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Open AccessArticle

Development of a Fingerprint-Based Scoring Function for the Prediction of the Binding Mode of Carbonic Anhydrase II Inhibitors

Department of Pharmacy, University of Pisa, 56126 Pisa, Italy
NEUROFARBA Department, Sezione di Scienze Farmaceutiche e Nutraceutiche, Università degli Studi di Firenze, Sesto Fiorentino, 50019 Florence, Italy
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2018, 19(7), 1851;
Received: 26 May 2018 / Revised: 16 June 2018 / Accepted: 20 June 2018 / Published: 23 June 2018
Carbonic anhydrase II (CAII) is a zinc-containing metalloenzyme whose aberrant activity is associated with various diseases such as glaucoma, osteoporosis, and different types of tumors; therefore, the development of CAII inhibitors, which can represent promising therapeutic agents for the treatment of these pathologies, is a current topic in medicinal chemistry. Molecular docking is a commonly used tool in structure-based drug design of enzyme inhibitors. However, there is still a need for improving docking reliability, especially in terms of scoring functions, since the complex pattern of energetic contributions driving ligand–protein binding cannot be properly described by mathematical functions only including approximated energetic terms. Here we report a novel CAII-specific fingerprint-based (IFP) scoring function developed according to the ligand–protein interactions detected in the CAII-inhibitor co-crystal structures of the most potent CAII ligands. Our IFP scoring function outperformed the ability of Autodock4 scoring function to identify native-like docking poses of CAII inhibitors and thus allowed a considerable improvement of docking reliability. Moreover, the ligand–protein interaction fingerprints showed a useful application in the binding mode analysis of structurally diverse CAII ligands. View Full-Text
Keywords: carbonic anhydrase II inhibitor; docking; scoring function carbonic anhydrase II inhibitor; docking; scoring function
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Poli, G.; Jha, V.; Martinelli, A.; Supuran, C.T.; Tuccinardi, T. Development of a Fingerprint-Based Scoring Function for the Prediction of the Binding Mode of Carbonic Anhydrase II Inhibitors. Int. J. Mol. Sci. 2018, 19, 1851.

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