Adaptive neuro-fuzzy inference system (ANFIS): A new approach to predictive modeling in QSAR applications: A study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists

2007-06-15
Buyukbingol, Erdem
Sisman, Arzu
Akyıldız, Murat
Alpaslan, Ferda Nur
Adejare, Adeboye
This paper proposes a new method, Adaptive Neuro-Fuzzy Inference System (ANFIS) to evaluate physicochemical descriptors of certain chemical compounds for their appropriate biological activities in terms of QSAR models with the aid of artificial neural network (ANN) approach combined with the principle of fuzzy logic. The ANFIS was utilized to predict NMDA (N-methyl-D-Aspartate) receptor binding activities of phencyclidine (PCP) derivatives. A data set of 38 drug-like compounds was coded with 1244 calculated molecular structure descriptors (clustered in 20 data sets) which were obtained from several sources, mainly from Dragon software. Prior to the progress to the ANFIS system, descriptors from the best subsets were selected using unsupervised forward selection (UFS) to eliminate redundancy and multicollinearity followed by fuzzy linear regression algorithm (FLR) which was used for variable selection. ANFIS was applied to train the final descriptors (Mor22m, E3s, R3v+, and Rle+) using a hybrid algorithm consisting of back-propagation and least-square estimation while the optimum number and shape of related functions were obtained through the subtractive clustering algorithm. Comparison of the proposed method with traditional methods, that is, multiple linear regression (MLR) and partial least-square (PLS) was also studied and the results indicated that the ANFIS model obtained from data sets achieved satisfactory accuracy.
BIOORGANIC & MEDICINAL CHEMISTRY

Suggestions

Robust background normalization method for one-channel microarrays
AKAL, TÜLAY; Purutçuoğlu Gazi, Vilda; Weber, Gerhard-Wilhelm (Walter de Gruyter GmbH, 2017-04-01)
Background: Microarray technology, aims to measure the amount of changes in transcripted messages for each gene by RNA via quantifying the colour intensity on the arrays. But due to the different experimental conditions, these measurements can include both systematic and random erroneous signals. For this reason, we present a novel gene expression index, called multi-RGX (Multiple-probe Robust Gene Expression Index) for one-channel microarrays.
Comparison of two inference approaches in Gaussian graphical models
Purutçuoğlu Gazi, Vilda; Wit, Ernst (Walter de Gruyter GmbH, 2017-04-01)
Introduction: The Gaussian Graphical Model (GGM) is one of the well-known probabilistic models which is based on the conditional independency of nodes in the biological system. Here, we compare the estimates of the GGM parameters by the graphical lasso (glasso) method and the threshold gradient descent (TGD) algorithm.
Effectiveness of conceptual change text-oriented instruction on students' understanding of cellular respiration concepts
Cakir, Os; Geban, Ömer; Yuruk, N (Wiley, 2002-07-01)
This study investigated the effect of conceptual change text-oriented instruction over traditional instruction on students' understanding of cellular respiration concepts and their attitudes toward biology as a school subject. The sample of this study consisted of 84 eleventh-grade students from four classes of a high school. Two of the classes were assigned randomly to the control group, and the other two classes were assigned randomly to the experimental group. During teaching the topic of cellular respir...
Compressed images for affinity prediction-2 (CIFAP-2): an improved machine learning methodology on protein-ligand interactions based on a study on caspase 3 inhibitors
Erdas, Ozlem; Andac, Cenk. A.; Gurkan-Alp, A. Selen; Alpaslan, Ferda Nur; Buyukbingol, Erdem (Informa UK Limited, 2015-01-01)
The aim of this study is to propose an improved computational methodology, which is called Compressed Images for Affinity Prediction-2 (CIFAP-2) to predict binding affinities of structurally related protein-ligand complexes. CIFAP-2 method is established based on a protein-ligand model from which computational affinity information is obtained by utilizing 2D electrostatic potential images determined for the binding site of protein-ligand complexes. The quality of the prediction of the CIFAP-2 algorithm was ...
The Karyote® Physico-Chemical Genomic, Proteomic, Metabolic Cell Modeling System
Ortoleva, P.; Berry, E.; Brun, Y.; Fan, J.; Fontus, M.; Hubbard, K.; Jaqaman, K.; Jarymowycz, L.; Navid, A.; Sayyed-Ahmad, A.; Shreif, Z.; Stanley, F.; Tuncay, Kağan; Weitzke, E.; Wu, L.-C. (Mary Ann Liebert Inc, 2003-01-01)
Modeling approaches to the dynamics of a living cell are presented that are strongly based on its underlying physical and chemical processes and its hierarchical spatio-temporal organization. Through the inclusion of a broad spectrum of processes and a rigorous analysis of the multiple scale nature of cellular dynamics, we are attempting to advance cell modeling and its applications. The presentation focuses on our cell modeling system, which integrates data archiving and quantitative physico-chemical model...
Citation Formats
E. Buyukbingol, A. Sisman, M. Akyıldız, F. N. Alpaslan, and A. Adejare, “Adaptive neuro-fuzzy inference system (ANFIS): A new approach to predictive modeling in QSAR applications: A study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists,” BIOORGANIC & MEDICINAL CHEMISTRY, pp. 4265–4282, 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36885.