Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Predicting estrogen receptor binding of chemicals using a suite of in silico methods – Complementary approaches of (Q)SAR, molecular docking and molecular dynamics
Cotterill, J.V. ; Palazzolo, L. ; Ridgway, C. ; Price, N. ; Rorije, E. ; Moretto, A. ; Peijnenburg, A. ; Eberini, I. - \ 2019
Toxicology and Applied Pharmacology 378 (2019). - ISSN 0041-008X
Estrogen receptor - In Silico - Low-mode molecular dynamics simulation - Molecular docking - QSAR

With the aim of obtaining reliable estimates of Estrogen Receptor (ER) binding for diverse classes of compounds, a weight of evidence approach using estimates from a suite of in silico models was assessed. The predictivity of a simple Majority Consensus of (Q)SAR models was assessed using a test set of compounds with experimental Relative Binding Affinity (RBA) data. Molecular docking was also carried out and the binding energies of these compounds to the ERα receptor were determined. For a few selected compounds, including a known full agonist and antagonist, the intrinsic activity was determined using low-mode molecular dynamics methods. Individual (Q)SAR model predictivity varied, as expected, with some models showing high sensitivity, others higher specificity. However, the Majority Consensus (Q)SAR prediction showed a high accuracy and reasonably balanced sensitivity and specificity. Molecular docking provided quantitative information on strength of binding to the ERα receptor. For the 50 highest binding affinity compounds with positive RBA experimental values, just 5 of them were predicted to be non-binders by the Majority QSAR Consensus. Furthermore, agonist-specific assay experimental values for these 5 compounds were negative, which indicates that they may be ER antagonists. We also showed different scenarios of combining (Q)SAR results with Molecular docking classification of ER binding based on cut-off values of binding energies, providing a rational combined strategy to maximize terms of toxicological interest.

Predictive models in ecotoxicology: Bridging the gap between scientific progress and regulatory applicability—Remarks and research needs
Vighi, Marco ; Barsi, Alpar ; Focks, Andreas ; Grisoni, Francesca - \ 2019
Integrated Environmental Assessment and Management 15 (2019)3. - ISSN 1551-3793 - p. 345 - 351.
Bioaccumulation modelling - Effect modelling - QSAR - Regulation - TK–TD

This paper concludes a special series of 7 articles (4 on toxicokinetic–toxicodynamic [TK–TD] models and 3 on quantitative structure-activity relationship [QSAR] models) published in previous issues of Integrated Environmental Assessment and Management (IEAM). The present paper summarizes the special series articles and highlights their contribution to the topic of increasing the regulatory applicability of effect models. For both TK–TD and QSAR approaches, we then describe the main research needs. The use of TK–TD models for describing sublethal effects must be better developed, particularly through the improvement of the dynamic energy budget (DEBtox) approach. The potential of TK–TD models for moving from lower (molecular) to higher (population) hierarchical levels is highlighted as a promising research line. Some relevant issues to improve the acceptance of QSAR models at the regulatory level are also described, such as increased transparency of the performance assessment and of the modeling algorithms, model documentation, relevance of the chosen target for regulatory needs, and improved mechanistic interpretability. Integr Environ Assess Manag 2019;00:000–000.

QSAR of 1,4-benzoxazin-3-one antimicrobials and their drug design perspectives
Bruijn, Wouter J.C. de; Hageman, Jos A. ; Araya-Cloutier, Carla ; Gruppen, Harry ; Vincken, Jean Paul - \ 2018
Bioorganic and Medicinal Chemistry 26 (2018)23-24. - ISSN 0968-0896 - p. 6105 - 6114.
2H-1,4-benzoxazin-3(4H)-one - Antibacterial - Antifungal - Benzoxazinoid - Benzoxazinone - Drug design - QSAR - SAR

Synthetic derivatives of 1,4-benzoxazin-3-ones have been shown to possess promising antimicrobial activity, whereas their natural counterparts were found lacking in this respect. In this work, quantitative structure-activity relationships (QSAR) of natural and synthetic 1,4-benzoxazin-3-ones as antimicrobials were established. Data published in literature were curated into an extensive dataset of 111 compounds. Descriptor selection was performed by a genetic algorithm. QSAR models revealed differences in requirements for activity against fungi, gram-positive and gram-negative bacteria. Shape, VolSurf, and H-bonding property descriptors were frequently picked in all models. The models obtained for gram-positive and gram-negative bacteria showed good predictive power (Q2 Ext 0.88 and 0.85, respectively). Based on the models generated, an additional set of 1,4-benzoxazin-3-ones, for which no antimicrobial activity had been determined in literature, were evaluated in silico. Additionally, newly designed lead compounds with a 1,4-benzoxazin-3-one scaffold were generated in silico by varying the positions and combinations of substituents. Two of these were predicted to be up to 5 times more active than any of the compounds in the current dataset. The 1,4-benzoxazin-3-one scaffold was concluded to possess potential for the design of new antimicrobial compounds with potent antibacterial activity, a multitarget mode of action, and possibly reduced susceptibility to gram negatives’ efflux pumps.

Predictive models in ecotoxicology : Bridging the gap between scientific progress and regulatory applicability
Focks, Andreas ; Grisoni, Francesca ; Barsi, Alpar ; Vighi, Marco - \ 2018
Integrated Environmental Assessment and Management 14 (2018)5. - ISSN 1551-3793 - p. 601 - 603.
Ecotoxicology - Models - QSAR - Regulation - TD/TK
This special series is the outcome of the session "Predictive models in ecotoxicology: Bridging the gap between scientific progress and regulatory applicability," held at the 27th SETAC Europe annual meeting (Brussels, May 2017). In this foreword the rationale behind the special series, the reasons for proposing it, and its objectives are described briefly.
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