Abstract
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.
Highlights
Carbonic anhydrases (CAs) belong to the superfamily of ubiquitous metalloenzymes and are characterized by the presence of a zinc metal ion in their active sites [1]
Based on the main ligand–protein interactions detected in the carbonic anhydrase II (CAII)-inhibitor co-crystal structures of the most active CAII ligands, we generated ligand–protein interaction fingerprints (IFPs) that were used to develop an efficient and reliable post-docking procedure, which was able to identify native-like binding poses of CAII inhibitors better than Autodock4 scoring function
The use of our IFP-based scoring function allowed the prediction of docking solutions with an average root-mean-square deviation (aRMSD) about 30% lower than that obtained by using Autodock4 scoring function and increased about 13% the number of reliable docking solutions
Summary
Carbonic anhydrases (CAs) belong to the superfamily of ubiquitous metalloenzymes and are characterized by the presence of a zinc metal ion in their active sites [1]. Very often the standard scoring functions are unable to discriminate the native-like docking poses from a large set of generated ligand dispositions, because protein–ligand binding is driven by a complex pattern of energetic contributions that cannot be fully described by mathematical functions that only include approximated energetic terms. In this context, the use of protein–ligand interaction fingerprints has been recently introduced as a promising tool in structure-based drug design and in docking studies, because it outperforms conventional scoring functions and improves the identification of accurate ligand binding modes, facilitating the discovery of active compounds through virtual screening studies [11]. In order to rely on an efficient post-docking processing for the analysis of CAII inhibitors, we propose the use of ligand–protein interaction fingerprints (IFPs) [13] for prioritizing the most relevant poses among the ones generated by docking calculations
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