Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling Approach
Small molecule inhibitors of adipocyte fatty-acid binding protein 4 (FABP4) have received interest following the recent publication of their pharmacologically beneficial effects. Recently, it was revealed that FABP4 is an attractive molecular target for the treatment of type 2 diabetes, other metabo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-10-01
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| Series: | Marine Drugs |
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| Online Access: | https://www.mdpi.com/1660-3397/17/11/624 |
| _version_ | 1798004135213137920 |
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| author | Giuseppe Floresta Davide Gentile Giancarlo Perrini Vincenzo Patamia Antonio Rescifina |
| author_facet | Giuseppe Floresta Davide Gentile Giancarlo Perrini Vincenzo Patamia Antonio Rescifina |
| author_sort | Giuseppe Floresta |
| collection | DOAJ |
| description | Small molecule inhibitors of adipocyte fatty-acid binding protein 4 (FABP4) have received interest following the recent publication of their pharmacologically beneficial effects. Recently, it was revealed that FABP4 is an attractive molecular target for the treatment of type 2 diabetes, other metabolic diseases, and some type of cancers. In past years, hundreds of effective FABP4 inhibitors have been synthesized and discovered, but, unfortunately, none have reached the clinical research phase. The field of computer-aided drug design seems to be promising and useful for the identification of FABP4 inhibitors; hence, different structure- and ligand-based computational approaches have been used for their identification. In this paper, we searched for new potentially active FABP4 ligands in the Marine Natural Products (MNP) database. We retrieved 14,492 compounds from this database and filtered through them with a statistical and computational filter. Seven compounds were suggested by our methodology to possess a potential inhibitory activity upon FABP4 in the range of 97−331 nM. ADMET property prediction was performed to validate the hypothesis of the interaction with the intended target and to assess the drug-likeness of these derivatives. From these analyses, three molecules that are excellent candidates for becoming new drugs were found. |
| first_indexed | 2024-04-11T12:18:47Z |
| format | Article |
| id | doaj.art-e9ab50e0b6be4a9784b11b817bf3f790 |
| institution | Directory Open Access Journal |
| issn | 1660-3397 |
| language | English |
| last_indexed | 2024-04-11T12:18:47Z |
| publishDate | 2019-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Marine Drugs |
| spelling | doaj.art-e9ab50e0b6be4a9784b11b817bf3f7902022-12-22T04:24:10ZengMDPI AGMarine Drugs1660-33972019-10-01171162410.3390/md17110624md17110624Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling ApproachGiuseppe Floresta0Davide Gentile1Giancarlo Perrini2Vincenzo Patamia3Antonio Rescifina4Department of Drug Sciences, University of Catania, V.le A. Doria, 95125 Catania, ItalyDepartment of Drug Sciences, University of Catania, V.le A. Doria, 95125 Catania, ItalyDepartment of Chemical Sciences, University of Catania, V.le A. Doria, 95125 Catania, ItalyDepartment of Drug Sciences, University of Catania, V.le A. Doria, 95125 Catania, ItalyDepartment of Drug Sciences, University of Catania, V.le A. Doria, 95125 Catania, ItalySmall molecule inhibitors of adipocyte fatty-acid binding protein 4 (FABP4) have received interest following the recent publication of their pharmacologically beneficial effects. Recently, it was revealed that FABP4 is an attractive molecular target for the treatment of type 2 diabetes, other metabolic diseases, and some type of cancers. In past years, hundreds of effective FABP4 inhibitors have been synthesized and discovered, but, unfortunately, none have reached the clinical research phase. The field of computer-aided drug design seems to be promising and useful for the identification of FABP4 inhibitors; hence, different structure- and ligand-based computational approaches have been used for their identification. In this paper, we searched for new potentially active FABP4 ligands in the Marine Natural Products (MNP) database. We retrieved 14,492 compounds from this database and filtered through them with a statistical and computational filter. Seven compounds were suggested by our methodology to possess a potential inhibitory activity upon FABP4 in the range of 97−331 nM. ADMET property prediction was performed to validate the hypothesis of the interaction with the intended target and to assess the drug-likeness of these derivatives. From these analyses, three molecules that are excellent candidates for becoming new drugs were found.https://www.mdpi.com/1660-3397/17/11/624fabp4a-fabpap2antidiabetesantiobesityantiatherosclerosisanticancercomputational toolscomputer-aided drug discovery |
| spellingShingle | Giuseppe Floresta Davide Gentile Giancarlo Perrini Vincenzo Patamia Antonio Rescifina Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling Approach Marine Drugs fabp4 a-fabp ap2 antidiabetes antiobesity antiatherosclerosis anticancer computational tools computer-aided drug discovery |
| title | Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling Approach |
| title_full | Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling Approach |
| title_fullStr | Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling Approach |
| title_full_unstemmed | Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling Approach |
| title_short | Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling Approach |
| title_sort | computational tools in the discovery of fabp4 ligands a statistical and molecular modeling approach |
| topic | fabp4 a-fabp ap2 antidiabetes antiobesity antiatherosclerosis anticancer computational tools computer-aided drug discovery |
| url | https://www.mdpi.com/1660-3397/17/11/624 |
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