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Updated: May 13, 2026
Deacetylation Assays to Unravel the Interplay between Sirtuins (SIRT2) and Specific Protein-substrates
Published on: February 27, 2016
Insights into SIRT2 inhibition from machine learning-assisted multi-level screening of the NCI database
Laila Abdulmohsen Jaragh-Alhadad1, Alaa H M Abdelrahman2, Peter A Sidhom3
1Chemistry Department, Faculty of Science, Kuwait University, P.O. Box 5969, Safat, 13060, Kuwait. laila.alhadad@ku.edu.kw.
Abstract:
The nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase Sirtuin 2 (SIRT2) plays a regulatory function in diverse cellular processes and has been linked to aging and the development of neurodegenerative and cancerous diseases. Consequently, targeting SIRT2 has emerged as a promising anticancer therapeutic strategy; however, currently available SIRT2 inhibitors and modulators often exhibit limited potency and suboptimal selectivity. Herein, the NCI database, containing more than 230,000 compounds, was systematically screened using an optimized AttentiveFP model to identify small molecules with potential SIRT2-inhibitory activity. The trained model predicted 23,238 NCI compounds as potentially active, which were subsequently subjected to docking computations against SIRT2. Upon docking estimations, the top-ranked NCI compounds bound to SIRT2 were advanced for molecular dynamics simulations (MDS) throughout 300 ns, along with binding energy (ΔGbinding) computations utilizing the MM-GBSA approach. Among these, NCI243049, NCI407129, and NCI248613 unveiled superior binding affinities toward SIRT2 over 300 ns MDS compared to the reference inhibitor SirReal2, with ΔGbinding values of -74.3, -73.1, -71.5, and -47.8 kcal/mol, respectively. Post-MD analyses consistently supported the promising stability and binding profiles of the identified NCI compounds bound to SIRT2 throughout 300 ns MDS. The physicochemical and ADMET features of the identified NCI compounds were predicted, indicating their favorable oral bioavailability and pharmacokinetic profiles. Eventually, DFT computations were executed to assess the chemical reactivity of the identified NCI compounds. Collectively, these findings highlighted NCI243049, NCI407129, and NCI248613 as promising SIRT2 inhibitors, meriting further validation through experimental assays for cancer therapy.
Insights
Researchers screened over 230,000 compounds to find new SIRT2 inhibitors for cancer therapy. Three compounds, NCI243049, NCI407129, and NCI248613, showed strong binding affinity and favorable properties for further development.
Area of Science:
- Biochemistry
- Computational Chemistry
- Pharmacology
Background:
- Sirtuin 2 (SIRT2) is a NAD+-dependent deacetylase implicated in aging and diseases like cancer and neurodegeneration.
- Targeting SIRT2 presents a potential anticancer strategy, but existing inhibitors lack potency and selectivity.
Purpose of the Study:
- To identify novel small molecules with SIRT2-inhibitory activity from the NCI database.
- To evaluate the binding affinity, stability, and pharmacokinetic properties of potential SIRT2 inhibitors.
Main Methods:
- Systematic screening of the NCI database using an AttentiveFP model.
- Docking simulations, 300 ns molecular dynamics simulations (MDS), and MM-GBSA binding energy calculations.
- Physicochemical, ADMET, and DFT computations to assess compound properties and reactivity.
Main Results:
- An optimized AttentiveFP model predicted 23,238 potentially active compounds.
- NCI243049, NCI407129, and NCI248613 demonstrated superior binding affinities to SIRT2 compared to a reference inhibitor.
- Predicted favorable oral bioavailability and pharmacokinetic profiles for the identified compounds.
Conclusions:
- NCI243049, NCI407129, and NCI248613 are promising SIRT2 inhibitors with potential for cancer therapy.
- These compounds warrant further experimental validation for their therapeutic efficacy.
