Results 1 to 10 of about 387,110 (116)

Predicting Antimicrobial Peptide Activity: A Machine Learning-Based Quantitative Structure–Activity Relationship Approach [PDF]

Pharmaceutics
Background: Peptides are a class of molecules that can be presented as good antimicrobials and with mechanisms that avoid resistance, and the design of peptides with good activity can be complex and laborious.
Eliezer I. Bonifacio-Velez de Villa, María E. Montoya-Alfaro, Luisa P. Negrón-Ballarte, Christian Solis-Calero   +3 more
doaj   +2 more sources

AdapTor: Adaptive Topological Regression for quantitative structure–activity relationship modeling [PDF]

Journal of Cheminformatics
Quantitative structure–activity relationship (QSAR) modeling has become a critical tool in drug design. Recently proposed Topological Regression (TR), a computationally efficient and highly interpretable QSAR model that maps distances in the chemical ...
Yixiang Mao, Souparno Ghosh, Ranadip Pal
doaj   +2 more sources

Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study [PDF]

BioImpacts, 2023
Introduction: Machine learning methods, coupled with a tremendous increase in computer power in recent years, are promising tools in modern drug design and drug repurposing.
Jurica Novak, Alena R. Zykova, Vladimir A. Potemkin, Vladimir V. Sharutin, Olga K. Sharutina   +4 more
doaj   +2 more sources

3D-QSAR-based pharmacophore determination and design of novel DPP-4 inhibitors [PDF]

Scripta Medica, 2022
Background/Aim: Therapy of diabetes mellitus type 2 includes drugs that act as inhibitors of dipeptidyl peptidase 4 (DPP-4) enzyme. Several DPP-4 inhibitors are marketed today and although they have favourable safety profile and tolerability, they show ...
Rogić Sanja, Gagić Žarko
doaj   +1 more source

QSAR studies for the acute toxicity of nitrobenzenes to the Tetrahymena pyriformis [PDF]

Journal of the Serbian Chemical Society, 2014
Quantitative structure-activity relationship (QSAR) models play a key role in finding the relationship between molecular structures and the toxicity of nitrobenzenes to Tetrahymena pyriformis.
Wang Dan-Dan, Feng Lin-Lin, He Guang-Yu, Chen Hai-Qun   +3 more
doaj   +1 more source

Design of cinnamaldehyde amino acid Schiff base compounds based on the quantitative structure–activity relationship [PDF]

Royal Society Open Science, 2017
Cinnamaldehyde amino acid Schiff base (CAAS) is a new class of safe, bioactive compounds which could be developed as potential antifungal agents for fungal infections.
Hui Wang, Mingyue Jiang, Shujun Li, Chung-Yun Hse, Chunde Jin, Fangli Sun, Zhuo Li   +6 more
doaj   +1 more source

QSAR, QSTR, and molecular docking studies of the anti-proliferative activity of phenylpiperazine derivatives against DU145 prostate cancer cell lines

Beni-Suef University Journal of Basic and Applied Sciences, 2020
Background Prostate cancer is the most common non-cutaneous cancer in males and accounts for about 4% of all cancer-related deaths in males annually.
Fabian A. Ikwu, Gideon A. Shallangwa, Paul A. Mamza   +2 more
doaj   +1 more source

Correlation between the lipophilicity and antifungal activity of some benzoxazole derivatives [PDF]

Acta Periodica Technologica, 2010
In the present work, a quantitative relationship between the lipophilicity and antifungal activity of some benzoxazole derivatives against Candida albicans was investigated by using QSAR (quantitative structure-activity relationship) analyses.
Podunavac-Kuzmanović Sanja O., Velimirović Sonja D.   +1 more
doaj   +1 more source

Quantitative Structure Activity Relationship Models for the Antioxidant Activity of Polysaccharides. [PDF]

PLoS ONE, 2016
In this study, quantitative structure activity relationship (QSAR) models for the antioxidant activity of polysaccharides were developed with 50% effective concentration (EC50) as the dependent variable.
Zhiming Li, Kaiying Nie, Zhaojing Wang, Dianhui Luo   +3 more
doaj   +1 more source

Improving the Biological Activity Prediction of Acetylcholinesterase and Butyl Cholinesterase Inhibitors Using Nonlinear Random Forest Algorithm

مجله دانشکده پزشکی اصفهان, 2020
Background: Due to the growing population of the elderly and the increasing trend of Alzheimer's disease, evaluation of acetylcholinesterase (AChE) and butyl cholinesterase (BChE) inhibitors, as major causes of Alzheimer's disease, is essential.
Fahimeh Motamedi, Alireza mehri Mehridehnavi, Fahimeh Ghasemi   +2 more
doaj   +1 more source