Hemant Kumar Deokar1,2, Hilaire Playa Barch1, John K Buolamwini1,2. 1. Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, 847 Monroe Avenue, Suite 327, Memphis, Tennessee, 38163, USA. 2. Department of Pharmaceutical Sciences, College of Pharmacy, Rosalind Franklin University of Medicine and Science, North Chicago, Illinois, 60064, USA.
Abstract
OBJECTIVE: The nucleoside transporter family is an emerging target for cancer, viral and cardiovascular diseases. Due to the difficulty in the expression, isolation and crystallization of membrane proteins, there is a lack of structural information on any of the mammalian and for that matter the human proteins. Thus the objective of this study was to build homology models for the three cloned concentrative nucleoside transporters hCNT1, hCNT2 and hCNT3 and validate them for screening towards the discovery of much needed inhibitors and probes. METHODS: The recently reported crystal structure of the Vibrio cholerae concentrative nucleoside transporter (vcCNT), has satisfactory similarity to the human CNT orthologues and was thus used as a template to build homology models of all three hCNTs. The Schrödinger modeling suite was used for the exercise. External validation of the homology models was carried out by docking a set of recently reported known hCNT1 nucleoside class inhibitors at the putative binding site using induced fit docking (IDF) methodology with the Glide docking program. Then, the hCNT1 homology model was subsequently used to conduct a virtual screening of a 360,000 compound library, and 172 compounds were obtained and biologically evaluated for hCNT 1, 2 and 3 inhibitory potency and selectivity. RESULTS: Good quality homology models were obtained for all three hCNTs as indicated by interrogation for various structural parameters and also external validated by docking of known inhibitors. The IDF docking results showed good correlations between IDF scores and inhibitory activities; particularly for hCNT1. From the top 0.1% of compounds ranked by virtual screening with the hCNT1 homology model, 172 compounds selected and tested for against hCNT1, hCNT2 and hCNT3, yielded 14 new inhibitors (hits) of (i.e., 8% success rate). The most active compound exhibited an IC50 of 9.05 μM, which shows a greater than 25-fold higher potency than phlorizin the standard CNT inhibitor (IC50 of 250 μM). CONCLUSION: We successfully undertook homology modeling and validation for all human concentrative nucleoside transporters (hCNT 1, 2 and 3). The proof-of-concept that these models are promising for virtual screening to identify potent and selective inhibitors was also obtained using the hCNT1 model. Thus we identified a novel potent hCNT1 inhibitor that is more potent and more selective than the standard inhibitor phlorizin. The other hCNT1 hits also mostly exhibited selectivity. These homology models should be useful for virtual screening to identify novel hCNT inhibitors, as well as for optimization of hCNT inhibitors.
OBJECTIVE: The nucleoside transporter family is an emerging target for cancer, viral and cardiovascular diseases. Due to the difficulty in the expression, isolation and crystallization of membrane proteins, there is a lack of structural information on any of the mammalian and for that matter the human proteins. Thus the objective of this study was to build homology models for the three cloned concentrative nucleoside transporters hCNT1, hCNT2 and hCNT3 and validate them for screening towards the discovery of much needed inhibitors and probes. METHODS: The recently reported crystal structure of the Vibrio cholerae concentrative nucleoside transporter (vcCNT), has satisfactory similarity to the human CNT orthologues and was thus used as a template to build homology models of all three hCNTs. The Schrödinger modeling suite was used for the exercise. External validation of the homology models was carried out by docking a set of recently reported known hCNT1 nucleoside class inhibitors at the putative binding site using induced fit docking (IDF) methodology with the Glide docking program. Then, the hCNT1 homology model was subsequently used to conduct a virtual screening of a 360,000 compound library, and 172 compounds were obtained and biologically evaluated for hCNT 1, 2 and 3 inhibitory potency and selectivity. RESULTS: Good quality homology models were obtained for all three hCNTs as indicated by interrogation for various structural parameters and also external validated by docking of known inhibitors. The IDF docking results showed good correlations between IDF scores and inhibitory activities; particularly for hCNT1. From the top 0.1% of compounds ranked by virtual screening with the hCNT1 homology model, 172 compounds selected and tested for against hCNT1, hCNT2 and hCNT3, yielded 14 new inhibitors (hits) of (i.e., 8% success rate). The most active compound exhibited an IC50 of 9.05 μM, which shows a greater than 25-fold higher potency than phlorizin the standard CNT inhibitor (IC50 of 250 μM). CONCLUSION: We successfully undertook homology modeling and validation for all human concentrative nucleoside transporters (hCNT 1, 2 and 3). The proof-of-concept that these models are promising for virtual screening to identify potent and selective inhibitors was also obtained using the hCNT1 model. Thus we identified a novel potent hCNT1 inhibitor that is more potent and more selective than the standard inhibitor phlorizin. The other hCNT1 hits also mostly exhibited selectivity. These homology models should be useful for virtual screening to identify novel hCNT inhibitors, as well as for optimization of hCNT inhibitors.
Entities:
Keywords:
Anticancer agents; Antiviral agents; Concentrative nucleoside transporter; Docking; High throughput virtual screening; Hit enrichment; Homology modeling
Authors: Hilaire Playa; Timothy A Lewis; Amal Ting; Byung-Chul Suh; Benito Muñoz; Robert Matuza; Brent J Passer; Stuart L Schreiber; John K Buolamwini Journal: Bioorg Med Chem Lett Date: 2014-10-28 Impact factor: 2.823
Authors: Vijaya L Damaraju; Kyla M Smith; Delores Mowles; Ireneusz Nowak; Edward Karpinski; James D Young; Morris J Robins; Carol E Cass Journal: Biochem Pharmacol Date: 2010-09-18 Impact factor: 5.858
Authors: Marçal Pastor-Anglada; Pedro Cano-Soldado; Míriam Molina-Arcas; M Pilar Lostao; Ignacio Larráyoz; Javier Martínez-Picado; F Javier Casado Journal: Virus Res Date: 2005-02 Impact factor: 3.303
Authors: Ian W Davis; Andrew Leaver-Fay; Vincent B Chen; Jeremy N Block; Gary J Kapral; Xueyi Wang; Laura W Murray; W Bryan Arendall; Jack Snoeyink; Jane S Richardson; David C Richardson Journal: Nucleic Acids Res Date: 2007-04-22 Impact factor: 16.971
Authors: Samuel K Kwofie; Bismark Dankwa; Emmanuel A Odame; Francis E Agamah; Lady P A Doe; Joshua Teye; Odame Agyapong; Whelton A Miller; Lydia Mosi; Michael D Wilson Journal: Molecules Date: 2018-06-27 Impact factor: 4.411
Authors: Romina Gabriela Armando; Diego Luis Mengual Gómez; Ezequiel Ivan Juritz; Pablo Lorenzano Menna; Daniel Eduardo Gomez Journal: Int J Mol Sci Date: 2018-10-18 Impact factor: 5.923