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Computational investigation of the radical-mediated mechanism of formation of difluoro methyl oxindoles: Elucidation of the reaction selectivity and yields
(2023-02-15)
Somnarin, Thanachon
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Krawmanee, Pacharaporn
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Gleeson, Matthew Paul
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Gleeson, Duangkamol
Oxindoles are an important class of heterocyclic alkaloids with demonstrated pharmacological activity at multiple biological targets. Preparation of new analogs through novel synthetic routes is therefore highly attractive. In this work, we report a computational study to investigate the synthesis of ethoxycarbonyldifluoromethylated oxindoles from N-arylmethacrylamides. The reaction tolerates a diverse range of acrylamides, shows yields ranging from approximately 38%–96%. We have applied density functional theory (DFT) to explore the reaction mechanism, kinetics and thermodynamics to gain further understanding. We demonstrate that a radical-based ring closure reaction is energetically more favorable than a heterolytic process, that the rate-determining step is the formation of the arylmethacrylamide radical, and that the product yields and selectivities are consistent with experiment. The results demonstrate that theoretical methods can prove useful to understand how such reaction and could be potentially employed to rapidly explore the reaction scope further.
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Theoretical studies to estimate the skin sensitization potential of chemicals of the Schiff base domain
(2020-06-15)
Gleeson, Duangkamol
;
Gleeson, Matthew Paul
Skin sensitization occurs when an exogenous chemical substance forms a covalent adduct with a dermal protein electrophile or nucleophile. This instigates an immune response which leads to inflammation. The local lymph node assay is an in vivo model used in the assessment of relative skin sensitizing potency of chemicals. The method is time consuming and expensive, as well as poses ethical questions given that a number of mice must be sacrificed for each compound assessed. In this work, we investigate the use of an inexpensive, rapid, and ethical method to predict the skin sensitization potential of Schiff base chemicals. We employ quantum chemical methods to rationalize the sensitization potential of 22 compounds with a diverse range of activities. To this end, we have evaluated the mechanistic profile associated with this type of reaction using gas-phase models. We subsequently use the predicted rate determining barriers and key physico-chemical parameters (such as logP) to establish stucture activity relationship (SAR) guidelines to predict the skin sensitization potential for new chemicals. We find that the predicted rate determining barriers for aldehydes, ketone, and 1,2 and 1,3 diones generally decrease in the given order, which concurs with the overall trends in sensitization. We find that lipophilicity also plays a role, with those chemicals displaying both low barriers to reaction, and lower lipophilicity (ie, diones), being more likely to display undesirable skin sensitization effects. These findings are in line with experiment-based observations in the literature and point to the value 3D quantum chemical calculations could have if combined with other orthogonal approaches to estimate skin sensitization potential of chemicals.
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Towards reproducible computational drug discovery
(2020-01-28)
Schaduangrat, Nalini
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Lampa, Samuel
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Simeon, Saw
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Gleeson, Matthew Paul
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Spjuth, Ola
The reproducibility of experiments has been a long standing impediment for further scientific progress. Computational methods have been instrumental in drug discovery efforts owing to its multifaceted utilization for data collection, pre-processing, analysis and inference. This article provides an in-depth coverage on the reproducibility of computational drug discovery. This review explores the following topics: (1) the current state-of-the-art on reproducible research, (2) research documentation (e.g. electronic laboratory notebook, Jupyter notebook, etc.), (3) science of reproducible research (i.e. comparison and contrast with related concepts as replicability, reusability and reliability), (4) model development in computational drug discovery, (5) computational issues on model development and deployment, (6) use case scenarios for streamlining the computational drug discovery protocol. In computational disciplines, it has become common practice to share data and programming codes used for numerical calculations as to not only facilitate reproducibility, but also to foster collaborations (i.e. to drive the project further by introducing new ideas, growing the data, augmenting the code, etc.). It is therefore inevitable that the field of computational drug design would adopt an open approach towards the collection, curation and sharing of data/code.
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Investigation of Factors Affecting the Performance of in silico Volume Distribution QSAR Models for Human, Rat, Mouse, Dog & Monkey
(2019-10-01)
Simeon, Saw
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Montanari, Dino
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Gleeson, Matthew Paul
Volume of distribution (Vd<inf>ss</inf>) is a measure of how effectively a drug molecule is distributed throughout the body. Along with the clearance, it determines the half-life and therefore the drug dosing interval. A number of different pre-clinical approaches are available to predict the Vd<inf>ss</inf> in human including quantitative structure activity relationship (QSAR) models. Vd<inf>ss</inf> QSAR models have been reported for human and rat, but not important pre-clinical species including dog, mouse and monkey. In this study, we have generated Vd<inf>ss</inf> QSAR model on the human and commonly used pre-clinical species, each of which differs in terms of size, chemical diversity and data quality. We discuss the model performance by species, assess the effect the domain of applicability and the relative merits of building chemical series-specific models. In addition, we compare the intrinsic variability of the experimental logVd<inf>ss</inf> data (∼1.2 fold error) to in-vivo interspecies differences (∼2 fold error) and in silico based models (∼3 fold error). This prompted us to explore whether one species could be used to predict another, particularly where little data for that species is available. i. e. does the expansion in domain of applicability prove beneficial over and above any deterioration due to the use of response values from an alternative species.
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In silico identification and in vitro validation of nogalamycin N-oxide (NSC116555) as a potent anticancer compound against non–small-cell lung cancer cells
(2019-03-01)
Obounchoey, Phongphat
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Tabtimmai, Lueacha
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Suphakun, Praphasri
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Thongkhao, Kannika
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Eurtivong, Chatchakorn
The epidermal growth factor receptor (EGFR) was found to be overexpressed in several cancers, especially in lung cancers. Finding new effective drug against EGFR is the key to cancer treatment. In this study, the GOLD docking algorithm was used to virtually screen for novel human EGFR inhibitors from the NCI database. Thirty-four hit compounds were tested for EGFR-tyrosine kinase (TK) inhibition. Two potent compounds, 1-amino-4-(4-[4-amino-2-sulfophenyl]anilino)-9,10-dioxoanthracene-2-sulfonic acid (NSC125910), and nogalamycin N-oxide (NSC116555) were identified with IC <inf>50</inf> values against EGFR-TK comparable to gefitinib; 16.14 and 37.71 nM, respectively. However, only NSC116555 demonstrated cytotoxic effects against non–small-cell lung cancer, A549, shown in the cell cytotoxicity assay with an IC <inf>50</inf> of 0.19 + 0.01 µM, which was more potent than gefitinib. Furthermore, NSC116555 showed cytotoxicity against A549 via apoptosis in a dose-dependent manner.
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Design, synthesis, and evaluation of the anticancer activity of 2-amino-aryl-7-aryl-benzoxazole compounds
(2017-11-01)
Khajondetchairit, Patcharaporn
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Phuangsawai, Oraphan
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Suphakun, Praphasri
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Rattanabunyong, Siriruk
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Choowongkomon, Kiattawee
A series of 2-amino-aryl-7-aryl-benzoxazole derivatives have been designed, synthesized, and evaluated as anticancer agents. Fourteen of the compounds exhibited cytotoxic effects toward human A549 lung cancer cells. We found 12l was the most potent with an EC<inf>50</inf> of 0.4 μm, equivalent to the anticancer drug doxorubicin, but had low selectivity following cross screening in monkey kidney Vero cells. Eight of the most potent or most selective compounds were further profiled in additional cell lines (MCF7, NCI-H187, and KB) to better understand their cytotoxic activity. Only compound 12l had a measurable EC<inf>50</inf> in a single cell line (3.3 μm in the KB cell line). Taken together, this data suggest the series as a whole display specific cytotoxicity toward A549 cells. Cheminformatics searches pointed to JAK2 as a possible target. A subset of compounds assayed at this target showed IC<inf>50</inf>s ranging from 10 to 0.08 μm; however, no clear correlation between JAK2 potency and A549 cytotoxicity was observed.
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Probing the structural and electronic factors affecting the adsorption and reactivity of alkenes in acidic zeolites using DFT calculations and multivariate statistical methods
(2005-01-01)
Tantanak, Duangkamol
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Limtrakul, Jumras
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Gleeson, Matthew Paul
Quantum mechanical (QM) cluster calculations have been performed on a model of ZSM-5 at DFT and MP2 levels. We investigated how the adsorption energies and the energetics of alkoxide intermediate formation of six different alkene substrates, ethene, propene, 1-butene, cis/trans butene, and isobutene, vary in this zeolite model. An analysis of the DFT geometric, electronic, and energetic parameters of the zeolite-substrate complexes, transition states, and alkoxide intermediates is performed using principal components analysis (PCA) and partial least squares (PLS). These deliver an insight into the correlated changes that occur between molecular structure and energy along the reaction coordinate between the physisorbed and chemisorbed species within the zeolite. To the best of our knowledge, this is the first occasion multivariate techniques such as PCA or PLS have been employed to profile the changes in electronics, distances, and angles in QM calculations of catalytic systems such as zeolites. We find the calculated adsorption and the alkoxide intermediate energies correlate strongly with the absolute charge on the substrate and the length of the substrate double bond. The transition states' energies are not affected by the zeolite framework as modeled, which explains why they correlate strongly with the gas-phase substrate protonation energy. Our cluster results show that for ethene, propene, 1-butene, and isobutene, the relative energetics associated with the formation of the alkoxide intermediate in ZSM-5 follow the same trends as calculations where the effects of the framework are included. © 2005 American Chemical Society.

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