Isfahan University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Application of Partial Least Squares and Radial Basis Function Neural Networks in Multivariate Imaging Analysis-Quantitative Structure Activity Relationship: Study of Cyclin Dependent Kinase 4 Inhibitors Publisher Pubmed



Saghaie L1, 2 ; Shahlaei M1, 3 ; Madadkarsobhani A4 ; Fassihi A1, 2
Authors
Show Affiliations
Authors Affiliations
  1. 1. Department of Medicinal Chemistry, Faculty of Pharmacy, Isfahan University of Medical Sciences, 81746-73461 Isfahan, Iran
  2. 2. Isfahan Pharmaceutical Sciences Research Center, 81746-73461 Isfahan, Iran
  3. 3. Department of Medicinal Chemistry, School of Pharmacy, Kermanshah University of Medical Sciences, Kermanshah, Iran
  4. 4. Department of Bioinformatics, Institute of Biophysics and Biochemistry, University of Tehran, Tehran, Iran

Source: Journal of Molecular Graphics and Modelling Published:2010


Abstract

The detailed application of multivariate image analysis (MIA) method for the evaluation of quantitative structure activity relationship (QSAR) of some cyclin dependent kinase 4 inhibitors is demonstrated. MIA is a type of data mining methods that is based on data sets obtained from 2D images. The purpose of this study is to construct a relationship between pixels of images of investigated compounds as independent and their bioactivities as a dependent variable. Partial least square (PLS) and principal components-radial basis function neural networks (PC-RBFNNs) were developed to obtain a statistical explanation of the activity of the molecules. The performance of developed models were tested by several validation methods such as external and internal tests and also criteria recommended by Tropsha and Roy. The resulted PLS model had a high statistical quality (R2 = 0.991 and RCV2=0.993) for predicting the activity of the compounds. Because of high correlation between values of predicted and experimental activities, MIA-QSAR proved to be a highly predictive approach. © 2010 Elsevier Inc. All rights reserved.
Related Docs
View other Related Docs
1. Qsar Study of Some Ccr5 Antagonists As Anti-Hiv Agents Using Radial Basis Function Neural Network and General Regression Neural Network on the Basis of Principal Components, Medicinal Chemistry Research (2012)
2. Computational Evaluation of Some Indenopyrazole Derivatives As Anticancer Compounds; Application of Qsar and Docking Methodologies, Journal of Enzyme Inhibition and Medicinal Chemistry (2013)
3. Prediction of P38 Map Kinase Inhibitory Activity of 3, 4-Dihydropyrido [3, 2-D] Pyrimidone Derivatives Using an Expert System Based on Principal Component Analysis and Least Square Support Vector Machine, Research in Pharmaceutical Sciences (2014)
4. Application of an Expert System Based on Genetic Algorithm-Adaptive Neuro-Fuzzy Inference System (Ga-Anfis) in Qsar of Cathepsin K Inhibitors, Expert Systems with Applications (2012)
5. Statistically Validated Qsar Study of Some Antagonists of the Human Ccr5 Receptor Using Least Square Support Vector Machine Based on the Genetic Algorithm and Factor Analysis, Medicinal Chemistry Research (2013)
6. Qsar Analysis for Some Diaryl-Substituted Pyrazoles As Ccr2 Inhibitors by Ga-Stepwise Mlr, Chemical Biology and Drug Design (2011)
7. Stepwise Mlr and Pcr Qsar Study of the Pharmaceutical Activities of Antimalarial 3-Hydroxypyridinone Agents Using B3lyp/6-311++G* *Descriptors, Medicinal Chemistry Research (2013)
8. Qsar and Docking Analysis of A2b Adenosine Receptor Antagonists Based on Non-Xanthine Scaffold, Medicinal Chemistry Research (2015)
Experts (# of related papers)
View all Related Experts
Afshin Fassihi (29)
Lotfollah Saghaie Dehkordi (17)
Other Related Docs
9. Quantitative Structure Activities Relationships of Some 2-Mercaptoimidazoles As Ccr2 Inhibitors Using Genetic Algorithm-Artificial Neural Networks, Research in Pharmaceutical Sciences (2013)
10. Qsar Study of Some 5-Methyl/Trifluoromethoxy-1H-Indole-2,3-Dione-3- Thiosemicarbazone Derivatives As Anti-Tubercular Agents, Research in Pharmaceutical Sciences (2009)
11. Comparative Quantitative Structure-Activity Relationship Study of Some 1-Aminocyclopentyl-3-Carboxyamides As Ccr2 Inhibitors Using Stepwise Mlr, Fa-Mlr, and Ga-Pls, Medicinal Chemistry Research (2012)
12. Validated Qsar Analysis of Some Diaryl Substituted Pyrazoles As Ccr2 Inhibitors by Various Linear and Nonlinear Multivariate Chemometrics Methods, European Journal of Medicinal Chemistry (2010)
13. Deep Neural Network in Qsar Studies Using Deep Belief Network, Applied Soft Computing Journal (2018)
14. A Modeling Study of Aldehyde Inhibitors of Human Cathepsin K Using Partial Least Squares Method, Research in Pharmaceutical Sciences (2011)
15. Linear and Nonlinear Qsar Modeling of 1,3,8-Substituted-9-Deazaxanthines As Potential Selective A2bar Antagonists, Medicinal Chemistry Research (2013)
16. Qsar Analysis of Some 1-(3,3-Diphenylpropyl)-Piperidinyl Amides and Ureas As Ccr5 Inhibitors Using Genetic Algorithm-Least Square Support Vector Machine, Medicinal Chemistry Research (2013)
17. Prediction of Partition Coefficient of Some 3-Hydroxy Pyridine-4-One Derivatives Using Combined Partial Least Square Regression and Genetic Algorithm, Research in Pharmaceutical Sciences (2014)
18. A Qsar Study of Some Cyclobutenediones As Ccr1 Antagonists by Artificial Neural Networks Based on Principal Component Analysis, DARU, Journal of Pharmaceutical Sciences (2011)
19. Accelerating Big Data Analysis Through Lasso-Random Forest Algorithm in Qsar Studies, Bioinformatics (2022)
20. Identification of New Potential Candidates to Inhibit Egf Via Machine Learning Algorithm, European Journal of Pharmacology (2024)
21. Study of Cxcr4 Chemokine Receptor Inhibitors Using Qspr and Molecular Docking Methodologies, Journal of Theoretical and Computational Chemistry (2019)
22. Docking and Qsar Studies of Some Quinazolinone Derivatives As Possible Inhibitors of Thyrosine Kinase, Turkish Computational and Theoretical Chemistry (2022)
23. A Deep Learning Model Based on the Bert Pre-Trained Model to Predict the Antiproliferative Activity of Anti-Cancer Chemical Compounds, SAR and QSAR in Environmental Research (2024)
24. A Quantitative Structure-Activity Relationship (Qsar) Study of Some Diaryl Urea Derivatives of B-Raf Inhibitors, Research in Pharmaceutical Sciences (2016)
25. Identification of Essential 2D and 3D Chemical Features for Discovery of the Novel Tubulin Polymerization Inhibitors, Current Topics in Medicinal Chemistry (2019)
26. Classification and Similarity Analysis of Binding-Database: A Survey on Application of Multi-Class Classifiers for Deriving General Rules From Large Compound Databases, Journal of Isfahan Medical School (2017)
27. Application of Artificial Neural Networks in Controlled Drug Delivery Systems, Applied Artificial Intelligence (2010)
28. The Artificial Neural Network-Based Qspr and Dft Prediction of Lipophilicity for Thioguanine, Main Group Chemistry (2022)
29. Qsar Study of Anthranilic Acid Sulfonamides As Inhibitors of Methionine Aminopeptidase-2 Using Ls-Svm and Grnn Based on Principal Components, European Journal of Medicinal Chemistry (2010)
30. Molecular Modelling Study on Pyrrolo[2,3-B]Pyridine Derivatives As C-Met Kinase Inhibitors: A Combined Approach Using Molecular Docking, 3D-Qsar Modelling and Molecular Dynamics Simulation, Molecular Simulation (2020)
31. Protein Kinase Inhibitors’ Classification Using K-Nearest Neighbor Algorithm, Computational Biology and Chemistry (2020)
32. Qsar Study of Pett Derivatives As Potent Hiv-1 Reverse Transcriptase Inhibitors, Journal of Molecular Graphics and Modelling (2009)
33. In Silico Screening for Novel Tyrosine Kinase Inhibitors With Oxindole Scaffold As Anti-Cancer Agents: Design, Qsar Analysis, Molecular Docking and Admet Studies, Journal of Computational Biophysics and Chemistry (2022)
34. Qsar Study of Antimicrobial 3-Hydroxypyridine-4-One and 3-Hydroxypyran-4-One Derivatives Using Different Chemometric Tools, International Journal of Molecular Sciences (2008)
35. Qsar Study of Isatin Analogues As in Vitro Anti-Cancer Agents, European Journal of Medicinal Chemistry (2010)
36. Estimation of Betamethasone Release Profiles From an in Situ Forming System Based on the Biodegradable Polymer Using Artificial Neural Networks, IFMBE Proceedings (2009)
37. Qsar Study of Anthranilic Acid Sulfonamides As Methionine Aminopeptidase-2 Inhibitors, Monatshefte fur Chemie (2012)
38. Application of Pc-Ann and Pc-Ls-Svm in Qsar of Ccr1 Antagonist Compounds: A Comparative Study, European Journal of Medicinal Chemistry (2010)
39. A Gu‑Net‑Based Architecture Predicting Ligand–Protein‑Binding Atoms, Journal of Medical Signals and Sensors (2023)
40. Qsar Study of P56 Lck Protein Tyrosine Kinase Inhibitory Activity of Flavonoid Derivatives Using Mlr and Ga-Pls, International Journal of Molecular Sciences (2008)
41. Computer-Aided Design of Novel Antibacterial 3-Hydroxypyridine-4-Ones: Application of Qsar Methods Based on the Molmap Approach, Journal of Computer-Aided Molecular Design (2012)