Simulating chalcogen bonding using molecular mechanics: a pseudoatom approach to model ebselen.

Area of Science:

• Computational chemistry
• Drug discovery
• Biophysics

Background:

• Ebselen, an organoselenium compound, shows therapeutic potential but lacks accurate in silico modeling methods.
• Existing computational techniques fail to capture key interactions of ebselen with biological targets.
• Understanding ebselen's binding is crucial for its development as a COVID-19 treatment.

Purpose of the Study:

• To develop an efficient and accurate computational method for modeling ebselen's binding to macromolecules.
• To incorporate the unique σ-hole interaction of selenium into molecular force fields.
• To enable reliable in silico studies of ebselen-target complexes.

Main Methods:

• Modification of the Generalized Amber Force Field (GAFF) to include parameters for selenium.
• Introduction of a positively charged pseudoatom to simulate the selenium σ-hole.
• Density functional theory (DFT) calculations for energy decomposition analysis.
• Molecular dynamics (MD) simulations of ebselen complexes, including the enzyme SOD1.

Main Results:

• The modified GAFF accurately models ebselen's σ-hole interactions, confirming their electrostatic nature.
• MD simulations successfully reproduced known binding of ebselen to SOD1.
• The developed model provides a robust tool for in silico drug discovery involving ebselen.

Conclusions:

• The enhanced force field enables accurate computational modeling of ebselen's interactions.
• This breakthrough facilitates in silico drug discovery and development for ebselen-based therapies.
• The method provides a foundation for studying other organoselenium compounds.