Elucidating and Confirming the Substrate and Cofactor Binding Site of RetSat and Identifying the Optimal Cofactor for Retinol Saturase – A Computational Insight

Retinol saturase (RetSat) is an enzyme that inhibits the conversion of all-trans-retinol to all-trans-retinoic acid (ATRA), which is crucial for protecting cells against malignancy. Despite its significance, no effective inhibitors targeting RetSat currently exist, and limited knowledge about its structure, cofactor, and substrate binding has hindered inhibitor design. In this study, we utilized computational techniques to reconstruct and validate the 3D atomic structure of RetSat, identifying its cofactor and substrate binding sites. NADH was determined to be the optimal cofactor and successfully docked into its binding site, followed by docking of retinol into the substrate-specific site. Analysis of the equilibrated complexes revealed key amino acids involved in cofactor and substrate binding, enabling the identification of potential catalytic residues. This study provides validated insights into RetSat’s structure and interactions, offering a foundation for designing RetSat inhibitors as potential anticancer agents and advancing the understanding of its role in cancer biology, thus paving the way for targeted therapeutic strategies. Received: 10 June 2024 | Revised: 10 October 2024 | Accepted: 22 January 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support this work are available upon reasonable request to the corresponding author. Author Contribution Statement Virangi Tharika Hewage: Software, Validation, Investigation, Data curation, Writing – original draft, Visualization. Ranga Srinath Jayakody: Conceptualization, Methodology, Validation, Formal analysis, Resources, Data curation, Writing – review & editing, Supervision, Project administration, Funding acquisition. Anura Jayasooriya: Formal analysis, Resources, Data curation, Writing - review & editing, Visualization, Supervision. Tharindu Senapathi: Software, Formal analysis, Resources, Data curation, Writing – review & editing, Visualization, Supervision. Krishna Govendar: Software, Formal analysis, Resources, Data curation, Writing – review & editing, Visualization, Supervision.

Authors

Institutions

Publication Details

Journal
Medinformatics
Published
2025-02-05
DOI
https://doi.org/10.47852/bonviewmedin42023586
Primary Topic
Advanced Fluorescence Microscopy Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Elucidating and Confirming the Substrate and Cofactor Binding Site of RetSat and Identifying the Optimal Cofactor for Retinol Saturase – A Computational Insight

Anura P. Jayasooriya, Tharindu Senapathi, Ranga Srinath Jayakody, Virangi Tharika Hewage et al.
Medinformatics
Advanced Fluorescence Microscopy Techniques
article

Elucidating and Confirming the Substrate and Cofactor Binding Site of RetSat and Identifying the Optimal Cofactor for Retinol Saturase – A Computational Insight

Anura P. Jayasooriya, Tharindu Senapathi, Ranga Srinath Jayakody, Virangi Tharika Hewage, Krishna Govendar
article en

Abstract

Retinol saturase (RetSat) is an enzyme that inhibits the conversion of all-trans-retinol to all-trans-retinoic acid (ATRA), which is crucial for protecting cells against malignancy. Despite its significance, no effective inhibitors targeting RetSat currently exist, and limited knowledge about its structure, cofactor, and substrate binding has hindered inhibitor design. In this study, we utilized computational techniques to reconstruct and validate the 3D atomic structure of RetSat, identifying its cofactor and substrate binding sites. NADH was determined to be the optimal cofactor and successfully docked into its binding site, followed by docking of retinol into the substrate-specific site. Analysis of the equilibrated complexes revealed key amino acids involved in cofactor and substrate binding, enabling the identification of potential catalytic residues. This study provides validated insights into RetSat’s structure and interactions, offering a foundation for designing RetSat inhibitors as potential anticancer agents and advancing the understanding of its role in cancer biology, thus paving the way for targeted therapeutic strategies. Received: 10 June 2024 | Revised: 10 October 2024 | Accepted: 22 January 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support this work are available upon reasonable request to the corresponding author. Author Contribution Statement Virangi Tharika Hewage: Software, Validation, Investigation, Data curation, Writing – original draft, Visualization. Ranga Srinath Jayakody: Conceptualization, Methodology, Validation, Formal analysis, Resources, Data curation, Writing – review & editing, Supervision, Project administration, Funding acquisition. Anura Jayasooriya: Formal analysis, Resources, Data curation, Writing - review & editing, Visualization, Supervision. Tharindu Senapathi: Software, Formal analysis, Resources, Data curation, Writing – review & editing, Visualization, Supervision. Krishna Govendar: Software, Formal analysis, Resources, Data curation, Writing – review & editing, Visualization, Supervision.

Medinformatics
University of Peradeniya (LK), University of Sri Jayewardenepura (LK), University of Johannesburg (ZA)
University of Sri Jayewardenepura
Openalex Percentile: Top 99%
Advanced Fluorescence Microscopy Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.