Relationships between Cellular Toxicity, the Maximum Tolerated Dose, Lipophilicity and Electrophilicity

1992 ◽  
Vol 20 (4) ◽  
pp. 549-562
Author(s):  
Herbert S. Rosenkranz ◽  
Edwin J. Matthews ◽  
Gilles Klopman
Keyword(s):  
Cultured Cells ◽  
Chemical Properties ◽  
Maximum Tolerated Dose ◽  
Log P ◽  
Lumo Energy ◽  
Cellular Toxicity ◽  
Water Partition Coefficient ◽  
The Us ◽  
Lowest Unoccupied Molecular Orbital ◽  
Rats And Mice

Results on cellular toxicity and maximum tolerated dose (MTD) for rats and mice were available for approximately 175 chemicals tested by the US National Toxicology Program. Additionally, the computed log P (log octanol-water partition coefficient) and the lowest unoccupied molecular orbital (LUMO) energy values, a measure of electrophilicity were also available for most of these chemicals. Analysis of the chemicals on the basis of their physical and quantum chemical properties and their toxic effects on cultured cells and rodents showed that: 1) as a group, the more toxic chemicals showed a trend towards higher LUMO energies (i.e. less electrophilic); 2) cytotoxic chemicals exhibited increased lipophilicity; and 3) cytotoxic chemicals were associated with increased systemic toxicity (as measured by the MTD). None of these relationships was expressed in a significant linear fashion as a function of the concentration at which the chemicals exhibited cytotoxicity.

Toxicity profile of aromatic compounds towards Scenedesmus obliquus: a QSAR study

2013 ◽  
Vol 91 (10) ◽  
pp. 943-950 ◽  
Author(s):  
Nasarul Islam ◽  
Altaf Hussain Pandith
Keyword(s):  
Aromatic Compounds ◽  
Scenedesmus Obliquus ◽  
Quantitative Structure Activity Relationship ◽  
Log P ◽  
Toxicity Profile ◽  
Qsar Study ◽  
Qsar Studies ◽  
Water Partition Coefficient ◽  
Lowest Unoccupied Molecular Orbital ◽  
First Time

The parameterization of molecular hydrophobicity and electrophilicity, contributing to the overall toxicity of aromatic compounds, has been the subject of many quantitative structure−activity relationship (QSAR) studies. So far, hydrophobicity has been largely described in terms of the logarithm of the octanol−water partition coefficient (log P) and the molecular electrophilicity in terms of the energy of the lowest unoccupied molecular orbital (ELUMO), the maximum acceptor superdeocalizability (Amax), and the electrophilicity index (ω). Here, we report for the first time the parameterization of these properties in terms of cumulative interplay of multiple descriptors. The toxicity data of 68 compounds were compiled in terms of 50% population growth inhibition (pIGC50) of Scenedesmus obliquus. The comparison of the two QSARs (pIGC50 = 0.175ELUMO + 0.057log P + 0.363ω + 0.019V – 3.292, R2adj = 0.761 and pIGC50 = 0.368ELUMO + 0.146α + 0.258ω + 0.021V − 1.170, R2adj = 0.776) reveals that polarizability (α) is a superior descriptor to log P for parameterization of hydrophobicity, when used in conjunction with ELUMO, ω, and V, for profiling of the toxicity of the test compounds. The overall results indicate that ω and α are better descriptors of electrophilicity and hydrophobicity, respectively, for mapping the toxicity profile of aromatic derivatives towards the target organism.

scholarly journals Comprehensive Virtual Screening of the Antiviral Potentialities of Marine Polycyclic Guanidine Alkaloids against SARS-CoV-2 (COVID-19)

Biomolecules ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 460
Author(s):  
Amr El-Demerdash ◽  
Ahmed M. Metwaly ◽  
Afnan Hassan ◽  
Tarek Mohamed Abd El-Aziz ◽  
Eslam B. Elkaeed ◽  
...  
Keyword(s):  
In Silico ◽  
Active Sites ◽  
Specific Treatment ◽  
Aqueous Solubility ◽  
Maximum Tolerated Dose ◽  
Binding Energies ◽  
Log P ◽  
Binding Affinities ◽  
Structural Protein ◽  
Guanidine Alkaloids

The huge global expansion of the COVID-19 pandemic caused by the novel SARS-corona virus-2 is an extraordinary public health emergency. The unavailability of specific treatment against SARS-CoV-2 infection necessitates the focus of all scientists in this direction. The reported antiviral activities of guanidine alkaloids encouraged us to run a comprehensive in silico binding affinity of fifteen guanidine alkaloids against five different proteins of SARS-CoV-2, which we investigated. The investigated proteins are COVID-19 main protease (Mpro) (PDB ID: 6lu7), spike glycoprotein (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), membrane glycoprotein (PDB ID: 6M17), and a non-structural protein (nsp10) (PDB ID: 6W4H). The binding energies for all tested compounds indicated promising binding affinities. A noticeable superiority for the pentacyclic alkaloids particularly, crambescidin 786 (5) and crambescidin 826 (13) has been observed. Compound 5 exhibited very good binding affinities against Mpro (ΔG = −8.05 kcal/mol), nucleocapsid phosphoprotein (ΔG = −6.49 kcal/mol), and nsp10 (ΔG = −9.06 kcal/mol). Compound 13 showed promising binding affinities against Mpro (ΔG = −7.99 kcal/mol), spike glycoproteins (ΔG = −6.95 kcal/mol), and nucleocapsid phosphoprotein (ΔG = −8.01 kcal/mol). Such promising activities might be attributed to the long ω-fatty acid chain, which may play a vital role in binding within the active sites. The correlation of c Log P with free binding energies has been calculated. Furthermore, the SAR of the active compounds has been clarified. The Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) studies were carried out in silico for the 15 compounds; most examined compounds showed optimal to good range levels of ADMET aqueous solubility, intestinal absorption and being unable to pass blood brain barrier (BBB), non-inhibitors of CYP2D6, non-hepatotoxic, and bind plasma protein with a percentage less than 90%. The toxicity of the tested compounds was screened in silico against five models (FDA rodent carcinogenicity, carcinogenic potency TD50, rat maximum tolerated dose, rat oral LD50, and rat chronic lowest observed adverse effect level (LOAEL)). All compounds showed expected low toxicity against the tested models. Molecular dynamic (MD) simulations were also carried out to confirm the stable binding interactions of the most promising compounds, 5 and 13, with their targets. In conclusion, the examined 15 alkaloids specially 5 and 13 showed promising docking, ADMET, toxicity and MD results which open the door for further investigations for them against SARS-CoV-2.

scholarly journals Exploring the octanol–water partition coefficient dataset using deep learning techniques and data augmentation

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Nadin Ulrich ◽  
Kai-Uwe Goss ◽  
Andrea Ebert
Keyword(s):  
Partition Coefficient ◽  
Data Augmentation ◽  
Environmental Chemistry ◽  
Chemical Properties ◽  
Predictive Performance ◽  
Chemical Structures ◽  
Tautomeric Forms ◽  
Learning Techniques ◽  
Water Partition Coefficient ◽  
Using Data

AbstractToday more and more data are freely available. Based on these big datasets deep neural networks (DNNs) rapidly gain relevance in computational chemistry. Here, we explore the potential of DNNs to predict chemical properties from chemical structures. We have selected the octanol-water partition coefficient (log P) as an example, which plays an essential role in environmental chemistry and toxicology but also in chemical analysis. The predictive performance of the developed DNN is good with an rmse of 0.47 log units in the test dataset and an rmse of 0.33 for an external dataset from the SAMPL6 challenge. To this end, we trained the DNN using data augmentation considering all potential tautomeric forms of the chemicals. We further demonstrate how DNN models can help in the curation of the log P dataset by identifying potential errors, and address limitations of the dataset itself.

scholarly journals Estimation of the retention behaviour of s-triazine derivatives applying multiple regression analysis of selected molecular descriptors

2013 ◽  
pp. 229-237 ◽  
Author(s):  
Lidija Jevric ◽  
Sanja Podunavac-Kuzmanovic ◽  
Strahinja Kovacevic ◽  
Natasa Kalajdzija ◽  
Bratislav Jovanovic
Keyword(s):  
Dissociation Constant ◽  
Water Solubility ◽  
Molecular Descriptors ◽  
Chemical Properties ◽  
Log P ◽  
Retention Factors ◽  
Solute Retention ◽  
Physico Chemical ◽  
Hydrophilic Lipophilic Balance ◽  
Triazine Derivatives

The estimation of retention factors by correlation equations with physico-chemical properties can be of great helpl in chromatographic studies. The retention factors were experimentally measured by RP-HPTLC on impregnated silica gel with paraffin oil using two-component solvent systems. The relationships between solute retention and modifier concentration were described by Snyder?s linear equation. A quantitative structure-retention relationship was developed for a series of s-triazine compounds by the multiple linear regression (MLR) analysis. The MLR procedure was used to model the relationships between the molecular descriptors and retention of s-triazine derivatives. The physicochemical molecular descriptors were calculated from the optimized structures. The physico-chemical properties were the lipophilicity (log P), connectivity indices (?), total energy (Et), water solubility (log W), dissociation constant (pKa), molar refractivity (MR), and Gibbs energy (GibbsE) of s-triazines. A high agreement between the experimental and predicted retention parameters was obtained when the dissociation constant and the hydrophilic-lipophilic balance were used as the molecular descriptors. The empirical equations may be successfully used for the prediction of the various chromatographic characteristics of substances, with a similar chemical structure.

scholarly journals Prediction of Biopharmaceutical Drug Disposition Classification System (BDDCS) by Structural Parameters

2019 ◽  
Vol 22 ◽  
pp. 247-269 ◽  
Author(s):  
Yeganeh Golfar ◽  
Ali Shayanfar
Keyword(s):  
Classification System ◽  
Drug Disposition ◽  
Structural Parameters ◽  
Log P ◽  
Metabolizing Enzymes ◽  
Acceptable Accuracy ◽  
Water Partition Coefficient ◽  
Pharmacokinetic Properties ◽  
Solvation Parameters ◽  
External Test

Modeling of physicochemical and pharmacokinetic properties is important for the prediction and mechanism characterization in drug discovery and development. Biopharmaceutics Drug Disposition Classification System (BDDCS) is a four-class system based on solubility and metabolism. This system is employed to delineate the role of transporters in pharmacokinetics and their interaction with metabolizing enzymes. It further anticipates drug disposition and potential drug-drug interactions in the liver and intestine. According to BDDCS, drugs are classified into four groups in terms of the extent of metabolism and solubility (high and low). In this study, structural parameters of drugs were used to develop classification-based models for the prediction of BDDCS class. Reported BDDCS data of drugs were collected from the literature, and structural descriptors (Abraham solvation parameters and octanol–water partition coefficient (log P)) were calculated by ACD/Labs software. Data were divided into training and test sets. Classification-based models were then used to predict the class of each drug in BDDCS system using structural parameters and the validity of the established models was evaluated by an external test set. The results of this study showed that log P and Abraham solvation parameters are able to predict the class of solubility and metabolism in BDDCS system with good accuracy. Based on the developed methods for prediction solubility and metabolism class, BDDCS could be predicted in the correct with an acceptable accuracy. Structural properties of drugs, i.e. logP and Abraham solvation parameters (polarizability, hydrogen bonding acidity and basicity), are capable of estimating the class of solubility and metabolism with an acceptable accuracy.

Apparent octanol/water partition coefficients of pentachlorophenol as a function of pH

1982 ◽  
Vol 60 (16) ◽  
pp. 2104-2106 ◽  
Author(s):  
Klaus L. E. Kaiser ◽  
Ilze Valdmanis
Keyword(s):  
Aqueous Solution ◽  
Ionic Strength ◽  
Partition Coefficient ◽  
Linear Function ◽  
Partition Coefficients ◽  
Extreme Values ◽  
Log P ◽  
Water Partition Coefficient ◽  
Non Linear ◽  
Good Agreement

The apparent 1-octanol/water partition coefficient (log PApp) of pentachlorophenol (PCP) varies in non-linear function with pH of the aqueous solution. In the range of pH 1.2 to 13.5 extreme values of log PApp 4.84 at pH 1.2 and log PApp 1.3 at pH 10.5 were observed. In the alkaline regime, log PApp increases strongly with the ionic strength. The ion-corrected partition coefficient of PCP was found to be log P 5.05 in good agreement with literature values.

Determination of Ionization Constant (pKa) and Octanol–Water Partition Coefficient (Log P) of Cyclopiazonic Acid

2005 ◽  
Vol 88 (5) ◽  
pp. 1367-1370 ◽  
Author(s):  
Victor S Sobolev
Keyword(s):  
Partition Coefficient ◽  
Potentiometric Titration ◽  
Ionization Constant ◽  
Cyclopiazonic Acid ◽  
Log P ◽  
Experimental Conditions ◽  
Water Partition Coefficient

Abstract The ionization constant (pKa) and the octanol–water partition coefficient (log P) of the important mycotoxin cyclopiazonic acid (CPA) were determined by means of potentiometric titration, and the lipophilicity profile (log D) was calculated. Under the experimental conditions, pKa of CPA = 2.97 ± 0.09, log P = 3.83 ± 0.10, and log D at pH 7.4 = −0.58.

scholarly journals Semiempirical Theoretical Studies of 1,3-Benzodioxole Derivatives as Corrosion Inhibitors

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Omnia A. A. El-Shamy
Keyword(s):  
Molecular Orbital ◽  
Corrosion Inhibitors ◽  
Energy Gap ◽  
Quantitative Structure Activity Relationship ◽  
Mulliken Charge ◽  
Semiempirical Methods ◽  
Log P ◽  
Chemical Calculation ◽  
Highest Occupied Molecular Orbital ◽  
Lowest Unoccupied Molecular Orbital

The efficiency of 1,3-benzodioxole derivatives as corrosion inhibitors is theoretically studied using quantum chemical calculation and Quantitative Structure Activity Relationship (QSAR). Different semiempirical methods (AM1, PM3, MNDO, MINDO/3, and INDO) are applied in order to determine the relationship between molecular structure and their corrosion protection efficiencies. Different quantum parameters are obtained as the energy of highest occupied molecular orbitalEHOMO, the energy of the lowest unoccupied molecular orbitalELUMO, energy gapΔEg, dipole momentμ, and Mulliken charge on the atom. QSAR approach is applied to elucidate some important parameters as the hydrophobicity (Log P), surface area (S.A), polarization(P), and hydration energy (EHyd).

Structure–Toxicity Relationships for the Fathead Minnow, Pimephales promelas: Narcotic Industrial Chemicals

1983 ◽  
Vol 40 (6) ◽  
pp. 743-748 ◽  
Author(s):  
Gilman D. Veith ◽  
Daniel J. Call ◽  
L. T. Brooke
Keyword(s):  
Fathead Minnow ◽  
Pimephales Promelas ◽  
Chemical Activity ◽  
Alkyl Halides ◽  
Log P ◽  
Industrial Chemicals ◽  
Water Partition Coefficient ◽  
The Common ◽  
Structure Toxicity Relationship ◽  
Toxicity Relationship

Narcosis is a reversible state of arrested activity of protoplasmic structures caused by a wide variety of organic chemicals. This nonspecific mode of toxic action was found predominant in acute toxicity studies of industrial chemicals and fish. This paper presents 96-h LC50 values for 65 industrial chemicals including alcohols, ketones, ethers, alkyl halides, and substituted benzenes. The common mode of action permitted the development of a structure–toxicity relationship as follows: log LC50 = −0.94 log P + 0.94 log (0.000068P + 1) −1.25 where P is the n-octanol/water partition coefficient. The data show that the toxicity of the chemicals to fish is directly comparable with the toxicity in mammals when expressed as chemical activity.

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