Exploring the most stable aptamer/target molecule complex by the stochastic tunnelling-basin hopping-discrete...

Area of Science:

• Computational Biology
• Biomolecular Simulations
• Structural Bioinformatics

Background:

• Accurate prediction of stable biomolecular complexes is crucial for drug discovery and understanding biological processes.
• Coarse-grained molecular dynamics (CGMD) offers a computationally efficient approach for large biomolecular systems.
• The epithelial cell adhesion molecule (EpCAM) is a significant target in cancer therapy.

Purpose of the Study:

• To investigate the stability of EpCAM-apt_EpA complexes in aqueous solution using a novel computational method.
• To analyze the influence of apt_EpA adsorption position on EpCAM stability and binding energy.
• To establish a new computational workflow for efficient biomolecular complex prediction.

Main Methods:

• Application of the stochastic tunnelling-basin hopping-discrete molecular dynamics (STUN-BH-DMD) method with the MARTINI coarse-grained (CG) model.
• Simulation of EpCAM-apt_EpA complexes in water, analyzing adsorption at different EpCAM positions.
• Root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses were performed.

Main Results:

• The apt_EpA configuration within the EpCAM pocket-like structure demonstrated higher stability and a lower energy barrier.
• EpCAM exhibited more conserved configurations in water when apt_EpA bound to the pocket region of the EpCAM dimer.
• Nucleobases 1 and 2 of apt_EpA showed increased flexibility, and binding energy was more continuous within the pocket structure.

Conclusions:

• The STUN-BH-DMD method combined with the CG model provides an efficient approach to identify stable biomolecular complexes.
• Adsorption within the EpCAM pocket significantly enhances the stability of the EpCAM-apt_EpA complex.
• This computational strategy can accelerate the discovery of therapeutic aptamer-protein interactions.