Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)

Martin, Yvonne C.; Abagyan, Ruben; Ferenczy, György G.; Gillet, Val J.; Oprea, Tudor I.; Ulander, Johan; Winkler, David A.; Zefirov, N. S.

doi:10.1515/pac-2012-1204

Cited by 14 publications

(7 citation statements)

References 83 publications

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“…Pharmacophore modeling was employed as a filter prior to the docking screening. Pharmacophores are able to rationalize the receptor activity analyzing the ligand chemical structures (Martin et al, 2016 ), and pharmacophore-based virtual screening are generally very fast compared to high-throughput docking (Cheng et al, 2012 ). The pharmacophore filter allowed us to eliminate compounds that would have been obvious outliers and to submit to the docking analysis only compounds that have the molecular determinants responsible for receptor activity, speeding the screening process.…”

Section: Resultsmentioning

confidence: 99%

Molecular Features Underlying Selectivity in Chicken Bitter Taste Receptors

Pizio

Shy

Behrens

et al. 2018

Front. Mol. Biosci.

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Chickens sense the bitter taste of structurally different molecules with merely three bitter taste receptors (Gallus gallus taste 2 receptors, ggTas2rs), representing a minimal case of bitter perception. Some bitter compounds like quinine, diphenidol and chlorpheniramine, activate all three ggTas2rs, while others selectively activate one or two of the receptors. We focus on bitter compounds with different selectivity profiles toward the three receptors, to shed light on the molecular recognition complexity in bitter taste. Using homology modeling and induced-fit docking simulations, we investigated the binding modes of ggTas2r agonists. Interestingly, promiscuous compounds are predicted to establish polar interactions with position 6.51 and hydrophobic interactions with positions 3.32 and 5.42 in all ggTas2rs; whereas certain residues are responsible for receptor selectivity. Lys3.29 and Asn3.36 are suggested as ggTas2r1-specificity-conferring residues; Gln6.55 as ggTas2r2-specificity-conferring residue; Ser5.38 and Gln7.42 as ggTas2r7-specificity conferring residues. The selectivity profile of quinine analogs, quinidine, epiquinidine and ethylhydrocupreine, was then characterized by combining calcium-imaging experiments and in silico approaches. ggTas2r models were used to virtually screen BitterDB compounds. ~50% of compounds known to be bitter to human are likely to be bitter to chicken, with 25, 20, 37% predicted to be ggTas2r1, ggTas2r2, ggTas2r7 agonists, respectively. Predicted ggTas2rs agonists can be tested with in vitro and in vivo experiments, contributing to our understanding of bitter taste in chicken and, consequently, to the improvement of chicken feed.

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Section: Resultsmentioning

confidence: 99%

Molecular Features Underlying Selectivity in Chicken Bitter Taste Receptors

Pizio

Shy

Behrens

et al. 2018

Front. Mol. Biosci.

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“…Lipophilicity determines the affinity of the molecule to the organic phase. It is expressed as the partition of substances in a two-phase system: liquid-liquid or liquid-solid; most often, lipophilicity is described by partition processes between polar (organic) and nonpolar (water) phases [7]. The traditional method of its determination is extraction in the octanol-water system [8, 9].…”

Section: Introductionmentioning

confidence: 99%

The Application of CA and PCA to the Evaluation of Lipophilicity and Physicochemical Properties of Tetracyclic Diazaphenothiazine Derivatives

Nycz–Empel

Bober

Wyszomirski

et al. 2019

Journal of Analytical Methods in Chemistry

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The subject of the study was 11 new synthetized tetracyclic diazaphenothiazine derivatives. Using thin-layer chromatography in a reverse phase system (RP-TLC), their RM0 lipophilicity parameter was determined. The mobile phase was composed of 0.2 M Tris buffer (pH = 7.4) and acetone (POCH S.A., Gliwice, Poland) in different concentrations. Using computer programs, based on different computational algorithms, theoretical values of lipophilicity (AClogP, ALOGP, ALOGPs, miLogP, MLOGP, XLOGP2, and XLOGP3) as well as molecular descriptors (molecular weight, volume of a molecule, dipole moment, polar surface, and energy of HOMO orbitals and LUMO orbitals) and parameters of biological activity: human intestinal absorption (HIA), plasma protein binding (PPB), and blood-brain barrier (BBB), were determined. The correlations between the experimental values of lipophilicity and theoretically calculated lipophilic values and also between experimental values of lipophilicity and values of physicochemical or biological properties were assessed. A certain relationship between structure and lipophilicity was found. On the other hand, the relationships between RM0 and physicochemical or biological properties were not statistically significant and therefore unusable. For all analysed values, an analysis of similarities and principal component analyses were also made. The obtained dendrograms for the analysis of lipophilicity and physicochemical and biological properties indicate the relationship between experimental values of lipophilicity and structure in the case of theoretical lipophilicity values only. PCA, on the other hand, showed that ALOGP, MLOGP, miLogP, and BBB and molar volume have the largest share in the description of the entire system. Distribution of compounds on the area of factors also indicates the connections between them related to their structure.

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“…A quantitative structure-activity relationship (QSAR) is defined as “an equation or other function that describes the relationship between a biological property of compounds, usually a measure of relative potency” namely an endpoint, “and one or more properties of the compounds”, ( 4 ). Ideally the endpoint refers to a single mechanism of action, but this is not the case of PPB.…”

Section: Introductionmentioning

confidence: 99%

QSAR Development for Plasma Protein Binding: Influence of the Ionization State

et al. 2018

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PurposeThis study explored several strategies to improve the performance of literature QSAR models for plasma protein binding (PPB), such as a suitable endpoint transformation, a correct representation of chemicals, more consistency in the dataset, and a reliable definition of the applicability domain.MethodsWe retrieved human fraction unbound (Fu) data for 670 compounds from the literature and carefully checked them for consistency. Descriptors were calculated taking account of the ionization state of molecules at physiological pH (7.4), in order to better estimate the affinity of molecules to blood proteins. We used different algorithms and chemical descriptors to explore the most suitable strategy for modeling the endpoint. SMILES (simplified molecular input line entry system)-based string descriptors were also tested with the CORAL software (CORelation And Logic). We did an outlier analysis to establish the models to use (or not to use) in case of well recognized families.ResultsInternal validation of the selected models returned Q2 values close to 0.60. External validation also gave r2 values always greater than 0.60. The CORAL descriptor based model for √fu was the best, with r2 0.74 in external validation.ConclusionsPerformance in prediction confirmed the robustness of all the derived models and their suitability for real-life purposes, i.e. screening chemicals for their ADMET profiling. Optimization of descriptors can be useful in order to obtain the correct results with a ionized molecule.Electronic supplementary materialThe online version of this article (10.1007/s11095-018-2561-8) contains supplementary material, which is available to authorized users.

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Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)

Cited by 14 publications

References 83 publications

Molecular Features Underlying Selectivity in Chicken Bitter Taste Receptors

Molecular Features Underlying Selectivity in Chicken Bitter Taste Receptors

The Application of CA and PCA to the Evaluation of Lipophilicity and Physicochemical Properties of Tetracyclic Diazaphenothiazine Derivatives

QSAR Development for Plasma Protein Binding: Influence of the Ionization State

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