Evaluation of Docking Target Functions by the Comprehensive Investigation of Protein-Ligand Energy Minima

Abstract

The adequate choice of the docking target function impacts the accuracy of the ligand positioning as well as the accuracy of the protein-ligand binding energy calculation. To evaluate a docking target function we compared positions of its minima with the experimentally known pose of the ligand in the protein active site. We evaluated five docking target functions based on either the MMFF94 force field or the PM7 quantum-chemical method with or without implicit solvent models: PCM, COSMO, and SGB. Each function was tested on the same set of 16 protein-ligand complexes. For exhaustive low-energy minima search the novel MPI parallelized docking program FLM and large supercomputer resources were used. Protein-ligand binding energies calculated using low-energy minima were compared with experimental values. It was demonstrated that the docking target function on the base of the MMFF94 force field in vacuo can be used for discovery of native or near native ligand positions by finding the low-energy local minima spectrum of the target function. The importance of solute-solvent interaction for the correct ligand positioning is demonstrated. It is shown that docking accuracy can be improved by replacement of the MMFF94 force field by the new semiempirical quantum-chemical PM7 method.

Influence of the Method of Hydrogen Atoms Incorporation Into the Target Protein on the Protein-Ligand Binding Energy

“…However, realization of mobility of the target protein atoms in the docking procedure needs adoption the new docking 102 approach: instead of the traditional docking technique using the preliminary calculated energy grid of probe ligand atoms in the eld of the target protein (see, for example, SOL [46]) the straightforward docking procedure must be used. In this docking procedure the protein-ligand energy is calculated directly in the frame of the given force eld for any ligand pose in the target protein active site (see, for example FLM [7,8] and SOL-T [22]). But such approach demands much more computational expenses, especially when the target protein atoms are moveable.…”

“…The APLITE program [6,8] adds hydrogen atoms according to the standard protonation states of amino acids at pH = 7,4. Protonation states of hisitidines were selected by the comparison of hydrogen atoms electrochemical potentials in "HD1" and "HE2" positions.…”

“…The free ligand conformation in equation (1) remains the same for all hydrogen atoms incorporation methods used for the protein preparation. This conformation corresponds to the energy global minimum in vacuum in MMFF94 force eld found by the FLM program [7,8]. The energy of the protein-ligand complex in (1) is equal to the energy local minimum in vacuum in MMFF94 force eld when the energy optimization is performed by LBFGS method starting from the native ligand pose in the crystallized complex structure.…”

Acoplamiento Molecular: Avances Recientes y Retos

“…Notable improvements on docking have been made when molecular dynamics are used to prepare the structures of molecular targets, for instance, to conduct energy minimization and assign charges (Alonso, Bliznyuk & Gready, 2006;Uehara & Tanaka, 2017). For ligand preparation, methods that have improved docking results include: optimization using semiempiric charges (Adeniyi & Soliman, 2017;Marzaro et al, 2013;Oferkin et al, 2015;Xu & Lill, 2013), COSMO solvation (Oferkin et al, 2015), molecular mechanics Poison-Boltzmann/ surface area (Halperin, Wolfson & Nussinov, 2002), and force field optimization (Zoete, Cuendet, Grosdidier & Michielin, 2011). Moreover, it has been shown that forcefield optimization with implicit solvent is comparable to advanced semi-empirical methods (e.g.…”

“…Hence, the first step is the identification of key water molecules and their contribution (Kumar & Zhang, 2013). Methods that have advanced the correct representation of water molecules in proteins include: free energy perturbation methods (Jorgensen & Thomas, 2008), Monte Carlo probability (Parikh & Kellogg, 2014), molecular dynamics of water on the binding site (as implemented by Schrödinger (Kumar & Zhang, 2013;Waszkowycz, Clark & Gancia, 2011)), water displacement as implemented by PLANTS (Korb, Stützle & Exner, 2009), "Attachment" of water molecules to ligands as additional torsions (Lie, Thomsen, Pedersen, Schiøtt & Christensen, 2011), QM/ MM hybrid methods (Xu & Lill, 2013), COSMO solvation, and semi-empirical charges for ligands (Oferkin et al, 2015). Additional methods are "hydrated docking" scripts for Autodock (Forli et al, 2016), protein-centric and ligand centric hydration as implemented by Rossetta (Lemmon & Meiler, 2013), Water docking using Vina (Ross, Morris & Biggin, 2012;Sridhar et al, 2017), WScore (Murphy et al, 2016), and grid inhomogeneous solvation theory applied by Autodock (Uehara & Tanaka, 2016).…”