Related Experiment Video
Updated: May 3, 2026
A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Employing steered MD simulations for effective virtual screening: Active pharmacophore search by dynamic corrections
Muhammet Eren Ulug1, Saima Ikram1, Ehsan Sayyah1
1Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahçeşehir University, Istanbul, Turkey; Lab for Innovative Drugs (Lab4IND), Computational Drug Design Center (HITMER), Bahçeşehir University, İstanbul, Türkiye.
Abstract:
The protein-protein interaction (PPI) between mitogen-activated protein kinase kinase 3 (MKK3), and MYC is a crucial regulator of oncogenic signaling, particularly in triple-negative breast cancer (TNBC). Despite its clinical significance, effective small molecule inhibitors targeting this interaction remain elusive. In this study, we employed a comprehensive in silico approach integrating dynamic structure-based pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics (MD) simulations to identify potential inhibitors disrupting the MKK3-MYC interaction. The pharmacophore-based screening of over 2 million compounds from ChemDiv and Enamine libraries led to the identification of 16,766 hits, which were further refined through docking and MD-based analyses. The top-ranked molecules underwent steered molecular dynamics (sMD) simulations to evaluate the mechanical stability of their binding interactions, followed by binding free energy calculations (MM/GBSA) to assess their affinity. Notably, several hit compounds exhibited stronger binding affinities and mechanical stability compared to the reference inhibitor SGI-1027, with Z332428622, 4476-2273, and 4292-0516 emerging as the most promising candidates. The lead compounds demonstrated stable interactions with key residues at the interface of MKK3 and MYC, suggesting their potential as novel modulators of MYC-driven malignancies. These findings provide a strong computational foundation for further experimental validation and offer promising candidates for targeted therapy development in MYC-dependent cancers.
Insights
Researchers identified potential small molecule inhibitors for the MKK3-MYC interaction, crucial in triple-negative breast cancer (TNBC). Computational methods pinpointed promising candidates like Z332428622 for targeted cancer therapy development.
Area of Science:
- Oncology
- Computational Chemistry
- Structural Biology
Background:
- The protein-protein interaction (PPI) between mitogen-activated protein kinase kinase 3 (MKK3) and MYC is a key driver of oncogenic signaling, especially in triple-negative breast cancer (TNBC).
- Developing effective small molecule inhibitors for the MKK3-MYC PPI remains a significant challenge in cancer therapy.
Purpose of the Study:
- To identify novel small molecule inhibitors that disrupt the MKK3-MYC interaction using a comprehensive in silico strategy.
- To provide a computational foundation for experimental validation of potential therapeutic agents targeting MYC-driven cancers.
Main Methods:
- Integrated dynamic structure-based pharmacophore modeling, virtual screening of large compound libraries (ChemDiv, Enamine), molecular docking, and molecular dynamics (MD) simulations.
- Utilized steered molecular dynamics (sMD) for mechanical stability evaluation and MM/GBSA for binding free energy calculations.
- Screened over 2 million compounds, refining hits through docking, MD, sMD, and binding energy assessments.
Main Results:
- Identified 16,766 initial hits from virtual screening, with top candidates undergoing rigorous computational analysis.
- Several identified compounds, including Z332428622, 4476-2273, and 4292-0516, demonstrated superior binding affinity and mechanical stability compared to the reference inhibitor SGI-1027.
- Lead compounds exhibited stable interactions with critical residues at the MKK3-MYC interface.
Conclusions:
- The study successfully identified promising small molecule candidates for inhibiting the MKK3-MYC interaction.
- These findings offer a strong computational basis for developing novel targeted therapies for MYC-dependent malignancies, particularly in TNBC.
- The identified compounds represent potential therapeutic agents for further experimental investigation and drug development.
