Results 31 to 40 of about 17,150 (158)

Environmental impact of PFAS: Filling data gaps using theoretical quantum chemistry and QSPR modeling

Environment International
Per- and polyfluorinated alkyl substances (PFAS), known for their widespread environmental presence and slow degradation, pose significant concerns. Of the approximately 10,000 known PFAS, only a few have undergone comprehensive testing, resulting in ...
Michalina Mudlaff, Anita Sosnowska, Leonid Gorb, Natalia Bulawska, Karolina Jagiello, Tomasz Puzyn   +5 more
doaj   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

Generative and Experimental Validation of High Refractive Index Polymers via Domain Knowledge Approach with Small Data

Advanced Intelligent Discovery, EarlyView.
This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo, Seigo Watanabe, Hana Matsunaga, Kenichi Oyaizu   +3 more
wiley   +1 more source

U‐Net‐Based Prediction of Concealed Volume Loss in AZ31 From Optical Corrosion Imprints and As‐Exposed Surface Topography

Advanced Intelligent Discovery, EarlyView.
How much material loss is concealed beneath a layer of corrosion products? This proof‐of‐concept study demonstrates how concealed volume loss is inferred from the optical appearance and as‐exposed surface topography of AZ31 corrosion imprints. By predicting postcleaning depth maps, a multimodal U‐Net model estimates hidden volume loss without chromic ...
Lars Dammann, Ci Song, Bahram Vaghefinazari, Tim Würger, Anna Lisitsyna, Shadi Albarqouni, Mikhail L. Zheludkevich, Sviatlana V. Lamaka, Christian Feiler   +8 more
wiley   +1 more source

Graph Theory-Based Sequence Descriptors as Remote Homology Predictors

Biomolecules, 2019
Alignment-free (AF) methodologies have increased in popularity in the last decades as alternative tools to alignment-based (AB) algorithms for performing comparative sequence analyses. They have been especially useful to detect remote homologs within the
Guillermin Agüero-Chapin, Deborah Galpert, Reinaldo Molina-Ruiz, Evys Ancede-Gallardo, Gisselle Pérez-Machado, Gustavo A. De la Riva, Agostinho Antunes   +6 more
doaj   +1 more source

QSAR ANALYSIS USING SEMI-EMPIRICAL AM1 METHOD, MOLECULAR DOCKING, AND ADMET STUDIES OF CHALCONE DERIVATIVES AS ANTIMALARIAL COMPOUNDS

Jurnal Kimia Riset, 2023
Malaria is a serious caused by protozoan parasites such as Plasmodium groups and has fatal consequences for human health. The increase in the resistance of the Plasmodium parasites toward existing antimalarial drugs prompts the exploration of novel ...
Muhammad Akbar S Kurniawan, Muhamad Jalil Baari, Sariyanti Sariyanti, Finarisnawati Finarisnawati   +3 more
doaj   +1 more source

A 3D Multitask Graph Neural Network Framework for Ames Mutagenicity Prediction

Advanced Intelligent Discovery, EarlyView.
Our proposed multitask graph neural network model has a high predictive accuracy for Ames mutagenicity. By operating directly on molecular graph representations instead of traditional molecular descriptors, and predicting strain‐specific results, the model outperforms most existing benchmarks.
Abigail E. Teitgen, Eugenia Ulzurrun, Nuria E. Campillo, Eduardo R. Hernández   +3 more
wiley   +1 more source

QSPR-driven prediction of analyte permeability for advancing CP-MIMS applications

Green Analytical Chemistry
Condensed Phase-Membrane Introduction Mass Spectrometry (CP-MIMS) is a sustainable and highly versatile approach within the framework of Direct Mass Spectrometry techniques, which enables real-time determination of target analytes by integrating sampling,
Enmanuel Cruz Muñoz, Veronica Termopoli, Davide Ballabio, Marco Orlandi, Viviana Consonni   +4 more
doaj   +1 more source

QSAR Model of Indeno[1,2-b]indole Derivatives and Identification of N-isopentyl-2-methyl-4,9-dioxo-4,9-Dihydronaphtho[2,3-b]furan-3-carboxamide as a Potent CK2 Inhibitor

Molecules, 2019
Casein kinase II (CK2) is an intensively studied enzyme, involved in different diseases, cancer in particular. Different scaffolds were used to develop inhibitors of this enzyme.
Samer Haidar, Christelle Marminon, Dagmar Aichele, Abdelhamid Nacereddine, Wael Zeinyeh, Abdeslem Bouzina, Malika Berredjem, Laurent Ettouati, Zouhair Bouaziz, Marc Le Borgne, Joachim Jose   +10 more
doaj   +1 more source

Accelerating green heterocyclic synthesis: Convergence of AI, automation, and sustainable chemistry

Bulletin of the Korean Chemical Society, EarlyView.
Green heterocyclic synthesis and data‐driven tools such as AI, high‐throughput experimentation, continuous flow, and self‐driving laboratories have developed largely in parallel. This review connects them and asks how green metrics such as E‐factor and PMI might serve as explicit optimization targets rather than post‐hoc measures, toward sustainable ...
Noor Aisyah Ahmad Shah, Amirreza Mottafegh, Su‐Hyun Yoo, Jongwoon Kim, Minseon Byeon, Juhwan Noh, Yea‐Lee Lee, Jin Suk Myung, Gwang‐Noh Ahn   +8 more
wiley   +1 more source