Abstract
Background: The Rab family proteins are involved in membrane trafficking, cell growth and differentiation. Rab38 is implicated in the biogenesis of melanosomes that help in the synthesis, storage and transport of melanin pigments. The Rab38 protein is overexpressed at the RNA level in melanoma cancer.
Aim and objective: The protein Rab38 is targeted for identification of novel antagonists as cancer drug candidates. Materials and methods: The 3D structure of Rab38 was generated using homology modelling method. The 3D model was validated. The active site was identified by using standard computational prediction tools like CASTp, efindsite and SiteMap. The study of protein-protein docking was performed between Rab38 and its natural substrate BLOC-3 using patchDock server tool. Virtual screening protocols were carried out using glide module. Various informatics tools like 1) Schrodinger Suite 2) Modeller 3) Accelrys Discovery Studio 4) PyMOL 5) SPDBV etc. are applied for the identification of novel inhibitors of Rab38. Results: The residues from SER35 to LEU63 of Rab38 protein are important for binding to ligands. The nineteen docked structures were obtained as an output of virtual screening. The compounds obtained show good glide score, and a common binding pattern at the active site. Conclusion: The benzosulfonamide and heterocyclic nitrogen moieties may be considered as pharmacophores for designing new anticancer leads with better docking score and admissible ADME properties. Our study helps in the identification of potential inhibitors against Rab38 and melanoma cancer.Keywords: G proteins, Rab38, melanoma, homology modelling, virtual screening, protein-protein docking.
Combinatorial Chemistry & High Throughput Screening
Title:Identification of Novel Antagonists for Rab38 Protein by Homology Modeling and Virtual Screening
Volume: 19 Issue: 10
Author(s): Aboubakr Haredi Abdelmonsef, Ramasree Dulapalli, Thirupathi Dasari, Lavanya Souda Padmarao, Thirupathi Mukkera and Uma Vuruputuri
Affiliation:
Keywords: G proteins, Rab38, melanoma, homology modelling, virtual screening, protein-protein docking.
Abstract: Background: The Rab family proteins are involved in membrane trafficking, cell growth and differentiation. Rab38 is implicated in the biogenesis of melanosomes that help in the synthesis, storage and transport of melanin pigments. The Rab38 protein is overexpressed at the RNA level in melanoma cancer.
Aim and objective: The protein Rab38 is targeted for identification of novel antagonists as cancer drug candidates. Materials and methods: The 3D structure of Rab38 was generated using homology modelling method. The 3D model was validated. The active site was identified by using standard computational prediction tools like CASTp, efindsite and SiteMap. The study of protein-protein docking was performed between Rab38 and its natural substrate BLOC-3 using patchDock server tool. Virtual screening protocols were carried out using glide module. Various informatics tools like 1) Schrodinger Suite 2) Modeller 3) Accelrys Discovery Studio 4) PyMOL 5) SPDBV etc. are applied for the identification of novel inhibitors of Rab38. Results: The residues from SER35 to LEU63 of Rab38 protein are important for binding to ligands. The nineteen docked structures were obtained as an output of virtual screening. The compounds obtained show good glide score, and a common binding pattern at the active site. Conclusion: The benzosulfonamide and heterocyclic nitrogen moieties may be considered as pharmacophores for designing new anticancer leads with better docking score and admissible ADME properties. Our study helps in the identification of potential inhibitors against Rab38 and melanoma cancer.Export Options
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Cite this article as:
Abdelmonsef Haredi Aboubakr, Dulapalli Ramasree, Dasari Thirupathi, Padmarao Souda Lavanya, Mukkera Thirupathi and Vuruputuri Uma, Identification of Novel Antagonists for Rab38 Protein by Homology Modeling and Virtual Screening, Combinatorial Chemistry & High Throughput Screening 2016; 19 (10) . https://dx.doi.org/10.2174/1386207319666161026153237
DOI https://dx.doi.org/10.2174/1386207319666161026153237 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
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