Prediction of solution phase association constants by mapping contact points in intermolecular complexes

Atomic surface site interaction points (AIP) provide a complete description of the non-covalent interactions that one molecule can make with another. The surface site interaction model for the properties of liquids at equilibrium (SSIMPLE) algorithm can be used to calculate the free energy change associated with the pairwise interaction between two AIPs on two different molecules in any solvent. Summing these pairwise AIP interactions across an intermolecular interface that involves multiple interacting sites can be used to calculate solution phase binding free energies and association constants. A computational tool that converts the three-dimensional structure of a complex into a set of AIP contacts has been developed along with a visualisation tool to display AIP interaction maps, allowing straightforward identification of the key intermolecular contacts that contribute most to the overall binding free energy in a complex. The method successfully reproduces solution phase association constants (to within an order of magnitude) for a range of host-guest complexes involving H-bonding, aromatic and hydrophobic interactions, but performs less well for halogen-bonds and complexes involving interactions between the extended π-surfaces of fullerene-type compounds.

Authors

Institutions

Publication Details

Journal
Physical Chemistry Chemical Physics
Published
2025-01-01
DOI
https://doi.org/10.1039/d5cp00398a
Citations
1
Primary Topic
Chemical Thermodynamics and Molecular Structure
Type
article
Field-Weighted Citation Impact
0.94

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prediction of solution phase association constants by mapping contact points in intermolecular complexes

Christopher A. Hunter, Katarzyna J. Zator
1 citations
Physical Chemistry Chemical Physics
Chemical Thermodynamics and Molecular Structure
0.94
article

Prediction of solution phase association constants by mapping contact points in intermolecular complexes

Christopher A. Hunter, Katarzyna J. Zator
article en
1 citations

Abstract

Atomic surface site interaction points (AIP) provide a complete description of the non-covalent interactions that one molecule can make with another. The surface site interaction model for the properties of liquids at equilibrium (SSIMPLE) algorithm can be used to calculate the free energy change associated with the pairwise interaction between two AIPs on two different molecules in any solvent. Summing these pairwise AIP interactions across an intermolecular interface that involves multiple interacting sites can be used to calculate solution phase binding free energies and association constants. A computational tool that converts the three-dimensional structure of a complex into a set of AIP contacts has been developed along with a visualisation tool to display AIP interaction maps, allowing straightforward identification of the key intermolecular contacts that contribute most to the overall binding free energy in a complex. The method successfully reproduces solution phase association constants (to within an order of magnitude) for a range of host-guest complexes involving H-bonding, aromatic and hydrophobic interactions, but performs less well for halogen-bonds and complexes involving interactions between the extended π-surfaces of fullerene-type compounds.

Physical Chemistry Chemical PhysicsVol. 27(21)
University of Cambridge (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 26%
Chemical Thermodynamics and Molecular Structure
0.94
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.