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Int. J. Mol. Sci. 2012, 13(6), 6665-6678; doi:10.3390/ijms13066665

Pharmacological Classification and Activity Evaluation of Furan and Thiophene Amide Derivatives Applying Semi-Empirical ab initio Molecular Modeling Methods

1
POLPHARMA SA Pharmaceutical Works, Starogard Gdanski 83-200, Poland
2
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Medical University of Gdansk, Gdansk 80-416, Poland
3
Department of Health Sciences, Division of Human Anatomy and Physiology, Pomeranian University of Slupsk, Slupsk 76-200, Poland
*
Author to whom correspondence should be addressed.
Received: 23 April 2012 / Revised: 16 May 2012 / Accepted: 21 May 2012 / Published: 30 May 2012
(This article belongs to the Special Issue Advances in Biomolecular Simulation)
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Abstract

Pharmacological and physicochemical classification of the furan and thiophene amide derivatives by multiple regression analysis and partial least square (PLS) based on semi-empirical ab initio molecular modeling studies and high-performance liquid chromatography (HPLC) retention data is proposed. Structural parameters obtained from the PCM (Polarizable Continuum Model) method and the literature values of biological activity (antiproliferative for the A431 cells) expressed as LD50 of the examined furan and thiophene derivatives was used to search for relationships. It was tested how variable molecular modeling conditions considered together, with or without HPLC retention data, allow evaluation of the structural recognition of furan and thiophene derivatives with respect to their pharmacological properties. View Full-Text
Keywords: furan derivatives; thiophene derivatives; HPLC; molecular modeling; structural analysis furan derivatives; thiophene derivatives; HPLC; molecular modeling; structural analysis
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Bober, L.; Kawczak, P.; Baczek, T. Pharmacological Classification and Activity Evaluation of Furan and Thiophene Amide Derivatives Applying Semi-Empirical ab initio Molecular Modeling Methods. Int. J. Mol. Sci. 2012, 13, 6665-6678.

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