Evaluation of DFT methods for predicting geometries and NMR spectra of Bi(III) dithiocarbamate complexes with antitumor properties.

CONTEXT: Bismuth complexes with dithiocarbamate ligands have attracted attention because of their biological applications, such as antimicrobial, antileishmanial, and anticancer properties. These complexes have high cytotoxic activity against cancer cells, being more active than the standard drugs cisplatin, doxorubicin, and tamoxifen. In the present study, we investigated the ability of some DFT methods to reproduce the geometries and NMR spectra of the Bi(III) dithiocarbamate complexes, selected based on their proven antitumor activity. Our investigation revealed that the M06-L/def2-TZVP/ECP/CPCM method presented good accuracy in predicting geometries, while the TPSSh/def2-SVP/ECP/CPCM method proved effective in analyzing the 13C NMR spectra of these molecules. In general, all examined methods exhibited comparable performance in predicting 1H NMR signals. METHODS: Calculations were performed with the Gaussian 09 program using the def2-SVP and def2-TZVP basis sets, employing relativistic effective core potential (ECP) for Bi and using the CPCM solvent model. The exchange-correlation functionals BP86, PBE, OLYP, M06-L, B3LYP, B3LYP-D3, M06-2X, TPSSh, CAM-B3LYP, and ωB97XD were used in the study. Geometry optimizations were started from crystallographic structures available at the Cambridge Structural Database. The theoretical results were compared with experimental data using the mean root-mean-square deviation (RMSD), mean absolute deviations (MAD), and linear correlation coefficient (R2).

Antiviral Activity of Flavonoids from Geopropolis of the Brazilian Jandaira Bee against Zika and Dengue Viruses.

Arthropod-borne viruses within the Flaviviridae family such as Zika (ZIKV) and dengue (DENV) are responsible for major outbreaks in tropical countries, and there are no specific treatments against them. Naringenin and 7-O-methyl naringenin are flavonoids that can be extracted from geopropolis, a natural material that the Brazilian Jandaira stingless bee (Melipona subnitida Ducke) produces to protect its nest. Here, these flavonoids were tested against ZIKV and DENV using Vero cells as a cellular model to perform a cytotoxicity assay and to define the effective concentrations of TCID50 as the readout method. The results demonstrated the antiviral activity of the compounds against both viruses upon the treatment of infected cells. The tested flavonoids had antiviral activity comparable with 6-methylmercaptopurine riboside (6-MMPr), used here as a positive control. In addition, to identify the possible action mechanism of the antiviral candidates, we carried out a docking analysis followed by a molecular dynamics simulation to elucidate naringenin and 7-O-methyl naringenin binding sites to each virus. Altogether, these results demonstrate that both flavonoids have potent antiviral effects against both viruses and warrant further in vivo trials.

Investigation of the structural dynamics of a knotted protein and its unknotted analog using molecular dynamics.

The role of knots in proteins remains elusive. Some studies suggest an impact on stability; the difficulty in comparing systems to assess this effect, however, has been a significant challenge. In this study, we produced and analyzed molecular dynamic trajectories considering three different temperatures of two variants of ornithine transcarbamylase (OTC), only one of which has a 31 knot, in order to evaluate the relative stability of the two molecules. RMSD showed equilibrated structures for the produced trajectories, and RMSF showed subtle differences in flexibility. In the knot moiety, the knotted protein did not show a great deal of fluctuation at any temperature. For the unknotted protein, the residue GLY243 showed a high fluctuation in the corresponding moiety. The fraction of native contacts (Q) showed a similar profile at all temperatures, with the greatest decrease by 436 K. The investigation of conformational behavior with principal component analysis (PCA) and dynamic cross-correlation map (DCCM) showed that knotted protein is less likely to undergo changes in its conformation under the conditions employed compared to unknotted. PCA data showed that the unknotted protein had greater dispersion in its conformations, which suggests that it has a greater capacity for conformation transitions in response to thermal changes. DCCM graphs comparing the 310 K and 436 K temperatures showed that the knotted protein had less change in its correlation and anti-correlation movements, indicating stability compared to the unknotted.

Discovery of RTA ricin subunit inhibitors: a computational study using PM7 quantum chemical method and steered molecular dynamics.

Ricin is a potent toxin derived from the castor bean plant and comprises two subunits, RTA and RTB. Because of its cytotoxicity, ricin has alarmed world authorities for its potential use as a chemical weapon. Ricin also affects castor bean agribusiness, given the risk of animal and human poisoning. Over the years, many groups attempted to propose small-molecules that bind to the RTA active site, the catalytic chain. Despite such efforts, there is still no effective countermeasure against ricin poisoning. The computational study carried out in the present work renews the discussion about small-molecules that may inhibit this toxin. Here, a structure-based virtual screening protocol capable of discerning active RTA inhibitors from inactive ones was performed to screen over 2 million compounds from the ZINC database to find novel scaffolds that strongly bind into the active site of the RTA. Besides, a novel score method based on ligand undocking force profiles and semi-empirical quantum chemical calculations provided insights into the rescore of docking poses. Summing up, the filtering steps pointed out seven main compounds, with the SCF00-451 as a promising candidate to inhibit the killing activity of such potent phytotoxin.

Thermochemical and Quantum Descriptor Calculations for Gaining Insight into Ricin Toxin A (RTA) Inhibitors.

In this work, we performed a study to assess the interactions between the ricin toxin A (RTA) subunit of ricin and some of its inhibitors using modern semiempirical quantum chemistry and ONIOM quantum mechanics/molecular mechanics (QM/MM) methods. Two approaches were followed (calculation of binding enthalpies, ΔH bind, and reactivity quantum chemical descriptors) and compared with the respective half-maximal inhibitory concentration (IC50) experimental data, to gain insight into RTA inhibitors and verify which quantum chemical method would better describe RTA-ligand interactions. The geometries for all RTA-ligand complexes were obtained after running classical molecular dynamics simulations in aqueous media. We found that single-point energy calculations of ΔH bind with the PM6-DH+, PM6-D3H4, and PM7 semiempirical methods and ONIOM QM/MM presented a good correlation with the IC50 data. We also observed, however, that the correlation decreased significantly when we calculated ΔH bind after full-atom geometry optimization with all semiempirical methods. Based on the results from reactivity descriptors calculations for the cases studied, we noted that both types of interactions, molecular overlap and electrostatic interactions, play significant roles in the overall affinity of these ligands for the RTA binding pocket.

PRIMoRDiA: A Software to Explore Reactivity and Electronic Structure in Large Biomolecules.

Plenty of enzymes with structural data do not have their mechanism of catalysis elucidated. Reactivity descriptors, theoretical quantities generated from resolved electronic structure, provide a way to predict and rationalize chemical processes of such systems. In this Application Note, we present PRIMoRDiA (PRIMoRDiA Macromolecular Reactivity Descriptors Access), a software built to calculate the reactivity descriptors of large biosystems by employing an efficient and accurate treatment of the large output files produced by quantum chemistry packages. Here, we show the general implementation details and the software main features. Calculated descriptors were applied for a set of enzymatic systems in order to show their relevance for biological studies and the software potential for use in large scale. Also, we test PRIMoRDiA to aid in the interaction depiction between the SARS-CoV-2 main protease and a potential inhibitor.

Theoretical characterization of the shikimate 5-dehydrogenase reaction from Mycobacterium tuberculosis by hybrid QC/MM simulations and quantum chemical descriptors.

In this study, we have investigated the enzyme shikimate 5-dehydrogenase from the causative agent of tuberculosis, Mycobacterium tuberculosis. We have employed a mixture of computational techniques, including molecular dynamics, hybrid quantum chemical/molecular mechanical potentials, relaxed surface scans, quantum chemical descriptors and free-energy simulations, to elucidate the enzyme's reaction pathway. Overall, we find a two-step mechanism, with a single transition state, that proceeds by an energetically uphill hydride transfer, followed by an energetically downhill proton transfer. Our mechanism and calculated free energy barrier for the reaction, 64.9 kJ mol- 1, are in good agreement with those predicted from experiment. An analysis of quantum chemical descriptors along the reaction pathway indicated a possibly important, yet currently unreported, role of the active site threonine residue, Thr65.

GPU algorithms for density matrix methods on MOPAC: linear scaling electronic structure calculations for large molecular systems.

Purification of the density matrix methods should be employed when dealing with complex chemical systems containing many atoms. The running times for these methods scale linearly with the number of atoms if we consider the sparsity from the density matrix. Since the efficiency expected from those methods is closely tied to the underlying parallel implementations of the linear algebra operations (e.g., P2 = P × P), we proposed a central processing unit (CPU) and graphics processing unit (GPU) parallel matrix-matrix multiplication in SVBR (symmetrical variable block row) format for energy calculations through the SP2 algorithm. This algorithm was inserted in MOPAC's MOZYME method, using the original LMO Fock matrix assembly, and the atomic integral calculation implemented on it. Correctness and performance tests show that the implemented SP2 is accurate and fast, as the GPU is able to achieve speedups up to 40 times for a water cluster system with 42,312 orbitals running in one NVIDIA K40 GPU card compared to the single-threaded version. The GPU-accelerated SP2 algorithm using the MOZYME LMO framework enables the calculations of semiempirical wavefunction with stricter SCF criteria for localized charged molecular systems, as well as the single-point energies of molecules with more than 100.000 LMO orbitals in less than 1 h. Graphical abstract Parallel CPU and GPU purification algorithms for electronic structure calculations were implemented in MOPAC's MOZYME method. Some matrices in these calculations, e.g., electron density P, are compressed, and the developed linear algebra operations deal with non-zero entries only. We employed the NVIDIA/CUDA platform to develop GPU algorithms, and accelerations up to 40 times for larger systems were achieved.

Elucidating Enzymatic Catalysis Using Fast Quantum Chemical Descriptors.

In general, computational simulations of enzymatic catalysis processes are thermodynamic and structural surveys to complement experimental studies, requiring high level computational methods to match accurate energy values. In the present work, we propose the usage of reactivity descriptors, theoretical quantities calculated from the electronic structure, to characterize enzymatic catalysis outlining its reaction profile using low-level computational methods, such as semiempirical Hamiltonians. We simulate three enzymatic reactions paths, one containing two reaction coordinates and without prior computational study performed, and calculate the reactivity descriptors for all obtained structures. We observed that the active site local hardness does not change substantially, even more so for the amino-acid residues that are said to stabilize the reaction structures. This corroborates with the theory that activation energy lowering is caused by the electrostatic environment of the active sites. Also, for the quantities describing the atom electrophilicity and nucleophilicity, we observed abrupt changes along the reaction coordinates, which also shows the enzyme participation as a reactant in the catalyzed reaction. We expect that such electronic structure analysis allows the expedient proposition and/or prediction of new mechanisms, providing chemical characterization of the enzyme active sites, thus hastening the process of transforming the resolved protein three-dimensional structures in catalytic information.

Semiempirical methods do Fukui functions: Unlocking a modeling framework for biosystems.

Obtaining reactivity information from the molecular electronic structure of a chemical system is a computationally intensive process. As a way of probing reactivity information around that, there exist electron density response variables, such as the Fukui functions (FFs), which are well-established descriptors that summarize the local susceptibility to react. These properties only require few single-point quantum chemical calculations, but even then, the intrinsic high cost and unfavorable computational complexity with respect to the number of atoms in the system makes this approach available only to small fragments and systems. In this study, we explore the computation of FFs, showing that semiempirical quantum chemical methods can be used to obtain the reactivity information equivalent to that of a Density Functional Theory (DFT) functional, for the eight entire polypeptide chains. The combination of semiempirical methods with the frozen orbital approximation allows for the obtention of these reactivity descriptors for biological systems with reasonable accuracy and speed, unlocking the utilization of these methods for such systems. These results for the frozen orbital approximation can be additionally improved when other molecular orbitals from the frontier band are employed in the computation. We also show the potential of this computational protocol in the ligand-protein complexes of HIV-1 protease, predicting which of those ligands are active inhibitors.

Assessment of semiempirical enthalpy of formation in solution as an effective energy function to discriminate native-like structures in protein decoy sets.

In this work, we tested the PM6, PM6-DH+, PM6-D3, and PM7 enthalpies of formation in aqueous solution as scoring functions across 33 decoy sets to discriminate native structures or good models in a decoy set. In each set these semiempirical quantum chemistry methods were compared according to enthalpic and geometric criteria. Enthalpically, we compared the methods according to how much lower was the enthalpy of each native, when compared with the mean enthalpy of its set. Geometrically, we compared the methods according to the fraction of native contacts (Q), which is a measure of geometric closeness between an arbitrary structure and the native. For each set and method, the Q of the best decoy was compared with the Q0 , which is the Q of the decoy closest to the native in the set. It was shown that the PM7 method is able to assign larger energy differences between the native structure and the decoys in a set, arguably because of a better description of dispersion interactions, however PM6-DH+ was slightly better than the rest at selecting geometrically good models in the absence of a native structure in the set. © 2016 Wiley Periodicals, Inc.

A topological assessment of the electronic structure of mesoionic compounds.

Mesoionic compounds belonging to the 1,3-oxazol-5-one, 1,3-diazole-4-thione and 1,3-thiazole-5-thione rings have been evaluated by a combination of Density Functional Theory, Quantum Theory of Atoms in Molecules, Electron Localization Function, Natural Bond Orbitals and Geodesic Electrostatic Potential Charge calculations. Atomic, bond, and ring properties have been considered to describe the electronic structure of mesoionic compounds. The results show that not only the ring type, but also the substituent groups have great influence on these properties. In addition, there is a significant and heterogeneous π-bonding contribution throughout the mesoionic rings. Finally, we conclude that some classical conceptions of charge localization and π-bonding contribution in these compounds are misleading or incomplete. © 2015 Wiley Periodicals, Inc.