Results 41 to 50 of about 29,861 (222)

Applications of QSPR and Machine Learning in Molecular Photonics

Advanced Optical Materials, EarlyView.
Quantitative structureproperty relationships (QSPR) and machine learning (ML) are transforming photochemistry by enabling pre‐synthetic screening of photoactive molecules. This review outlines advances in data‐driven discovery of optical materials and functional dyes, identifies effective descriptors and models for photophysical processes, and provides
Andrey A. Buglak, Platon P. Chebotaev, Mikhail A. Filatov   +2 more
wiley   +1 more source

QSAR-Co-X: An Open Source Toolkit for Multi-Target QSAR Modelling [PDF]

Journal of Cheminformatics, 2020
Abstract Quantitative structure activity relationships (QSAR) modelling is a well-known computational tool, often used in a wide variety of applications. Yet one of the major drawbacks of conventional QSAR modelling tools is that models are set up based on a limited number of experimental and/or theoretical conditions.
M. Natália Dias Soeiro Cordeiro, Amit Kumar Halder   +1 more
openaire   +5 more sources

Electronic and Steric Tuning of Molecular Acidity toward Unified Models for Excited State Proton Transfer

Advanced Science, EarlyView.
Conventional excited‐state proton transfer (ESPT) theories explain the kinetics of fluorescent photoacids, but face challenges for weakly or nonfluorescent ones. This missing link is bridged by making and dissecting series of green fluorescent protein chromophore derivatives with varied photoacidities via strategic substitutions. Structure‐photoacidity
Cheng Chen, Ivan N. Myasnyanko, Mikhail S. Baranov, Chong Fang   +3 more
wiley   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

Theoretical chemistry study on metabolism influencing factors of two kinds of non-hormonal pregnancy-terminating drugs(两类非甾类终止妊娠药物代谢影响因素理论化学研究)

Zhejiang Daxue xuebao. Lixue ban, 2004
釆用半经验AMI量子化学方法计算了两类非甾类终止妊娠化合物的物理化学参数，并用多元线性回归分析法对所研究化合物的代谢强度进行QSAR研究，得到了较好的结果.两个模型互相验证，结果一致，有较高的预测能力.根据所建立的模型，化合物较高的生成热以及主要代谢位置上的前沿电子密度均为代谢的不利因素，这可能与化合物体内代谢历程有关.
HUGui-xiang(胡桂香), YUQing-sen(俞庆森), WANGYan-hua(王艳花), ZHANGBing(张兵), SHANGZhi-cai(商志才), WUTian-xing(吴天星)   +5 more
doaj   +1 more source

Automating QSAR expertise [PDF]

Chemistry Central Journal, 2008
The Discovery Bus, a multi-agent software system designed for automating aspects of Molecular Design, particularly expert decision making, is described. It extends approaches aimed at automating the processing of drug discovery information but where control remains with the human expert, to automating the “tacit knowledge” of the expert and best ...
Damjan Krstajic, David E. Leahy
openaire   +2 more sources

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Prediction of cytotoxicity of heavy metals adsorbed on nano-TiO2 with periodic table descriptors using machine learning approaches

Beilstein Journal of Nanotechnology, 2023
Nanoparticles with their unique features have attracted researchers over the past decades. Heavy metals, upon release and emission, may interact with different environmental components, which may lead to co-exposure to living organisms.
Joyita Roy, Souvik Pore, Kunal Roy
doaj   +1 more source

Characterizing local and systemic exposure to clobetasol propionate in healthy subjects and patients with atopic dermatitis

British Journal of Clinical Pharmacology, EarlyView.
Abstract Aims There is a potential risk of systemic side‐effects with the use of potent corticosteroids, such as clobetasol propionate (CP). This concern is of particular interest in paediatric patients. The aim of this study was to develop and verify a physiologically based pharmacokinetic (PBPK) model to describe the local and systemic exposure to CP
Janna K. Duong, Sven van Dijkman, Gary Ong, Alexandra Marta, Adriana Ceci, Ernesto Bonifazi, Oscar Della Pasqua   +6 more
wiley   +1 more source

Critical insights into the potential risks of antipsychotic drugs to fish, including through effects on behaviour. [PDF]

Biol Rev Camb Philos Soc
ABSTRACT Antipsychotic drugs (APDs) are a diverse class of neuroactive pharmaceuticals increasingly detected in surface and ground waters globally. Some APDs are classified as posing a high environmental risk, due, in part, to their tendency to bioaccumulate in wildlife, including fish.
Wasser-Bennett G, Brown AR, Maynard SK, Owen SF, Tyler CR.   +4 more
europepmc   +2 more sources