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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
Computational Tool to Design Small Synthetic Inhibitors Selective for XIAP-BIR3 Domain
Marc Farag1, Charline Kieffer1, Nicolas Guedeney1
1Normandie Univ., UNICAEN, CERMN, 14000 Caen, France.
Abstract:
X-linked inhibitor of apoptosis protein (XIAP) exercises its biological function by locking up and inhibiting essential caspase-3, -7 and -9 toward apoptosis execution. It is overexpressed in multiple human cancers, and it plays an important role in cancer cells' death skipping. Inhibition of XIAP-BIR3 domain and caspase-9 interaction was raised as a promising strategy to restore apoptosis in malignancy treatment. However, XIAP-BIR3 antagonists also inhibit cIAP1-2 BIR3 domains, leading to serious side effects. In this study, we worked on a theoretical model that allowed us to design and optimize selective synthetic XIAP-BIR3 antagonists. Firstly, we assessed various MM-PBSA strategies to predict the XIAP-BIR3 binding affinities of synthetic ligands. Molecular dynamics simulations using hydrogen mass repartition as an additional parametrization with and without entropic term computed by the interaction entropy approach produced the best correlations. These simulations were then exploited to generate 3D pharmacophores. Following an optimization with a training dataset, five features were enough to model XIAP-BIR3 synthetic ligands binding to two hydrogen bond donors, one hydrogen bond acceptor and two hydrophobic groups. The correlation between pharmacophoric features and computed MM-PBSA free energy revealed nine residues as crucial for synthetic ligand binding: Thr308, Glu314, Trp323, Leu307, Asp309, Trp310, Gly306, Gln319 and Lys297. Ultimately, and three of them seemed interesting to use to improve XIAP-BR3 versus cIAP-BIR3 selectivity: Lys297, Thr308 and Asp309.
Insights
Researchers developed a computational model to design selective XIAP-BIR3 antagonists for cancer therapy. This approach optimizes drug design by identifying key residues for improved selectivity and reduced side effects.
Area of Science:
- Biochemistry
- Computational Chemistry
- Pharmacology
Background:
- X-linked inhibitor of apoptosis protein (XIAP) overexpression promotes cancer cell survival by inhibiting apoptosis.
- Targeting the XIAP-BIR3 domain is a promising strategy to restore apoptosis in cancer treatment.
- Current XIAP-BIR3 antagonists lack selectivity, inhibiting cIAP1-2 and causing side effects.
Purpose of the Study:
- To design and optimize selective synthetic XIAP-BIR3 antagonists using a theoretical model.
- To identify key molecular features and residues for selective XIAP-BIR3 inhibition.
- To improve the therapeutic potential of XIAP antagonists by minimizing off-target effects.
Main Methods:
- Utilized molecular dynamics simulations with MM-PBSA to predict binding affinities.
- Employed hydrogen mass repartition and interaction entropy for enhanced simulation accuracy.
- Generated and optimized 3D pharmacophores based on computational predictions.
Main Results:
- A five-feature pharmacophore model accurately predicted XIAP-BIR3 ligand binding.
- Identified nine crucial residues (Thr308, Glu314, Trp323, Leu307, Asp309, Trp310, Gly306, Gln319, Lys297) for ligand interaction.
- Highlighted Lys297, Thr308, and Asp309 as key targets for enhancing XIAP-BIR3 versus cIAP-BIR3 selectivity.
Conclusions:
- The developed computational model enables the design of selective XIAP-BIR3 antagonists.
- Targeting specific residues can improve drug selectivity and reduce adverse effects.
- This strategy holds promise for developing novel cancer therapeutics with enhanced safety profiles.
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