In silico Evaluation of Cucurbit[6]uril as a Potential Detector for Cocaine and Its Adulterants Lidocaine, Caffeine, and Procaine

Illicit drugs and their trafficking require worldwide efforts in investigation, detection, and control. Colorimetric tests are often applied to identify drugs. Cocaine has some well-known adulterants that can provide a false positive response. Cucurbit[6]uril (CB[6]) has been suggested as a potential detector for cocaine and other illicit drugs. This work uses in silico methods to evaluate the use of CB[6] to detect cocaine and these interfering substances. More specifically, this work analyzes different possibilities of CB[6] complexation with cocaine, lidocaine, caffeine, and procaine and compares the results achieved for cocaine and its adulterants. Different methodologies were employed: quantum chemistry was investigated through DFT B3LYP/TZVP (density functional theory-Becke, three-parameter, Lee-Yang-Parr with triple zeta valence plus polarization basis set) and the semi-empirical methods Austin model 1 (AM1), parametric methods 3, 6, and 7 (PM3, PM6, PM7), and Recife model 1 (RM1). We used these methodologies intending to compare the reasonability and reproducibility of the results in the gas phase condition. Solvent influence was studied by molecular dynamics (MD) simulations. Results showed that CB[6] does not bind to these substances, as judged from the positive values of binding free energy obtained with all methods. DFT and MD were the most reliable methods whereas semiempirical ones were not reproductible in describing these systems. Results also showed that interactions are not specific, so CB[6] does not provide a good response for cocaine detection.

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In-silico Molecular Docking and ADME/Pharmacokinetic Prediction Studies of Some Novel Carboxamide Derivatives as Anti-tubercular Agents

Chemistry Africa ◽

10.1007/s42250-020-00162-3 ◽

2020 ◽

Vol 3 (4) ◽

pp. 989-1000

Author(s):

Mustapha Abdullahi ◽

Shola Elijah Adeniji

Keyword(s):

Molecular Docking ◽

Binding Affinity ◽

In Silico ◽

Density Functional ◽

Docking Simulation ◽

Basis Set ◽

Hybrid Functional ◽

Standard Drug

AbstractMolecular docking simulation of thirty-five (35) molecules of N-(2-phenoxy)ethyl imidazo[1,2-a]pyridine-3-carboxamide (IPA) with Mycobacterium tuberculosis target (DNA gyrase) was carried out so as to evaluate their theoretical binding affinities. The chemical structure of the molecules was accurately drawn using ChemDraw Ultra software, then optimized at density functional theory (DFT) using Becke’s three-parameter Lee–Yang–Parr hybrid functional (B3LYP/6-311**) basis set in a vacuum of Spartan 14 software. Subsequently, the docking operation was carried out using PyRx virtual screening software. Molecule 35 (M35) with the highest binding affinity of − 7.2 kcal/mol was selected as the lead molecule for structural modification which led to the development of four (4) newly hypothetical molecules D1, D2, D3 and D4. In addition, the D4 molecule with the highest binding affinity value of − 9.4 kcal/mol formed more H-bond interactions signifying better orientation of the ligand in the binding site compared to M35 and isoniazid standard drug. In-silico ADME and drug-likeness prediction of the molecules showed good pharmacokinetic properties having high gastrointestinal absorption, orally bioavailable, and less toxic. The outcome of the present research strengthens the relevance of these compounds as promising lead candidates for the treatment of multidrug-resistant tuberculosis which could help the medicinal chemists and pharmaceutical professionals in further designing and synthesis of more potent drug candidates. Moreover, the research also encouraged the in vivo and in vitro evaluation study for the proposed designed compounds to validate the computational findings.

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A Combined Experimental and Theoretical Study on the Reaction Mechanism and Molecular Structure of 4-(Diphenylamino)-3-iodo-2(5H)-furanone

Australian Journal of Chemistry ◽

10.1071/ch16616 ◽

2017 ◽

Vol 70 (7) ◽

pp. 837

Author(s):

Xiumei Song ◽

Fuling Xue ◽

Zongcai Feng ◽

Yun Wang ◽

Zhaoyang Wang ◽

...

Keyword(s):

Molecular Structure ◽

Density Functional ◽

Reaction Pathway ◽

Theoretical Calculations ◽

Calculation Model ◽

Basis Set ◽

Functional Theory ◽

Evaporation Technique ◽

Molecular Structure Analysis ◽

Semi Empirical

The simultaneous α-iodination and Nβ-arylation mechanism of 5-alkyloxy-4-phenylamino-2(5H)-furanone by (diacetoxyiodo)benzene was investigated by means of density functional theory (DFT) with B3LYP/6-31G*//LANL2DZ, selecting 4-(diphenylamino)-5-methyloxy-3-iodo-2(5H)-furanone as the calculation model. In addition, the effect of solvent on the reaction pathway was investigated using the Polarisable Continuum Model (PCM). Good agreement was found between the computational and the experimental results. Furthermore, single crystals of 4-(diphenylamino)-5-ethoxy-3-iodo-2(5H)-furanone were grown by slow evaporation technique. The molecular structure analysis was performed by single crystal X-ray analysis and theoretical calculations using a semi-empirical quantum chemical method and DFT/B3LYP methods with a LANL2DZ as basis set.

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Computer-Based Approaches for Determining the Pharmacological Profile of 5-(3-Nitro-Arylidene)-Thiazolidine-2,4-Dione

Biointerface Research in Applied Chemistry ◽

10.33263/briac116.1380613828 ◽

2021 ◽

Vol 11 (6) ◽

pp. 13806-13828

Keyword(s):

Molecular Docking ◽

In Silico ◽

Density Functional ◽

Biological Activities ◽

Computational Approach ◽

Basis Set ◽

Pharmacological Profile ◽

Dft Methods ◽

Starting Point ◽

In Silico Studies

The development of novel and safe compounds is a challenging task in the drug discovery trajectory. Accordingly, the individuation of promising core molecules with biological activities could pave the way to develop effective drugs to treat a given disease. The use of a computational approach can reduce the time for identifying promising core molecules characterizing their potential pharmacological profile and providing hints for the synthesis of novel derivatives with increased predicted pharmacological activity. Following this strategy, starting from a core molecule thiazolidine-2,4-dione, the derivative of 5-(3-nitro-arylidene)-thiazolidine-2,4-dione was synthesized to investigate the biological and pharmacological potential. An extensive computational investigation was performed employing ab initio calculations by using Density Functional Theory (DFT), and subsequent in silico studies were accomplished by molecular docking calculation. The structures 5-(3-nitro-arylidene)-thiazolidine-2,4-dione were fully optimized using multiparametric DFT methods were calculated at the B3LYP/6-31+G (d, p) level basis set. Besides gaining insights into the potential pharmacological profile of the selected derivative, molecular docking against some selected drug targets, ADME, and PASS prediction were performed. According to charges and molecular electrostatic potential (MESP) calculation, the N-H region could offer promising active site interactions for protein binding. Furthermore, Homo-Lumo and global reactivity values indicate a good profile for the selected compound, and UV-Vis provides further insights about its properties, potentially helpful for further experimental analysis. Notably, the in silico investigation indicated that EGFR and ORF2 enzymes could represent the selected drug-like compound's possible targets. Conclusively, the proposed computational approach demonstrated that it is possible to evaluate a proposed compound's bioactivity profile. We characterized 5-(3-nitro-arylidene)-thiazolidine-2,4-dione derivative, suggesting it as a good starting point for developing interesting hit compounds with a relevant pharmacological profile.

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Understanding the Role of R266K Mutation in Cystathionine β-Synthase (CBS) Enzyme: An in Silico Study

10.26434/chemrxiv.13567349 ◽

2021 ◽

Author(s):

Aashish Bhatt ◽

Md. Ehesan Ali

Keyword(s):

Hydrogen Bonding ◽

In Silico ◽

Density Functional ◽

Experimental Studies ◽

Salt Bridge ◽

Md Simulations ◽

Enzymatic Activities ◽

Wild Type ◽

Long Distance

<div>Human cystathionine β-synthase (hCBS) is a unique pyridoxal 5’-phosphate (PLP) dependent enzyme that catalyses the condensation reactions in the transsulfuration pathways. The specific role of Heme in the enzymatic activities has not yet been established, however, several experimental studies indicated the bi-directional communications between the Heme and PLP. Performing classical molecular dynamics (MD) simulations upon developing the necessary force field parameters for the cysteine and histidine bound hexa-coordinated Heme, we have investigated In Silico dynamical aspects of the bi-directional communications. Furthermore, we have investigated the comparative aspects of electron density overlap across the communicating pathways adopting the density functional theory (DFT) in conjunction with the hybrid exchange correlation functional for the CSBWT (wild-type) and CBSR266K (mutated) case. The atomistic dynamical simulations and subsequent explorations of the electronic structure not only confirm the reported observations but provide an in-depth mechanistic understating of how the non-covalent hydrogen bonding interactions with Cys52 control the such long-distance communication. Our study also provides a convincing answer to the reduced enzymatic activities in the R266K hCBS in comparison to the wild-type enzymes. We further realized that the difference in hydrogen-bonding patterns as well as salt-bridge interactions play the pivotal role in such long distant bi-directional communications.</div>

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Key Interacting Residues Between RBD of SARS-CoV-2 and ACE2 Receptor: Combination of Molecular Dynamic Simulation and Density Functional Calculation

10.26434/chemrxiv.14582484.v1 ◽

2021 ◽

Author(s):

Bahaa Jawad ◽

Puja Adhikari ◽

Rudolf Podgornik ◽

Wai-Yim Ching

Keyword(s):

Density Functional ◽

Vaccine Development ◽

Hydrophobic Interactions ◽

Binding Free Energy ◽

Tight Binding ◽

Md Simulations ◽

Functional Theory ◽

Generalized Born ◽

The Density Functional Theory ◽

Key Residues

The spike protein of SARS-CoV-2 binds to ACE2 receptor via its receptor-binding domain (RBD), with the RBD-ACE2 complex presenting an essential molecular target for vaccine development to stall the virus infection proliferation. The computational analysis at molecular, amino acid (AA) and atomic levels have been performed systematically to identify the key interacting AAs in the formation of the RBD-ACE2 complex, including the MD simulations with molecular mechanics generalized Born surface area (MM-GBSA) method to predict binding free energy (BFE) and to determine the actual interacting AAs, as well as two ab initio quantum chemical protocols based on the density functional theory (DFT) implementation. Based on MD results, Q493, Y505, Q498, N501, T500, N487, Y449, F486, K417, Y489, F456, Y495, and L455 have been identified as hotspots in RBD, while those in ACE2 are K353, K31, D30, D355, H34, D38, Q24, T27, Y83, Y41, E35, and E37. Both the electrostatic and hydrophobic interactions are the main driving force to form the AA-AA binding pairs. We confirm that Q493, N501, F486, K417, and F456 in RBD are the key residues responsible for the tight binding of SARS-CoV-2 with ACE2 compared to SARS-CoV. The DFT results reveal that N487, Q493, Y449, T500, G496, G446 and G502 in RBD form pairs via specific hydrogen bonding with Q24, H34, E35, D38, Y41, Q42 and K353 in ACE2.

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Identification of promising drug candidates against Non-Structural Protein 15 (NSP15) from SARS-CoV-2: an in silico assisted drug-repurposing studies

10.26434/chemrxiv.12407711 ◽

2020 ◽

Author(s):

Rameez Jabeer Khan ◽

Rajat Kumar Jha ◽

Ekampreet Singh ◽

Monika Jain ◽

Gizachew Muluneh Amera ◽

...

Keyword(s):

Free Energy ◽

In Silico ◽

Binding Free Energy ◽

Drug Repurposing ◽

Md Simulations ◽

Therapeutic Agents ◽

Global Dynamics ◽

Host Immune System ◽

Structural Protein ◽

Drug Candidates

<div>The recent COVID-19 pandemic caused by SARS-CoV-2 has recorded a high number of infected people across the globe. The notorious nature of the virus makes it necessary for us to identify promising therapeutic agents in a time-sensitive manner. The current study utilises an in silico based drug repurposing approach to identify potential drug candidates targeting non-structural protein 15 (NSP15), i.e. a uridylate specific endoribonuclease of SARS-CoV-2</div><div>which plays an indispensable role in RNA processing and viral immune evasion from the host immune system. NSP15 was screened against an in-house library of 123 antiviral drugs obtained from the DrugBank database from which three promising drug candidates were identified based on their estimated free energy of binding (ΔG), estimated inhibition constant (Ki), the orientation of drug molecules in the active site and the key interacting residues of</div><div>NSP15. The MD simulations were performed for the selected NSP15-drug complexes along with free protein to mimic on their physiological state. The binding free energies of the selected NSP15-drug complexes were also calculated using the trajectories of MD simulations of NSP15-drug complexes through MM/PBSA (Molecular Mechanics with Poisson-Boltzmann and surface area solvation) approach where NSP15-Simeprevir (-242.559 kJ/mol) and NSP15-Paritaprevir (-149.557 kJ/mol) exhibited the strongest binding affinities. Together with the results of molecular docking, global dynamics, essential dynamics and binding free energy analysis, we propose that Simeprevir and Paritaprevir are promising drug candidates for the inhibition of NSP15 and could act as potential therapeutic agents against SARS-CoV-2.</div>

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Comparing Study of The Stability and spectral properties vibrations for some Tellurium (IV) compounds containing cycloctadienyl group by Quantum Mechanical Calculations

Baghdad Science Journal ◽

10.21123/bsj.10.3.1041-1049 ◽

2013 ◽

Vol 10 (3) ◽

pp. 1041-1049

Author(s):

Baghdad Science Journal

Keyword(s):

Density Functional ◽

Heat Of Formation ◽

Basis Set ◽

Orbital Energy ◽

Empirical Methods ◽

Geometrical Structures ◽

Functional Theory ◽

Exchange Correlation ◽

The Stability ◽

Semi Empirical

Density Functional Theory (DFT) with B3LYP hybrid exchange-correlation functional and 3-21G basis set and semi-empirical methods (PM3) were used to calculate the energies (total energy, binding energy (Eb), molecular orbital energy (EHOMO-ELUMO), heat of formation (?Hf)) and vibrational spectra for some Tellurium (IV) compounds containing cycloctadienyl group which can use as ligands with some transition metals or essential metals of periodic table at optimized geometrical structures.

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In-silico Design of Aryl and Aralkyl Amine-Based Triazolopyrimidine Derivatives with Enhanced Activity Against Resistant Plasmodium falciparum

Chemistry Africa ◽

10.1007/s42250-020-00199-4 ◽

2020 ◽

Author(s):

Zakari Ya’u Ibrahim ◽

Adamu Uzairu ◽

Gideon Shallangwa ◽

Stephen Abechi

Keyword(s):

In Silico ◽

Density Functional ◽

Antimalarial Activity ◽

Qsar Model ◽

Quantitative Structure Activity Relationship ◽

Randomization Test ◽

Basis Set ◽

Coefficient Of Determination ◽

Statistical Parameters ◽

Leave One Out

Abstract A blend of genetic algorithm with multiple linear regression (GA-MLR) method was utilized in generating a quantitative structure–activity relationship (QSAR) model on the antimalarial activity of aryl and aralkyl amine-based triazolopyrimidine derivatives. The structures of derivatives were optimized using density functional theory (DFT) DFT/B3LYP/6–31 + G* basis set to generate their molecular descriptors, where two (2) predictive models were developed with the aid of these descriptors. The model with an excellent statistical parameters; high coefficient of determination (R2) = 0.8884, cross-validated R2 (Q2cv) = 0.8317 and highest external validated R2 (R2pred) = 0.7019 was selected as the best model. The model generated was validated through internal (leave-one-out (LOO) cross-validation), external test set, and Y-randomization test. These parameters are indicators of robustness, excellent prediction, and validity of the selected model. The most relevant descriptor to the antimalarial activity in the model was found to be GATS6p (Geary autocorrelation—lag 6/weighted by polarizabilities), in the model due to its highest mean effect. The descriptor (GATS6p) was significant in the in-silico design of sixteen (16) derivatives of aryl and aralkyl amine-based triazolopyrimidine adopting compound DSM191 with the highest activity (pEC50 = 7.1805) as the design template. The design compound D8 was found to be the most active compound due to its superior hypothetical activity (pEC50 = 8.9545).

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Key Interacting Residues Between RBD of SARS-CoV-2 and ACE2 Receptor: Combination of Molecular Dynamic Simulation and Density Functional Calculation

10.26434/chemrxiv.14582484 ◽

2021 ◽

Author(s):

Bahaa Jawad ◽

Puja Adhikari ◽

Rudolf Podgornik ◽

Wai-Yim Ching

Keyword(s):

Density Functional ◽

Vaccine Development ◽

Hydrophobic Interactions ◽

Binding Free Energy ◽

Tight Binding ◽

Md Simulations ◽

Functional Theory ◽

Generalized Born ◽

The Density Functional Theory ◽

Key Residues

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Quantum Chemical Methods for Modeling Covalent Modification of Biological Thiols

10.26434/chemrxiv.8061845.v1 ◽

2019 ◽

Author(s):

Ernest Awoonor-Williams ◽

William Isley ◽

Stephen Dale ◽

Erin Johnson ◽

Haibo Yu ◽

...

Keyword(s):

Density Functional ◽

Functional Performance ◽

Low Cost ◽

Md Simulations ◽

Potential Of Mean Force ◽

Covalent Modification ◽

Dft Methods ◽

Aqueous Solvent ◽

Exact Exchange ◽

Semi Empirical

Targeted covalent inhibitor drugs require computational methods that go beyond simple molecular-mechanical force fields in order to model the chemical reactions that occur when they bind to their targets. Here, several semi-empirical and density-functional theory (DFT) methods are assessed for their ability to describe the potential energy surface and reaction energies of the covalent modification of a thiol by an electrophile. Functionals such as PBE and B3LYP fail to predict a stable enolate intermediate. This is largely due to delocalization error, which spuriously stabilizes the pre-reaction complex, in which excess electron density is transferred from the thiolate to the electrophile. Functionals with a high-exact exchange component, range-separated DFT functionals, and variationally-optimized exact exchange (i.e., the LC-B05minV functional) correct this issue to various degrees. The large gradient behaviour of the exchange enhancement factor is also found to significantly affect the results, leading to the improved performance of PBE0. While ωB97X-D and M06-2X were easonably accurate, no method provided quantitative accuracy for all three electrophiles, making this a very strenuous test of functional performance. Additionally, one drawback of M06-2X was that MD simulations using this functional were only stable if a fine integration grid was used. The low-cost semi-empirical methods, PM3, AM1, and PM7, provide a qualitatively correct description of the reaction mechanism, although the energetics are not quantitatively reliable. As a proof of concept, the potential of mean force for the addition of methylthiolate to MVK was calculated using QM/MM MD in an explicit polarizable aqueous solvent.

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