Enzyme structure-based methods

Enzyme structure-based methods predict the stable binding mode of a substrate or inhibitor in the CYP binding site. As X-ray crystal structures are now available for all major xenobiotic-metabolizing CYP forms, the structure-based methods can be widely applied across different phase I metabolism pathways. The orientation of a ligand in the enzyme binding site depends on the shape and electrostatics complementarity between the ligand and the enzyme. Many of the evaluated structure-based methods rely on molecular docking but also fingerprint matching and MD simulations are used (Table 2) (Tyzack and Kirchmair 2019). Structure-based methods are mostly used to investigate specific ligand-CYP interactions as the flexibility, complex water interactions and the hydrophobic binding sites of CYP enzymes pose challenges to these approaches, especially molecular docking (Tyzack and Kirchmair 2019). In addition, they are computationally expensive and often require expert knowledge for the setup and analysis of the results. Consequently, the methods have been usually tested on just few CYP isoforms and relatively small datasets (Table 2). However, structure-based methods offer interpretable and precise information of the atomic ligand-CYP interactions that define the ligand orientation in the CYP active site. The predictions are also isoform-specific by default as they are based on the 3D structure of a specific CYP enzyme. In addition to binding mode and

SOM prediction, the obtained structural information can be used to rationalize experimental results or to help rational molecule design.

TABLE 2 Enzyme structure-based methods for SOM prediction of CYP substrates.

Method/

reference Description Targeted

CYPs SOM prediction rate¹ (Evaluation set size)² (Zamora et al.

2003) Distance-based 2D fingerprints to match ligand and CYP binding site.

(Hritz et al. 2008) CYP structures from MD

simulations for docking. 2D6 Top1

71% 1 structure,

et al. 2009a) Inclusion of crystal water in docking. SOM prediction,

2010) MD simulations with a specific ligand to derive CYP hydration sites and structures for

2014) CYP structures from MD

simulations for docking. 2A6 Top1 57.3%, Top3 65.6% one or a couple of ligands.

1A1, 1A2, 1B1, 2C9, 2C11, 2E1, 3A4

-

1: Prediction rates are not comparable due to differences in evaluation sets.

2: The number of substrates in the evaluation set with the exception of Zamora et al. (2003), where the number of reactions, instead of substrates, was reported.

Top1-3: Number of substrates that have a correct prediction among the top 1-3 predictions.

In the case of substrate binding mode prediction, the likely SOM(s) of the substrate can be derived from the predicted binding mode(s). A likely SOM should be accessible for oxidation by the heme, i.e. lie relatively close to the heme

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iron with no other substrate atoms to shield the reaction. However, there should still be space for an oxygen to bind to the iron. In docking and MD simulation approaches, a binding mode prediction is considered correct if at least one SOM lies within 6 Å of the heme iron and is thus accessible for the reaction (Hritz et al.

2008, Vasanthanathan et al. 2009a, Panneerselvam et al. 2015, Sato et al. 2017, Jandova et al. 2019). Such a distance-based approach is reasonable as it leaves space for the oxygen. However, multiple substrate positions can lie at the proximity of the heme iron, and thus more than one SOM prediction is possible from the acquired binding pose (Raunio et al. 2015). Accordingly, SOM prediction with the 6 Å rule is specific to a region rather than an atom in the substrate. In a few approaches where either tethered docking or distance-based fingerprints are used to match the substrate with the CYP enzyme, the prediction is precise as each potential SOM is subjected to the proximity of the heme iron and thus gains an individual score (Zamora et al. 2003, Cruciani et al. 2005, 2013, Tyzack et al.

2013).

The consideration of the CYP binding site flexibility is crucial to find binding modes for substrates of varying size and shape. The available crystal structures do not necessarily represent CYP conformations that would reasonably accommodate the studied ligands. Accordingly, relaxation of the enzyme structure in MD simulations prior to docking can significantly improve the prediction success of molecular docking (Hritz et al. 2008, Sheng et al. 2014).

The utilization of more than one CYP conformation has also been demonstrated highly successful (Hritz et al. 2008). Docked ligand poses can also be further subjected to MD simulations where the enzyme can adjust to the new ligand (Bello et al. 2014, Panneerselvam et al. 2015, Sato et al. 2017, Juvonen et al. 2020). A largely diverging approach from docking is to utilize less explicit 2D or 3D distance-based fingerprints for binding mode evaluation as the fingerprints do not define the atomic interactions as strictly as traditional molecular docking (Zamora et al. 2003, Cruciani et al. 2005, 2013).

Water-mediated ligand-CYP interactions can be taken into account in both molecular docking and MD simulations. In docking algorithms, crystal structure water molecules can be included in the protein 3D structure (Zhou et al. 2006, Vasanthanathan et al. 2009a). Other approaches are to predict the hydration sites computationally (De Graaf et al. 2005) or derive water positions from hydration sites observed in MD simulations of the CYP enzyme (Santos et al. 2010).

However, the effect of including fixed water molecules in docking varies between different substrates and enzyme conformations as the water positions may not be optimal for all ligand-CYP complexes (Vasanthanathan et al. 2009a, Santos et al. 2010). In MD simulations, waters are an innate part of the method as they are carried out in an explicit solvent. In MD simulations, water networks have been shown to differ from one ligand to another in CYP1A2 (Watanabe et al. 2017).

Simulations of isoforms 2A6, 2B4, 2C8, 2C9, 2D6, 2E1 and 3A4 have demonstrated that water molecules at the CYP binding site can readily exchange with the bulk solvent in MD simulations, the rate depending on the flexibility of the CYP isoform (Rydberg et al. 2007, Hendrychova et al. 2012).

Molecular docking takes only into account the energetic but not the dynamic stability of the substrate-binding modes. MD simulations naturally provide a view of both energetic and dynamic substrate stability. The simulated ligand poses can be ranked by binding energy estimations (Bello et al. 2014, Sato et al. 2017, Juvonen et al. 2020). Dynamic stability can be considered either by a manual/visual analysis or by automatic clustering different ligand poses that are observed during the simulations, consequently evaluating the occurrence rates of the different poses (Bello et al. 2014, Panneerselvam et al. 2015, Sato et al. 2017, Juvonen et al. 2020).

Combining ligand-based reactivity descriptors with binding mode-based SOM prediction can make the prediction more accurate and adds the crucial effect of the chemical nature of the ligand to the prediction (Cruciani et al. 2005, 2013, Tyzack et al. 2013, Sato et al. 2017). As the role of ligand-CYP interactions for SOM selectivity increases for larger substrates and smaller CYP binding sites, or vice versa for ligand-based reactivity, the weight of structure-based binding mode prediction and ligand-based reactivity can be adjusted based on those factors (Cruciani et al. 2013).