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Updated: Feb 15, 2026

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up
Published on: March 26, 2018
Prediction of Hot Spots at Myeloid Cell Leukemia-1-Inhibitor Interface Using Energy Estimation and Alanine Scanning
Parthiban Marimuthu1,2, Kalaimathy Singaravelu3
1Structural Bioinformatics Laboratory (SBL), Faculty of Science and Engineering, Biochemistry, Åbo Akademi University , Tykistökatu 6A, FI-20520 Turku, Finland.
Abstract:
Myeloid cell leukemia 1 (Mcl1) is an antiapoptotic protein that plays central role in apoptosis regulation. Also, Mcl1 has the potency to resist apoptotic cues resulting in up-regulation and cancer cell protection. A molecular probe that has the potential to specifically target Mcl1 and thereby provoke its down-regulatory activity is very essential. The aim of the current study is to probe the internal conformational dynamics of protein motions and potential binding mechanism in response to a series of picomolar range Mcl1 inhibitors using explicit-solvent molecular dynamics (MD) simulations. Subsequently, domain cross-correlation and principal component analysis was performed on the snapshots obtained from the MD simulations. Our results showed significant differences in the internal conformational dynamics of Mcl1 with respect to binding affinity values of inhibitors. Further, the binding free energy estimation, using three different samples, was performed on the MD simulations and revealed that the predicted energies (ΔGmmgbsa) were in good correlation with the experimental values (ΔGexpt). Also, the energies obtained using all sampling models were efficiently ranked. Subsequently, the decomposition energy analysis highlighted the major energy-contributing residues at the Mcl1 binding pocket. Computational alanine scanning performed on high energy-contributing residues predicted the hot spot residues. The dihedral angle analysis using MD snapshots on the predicted hot spot residue exhibited consistency in side chain conformational motion that ultimately led to strong binding affinity values. The findings from the present study might provide valuable guidelines for the design of novel Mcl1 inhibitors that might significantly improve the specificity for new-generation chemotherapeutic agents.
Insights
Targeting myeloid cell leukemia 1 (Mcl1) with novel inhibitors shows promise. Molecular dynamics simulations reveal how Mcl1 inhibitors bind, guiding the development of new cancer therapies.
Area of Science:
- Biochemistry
- Computational Biology
- Drug Discovery
Background:
- Myeloid cell leukemia 1 (Mcl1) is an antiapoptotic protein crucial for cancer cell survival.
- Targeting Mcl1 is essential for developing effective cancer chemotherapeutics.
- Understanding Mcl1 inhibitor binding mechanisms is key for drug design.
Purpose of the Study:
- To investigate the internal conformational dynamics of Mcl1.
- To elucidate the binding mechanism of picomolar range Mcl1 inhibitors.
- To guide the design of novel, specific Mcl1 inhibitors for cancer therapy.
Main Methods:
- Explicit-solvent molecular dynamics (MD) simulations.
- Domain cross-correlation and principal component analysis.
- Binding free energy estimation (MMGBSA) and computational alanine scanning.
Main Results:
- Mcl1 conformational dynamics differ based on inhibitor binding affinity.
- Predicted binding free energies correlate well with experimental values.
- Identified key residues and hot spots in the Mcl1 binding pocket.
Conclusions:
- MD simulations provide insights into Mcl1 inhibitor binding.
- Computational methods accurately predict binding affinities.
- Findings support the rational design of next-generation Mcl1-targeted cancer drugs.
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