Article
Automation & Control Systems
Arkaprava Banerjee, Mainak Chatterjee, Priyanka De, Kunal Roy
Summary: In this study, a similarity-based read-across algorithm for predicting toxicity of untested compounds was developed. The results indicated that weighted standard deviation of predicted response values is the most deterministic feature for reliability of predictions. These reliability measures provide greater confidence in the quality of quantitative predictions from the chemical read-across tool for new query compounds.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2022)
Article
Biochemistry & Molecular Biology
Ana Yisel Caballero Alfonso, Chayawan Chayawan, Domenico Gadaleta, Alessandra Roncaglioni, Emilio Benfenati
Summary: The reduction and replacement of in vivo tests have become crucial in terms of resources and animal benefits. The read-across approach reduces the number of substances to be tested, exploiting existing experimental data to predict the properties of untested substances. In this paper, a workflow is introduced to support analogue identification for read-across. The workflow combines multiple similarity metrics to improve the predictions of toxicity.
Article
Chemistry, Medicinal
Atsushi Yoshimori, Juergen Bajorath
Summary: Lead optimization involves the generation of analogue series with sustainable SAR progression. During multi-property optimization, if roadblocks occur, it is desirable to replace an analogue series with another one that has a different core structure but similar SAR characteristics for a given target. It is also found that SAR transfer events across different targets are more common than expected.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Article
Chemistry, Medicinal
Cathy Lester, ElLantae Byrd, Mahmoud Shobair, Gang Yan
Summary: Structure activity relationship (SAR)-based read-across is important for toxicological safety assessment, but justifying the prediction is challenging. A quantitative approach was introduced to consider biological and toxicological features and calculate a similarity score for systemic toxicity prediction. Fingerprint keys were used to compare attributes for 14 case study chemicals and their potential analogues. Machine learning determined the importance of each similarity attribute for different structure classes. This approach improves transparency and consistency, facilitating regulatory acceptance.
CHEMICAL RESEARCH IN TOXICOLOGY
(2023)
Article
Chemistry, Medicinal
Dimitra-Danai Varsou, Nikoletta-Maria Koutroumpa, Haralambos Sarimveis
Summary: This study presents a computational workflow for grouping engineered nanomaterials (ENMs) and predicting their toxicity-related end points. A mixed integer-linear optimization program (MILP) problem is formulated to automatically filter noisy variables and develop specific predictive models for each group. The method demonstrates good performance through application to benchmark datasets and comparison with alternative predictive modeling approaches.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Pharmacology & Pharmacy
Guohui Sun, Peiying Bai, Tengjiao Fan, Lijiao Zhao, Rugang Zhong, R. Stanley Mcelhinney, T. Brian H. Mcmurry, Dorothy J. Donnelly, Joan E. Mccormick, Jane Kelly, Geoffrey P. Margison
Summary: This study aimed to design and synthesize potential MGMT inactivators to overcome MGMT-mediated tumor resistance. The inactivation potency of these compounds was determined using MGMT inactivation assays, and the correlation between chemical structure and MGMT-inactivating ability was analyzed using QSAR modeling. The study identified key structural features associated with MGMT inactivation, providing insights for the design of MGMT inactivators in cancer treatment.
Article
Chemistry, Multidisciplinary
Richard K. Cross, Dave Spurgeon, Claus Svendsen, Elma Lahive, Simon Little, Frank von der Kammer, Frederic Loosli, Marianne Matzke, Teresa F. Fernandes, Vicki Stone, Willie J. G. M. Peijnenburg, Eric A. J. Bleeker
Summary: Even small changes in physicochemical properties of nanoforms (NFs) can influence their environmental fate and hazard. Testing and characterizing each individual NF will not be feasible due to the large number of new materials being developed. Targeting the most relevant form of the NF for a given exposure is important for efficient risk assessment. In aquatic systems, functional fate processes play a key role in determining the exposure relevant form of NFs. Grouping of NFs and read-across based on functional fate pathways can be justified by considering the shared fate and hazard profile. A new Integrated Approaches to Testing and Assessment (IATA) is presented, focusing on dissolution, dispersion stability, chemical transformations, and the contribution to toxicity from particles and dissolved components. This IATA can be used as a template for future in vivo kinetic assessments.
Article
Medicine, Legal
Cathy C. Lester, Gang Yan
Summary: Matched molecular pair analysis (MMPA) offers a systematic method for identifying chemical substitutions to cover the safety of a target chemical. The analysis revealed that only five categories of substitutions per chemical class were necessary to link all molecular pairs, outlining a strategy for searching potential analogs. This approach provides interpretable structural comparisons sensitive to small differences in local structure, in contrast to quantitative similarity measures showing little correlation with analog suitability.
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2021)
Article
Environmental Sciences
Frederic Loosli, Kirsten Rasmussen, Hubert Rauscher, Richard K. Cross, Nathan Bossa, Willie Peijnenburg, Josje Arts, Marianne Matzke, Claus Svendsen, David Spurgeon, Per Axel Clausen, Emmanuel Ruggiero, Wendel Wohlleben, Frank von der Kammer
Summary: Before introducing a new nanoform on the market, it is important to evaluate its potential adverse effects through hazard and risk assessment. Grouping and read-across of nanoforms can help reduce resource consumption and maximize the use of existing data for assessment. The impact of nanoforms on human health and the environment depends greatly on their concentration and physicochemical properties, making knowledge of these properties essential for assessing similarity.
Article
Biochemistry & Molecular Biology
Edoardo Luca Vigano, Erika Colombo, Giuseppa Raitano, Alberto Manganaro, Alessio Sommovigo, Jean Lou C. M. Dorne, Emilio Benfenati
Summary: This study developed a new open-access software called VERA, which assesses the similarity between chemicals using structural alerts, pre-defined molecular groups, and structural similarity. VERA can accurately identify botanicals associated with carcinogenicity and provide clusters of similar substances.
Article
Toxicology
Ana Y. Caballero Alfonso, Liadys Mora Lagares, Marjana Novic, Emilio Benfenati, Anil Kumar, Chayawan
Summary: The identification of structural alerts in azole-based chemicals for predicting aromatase activity is important for toxicological assessment and safe drug design.
TOXICOLOGY IN VITRO
(2022)
Article
Thermodynamics
Chengcheng Liu, Keli Lin, Yiru Wang, Bin Yang
Summary: In this study, a multi-fidelity neural network-based surrogate model (MFNNSM) is proposed to accelerate the uncertainty quantification (UQ) of chemical kinetic models. The MFNNSM utilizes the similarity between different fidelity samples to transfer or generate high-fidelity samples. Experimental results show that the MFNNSM can achieve acceleration factors up to 6 and increase to 10 when reusing samples under different conditions.
COMBUSTION AND FLAME
(2023)
Article
Biotechnology & Applied Microbiology
Roy Geerts, Daan M. van Vliet, Michael van den Born, Caroline M. Plugge, Cornelis G. van Ginkel
Summary: Alkyl polyglucosides, consisting of hydrophobic alkyl chains and hydrophilic saccharide moieties, demonstrate ready biodegradability in water and are easily metabolized by microorganisms.
INTERNATIONAL BIODETERIORATION & BIODEGRADATION
(2021)
Article
Chemistry, Medicinal
Hamid Safizadeh, Scott W. Simpkins, Justin Nelson, Sheena C. Li, Jeff S. Piotrowski, Mami Yoshimura, Yoko Yashiroda, Hiroyuki Hirano, Hiroyuki Osada, Minoru Yoshida, Charles Boone, Chad L. Myers
Summary: The study systematically benchmarked 11 different molecular fingerprint encodings combined with 13 different similarity coefficients using chemical-genetic interaction data from yeast as a proxy for biological activity. It found that the all-shortest path fingerprints paired with the Braun-Blanquet similarity coefficient provided superior performance across different compound collections. Additionally, a machine learning pipeline based on support vector machines offered a fivefold improvement relative to the best unsupervised approach, indicating the potential of using high-dimensional chemical-genetic data for improving prediction of biological functions from chemical structures.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Toxicology
Susann Fayyaz, Reinhard Kreiling, Ursula G. Sauer
Summary: This article presents the outcomes of higher-tier studies on methyl paraben and propyl paraben using Wistar rats under EU chemicals legislation. The findings were used to assess ethyl paraben and butyl paraben, confirming their similarity and lack of toxicity. Results indicate that these linear n-alkyl parabens do not exhibit endocrine disrupting properties.
ARCHIVES OF TOXICOLOGY
(2021)
Article
Medicine, Legal
Fiona Sewell, Ian Ragan, Graham Horgan, David Andrew, Thomas Holmes, Irene Manou, Boris P. Mueller, Tim Rowan, Barbara G. Schmitt, Marco Corvaro
Summary: There are currently three test guidelines for acute oral toxicity studies, but the subjectivity of one guideline may be hindering its wider use. In order to address this, the NC3Rs and EPAA collaborated to analyze historical data and provide recommendations on the recognition of 'evident toxicity'.
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2024)
Article
Medicine, Legal
Michael DeVito, Bas Bokkers, Majorie B. M. van Duursen, Karin van Ede, Mark Feeley, Elsa Antunes Fernandes Gaspar, Laurie Haws, Sean Kennedy, Richard E. Peterson, Ron Hoogenboom, Keiko Nohara, Kim Petersen, Cynthia Rider, Martin Rose, Stephen Safe, Dieter Schrenk, Matthew W. Wheeler, Daniele S. Wikoff, Bin Zhao, Martin van den Berg
Summary: In October 2022, the World Health Organization reevaluated the toxic equivalency factors (TEFs) for chlorinated dioxin-like compounds in a panel convened in Lisbon. This effort utilized an updated database, Bayesian dose response modeling, and meta-analysis to derive Best-Estimate TEFs. Applying these new TEFs may result in lower total toxic equivalents for dioxin-like chemicals.
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2024)