title: Towards automated binding affinity prediction using an iterative linear interaction energy approach.
abstract: Binding affinity prediction of potential drugs to target and off-target proteins is an essential asset in drug development. These predictions require the calculation of binding free energies. In such calculations, it is a major challenge to properly account for both the dynamic nature of the protein and the possible variety of ligand-binding orientations, while keeping computational costs tractable. Recently, an iterative Linear Interaction Energy (LIE) approach was introduced, in which results from multiple simulations of a protein-ligand complex are combined into a single binding free energy using a Boltzmann weighting-based scheme. This method was shown to reach experimental accuracy for flexible proteins while retaining the computational efficiency of the general LIE approach. Here, we show that the iterative LIE approach can be used to predict binding affinities in an automated way. A workflow was designed using preselected protein conformations, automated ligand docking and clustering, and a (semi-)automated molecular dynamics simulation setup. We show that using this workflow, binding affinities of aryloxypropanolamines to the malleable Cytochrome P450 2D6 enzyme can be predicted without a priori knowledge of dominant protein-ligand conformations. In addition, we provide an outlook for an approach to assess the quality of the LIE predictions, based on simulation outcomes only.
authors.affiliation: AIMMS Division of Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands. c.r.vosmeer@vu.nl.
authors.forename: C Ruben
authors.initials: CR
authors.lastname: Vosmeer
authors.affiliation: AIMMS Division of Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands. r.pool@vu.nl.
authors.forename: René
authors.initials: R
authors.lastname: Pool
authors.affiliation: AIMMS Division of Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands. mariel.vanstee@tno.nl.
authors.forename: Mariël F
authors.initials: MF
authors.lastname: Van Stee
authors.affiliation: AIMMS Division of Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands. lovorka.peric@gmail.com.
authors.forename: Lovorka
authors.initials: L
authors.lastname: Peric-Hassler
authors.affiliation: AIMMS Division of Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands. n.p.e.vermeulen@vu.nl.
authors.forename: Nico P E
authors.initials: NP
authors.lastname: Vermeulen
authors.affiliation: AIMMS Division of Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands. d.p.geerke@vu.nl.
authors.forename: Daan P
authors.initials: DP
authors.lastname: Geerke
mesh_terms: D001331:Automation; D001665:Binding Sites; D016000:Cluster Analysis; D019389:Cytochrome P-450 CYP2D6 / Q000737:chemistry / Q000378:metabolism*; D008024:Ligands; D062105:Molecular Docking Simulation; D011412:Propanolamines / Q000737:chemistry / Q000378:metabolism; D011485:Protein Binding; D017434:Protein Structure, Tertiary; D013816:Thermodynamics
chemical_list: D008024:Ligands; D011412:Propanolamines; D019389:Cytochrome P-450 CYP2D6