MOLECULAR DOCKING STUDIES FOR IDENTIFICATION OF POTENT PHOSPHOINOSITIDE 3-KINASES (PI3KS) INHIBITORS

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1 CHAPTER 7 MLECULAR DCKIG STUDIES FR IDETIFICATI F PTET PHSPHISITIDE 3-KIASES (PI3KS) IHIBITRS 7.1 Introduction Phosphoinositide 3 kinases (PI3Ks) constitute a class of enzymes that catalyse phosphorylation of the 3 hydroxyl position of phosphoinositides (PIs) at the inositol ring. PI3Ks are classified into three major classes on the basis of substrate specificity and sequence homology. The class IA PI3Ks, comprised of a regulatory subunit (p85) and three different catalytic subunits (p110α, p110β, p110δ), are activated by receptor tyrosine kinases (Katso et al., 2001). They have a vital role in a variety of physiological processes such as metabolism, regulation, cell survival, mitogenic signaling, cytoskeletal remodeling and vesicular trafikking (Cantley, 2002; Wymann et al., 2003). There is a great deal of interest in PI3Ks as cancer targets, particularly for the p110α isoform which is mutated and/or over expressed in more than 30% of tumours. The recent discoveries that the p110α isoform undergoes gene amplification (Stephens et al., 2005) and is frequently mutated in primary tumors (Gymnopoulos et al., 2007; Samuels et al., 2004; Vogt et al., 2007), together with evidence that PTE, a lipid phosphatase which acts as a negative regulator, is a commonly inactivated tunor suppressor (Cantley et al., 1999), have genetically validated p110α as an attractive target for cancer therapy. Thus, inhibitors of these enzymes are expected to be useful in cancer treatment and hence have been extensively explored as an attractive therapeutic candidates (Marone et al., 2008). In this chapter we focus on design of specific inhibitors for class I PI3K, particularly PI3Kα using computational approach. Since, the 3D crystal structure of Pi3K α is available, we largely focus on structure based design. 151

2 7.2 Material and methods The crystal structures of Pi3K available in PDB were downloaded for the present study. The compounds belonging to the series viz. Imidazoquinoline, liphagal and tetrazolyl quinazolinone were used for generating virtual library for docking studies. For customization of the exsiting software for our target a quantitative relationship between the various docking scoring functions and Pi3K inhibitory activity was established using ligand based studies Docking studies of PI3K isoforms with the ligands All the computational studies were carried out in the Schrodinger suite 2012 molecular modeling software. The 2D structures of all the molecules were built in the maestro window. All the molecules were then converted to their respective 3D structure, with various conformers, tautomers and ionization states using the Ligprep and Confgen modules (Watts et al., 2010; Chen et al., 2010). The molecules were then minimized using the PLS_2005 force field. The 3D crystal structures of PI3Kα (PDB ID: 3HHM) (Mandelkar et al, 2009) and PI3Kδ (PDB Id: 2WXF) (Berndt et al., 2010) reported in Protein Data Bank (PDB) were used as receptors for docking studies. The proteins were downloaded from the PDB and were prepared for docking using the Protein Preparation wizard. Hydrogens were added to the proteins and the missing loops were built. Bond length and bond order correction was also carried out for preparing the proteins for docking studies. The active site grid was generated based on the already co crystallized ligand of the receptor using receptor grid generation module. The co crystallized ligand was extracted and docked again in order to establish a docking protocol for the selected target. Further the ligand dataset was docked on to the receptor through the identified grid using Glide module and flexible docking was carried out for all the conformers in order to find out the binding mode of these ligands. The standard precision (SP) scoring function of Glide was used for carrying out these studies (Friesner et al., 2004; Halgren et al., 2004). The detailed methodology is described in the Methodology chapter (Section3.3, Chapter 3). 152

3 7.2.2 Selection of dataset (ligand compounds) The following class of compounds were selected for the docking studies: i. Imidazoquinoline analogs (VP BEZ235) The parent compound being from ovartis, and the first PI3K inhibitor to enter the clinical trials. Presently it is in Phase I clinical trials. BEZ235 is an imidazoquinoline derivative and a known PI3K inhibitor. A virtual library of compounds was created based on this compound and docked onto the crystal structure of PI3K. Grid was generated based on the co crystallized structure and all the molecules of BEZ library were docked on to that grid. Preliminary docking studies for the following series of compounds have also been initiated: ii. iii. Liphagal analogs Liphagal was first selective inhibitor of PI3Kα. Tetrazolyl Quinazolinone analogs (CAL 101) The parent compound showed promising Phase I results and presently is in early Phase II clinical trials. CAL101 is a selective PI3K class I inhibitor of Pi3Kδ. Hence, docking studies of its analogs were carried out on both PI3Kα and Pi3Kδ in order to compare the ligand receptor interaction and dock score of these two receptors with tetrazolyl quinazoline analogs Quantitative energy value scoring function activity relationship In order to customize the generic software Schrodinger for the target Pi3K α, a quantitative regression analysis was carried out between the experimental IC 50 values of the known inhibitors (Hayakawa et al., 2006; Hayakawa et al., 2007(a c)) and the scoring functions used for their docking analyses with the selected target (PI3Kα). A data set of 65 molecules was taken from literature for this study which was suitable divided into training set data and test set data. A highly statistical model was prepared for the theoretical evaluation of the inhibitory activity of a new molecule towards PI3Kα. The model along with dock scores and interaction studies (of ligand with target) will also help in lead optimisation and would contribute 153

4 towards the identification of a novel PI3Kα inhibitor. The detailed QSAR methodology is described in the methodology chapter (Section 3.5, Chapter 3). 7.3 Results and Discussion In order to understand the constitution of PI3Kα, the 3D crystal structure of Pi3K was analyzed with respect to various domains present in it. PI3Kα comprises of Adaptor Binding Domain (ABD), RAS Binding Domain (RBD), C2, Helical and the Kinase domain. Further, the kinase domain is divided into Lobe and C Lobe, and contains some specific interesting regions for the ligand recognition and binding such as Activation loop, Hinge region, Gatekeeper residues etc. (as shown in Figure 7.1). The 3D crystal structure was analyzed using the software Schrodinger, in order to identify these regions within the structure. Also, the respective location of the co crystallized and other docked ligands was determined within the structure, with respect to the identified regions of the kinase. Table 7.1: Reported 3D structures for human PI3Kα S. PDB ID LEGTH LIGAD CHAIS SPECIES 1. 3HHM * 1091,373 PRESET A,B Homo sapiens 2. 3HIZ* 1096,373 ABSET A,B Homo sapiens 3. 2EQ 158 ABSET A Homo sapiens 4. 2RD0 1096,279 ABSET A,B Homo sapiens The above given table (Table 7.1) shows the reported 3D structure for human PI3K α of which 3HHM and 3HIZ are mutants (His1047Arg) where as 2EQ and 2RD0 are the wild types. 3HHM was co crystallized with ligand (wortmanin). Since more than 1,500 PIK3CA mutations in diverse tumor types have been discovered (Liu et al., 2009). The most common mutant is His1047Arg (Mandelkera et al., 2009), and mutations at this residue in breast and uterine cancers are associated with clinical prognosis (Mandelkera et al., 2009; Janku et al., 2011; Flavia et al., 2012), so we took 3HHM 3D structure for the docking analysis. 154

5 Figure 7.1. Structural analysis and identification of ligand recognition regions of Pi3K-α. 155

6 The co crystallized ligand wortmanin was extracted from the downloaded 3D crystal structure and was again docked using several docking protocols in Glide. The best conformation match was observed using the standard precision (SP) scoring function of Glide. The co crystallized and docked pose of wortmanin within the binding pocket of PI3K α is shown in Figures 7.2(a) and 7.2(b) respectively. (a) (b) Figure 7.2 rientation of wortmanin within the binding pocket of PI3K-α in (a) 3D crystal structure 3HHM in PDB and (b) obtained using docking studies. 156

7 7.3.1 Molecular docking studies and interaction analysis of Imidazoquinoline analogs with PI3Kα BEZ235 is an imidazoquinoline derivative and a known PI3K inhibitor. A virtual library of about 500 compounds was created based on this compound and docked onto the crystal structure of PI3K. Grid was generated based on the co crystallized structure and all the molecules of BEZ library were docked on to that grid. The top 20 molecules (ranked better than the co crystallized ligand) on the basis of their dock scores are shown in table 7.2. From a library of about 500 molecules designed on the basis of SAR studies reported in literature, 20 molecules showed better predicted binding affinity than the standard (BEZ235), based on the dock score. The interaction of the best analog i.e., IZQ23 showed the involvement of hinge region residue Val851 in H bonding with the ligand, apart from Ser774 and Ser854. The extra stability to the ligand is proposed to be provided by the hydrophobic cleft formed by the residues Trp780, Leu807, Tyr836, Ile848,Val850, Val851, Met922, Phe930, Ile932 and Phe934 with Trp780 and Tyr836 also involved in π π interaction with the ligand as shown in Figure 7.3. It was observed that the sulphonate group increases the binding affinity of the ligand within the binding pocket of PI3K α by orienting it in such a fashion that the oxygen of the sulphonate is involved in H bonding with Ser854 and the hinge residue Val851 is involved in H bonding with hydrogen of the amide group. From the dock scores of other ligands in the library it was observed that the presence of halogen increases the affinity towards the receptor. The structures with dock scores of the molecules possessing better affinity than the standard are given in Table 7.2. Besides this, docking studies were also initiated with the other two series of compounds viz., liphagal analogs and tetrazolyl quinazolinone series. The validation (as well as feedback for modification) of the in silico studies was carried out by wet lab experiments carried out at Pharmacology division, IIIM Jammu. 157

8 Figure 7.3. Interaction of the in silico best Imidazoquinoline analog within the binding pocket of Pi3Kα 158

9 Table 7.2: Dockscores of BEZ library having scores better than the co-crystallized ligand (wortmanin). S.o Molecule ame Structure Dockscore 1 IZQ H S 2 IZQ45 C H CH3 H 2 3 IZQ IZQ8 S 9.31 H 5 IZQ

10 6 IZQ IZQ H Cl 8 IZQ H 2 9 IZQ IZQ C H 3 H H 11 IZQ C H 3 H 160

11 12 IZQ C H 3 13 IZQ C H 3 CH IZQ IZQ H 16 IZQ33 C H CH

12 17 IZQ H 18 IZQ F 19 IZQ F F 20 IZQ Cl 21 Wortmanin BEZ (standard) 162

13 7.3.2 Molecular docking studies of Liphagal derivatives and Tetrazolyl Quinazolinone series with PI3Kα Docking studies were also initiated on Liphagal derivatives and tetrazolyl quinazolinone series. Liphagal is the selective inhibitor of PI3kα. A series of liphagal analogs were generated based on the available patent space and the constituent of the binding pocket of PI3kα. Whereas, the purinyl quinazolinone scaffold (CAL 101) showed some promising Phase I results and presently is in Phase II studies. CAL101 is a selective PI3K class I inhibitor of PI3Kδ. Based on the inputs from our medicinal chemistry lab with respect to the available patent space, a series of molecules were designed and docked onto the 3D structure of PI3Kα and PI3Kδ. Majorly, all the molecules showed comparable dock scores with liphagal, except for a boronic acid derivative of liphagal that showed exceptionally good scores. From the interaction figure of liphagal (Figure 7.4), it was observed that Val851, the hinge residue is involved in H bonding with one of the hydroxyl group in the phenyl moiety of the molecule. Also, the formyl group is involved in H bonding with Gln859. The phenyl is involved in π π interaction with Trp780. From the docking studies of the liphagal derivatives, it was observed that the boronic acid derivatives shows significantly enhanced binding affinity towards the target. The introduction of boronic acid strengthens the H bonding with the pivotal residues such as Val851 and Gln859 and further the orientation is quite favourable for π π interactions with Trp780. A small hydrophobic cleft formed by the residues Ile800, Tyr836, Ile848 and Val850 also may help in the strong interaction between the ligand and the receptor (as shown in figure 7.4). The validation (as well as feedback for modification) of the in silico studies was carried out by wet lab experiments carried out at Pharmacology division, IIIM Jammu. 163

14 nd (b) boronic acid derivativee of liphagal within the bindiing pocket Figure 7.4. Interaction of (a) liphagal an of PI3K-α 164

15 From the docking studies of tetrazolyl quinazolinone series, it was observed that the series has better affinity towards PI3Kδ than PI3K α. The dock scores of PI3Kα with all the molecules was much higher (less binding affinity) than the standard. The binding affinity of all the molecules docked on PI3Kδ was also comparatively lesser than the standard, except for a boronic acid derivative of tetrazolyl quinazolinone (Figure 7.5) where it was well comparable with the standard. nce again, the role of boronic acid in ligand binding was surfaced out. It was observed that boronic acid plays an important role in the ligand binding. Based on the interaction figure, no specific residue could be identified for PI3Kδ that tends to play a crucial role in ligand binding, unlike the case of its other isoform PI3Kα. Though, Glu826 & Val828 and Lys779 & Asp911 are involved in H bonding with the standard (CAL101) and the boronic acid derivative respectively (Figure 7.5). Further studies on this would be taken up on the form of a project. The validation (as well as feedback for modification) of the in silico studies was carried out by wet lab experiments carried out at Pharmacology division, IIIM Jammu. 165

16 (a) (b)) o (a) standaard Figure 7.5 Interactioon figures of molecule i.e., CAL1011 within the biinding pocket of hin PI3Kα, (b) standard molecule i.e., CAL101 with ding pocket oof PI3Kδ and (c) the boron nic the bind acid deerivative of teetrazolyl quinaazolinone with hin the bind ding pocket off PI3Kδ (c) 166

17 Further, in order to customize the generic software Schrodinger for the target PI3Kα, a quantitative regression analysis was carried out between the experimental IC 50 values of the known inhibitors (from literature) and the scoring functions used for their docking analyses with the selected target (PI3Kα). A data set of 65 molecules was taken from literature (Hayakawa et al., 2006; Hayakawa et al., 2007(a c)) for this study which was suitably divided into training set data and test set data. A highly statistical model was prepared for the theoretical evaluation of the inhibitory activity of a new molecule towards PI3Kα. The model along with dock scores and interaction studies (of ligand with target) will also help in lead optimisation and would contribute towards the identification of a novel PI3K α inhibitor. Final Model: Activity = *r_glide_res:a836_dist *r_glide_xp_lipophilic Evd W 1.22 * r_glide_res:a856_vdw 0.46 * r_glide_res: A854_Eint 0.13 * r_i_glide_ecoul * r_glide_res: A932_dist 2.37 * r_glide_res:a 930_vdw+3.33 * r_glide_res:a 836_h bond =50; LF=0.459; r 2 =0.882; r 2 adj=0.858 Ftest=38.152; LSE=0.212; r=0.939; q 2 = Conclusion From the available 3D crystal structure of PI3K α and its docking studies with several classes of compounds, it was observed that the hinge region (Val851) plays a major role for the identification and binding of ATP competitor inhibitor. Besides this, Tyr836, Gln859 also plays an important role. The role of aldehyde moiety in liphagal was also identified from its interaction, where Gln859 is directly involved in H bonding with the formyl group of liphagal. Allosteric site is proposed to be nearby the ATP binding site, but the effective residues are still not clear. The role of boronic acid moiety in the ligand significantly improves the binding for PI3Kα as well as 167

18 PI3Kδ. It was also observed that the tetrazolyl quinazolinone derivatives has better affinity towards PI3Kδ than PI3Kα. In order to customize the existing generalized docking software, a QEvAR study was carried out based on the known PI3Kα inhibitors where activity was made a dependent variable and the scoring functions used in Glide as the dependent variables. 168