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      Design and prediction of new anticoagulants as a selective Factor IXa inhibitor via three-dimensional quantitative structure-property relationships of amidinobenzothiophene derivatives

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          Factor IXa (FIXa), a blood coagulation factor, is specifically inhibited at the initiation stage of the coagulation cascade, promising an excellent approach for developing selective and safe anticoagulants. Eighty-four amidinobenzothiophene antithrombotic derivatives targeting FIXa were selected to establish three-dimensional quantitative structure–activity relationship (3D-QSAR) and three-dimensional quantitative structure–selectivity relationship (3D-QSSR) models using comparative molecular field analysis and comparative similarity indices analysis methods. Internal and external cross-validation techniques were investigated as well as region focusing and bootstrapping. The satisfactory q 2 values of 0.753 and 0.770, and r 2 values of 0.940 and 0.965 for 3D-QSAR and 3D-QSSR, respectively, indicated that the models are available to predict both the inhibitory activity and selectivity on FIXa against Factor Xa, the activated status of Factor X. This work revealed that the steric, hydrophobic, and H-bond factors should appropriately be taken into account in future rational design, especially the modifications at the 2′-position of the benzene and the 6-position of the benzothiophene in the R group, providing helpful clues to design more active and selective FIXa inhibitors for the treatment of thrombosis. On the basis of the three-dimensional quantitative structure–property relationships, 16 new potent molecules have been designed and are predicted to be more active and selective than Compound 33, which has the best activity as reported in the literature.

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          Most cited references 27

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          Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.

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            Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity.

            An alternative approach is reported to compute property fields based on similarity indices of drug molecules that have been brought into a common alignment. The fields of different physicochemical properties use a Gaussian-type distance dependence, and no singularities occur at the atomic positions. Accordingly, no arbitrary definitions of cutoff limits and deficiencies due to different slopes of the fields are encountered. The fields are evaluated by a PLS analysis similar to the CoMFA formalism. Two data sets of steroids binding to the corticosteroid-binding-globulin and thermolysin inhibitors were analyzed in terms of the conventional CoMFA method (Lennard-Jones and Coulomb potential fields) and the new comparative molecular similarity indices analysis (CoMSIA). Models of comparative statistical significance were obtained. Field contribution maps were produced for the different models. Due to cutoff settings in the CoMFA fields and the steepness of the potentials close to the molecular surface, the CoMFA maps are often rather fragmentary and not contiguously connected. This makes their interpretation difficult. The maps obtained by the new CoMSIA approach are superior and easier to interpret. Whereas the CoMFA maps denote regions apart from the molecules where interactions with a putative environment are to be expected, the CoMSIA maps highlight those regions within the area occupied by the ligand skeletons that require a particular physicochemical property important for activity. This is a more significant guide to trace the features that really matter especially with respect to the design of novel compounds.
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              Three-dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factor Xa.

              Three-dimensional quantitative structure-activity relationship (3D QSAR) methods were applied using a training set of 72 inhibitors of the benzamidine type with respect to their binding affinities (Ki values) toward thrombin, trypsin, and factor Xa to yield statistically reliable models of good predictive power. Two methods were compared: the widely used comparative molecular field analysis (CoMFA) and the recently reported CoMSIA approach (comparative molecular similarity indices analysis). CoMSIA produced significantly better results for all correlations. Furthermore, in contrast to CoMFA, CoMSIA is not sensitive to changes in orientation of the superimposed molecules in the lattice. The correlation results obtained by CoMSIA were graphically interpreted in terms of field contribution maps allowing physicochemical properties relevant for binding to be easily mapped back onto molecular structures. The advantage of this feature is demonstrated using the maps to design new molecules. Finally, the CoMSIA method was applied to elucidate structural features among ligands which are responsible for affinity differences toward thrombin and trypsin. These selectivity-determining features were interpreted graphically in terms of spatial regions responsible for affinity discrimination. Such indicators are highly informative for the lead optimization process with respect to selectivity enhancement.

                Author and article information

                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                Drug Design, Development and Therapy
                Dove Medical Press
                23 March 2015
                : 9
                : 1743-1759
                [1 ]Guangdong Province Key Laboratory of Pharmacodynamic Constituents of Traditional Chinese Medicine and New Drugs Research, College of Pharmacy, Jinan University, Guangzhou, People’s Republic of China
                [2 ]College of Pharmacy, China Pharmaceutical University, Nanjing, People’s Republic of China
                [3 ]Department of Chemistry, Wayne State University, Detroit, Michigan, USA
                [4 ]College of Pharmacy, University of South Florida, Tampa, FL, USA
                Author notes
                Correspondence: Shu-Feng Zhou, College of Pharmacy, University of South Florida, Tampa, FL 33612, USA, Tel +1 813 974 5699, Fax +1 813 9059890, Email szhou@
                Ping-Hua Sun, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of Traditional Chinese Medicine and New Drugs Research, College of Pharmacy, Jinan University, Guangzhou 510632, People’s Republic of China, Tel +86 20 8522 1367, Fax +86 20 8522 4766, Email biochemdoctor@

                *These authors contributed equally to this work

                © 2015 Gao et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License

                The full terms of the License are available at Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Original Research

                Pharmacology & Pharmaceutical medicine

                benzothiophene antithrombosis, comfa, comsia, 3d-qsar, 3d-qssr


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