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Computational Analysis of CRTh2 receptor antagonist: A Ligand-based CoMFA and CoMSIA approach.
Comput Biol Chem. 2015 Jun; 56:109-21.CB

Abstract

CRTh2 receptor is an important mediator of inflammatory effects and has attracted much attention as a therapeutic target for the treatment of conditions such as asthma, COPD, allergic rhinitis and atopic dermatitis. In pursuit of better CRTh2 receptor antagonist agents, 3D-QSAR studies were performed on a series of 2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl) acetic acids. There is no crystal structure information available on this protein; hence in this work, ligand-based comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed by atom by atom matching alignment using systematic search and simulated annealing methods. The 3D-QSAR models were generated with 10 different combinations of test and training set molecules, since the robustness and predictive ability of the model is very important. We have generated 20 models for CoMFA and 100 models for CoMSIA based on two different alignments. Each model was validated with statistical cut off values such as q(2)>0.4, r(2)>0.5 and r(2)pred>0.5. Based on better q(2) and r(2)pred values, the best predictions were obtained for the CoMFA (model 5 q(2)=0.488, r(2)pred=0.732), and CoMSIA (model 45 q(2)=0.525, r(2)pred=0.883) from systematic search conformation alignment. The high correlation between the cross-validated/predicted and experimental activities of a test set revealed that the CoMFA and CoMSIA models were robust. Statistical parameters from the generated QSAR models indicated the data is well fitted and have high predictive ability. The generated models suggest that steric, electrostatic, hydrophobic, H-bond donor and acceptor parameters are important for activity. Our study serves as a guide for further experimental investigations on the synthesis of new CRTh2 antagonist.

Authors+Show Affiliations

Department of Bioinformatics, School of Bioengineering, SRM University, SRM Nagar, Kattankulathur, Chennai 603203, India.Department of Chemistry and Department of Carbon Materials, Chosun University, Gwangju 501-759, South Korea. Electronic address: hsohn@chosun.ac.kr.Department of Bioinformatics, School of Bioengineering, SRM University, SRM Nagar, Kattankulathur, Chennai 603203, India. Electronic address: thiru.murthyunom@gmail.com.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

25935115

Citation

Babu, Sathya, et al. "Computational Analysis of CRTh2 Receptor Antagonist: a Ligand-based CoMFA and CoMSIA Approach." Computational Biology and Chemistry, vol. 56, 2015, pp. 109-21.
Babu S, Sohn H, Madhavan T. Computational Analysis of CRTh2 receptor antagonist: A Ligand-based CoMFA and CoMSIA approach. Comput Biol Chem. 2015;56:109-21.
Babu, S., Sohn, H., & Madhavan, T. (2015). Computational Analysis of CRTh2 receptor antagonist: A Ligand-based CoMFA and CoMSIA approach. Computational Biology and Chemistry, 56, 109-21. https://doi.org/10.1016/j.compbiolchem.2015.04.007
Babu S, Sohn H, Madhavan T. Computational Analysis of CRTh2 Receptor Antagonist: a Ligand-based CoMFA and CoMSIA Approach. Comput Biol Chem. 2015;56:109-21. PubMed PMID: 25935115.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Computational Analysis of CRTh2 receptor antagonist: A Ligand-based CoMFA and CoMSIA approach. AU - Babu,Sathya, AU - Sohn,Honglae, AU - Madhavan,Thirumurthy, Y1 - 2015/04/20/ PY - 2014/08/28/received PY - 2015/04/07/revised PY - 2015/04/18/accepted PY - 2015/5/4/entrez PY - 2015/5/4/pubmed PY - 2016/2/18/medline KW - 3D-QSAR KW - CRTh2 KW - CoMFA KW - CoMSIA SP - 109 EP - 21 JF - Computational biology and chemistry JO - Comput Biol Chem VL - 56 N2 - CRTh2 receptor is an important mediator of inflammatory effects and has attracted much attention as a therapeutic target for the treatment of conditions such as asthma, COPD, allergic rhinitis and atopic dermatitis. In pursuit of better CRTh2 receptor antagonist agents, 3D-QSAR studies were performed on a series of 2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl) acetic acids. There is no crystal structure information available on this protein; hence in this work, ligand-based comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed by atom by atom matching alignment using systematic search and simulated annealing methods. The 3D-QSAR models were generated with 10 different combinations of test and training set molecules, since the robustness and predictive ability of the model is very important. We have generated 20 models for CoMFA and 100 models for CoMSIA based on two different alignments. Each model was validated with statistical cut off values such as q(2)>0.4, r(2)>0.5 and r(2)pred>0.5. Based on better q(2) and r(2)pred values, the best predictions were obtained for the CoMFA (model 5 q(2)=0.488, r(2)pred=0.732), and CoMSIA (model 45 q(2)=0.525, r(2)pred=0.883) from systematic search conformation alignment. The high correlation between the cross-validated/predicted and experimental activities of a test set revealed that the CoMFA and CoMSIA models were robust. Statistical parameters from the generated QSAR models indicated the data is well fitted and have high predictive ability. The generated models suggest that steric, electrostatic, hydrophobic, H-bond donor and acceptor parameters are important for activity. Our study serves as a guide for further experimental investigations on the synthesis of new CRTh2 antagonist. SN - 1476-928X UR - https://www.unboundmedicine.com/medline/citation/25935115/Computational_Analysis_of_CRTh2_receptor_antagonist:_A_Ligand_based_CoMFA_and_CoMSIA_approach_ DB - PRIME DP - Unbound Medicine ER -