MR spectroscopic imaging (MRSI) data recently showed encouraging results; however, supervised learning requires ground truth fitted spectra, which is not practical. Moreover, this work investigates the feasibility and efficiency of the LCM-based self-supervised DL method for the analysis of MRS data. METHOD: We present a novel DL-based method for the quantification of relative metabolite concentrations, using quantum-mechanics simulated metabolite responses and neural networks. We trained, validated, and evaluated the proposed networks with simulated and publicly accessible in-vivo human brain MRS data and compared the performance with traditional methods. A novel adaptive macromolecule fitting algorithm is included. We investigated the performance of the proposed methods in a Monte Carlo (MC) study. RESULT: The validation using low-SNR simulated data demonstrated that the proposed methods could perform quantification comparably to other methods. The applicability of the proposed method for the quantification of in-vivo MRS data was demonstrated. Our proposed networks have the potential to reduce computation time significantly. CONCLUSION: The proposed model-constrained deep neural networks trained in a self-supervised manner can offer fast and efficient quantification of MRS and MRSI data. Our proposed method has the potential to facilitate clinical practice by enabling faster processing of large datasets such as high-resolution MRSI datasets, which may have thousands of spectra.
- MeSH
- deep learning * MeSH
- lidé MeSH
- magnetická rezonanční spektroskopie MeSH
- magnetická rezonanční tomografie metody MeSH
- mozek diagnostické zobrazování metabolismus MeSH
- neuronové sítě MeSH
- počítačové zpracování obrazu metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Guanine radical cation (G•+) is a key intermediate in many oxidative processes occurring in nucleic acids. Here, by combining mixed Quantum Mechanical/Molecular Mechanics calculations and Molecular Dynamics (MD) simulations, we study how the structural behaviour of a tract GGG(TTAGGG)3 (hereafter Tel21) of the human telomeric sequence, folded in an antiparallel quadruple helix, changes when one of the G bases is ionized to G•+ (Tel21+). Once assessed that the electron-hole is localized on a single G, we perform MD simulations of twelve Tel21+ systems, differing in the position of G•+ in the sequence. When G•+ is located in the tetrad adjacent to the diagonal loop, we observe substantial structural rearrangements, which can decrease the electrostatic repulsion with the inner Na+ ions and increase the solvent exposed surface of G•+. Analysis of solvation patterns of G•+ provides new insights on the main reactions of G•+, i.e. the deprotonation at two different sites and hydration at the C8 atom, the first steps of the processes producing 8oxo-Guanine. We suggest the main structural determinants of the relative reactivity of each position and our conclusions, consistent with the available experimental trends, can help rationalizing the reactivity of other G-quadruplex topologies.
- MeSH
- DNA chemie MeSH
- G-kvadruplexy * MeSH
- guanin chemie MeSH
- ionty chemie MeSH
- konformace nukleové kyseliny MeSH
- kvantová teorie * MeSH
- lidé MeSH
- molekulární modely MeSH
- oxidační stres * MeSH
- rozpustnost MeSH
- simulace molekulární dynamiky * MeSH
- telomery chemie MeSH
- Check Tag
- lidé 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.
Ischemia reperfusion injury is a complex process consisting of a seemingly chaotic but actually organized and compartmentalized shutdown of cell function, of which oxidative stress is a key component. Studying oxidative stress, which results in an imbalance between reactive oxygen species (ROS) production and antioxidant defense activity, is a multi-faceted issue, particularly considering the double function of ROS, assuming roles as physiological intracellular signals and as mediators of cellular component damage. Herein, we propose a comprehensive overview of the tools available to explore oxidative stress, particularly in the study of ischemia reperfusion. Applying chemistry as well as biology, we present the different models currently developed to study oxidative stress, spanning the vitro and the silico, discussing the advantages and the drawbacks of each set-up, including the issues relating to the use of in vitro hypoxia as a surrogate for ischemia. Having identified the limitations of historical models, we shall study new paradigms, including the use of stem cell-derived organoids, as a bridge between the in vitro and the in vivo comprising 3D intercellular interactions in vivo and versatile pathway investigations in vitro. We shall conclude this review by distancing ourselves from "wet" biology and reviewing the in silico, computer-based, mathematical modeling, and numerical simulation options: (a) molecular modeling with quantum chemistry and molecular dynamic algorithms, which facilitates the study of molecule-to-molecule interactions, and the integration of a compound in a dynamic environment (the plasma membrane...); (b) integrative systemic models, which can include many facets of complex mechanisms such as oxidative stress or ischemia reperfusion and help to formulate integrated predictions and to enhance understanding of dynamic interaction between pathways.
Poisoning with organophosphorus compounds used as pesticides or misused as chemical weapons remains a serious threat to human health and life. Their toxic effects result from irreversible blockade of the enzymes acetylcholinesterase and butyrylcholinesterase, which causes overstimulation of the cholinergic system and often leads to serious injury or death. Treatment of organophosphorus poisoning involves, among other strategies, the administration of oxime compounds. Oximes reactivate cholinesterases by breaking the covalent bond between the serine residue from the enzyme active site and the phosphorus atom of the organophosphorus compound. Although the general mechanism of reactivation has been known for years, the exact molecular aspects determining the efficiency and selectivity of individual oximes are still not clear. This hinders the development of new active compounds. In our research, using relatively simple and widely available molecular docking methods, we investigated the reactivation of acetyl- and butyrylcholinesterase blocked by sarin and tabun. For the selected oximes, their binding modes at each step of the reactivation process were identified. Amino acids essential for effective reactivation and those responsible for the selectivity of individual oximes against inhibited acetyl- and butyrylcholinesterase were identified. This research broadens the knowledge about cholinesterase reactivation and demonstrates the usefulness of molecular docking in the study of this process. The presented observations and methods can be used in the future to support the search for new effective reactivators.
- MeSH
- acetylcholinesterasa metabolismus MeSH
- aktivace enzymů MeSH
- butyrylcholinesterasa metabolismus MeSH
- cholinesterasové inhibitory farmakologie MeSH
- fosfor chemie MeSH
- katalytická doména MeSH
- konformace proteinů MeSH
- kvantová teorie MeSH
- lidé MeSH
- ligandy MeSH
- molekulární modely MeSH
- myši MeSH
- organofosfáty chemie MeSH
- oximy chemie MeSH
- proteosyntéza MeSH
- reaktivátory cholinesterasy farmakologie MeSH
- sarin chemie MeSH
- shluková analýza MeSH
- simulace molekulového dockingu * MeSH
- vazba proteinů MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- myši MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
The fluorescent molecule diphenylhexatriene (DPH) has been often used in combination with fluorescence anisotropy measurements, yet little is known regarding the non-linear optical properties. In the current work, we focus on them and extend the application to fluorescence, while paying attention to the conformational versatility of DPH when it is embedded in different membrane phases. Extensive hybrid quantum mechanics/molecular mechanics calculations were performed to investigate the influence of the phase- and temperature-dependent lipid environment on the probe. Already, the transition dipole moments and one-photon absorption spectra obtained in the liquid ordered mixture of sphingomyelin (SM)-cholesterol (Chol) (2:1) differ largely from the ones calculated in the liquid disordered DOPC and solid gel DPPC membranes. Throughout the work, the molecular conformation in SM:Chol is found to differ from the other environments. The two-photon absorption spectra and the ones obtained by hyper-Rayleigh scattering depend strongly on the environment. Finally, a stringent comparison of the fluorescence anisotropy decay and the fluorescence lifetime confirm the use of DPH to gain information upon the surrounding lipids and lipid phases. DPH might thus open the possibility to detect and analyze different biological environments based on its absorption and emission properties.
- MeSH
- cholesterol chemie MeSH
- difenylhexatrien chemie MeSH
- fluorescenční barviva chemie MeSH
- fluorescenční polarizace MeSH
- lipidové dvojvrstvy chemie MeSH
- molekulární konformace MeSH
- sfingomyeliny chemie MeSH
- simulace molekulární dynamiky MeSH
- tranzitní teplota MeSH
- vztahy mezi strukturou a aktivitou MeSH
- změna skupenství MeSH
- Publikační typ
- časopisecké články MeSH
Halogenated phenols, such as 2,4-dichlorophenol (2,4-DCP) and 4-bromophenol (4-BP) are pollutants generated by a various industrial sectors like chemical, dye, paper bleaching, pharmaceuticals or in an agriculture as pesticides. The use of Horseradish peroxidase (HRP) in the halogenated phenols treatment has already been mentioned, but it is not well understood how the different phenolic substrates can bind in the peroxidase active site nor how these specific interactions can influence in the bioremediation potential. In this work, different removal efficiencies were obtained for phenolic compounds investigated using HRP as catalyst (93.87 and 59.19% to 4BP and 2,4 DCP, respectively). Thus, to rationalize this result based on the interactions of phenols with active center of HRP, we combine computational and experimental methodologies. The theoretical approaches utilized include density functional theory (DFT) calculations, docking simulation and quantum mechanics/molecular mechanics (QM/MM) technique. Michaelis Menten constant (Km) obtained through experimental methodologies were 2.3 and 0.95 mM to 2,4-DCP and 4-BP, respectively, while the specificity constant (Kcat/Km) found was 1.44 mM-1 s-1 and 0.62 mM-1 s-1 for 4-BP and 2,4-DCP, respectively. The experimental parameters appointed to the highest affinity of HRP to 4-BP. According to the molecular docking calculations, both ligands have shown stabilizing intermolecular interaction energies within the HRP active site, however, the 4-BP showed more stabilizing interaction energy (-53.00 kcal mol-1) than 2,4-dichlorophenol (-49.23 kcal mol-1). Besides that, oxidative mechanism of 4-BP and 2,4-DCP was investigated by the hybrid QM/MM approach. This study showed that the lowest activation energy values for transition states investigated were obtained for 4-BP. Therefore, by theoretical approach, the compound 4-BP showed the more stabilizing interaction and activation energy values related to the interaction within the enzyme and the oxidative reaction mechanism, respectively, which corroborates with experimental parameters obtained. The combination between experimental and theoretical approaches was essential to understand how the degradation potential of the HRP enzyme depends on the interactions between substrate and the active center cavity of the enzyme.
