1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 DOI: 10.1002/minf.201800090 A QSAR Study for Analgesic and Anti-inflammatory Activities of 5-/6-Acyl-3-alkyl-2-Benzoxazolinone Derivatives Gulcin Tugcu* [a] and Meric Koksal [b] This paper is dedicated to Prof. Paola Gramatica on the occasion of her retirement. Abstract: In this publication, QSAR models were developed to predict analgesic and anti-inflammatory activities of some 2-benzoxazolinone derivatives using multiple linear regression method. The models were validated internally and externally according to the OECD principles. With the help of these models, pronounced molecular properties of these compounds related to activities were also explored. The developed models demonstrated that hydrophobicity, the number of halogens, and the shape of the molecular structure of these candidate drugs are prominent to represent analgesic and anti-inflammatory activities. Based on the previously tested compounds and the developed models, 77 new compounds were designed as potential analgesic and anti-inflammatory drugs. Majority of the newly designed compounds demonstrated promising an- algesic and anti-inflammatory activity. Keywords: 2-benzoxazolinones · analgesic · anti-inflammatory · drug design · QSAR 1 Introduction Nonsteroidal anti-inflammatory drugs (NSAIDs), which are used for the treatment of inflammation, pain, and fever, are widely prescribed and available for over-the-counter sale worldwide. Long term administration of NSAIDs frequently causes gastric side effects because of nonselective inhibition of cyclooxygenases (COXs). [1] Anti-inflammatory activity of NSAIDs was reported to accompany analgesic potency of the same drugs. [2] Both complex characteristic of these activities and variable benefit/risk profile of existing NSAIDs create a valid approach and need for development of more potent and safer novel drug candidates. Different strategies, such as chemical modifications and in silico studies, are used to improve the safety profile and the chemical/biological activity of a lead compound. The strategy involving Quantitative Structure Activity Relation- ship (QSAR), which processes a molecular structure with a well-defined property such as lipophilicity or polarizability, is generally effective to predict biological activity. [3,4] Most QSAR models are formally-developed predictive mathemat- ical models relating the molecular structure of a compound with a particular activity. [5] Such models predict the activities of the compounds on the basis that similar compounds have similar activities. In addition, they may also be helpful in explaining the mechanism of the studied activity in a biological system. Arising from their in silico nature, QSAR studies are expected to reduce the cost and the number of animals used for testing [6] as well as shorten the duration of testing. Several requirements and principles are defined formally for the design of a QSAR model. According to the OECD principles, a QSAR model should have appropriate measures of goodness-of-fit, robustness, and predictivity for a reliable model associated with the following information: 1 a defined endpoint, 2 an unambiguous algorithm, 3 a defined domain of applicability, 4 appropriate measures of goodness-of-fit, robustness, and predictivity, and 5 a mechanistic interpretation, if possible. [7] The generation of a proper QSAR model is based on the quality of the activity data used for modeling. However, the development of QSAR models using compiled data from the literature has the risk of yielding misleading results originating from the discrepancies between laboratories. Therefore, high quality experimental data generated in the [a] G. Tugcu Department of Toxicology Faculty of Pharmacy Yeditepe University 34755 Atasehir, Istanbul, Turkey phone/fax: 90 216 578000090/90 216 5780299 E-mail: gulcin.tugcu@yeditepe.edu.tr [b] M. Koksal Department of Pharmaceutical Chemistry Faculty of Pharmacy Yeditepe University 34755 Atasehir, Istanbul, Turkey Supporting information for this article is available on the WWW under https://doi.org/10.1002/minf.201800090 Full Paper www.molinf.com © 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim Mol. Inf. 2019, 38, 1800090 (1 of 9) 1800090