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Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

submitted on 12.03.2021, 17:41 and posted on 17.03.2021, 04:48 by Ariane Nunes Alves, Fabian Ormersbach, Rebecca Wade
There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each protein-ligand complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of protein-
ligand complexes to predict binding parameters. We introduce the option to use multiple structures to describe each ligand-protein complex into COMBINE analysis and
apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (koff) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression and allowed the computation of koff values. The QSKR model obtained using single, energy minimized crystal structures for each ligand-protein complex had a higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, the incorporation of protein-ligand flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, like interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures, showing that COMBINE analysis is a promising method to design leads with improved kinetic rates for flexible proteins.


Alexander von Humboldt Foundation

Capes (process number 88881.162167/2017-01)

Cluster of Excellence CellNetworks (DFG, EXC81)

Klaus Tschira Foundation


Email Address of Submitting Author


Heidelberg Institute for Theoretical Studies



ORCID For Submitting Author


Declaration of Conflict of Interest

No conflict of interest.