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Updated: Mar 29, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
"Adapted Linear Interaction Energy": A Structure-Based LIE Parametrization for Fast Prediction of Protein-Ligand
Mats Linder1, Anirudh Ranganathan1, Tore Brinck1
1Applied Physical Chemistry, KTH Royal Institute of Technology, Teknikringen 30, S-100 44 Stockholm, Sweden.
Abstract:
We present a structure-based parametrization of the Linear Interaction Energy (LIE) method and show that it allows for the prediction of absolute protein-ligand binding energies. We call the new model "Adapted" LIE (ALIE) because the α and β coefficients are defined by system-dependent descriptors and do therefore not require any empirical γ term. The best formulation attains a mean average deviation of 1.8 kcal/mol for a diverse test set and depends on only one fitted parameter. It is robust with respect to additional fitting and cross-validation. We compare this new approach with standard LIE by Åqvist and co-workers and the LIE + γSASA model (initially suggested by Jorgensen and co-workers) against in-house and external data sets and discuss their applicabilities.
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