Article
Agriculture, Multidisciplinary
Xin Yang, Tian Wang, Petar Zuvela, Mingtai Sun, Chunyuhang Xu, Hongling Zheng, Xiang Wang, Linzhi Jing, Ke Du, Suhua Wang, Ming Wah Wong, Dejian Huang
Summary: Flavonoids, as effective hypochlorite scavengers, exhibit a clear relationship between their structure and activity.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2022)
Article
Chemistry, Medicinal
Tarapong Srisongkram
Summary: A stacked ensemble quantitative read-across structure-activity relationship algorithm was developed for predicting skin irritation toxicity, and its reliability and accuracy were validated using validation and test datasets.
CHEMICAL RESEARCH IN TOXICOLOGY
(2023)
Article
Engineering, Environmental
Yawei Liu, Zhiwen Cheng, Shiqiang Liu, Yuanyang Ren, Tao Yuan, Xuxiang Zhang, Maohong Fan, Zhemin Shen
Summary: A QSAR model was established to predict the rate constant (kNO3) for the chemical degradation of VOCs using the kNO3 of 189 VOCs and quantum chemical parameters. The model revealed that EHOMO and f(-)x were the key intrinsic factors determining kNO3, while EGAP, f(0)n, and BOx also significantly affected kNO3.
CHEMICAL ENGINEERING JOURNAL
(2022)
Article
Engineering, Environmental
Yan Liu, Jianfa Gao, Qingyao Zhu, Xi Zhou, Wenhai Chu, Jingxiong Huang, Changkun Liu, Bo Yang, Mengting Yang
Summary: This study reports the effective degradation of halogenated aromatic disinfection byproducts (DBPs) by ZVI/Cu and establishes a novel mechanism-based quantitative structure-activity relationship model to predict degradation rate constants. The study found that ZVI/Cu can effectively degrade not only aliphatic DBPs but also new emerging aromatic DBPs formed in chlorinated and chloraminated drinking water. A quantitative structure-activity relationship model was developed to predict the degradation rate constants of other aromatic DBPs, and optimized descriptors were identified.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Review
Biochemistry & Molecular Biology
Tao Huang, Guohui Sun, Lijiao Zhao, Na Zhang, Rugang Zhong, Yongzhen Peng
Summary: Nitroaromatic compounds are widely present in the environment due to industrial use, posing potential threats to human health and the environment. Quantitative structure-activity relationship (QSAR) is introduced as a cost-effective tool to predict their toxicity and reduce animal testing. However, systematic reviews on the QSAR modeling of NACs toxicity are less reported.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Environmental Sciences
M. Sigurnjak Bures, S. Ukic, M. Cvetnic, V. Prevaric, M. Markic, M. Rogosic, H. Kusic, T. Bolanca
Summary: The study focuses on developing QSAR models to predict the toxicity of binary mixtures towards bioluminescent bacteria Vibrio fischeri. The models successfully predict toxicity and identify factors influencing toxicity levels. The analysis of descriptors in the models provides insight into toxic mechanisms of binary systems.
ENVIRONMENTAL POLLUTION
(2021)
Review
Nanoscience & Nanotechnology
Ewelina Wyrzykowska, Alicja Mikolajczyk, Iseult Lynch, Nina Jeliazkova, Nikolay Kochev, Haralambos Sarimveis, Philip Doganis, Pantelis Karatzas, Antreas Afantitis, Georgia Melagraki, Angela Serra, Dario Greco, Julia Subbotina, Vladimir Lobaskin, Miguel A. Banares, Eugenia Valsami-Jones, Karolina Jagiello, Tomasz Puzyn
Summary: This Review discusses the importance of a comprehensive system for defining nanomaterial descriptors in enabling a safe-and-sustainable-by-design concept for engineered nanomaterials. The unique nanoscale properties of engineered nanomaterials can pose risks to human health and the environment, making it crucial to design new nanomaterials with safety and sustainability in mind. Physicochemical characteristics, such as chemical composition and size, play a key role in the biological activity of nanomaterials, and nanodescriptors can be used to optimize their functionality and minimize health and environmental hazards. The successful integration of experimental data and computational models is essential for the safe adoption of nanomaterials on a large scale.
NATURE NANOTECHNOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Stefan M. Kohlbacher, Thierry Langer, Thomas Seidel
Summary: QSAR methods are commonly used in drug discovery, where pharmacophores provide advantageous properties for building quantitative SAR models that can generalize to different datasets with low requirements.
JOURNAL OF CHEMINFORMATICS
(2021)
Article
Oncology
Serenella Medici, Massimiliano Peana, Alessio Pelucelli, Maria Antonietta Zoroddu
Summary: Despite the increasing number and variety of nanoparticles, there is still a lack of clear guidelines to control their exposure and evaluate potential toxicity. The issue of nanomaterials' toxicity is gaining awareness among scientists and producers, yet consumers often remain largely unaware of the presence and potential risks of nanomaterials.
SEMINARS IN CANCER BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Philipe de Oliveira Fernandes, Joao Paulo A. Martins, Eduardo B. de Melo, Renata Barbosa de Oliveira, Thales Kronenberger, Vinicius Goncalves Maltarollo
Summary: The study suggests that aliphatic substituents at the hydrazone moiety are crucial for the antifungal activity of thiazolylhydrazones. Modern techniques were used to create QSAR models with high predictive power, supporting the design of new antifungal compounds.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2022)
Article
Engineering, Environmental
Mainak Chatterjee, Kunal Roy
Summary: This study developed three different mixture-Quantitative Structure-Activity Relationship (mixture-QSAR) models for three different bacterial species. Interspecies modeling was explored to find inter-correlation among the toxicity of the studied organisms, and quantitative structure activity-activity relationship (QSAAR) models were developed. All the models were validated using internal and external validation tests as suggested in the OECD guidelines.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Engineering, Environmental
Yawei Liu, Yujia Tan, Zhiwen Cheng, Shiqiang Liu, Yuanyang Ren, Xuejun Chen, Maohong Fan, Zhemin Shen
Summary: QSAR modeling is a promising tool for guiding the development of environmental technologies. This study explores the characteristics and differences of six coagulation systems in removing dyes, revealing the dominant degradation processes and adsorption mechanisms.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Environmental Sciences
Venkata Sai Reddy Ramireddy, Rakshitha Kurakula, Padmanaban Velayudhaperumal Chellam, Anina James, Eric D. van Hullebusch
Summary: The present study analyzes the degraded products of three azo dyes and predicts their toxicity using in silico methods. The results suggest that the degradation products are toxic and may accumulate in the environment. Proper treatment of these products is crucial.
ENVIRONMENTAL RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Ajaykumar Gandhi, Vijay Masand, Magdi E. A. Zaki, Sami A. Al-Hussain, Anis Ben Ghorbal, Archana Chapolikar
Summary: In this study, a quantitative structure-activity relationships (QSAR) model was developed for 219 in vitro MDA-MB-231 TNBC cell antagonists, identifying significant structural features governing anti-tumor activity. The GA-MLR methodology was utilized to build highly predictive QSAR models that adhered to OECD guidelines and demonstrated robust statistical parameters above threshold values. These validated QSAR models exhibit a balance of description and statistical approaches, proving their utility in the development of MDA-MB-231 TNBC cell antagonists.
Article
Biochemical Research Methods
Vishakha Gautam, Rahul Gupta, Deepti Gupta, Anubhav Ruhela, Aayushi Mittal, Sanjay Kumar Mohanty, Sakshi Arora, Ria Gupta, Chandan Saini, Debarka Sengupta, Natarajan Arul Murugan, Gaurav Ahuja
Summary: deepGraphh is a one-stop web service that offers a variety of graph-based methods for model generation and prediction in chemoinformatics.
BRIEFINGS IN BIOINFORMATICS
(2022)
