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Updated: May 28, 2026

From Molecules to Materials: Engineering New Ionic Liquid Crystals Through Halogen Bonding
Published on: March 24, 2018
Halogen bonding in ligand-receptor systems in the framework of classical force fields
Stefano Rendine1, Stefano Pieraccini, Alessandra Forni
1Dipartimento di Chimica Fisica ed Elettrochimica and INSTM UdR, Università degli Studi di Milano, Via Golgi 19, 20133, Milano, Italy.
This study introduces a new method to accurately simulate halogen bonds in protein-ligand complexes. The approach uses pseudo-atoms to model electrostatic potential, improving molecular dynamics simulations for drug discovery.
Area of Science:
- Biochemistry
- Computational Chemistry
- Drug Discovery
Background:
- Halogen bonding is a crucial non-covalent interaction in protein-ligand complexes.
- Many pharmaceuticals contain halogens and form halogen bonds with biological targets.
- Traditional force fields struggle to model the electrostatic anisotropy of halogen bonds.
Purpose of the Study:
- To develop a computational method for accurately simulating halogen bonds in biomolecular systems.
- To improve molecular dynamics simulations of halogenated ligands interacting with proteins.
Main Methods:
- Introduction of pseudo-atoms on halogen atoms to model electrostatic potential anisotropy.
- Performing molecular dynamics simulations on protein-halogenated ligand complexes.
- Comparison of simulation results with experimental crystallographic data and QM/MM calculations.
Main Results:
- The pseudo-atom approach accurately describes the electrostatic potential anisotropy of halogens.
- Molecular dynamics simulations using this method reproduce experimental values for protein-ligand complexes.
- The findings align with crystallographic data and QM/MM results.
Conclusions:
- The pseudo-atom method provides a reliable way to study halogen bonding in drug discovery.
- This approach enhances the accuracy of molecular dynamics simulations for halogenated compounds.
- The method is validated against experimental and advanced computational data.
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