Results 21 to 30 of about 16,010 (186)

2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors [PDF]

BioMed Research International, 2017
Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine
Manman Zhao, Lin Wang, Linfeng Zheng, Mengying Zhang, Chun Qiu, Yuhui Zhang, Dongshu Du, Bing Niu   +7 more
openaire   +2 more sources

Acidity of HOCN, HSCN, HNCO, HNCS: A treatment from the viewpoint of ab initio approach [PDF]

Journal of the Serbian Chemical Society, 2005
The electronic structures of the molecules HOCN, HSCN, HNCO, HNCS and the anions OCN -, SCN - have been investigated ab initio at the RHF/6-31G(d) RHF/6-31G(d,p), MP2/6-31G(d)//RHF/6-31G(d) and MP2/6-31G(d,p)//RHF/6-31G(d,p) theory levels.
Pankratov Alexei N., Khmelev Sergei S.
doaj   +1 more source

Virtual docking screening and QSAR studies to explore AKT and mTOR inhibitors acting on PI3K in cancers

Contemporary Oncology, 2020
The phosphoinositide 3-kinase (PI3K) pathway is an important regulator of cell proliferation and metabolism. PI3K activation initiates a signal transduction cascade, of which the major effectors are the kinases AKT and mTOR.
Ilham Kandoussi, Oussama Benherrif, Wiame Lakhlili, Jamal Taoufik, Azeddine Ibrahimi   +4 more
doaj   +1 more source

Approaches to predict ligands affinity towards translocator protein TSPO 18 kDa in order to create molecules possessing neuropsychotropic activity

Фармакокинетика и Фармакодинамика, 2019
Predict of anxiolytic activity and affinity for the translocator protein (TSPO), compounds in the 1-arylpyrrolo[1,2-a]pyrazine-3-carboxamide series by QSAR (Quantitative structure-activity relationship) and molecular docking was carried out.
N. M. Baraboshkin, A. S. Pantileev, G. V. Mokrov   +2 more
doaj   +1 more source

QSAR based on hybrid optimal descriptors as a tool to predict antibacterial activity against Staphylococcus aureus

Frontiers in Bioscience-Landmark, 2022
Background: Staphylococcus aureus bacterial infections are still a serious health care problem. Therefore, the development of new drugs for these infections is a constant requirement. Quantitative structure–activity relationship (QSAR) methods can assist
Karel Nesměrák, Andrey Toropov, Ilkay Yildiz   +2 more
doaj   +1 more source

QSAR Analysis of Natural Lupeol Analogs as Antimalarial agents [PDF]

BIO Web of Conferences
Malaria is an infectious disease that affects millions of people caused by Plasmodium parasite. The growing Plasmodium resistance underscores existing antimalarial drugs and necessities novel antimalarial drugs with high efficiency. Lupeol is a naturally
Rajathei David Mary
doaj   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Dual‐Substrate Synergistic Photocatalysis: Exogenous Reagent‐Free Co‐Removal of Phenol and Cr(VI) via Electron‐Donor‐Mediated Redox Coupling over Modified Carbon Nitride

Advanced Science, EarlyView.
An exogenous reagent‐free dual‐substrate strategy harnesses phenol as an intrinsic electron donor to drive synchronous phenol degradation and Cr(VI) reduction over modified carbon nitride. π–π stacking and hydrogen bonding direct electron transfer to the catalyst, enriching photogenerated electrons and accelerating Cr(VI) reduction 6.4‐fold. This waste‐
Xiaoman Zhang, Qiyu Wang, Xiaodan Liu, Shuqi Wan, Cuiwei Du, Qilu Li, Chongfei Yu, Shuying Dong, Xianfa Su, Chun Hu   +9 more
wiley   +1 more source

Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction

Advanced Science, EarlyView.
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen, Guancen Lin, Chuan‐Shen Hu, Yong Wang   +3 more
wiley   +1 more source

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