Design and In-Silico ADMET Analysis of new Benzopyrane-derived Pim-1 Inhibitors

Zein Alabdeen Khdar¹*, Faten Sliman², Mohammad Kousara³

¹Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishreen University, Lattakia, Syria.

²Department of Pharmaceutical Chemistry, Faculty of pharmacy, Tartous University, Syria.

³Department of Pharmaceutical Chemistry, Faculty of pharmacy, Tishreen University, Lattakia, Syria

*Corresponding Author E-mail: Fatensliman@tartous-univ.edu.sy, mohammadkousara@tishreen.edu.sy, zen.khdar@hotmail.com

ABSTRACT:

Pim-1 (Proviral Insertion site of Molony Murine Leukemia virus) kinases is an oncogene which is known to be over expressed and dysregulated in hematological and solid tumors suggesting that inhibition of Pim-1 signaling could provide patients with therapeutic benefits. Herein, we describe our effort towards this goal by using molecular modeling methods. We have designed (64) compounds derived from 2-(3,4-dihydro-1-Benzopyran) acetic acid (compound 5). The docking study with Pim-1 crystal structure was performed by using CDocker and Ligand fit docking methods. Then hits were filtered based on In-silico ADMET properties. This study led to conclude that compounds Benz30 and Benz53 could be promise Pim-1 inhibitors with preferred ADMET properties.

KEYWORDS: Pim-1, hinge region, tumors, benzopyran, CDocker, Ligand fit, ADMET.

INTRODUCTION:

Pim (Proviral Insertion site of Molony Murine Leukemia virus) kinases are a family of Serine/Threonine kinases in the CAMK group (Calcium/calmoduline-dependent protein kinase).^[1,2] Pim family consists of three isoforms: Pim-1, Pim-2 and Pim-3, which share high structural homology (more than 60%) and are differentiated from other kinases by their unique hinge regions which give the chance to design rational selective kinase inhibitors.^[3-5] Pim-1 hinge region consists of six amino acids Glu121, Arg122, Pro123, Glu124 , Pro125 and Val126.^[6,7] It is obvious that Pim-1 is the only protein kinase with proline moiety at 123 position, where proline is not capable to form hydrogen bond with ATP molecule. More than that, Pro123 is in Cis conformation which lead to a kink within the hinge region (fig.1)^[6,7]

Fig.1: Pim-1 unique hinge region.

On the other hand, Pim Kinases have continuous activity ^[8,9], so they are regulated at the level of transcription ^{[10, 11]}, translation and proteasomal degradation^[12,13]. It is evident that Pim-1 plays a key role in a variety of biological processes including cell survival, proliferation, differentiation and apoptosis by interacting with several biological substrates^[14] such as BAD^[15,16], P53^14] , Cdc25C^[17] , Cdc25A^[18] and ASK-1^[19]. Pim-1 oncogene is known to be overexpressed and dys-regulated in hematological and solid tumors such as Diffuse large B-cell lymphoma (DLBCL), pancreatic, oral and prostate cancers.^[4,20,21] Based upon the proved roles of Pim-1 kinase in tumorigenesis, it is considered as an attractive target for cancer therapy. There have been several reports of selective Pim-1 inhibitors including three clinical compounds, SGI-1776^[22], AZD-1208^[23] and PIM-447^[24] (compounds 1, 2, 3) (Fig.2).

Fig.2: Chemical structures of compounds SGI-1776, AZD-1208 and PIM-447.

Xiang et al discovered a series of novel benzofuran-2-carboxylic acids as potent Pim-1 inhibitors. They have reported that compound (4) exhibited potent inhibition towards Pim-1 and Pim-2 with IC₅₀ values of o.oo1 and 0.004 µM, respectively. The crystal structure revealed key interactions between compound 4 and the Pim-1 protein, especially the carboxyl group which form a salt bridge with Lys67 and Asp186 ( Fig.3).^[25]

Fig.3: The crystal structure of compound 4/Pim-1 complex (PDB code is 3r02).

Another attempt was accomplished by F. Sliman et al. They have studied a series of quinoline derivatives and showed that 8-hydroxy quinoline-7-carboxylic acid moiety seemed to be important for the Pim-1 inhibitory activity by forming critical interactions with Asp186 and Lys67 residues within the ATP binding site. Compound (5) exhibited the best activity with IC₅₀ value of 0.2µM. ^[26] (Fig. 4)

Fig.4: The interactions between compound (5) and Pim-1 active site.

Additionally, we have deeply studied the binding mode of various Pim-1 inhibitors which were crystalized with the protein and were derived from numerous chemical heterocycles such as indole^[27], imidazopyridazine^[28] and Azaindazole^[29]. It was clear that most of these compounds were not able to fill the whole active site, so they were characterized with low affinity.

This encouraged us to choose 2-(3,4-dihydro-1-Benzopyran) acetic acid (compound 6) (Fig.5) to be a scaffold structure in our study aiming at designing compounds which have key interactions with active site.

Fig.5: Chemical structure of compound 6.

Nowadays, nobody can deny the fact and truth that computer-aided drug design (CADD) methods play a fundamental role in the development of new drugs.^[30-32] These methods are classified into two categories: structure-based drug design (SBDD) and ligand-based drug design (LBDD)^[33]. The most beneficial advantages of using CADD methods in drug discovery is cost and time saving and the predictive power of CADD facilitates choosing of promising candidates by In-Silico ADMET prediction^.[34,35] Herein, we report our efforts towards finding new potent inhibitors of Pim-1 kinase with promise pharmacokinetic properties.

METHODS AND MATERIALS:

Pim-1 crystal structures was obtained from PDB (protein data bank). ChemBioDraw Ultra 11.0 was used to design a set of compounds for the docking study. Docking study and In-Silico ADMET prediction were performed by Accelrys discovery studio 2.5 software.

Choosing the template crystal structure:

Aiming at choosing the most valid crystal structure to be used in our study, we firstly downloaded all the available Pim-1 crystal structures from PDB. After that, we classified these structures according to several parameters: resolution, type of structure (apo-protein or complex), efficacy and the binding-participated amino acids.

Preparation the crystal structure of Pim-1:

It is well known that the extracted crystal structure from PDB does not have hydrogen atoms, so firstly hydrogen atoms must be added by applying several force fields (CHARMm). Adding hydrogen atoms lead to 3D obstructions and subsequently to a high energy and unstable molecule, which should be minimized. Minimization of the crystal structure was performed by using adopted basis minimization aiming at finding the most stable and less energy structure and reducing H-H interactions without affecting the basic protein skeleton atoms. Then, the active site was determined and sphere surrounded.^[36]

Design compounds library:

Firstly, we have designed a group of compounds (Benz1-Benz36) derived from 2-(3,4-dihydro-1-Benzopyran) acetic acid (compound 6) by adding a variety of substituents at 6 and 8 sites (as shown in table 1).

Table (1): The structural features of compounds Benz1-Benz36.

R₂	R₁	Compound	R₂	R₁	Compound
(CH₂)₂OH		Benz19	CH₂OH		Benz1
(CH₂)₂OH		Benz20	CH₂OH		Benz2
(CH₂)₂OH		Benz21	CH₂OH		Benz3
(CH₂)₂OH		Benz22	CH₂OH		Benz4
(CH₂)₂OH		Benz23	CH₂OH		Benz5
(CH₂)₂OH		Benz24	CH₂OH		Benz6
(CH₂)₂OH		Benz25	CH₂OH		Benz7
(CH₂)₂OH		Benz26	CH₂OH		Benz8
(CH₂)₂OH		Benz27	CH₂OH		Benz9
(CH₂)₂OH		Benz28	CH₂OH		Benz10
(CH₂)₂OH		Benz29	CH₂OH		Benz11
(CH₂)₂OH		Benz30	CH₂OH		Benz12
(CH₂)₂OH		Benz31	CH₂OH		Benz13
(CH₂)₂OH		Benz32	CH₂OH		Benz14
(CH₂)₂OH		Benz33	CH₂OH		Benz15
(CH₂)₂OH		Benz34	CH₂OH		Benz16
(CH₂)₂OH		Benz35	CH₂OH		Benz17
(CH₂)₂OH		Benz36	CH₂OH		Benz18

Aiming at studying the effects of acetic acid group position, we have designed a new group of compounds (Benz37-Benz56) which contain 3-acetic acid group, a double bound on 2 position and group of substituents at 5 and 7 positions (table 2).

Table (2): The structural features of compounds Benz37-Benz56.

R₂	R₁	Compound	R₂	R₁	Compound
CH₂OH		Benz47	CH₂OH		Benz37
(CH₂)₂OH		Benz48	CH₂OH		Benz38
(CH₂)₂OH		Benz49	CH₂OH		Benz39
(CH₂)₂OH		Benz50	CH₂OH		Benz40
(CH₂)₂OH		Benz51	CH₂OH		Benz41
(CH₂)₂OH		Benz52	CH₂OH		Benz42
(CH₂)₂OH		Benz53	CH₂OH		Benz43
(CH₂)₂OH		Benz54	CH₂OH		Benz44
(CH₂)₂OH		Benz55	CH₂OH		Benz45
(CH₂)₂OH		Benz56	CH₂OH		Benz46

Another group of compounds (Benz56-Benz64) were designed by adding specific substituents at 5 and 8 positions (table 3).

Table (3): The structural features of compounds Benz57-Benz64.

R₂	R₁	Compound	R₂	R₁	compound
CH₂OH		Benz61	CH₂OH		Benz57
CH₂NH₂		Benz62	CH₂NH₂		Benz58
CH₂OH		Benz63	CH₂OH		Benz59
CH₂NH₂		Benz64	CH₂NH₂		Benz60

Docking study:

Docking studies could be accomplished by using more than one method, where the complementary between results give more valid and accurate information about compounds binding and affinity. We have chosen CDocker and Ligand fit docking methods to do docking study in our work.

CDocker:

By using CDocker method, we can generate all the possible conformations of the compound in the protein active site. Then the results can be assessed by both the –CDocker energy and the number of interactions between protein and ligand. This method requires preparing the crystal structure (as mentioned before) and preparing designed compounds by using Accelrys Discovery Studio protocol and applying force field.

The designed compounds should be prepared by using Accelrys Discovery Studio 2.5 protocol and applying force field.

Before starting this study, it is important to make sure that the used method is valid by comparing the conformation of the reference compound with its conformations generated by docking method, where RMSD (Root Mean Square Deviation) should not exceed 2A^°.^{[37, 38]}

Ligand Fit Docking:

Ligand fit docking is a novel method for shape-directed rapid docking of ligands to protein active site. Docking could be rigid or flexible depending on the number of Monte Carlo trials number. We have accomplished a flexible docking with a number of Monte Carlo trials equals 15000^{[39, 40]}. This method also requires validation and preparation of protein and ligands (as mentioned before in CDocker method). The results are evaluated based on several score functions such as PLP (Piecewise Linear Potential) and Jain scoring function.

RESULTS AND DISCUSSION:

Selecting Pim-1 crystal structures:

We have selected the crystal structure 5KZI which has high accuracy with a resolution value of 2.1 A°. It is a complex between compound 7 (IC₅₀=0.1nM) and Pim-1 active site (Fig.6)

Fig.6: The crystal structure of compound 7/Pim-1 complex (PDB code is 5kzi ).

Docking study:

CDocker:

According to the validation study, the RMSD values showed that the crystal structure 5KZI and the used protocol are valid and could be confidingly used for docking study, where the RMSD values of all compound 6-generated conformations were less than 1 A°.

After that, docking study was continued on designed compounds derived from 2-(3,4-dihydro-1-Benzopyran) acetic acid (compound 6).

According to compounds (Benz1-Benz18), the –CDocker energy values varied between 36.5318 and 54.9426 (table 4). Docking study of these compounds showed that the benzopyran core came close to the hinge region without forming any bond with amino acids found in it. The carboxyl group participated in a water-mediated hydrogen bond with Phe187 in most compounds except Benz11, where it formed a hydrogen bond with Lys67. While the hydroxyl group formed either direct or water-mediated hydrogen bonds with Asn172 and Glu171. As for R₂ substituent, It formed a π interaction with Phe49(fig.7).

Fig.7: The binding mode of compounds Benz1-Benz18 with Pim-1 active site.

Table (4): The –CDocker energy values of compounds Benz1-Benz36

-CDocker energy	compound	-CDocker energy	compound
46.0112	Benz19	39.7699	Benz1
44.0021	Benz20	46.0872	Benz2
51.1855	Benz21	54.9426	Benz3
47.8745	Benz22	45.5248	Benz4
27.2009	Benz23	36.5318	Benz5
48.2611	Benz24	44.1392	Benz6
48.9354	Benz25	46.295	Benz7
43.4915	Benz26	40.742	Benz8
52.3635	Benz27	53.4888	Benz9
44.9553	Benz28	44.2815	Benz10
42.639	Benz29	43.9945	Benz11
39.7371	Benz30	41.4593	Benz12
50.8202	Benz31	47.7988	Benz13
43.6505	Benz32	44.9468	Benz14
50.7606	Benz33	50.3849	Benz15
51.5357	Benz34	43.77	Benz16
50.4582	Benz35	56.1563	Benz17
36.3394	Benz36	39.7828	Benz18

Aiming at studying the effects of the R₂ substituent length, we have designed compounds (Benz19-Benz36) which had hydroxyl ethyl group instead of hydroxyl methyl one (table 4). The docking study presented that increasing the length of alkyl group did not lead to that important increase in affinity towards Pim-1 active site, where these compounds did not form any interaction with the crucial amino acids in the hinge region except compound Benz30 (-CDocker energy= 39.7371) in which the hydroxyl group formed direct and water-mediated hydrogen interactions with Val126 (the last amino acid in the hinge region). More than that, The carboxyl group also formed a water-mediated hydrogen bond with Phe187 (Fig.8).

Fig.8: A comparison between the binding type of compound Benz12 (A) and compound Benz30 (B).

The compounds (Benz37-Bnz56) were designed to study the effects of both acetyl group position and the presence of a double bond at C2 position.

Table (5): The –CDocker energy values of compounds Benz37-Benz56

-CDocker energy	compound	-CDocker energy	compound
20.1787	Benz47	24.741	Benz37
30.4634	Benz48	29.6919	Benz38
27.9986	Benz49	32.2412	Benz39
29.0941	Benz50	24.7384	Benz40
22.8096	Benz51	21.0083	Benz41
18.6007	Benz52	28.8404	Benz42
25.2507	Benz53	25.4693	Benz43
26.1586	Benz54	18.9596	Benz44
20.6420	Benz55	24.0737	Benz45
23.3973	Benz56	20.2513	Benz46

Comparing with the previous designed compounds, the hydroxy methyl derivatives (Benz37-Benz47) exhibit higher affinity towards Pim-1 active site by forming higher number of interactions, but no compound formed interactions with critical amino acids in hinge region. According to compounds Benz41,43,44,46,47, the carboxyl group formed two hydrogen interactions with Lys67 and Asp186 which have a key role in stabilizing the structure of Pim-1 active side. Additionally, the hydroxyl group formed a hydrogen bond with Asp128 (Fig.9 and Table5)

Fig.9: The binding mode of compounds Benz41,43,44,46,47 with Pim-1 active site.

On the other hand, the docking study of hydroxy ethyl derivatives (Benz48-Benz56) showed the importance of increasing the alkyl group length, where this led to compounds with key interactions with hinge region such as compounds Benz50 and Benz53 which had –CDocker energy values of 29.914 and 25.2507 respectiely.

As shown in fig.10, the carboxyl group of compound Benz50 formed two hydrogen bonds with Lys67 and Asp186. While the hydroxyl group came close to the hinge region and formed a hydrogen bond with Glu121 (the first amino acid in the hinge region)

Fig.10: the interactions between compound Benz50 and Pim-1 active site.

Also the compound Benz53 took part in important interactions with Pim-1 active site, where the carboxyl group and hydroxyl group formed a hydrogen bond with Asp186 and Glu121, respectively (Fig.11)

Fig.11: the interactions between compound Benz53 and Pim-1 active site.

The deep study of compounds (Benz37-Benz56) ,which have substituents at C5 and C7 positions, showed that in most compounds the substituent R₁ was oriented out of the active site and the unsubstituted C8 position was sited next to hinge region. Based upon these findings, we have designed compounds (Benz57-Benz64) which were substituted at C5 and C8 positions. these compounds could be classified into two groups: hydroxyl derivatives (Benz57, 59, 61, 63) and amino derivatives (Benz58, 60, 62, 64) (table 6)

Table (6): The –CDocker energy values of compounds Benz57-Benz64

-CDocker energy	compound
21.4319	Benz57
40.2409	Benz58
19.7809	Benz59
40.3532	Benz60
25.0571	Benz61
46.7477	Benz62
31.8469	Benz63
50.5446	Benz64

The docking study of these compounds showed that the amino derivatives exhibited higher affinity towards active site than the hydroxyl ones. Among the hydroxyl derivatives, only compounds Benz57 and Benz63 formed interactions with active site, where the aromatic amine group of compound Benz57 formed two hydrogen bonds with Glu171 and Asn172, While the carboxyl group of compound Benz63 formed two hydrogen bonds with Lys67 and Asp186 (Fig.12)

Fig.12: A comparison between binding mode of hydroxyl derivatives (A) and amino derivatives (B)

According to amino derivatives, they participated in more critical interactions with active site as the following:

· 74Compound Benz58 (-CDocker energy = 40.2409): The carboxyl group formed two hydrogen bonds with Lys67 and Asp186. The amino methyl group formed a hydrogen bond with Asp128. Whereas, the aromatic amine of R₁ substituent formed a hydrogen bond with Glu121 (Fig.13).

Fig.13: The interactions between Benz58 and Pim-1 active site.

· Compound Benz60(-CDocker energy = 40.2533) also formed the same interactions that of Benz58 (Fig.14).

Fig.14: The interactions between Benz60 and Pim-1 active site.

· Compound Benz62(-CDocker energy = 46.7477): The carboxyl group formed two hydrogen bonds with Lys67 and Asp186. The amino methyl group formed a hydrogen bond with Asp128 (Fig.15).

Fig.15: The interactions between Benz62 and Pim-1 active site.

· Compound Benz64(-CDocker energy = 50.5446) showed high affinity by forming important interactions: The carboxyl group formed two hydrogen bonds with Lys67 and Asp186. The amino methyl group formed a hydrogen bond with Asp128 and Glu171 (Fig16)

Fig.16: The interactions between Benz64 and Pim-1 active site.

Based upon the aforementioned results, we can state that compounds Benz30, Benz 41, Benz 43, Benz 44, Benz 46, Benz 47, Benz 50, Benz 53, Benz 58, Benz 60, Benz 62 and Benz 64 showed the highest affinity towards Pim-1 among the designed compounds, so that they can be considered as hits.

Ligand fit docking:

Before starting the docking study, the crystal structure of Pim-1 5KZI was also prepared by adding hydrogen atoms and minimization. Then the active sites were defined by using Accelrys Discovery Studio 2.5 tool: find sites from receptor cavities. Moreover, the validation study showed that the used docking method is valid based on RMSD values (less than 1Aº).

The ligand fit docking method was applied for the hits to get more accurate information about their affinity. We have used several score functions to assess the results such as PLP-1, PLP-2, Jain and Dock score. Aiming at evaluation of hits score functions, they were compared to the reference compound 7 (table 7).

Table (7): The score function values of Hits (Ligandfit docking).

-PLP-2	-PLP-1	Compound
69.03	70.83	Benz30
49.13	35.64	Benz41
69.89	73.52	Benz43
66.81	66.99	Benz44
73.4	73.09	Benz46
57.5	54.45	Benz47
58.09	63.41	Benz50
60.2	49.85	Benz53
58.52	57	Benz58
55.5	45.24	Benz60
68.79	63.75	Benz62
64.84	64.79	Benz64
99.57	96.69	Compound 7

Based on the applied score functions, we can notice that compounds Benz30, Benz43, Benz44, Benz46, Benz62, Benz53 and Benz64 have the best score functions if compared with the reference compound 6, subsequently this emphasizes their predicted ability to interact with Pim-1 active site and they could be a promising Pim-1 inhibitors.

Filtration of Hits:

Determination of Molecular properties:

Based upon the truth that oral bioavailability is highly affected by molecular properties of drug molecule, we have calculated the molecular properties of hit compounds by using Accelrys Discovery Studio 2.5 software. The Lipinski's rules of five shows that the absorption of a ligand is higher when: molecular weight less than 500 D, calculated log P value less than 5, no more than 5 hydrogen bond donor (HBD) groups, no more than 10 hydrogen bond acceptor (HBA) groups and no more than 10 rotatable bonds.

As shown in table (8), it is obvious that all the hits are in accordance with Lipinski's rules of five, so they are anticipated to have good oral bioavailability.

Table (8): Molecular properties of Hits.

Polar Surface area	Num. Rings	Num. Rotable bonds	Num. HBD	Nun. HBA	Molecular Weight	ALogP	Compound
0.261	3	8	1	6	356.392	0.755	Benz30
0.292	3	6	2	5	333.379	-1.59	Benz41
0.316	3	5	2	6	311.312	-0.096	Benz43
0.308	3	5	1	6	312.279	-0.086	Benz44
0.321	3	5	2	6	327.308	0.822	Benz46
0.334	3	5	2	6	326.323	0.318	Benz47
0.284	3	7	2	6	339.365	0.067	Benz50
0.3	3	6	3	5	332.394	-2.022	Benz53
0.351	3	5	2	5	326.347	-0.977	Benz58
0.308	3	6	1	5	326.347	-1.374	Benz62
0.316	3	6	2	5	325.362	-1.549	Benz64
0.338	3	5	2	5	327.331	-0.472	Benz60

In-Silico ADMET analysis:

ADMET refers to absorption, distribution, metabolism, excretion and toxicity properties for a molecule. They were predicted for hit compounds by using ADMET descriptors in Accelrys Discovery studio 2.5. There are six mathematical models are used to quantitatively predict properties of a set of compounds. These models contain: aqueous solubility (predict solubility in water at 25ºC, blood brain barrier (BBB) penetration, cytochrome P450 (CYP450) 2D6 inhibition, hepatotoxicity, human intestinal absorption (HIA) and plasma protein binding. ^[41,
42] These ADMET descriptors give us the chance to get rid of compounds with undesired ADMET characteristics. An ADMET model was also generated to predict the human intestinal absorption (HIA) and Blood Brain Barrier (BBB) penetration of tested compounds. The model includes 95 and 99% confidence ellipses in the ADMET_PSA_2D and ADMET_ALogP98 plan as shown in figure (17).

Fig.17: Plot of Polar Surface Area (PSA) vs. LogP for a standard and test set showing the 95% and 99% confidence limit ellipses corresponding to the Blood Brain Barrier and Intestinal Absorption models.

Table (9): In silico ADMET properties of hits.

*In silico* ADMET properties								Componds
PSA 2D	AlogP98	PPB level	CYP2D6 inhibition	Hepato-toxicity	Solubility level	Absorption level	BBB level	Componds
84.538	0.755	0 (<90%)	1 (inhibitor)	0 (non-toxic)	4 (optimal)	0 (good)	3 (low)	Benz30
94.092	-1.59	2 (>95%)	0 (non-inhibitor)	0 (non-toxic)	4 (optimal)	1 (moderate)	4 (Undefined)	Benz41
99.817	-0.096	0 (<90%)	1 (inhibitor)	1 (toxic)	4 (optimal)	0 (good)	3 (low)	Benz43
88.418	-0.086	0 (<90%)	1 (inhibitor)	1 (toxic)	4 (optimal)	0 (good)	3 (low)	Benz44
77.157	0.823	0 (<90%)	1 (inhibitor)	1 (toxic)	4 (optimal)	0 (good)	3 (low)	Benz46
111.25	0.318	0 (<90%)	1 (inhibitor)	1 (toxic)	4 (optimal)	0 (good)	3 (low)	Benz47
95.976	0.067	0 (<90%)	1 (inhibitor)	1 (toxic)	4 (optimal)	0 (good)	3 (low)	Benz50
99.856	-2.022	0 (<90%)	0 (non-inhibitor)	0 (non-toxic)	5 (too- soluble)	2 (low)	4 (Undefined)	Benz53
105.53	-0.977	0 (<90%)	1 (inhibitor)	1 (toxic)	4 (optimal)	1 (moderate)	4 (Undefined)	Benz58
88.418	-1.374	2 (>95%)	1 (inhibitor)	1 (toxic)	4 (optimal)	1 (moderate)	4 (Undefined)	Benz62
84.538	-1.548	2 (>95%)	1 (inhibitor)	1 (toxic)	4 (optimal)	1 (moderate)	4 (Undefined)	Benz64
94.092	-0.472	1 (>90%)	1 (inhibitor)	1 (toxic)	4 (optimal)	0 (good)	3 (low)	Benz60

As shown in table (9), the upper limit of PSA_2D value for the 95% confidence ellipsoid is at 111.25 for compound Benz47, while the lower value is 77.157 for compound Benz46 and the AlogP89 values are less than 5. All of these values are within the standard range shown in figure (17), which confirm that these compounds are good in absorption through human intestinal except compound Benz53 which exhibits low absorption levels. Additionally, these compounds exhibit low ability to penetrate blood brain barrier (BBB). This can be justified by high aqueous solubility levels of these compounds. Furthermore, some of these compounds exhibited an ability to cause hepatotoxicity or to inhibit cytochrome p450.

Pim-2 inhibition Probability:

It was proven that Pim-2 also plays a critical roles in various vital functions such as growth and cell division. Additionally, many reports showed that Pim-2 is overexpressed mainly in multiple myeloma, so many researches focused on developing Pim-1,2 inhibitors which was difficult due to the high affinity between Pim-2 and ATP (ATP K_m for Pim-2 = 4 μM, ATP K_m for Pim-1=160 μM) ^{[43, 44]}

Docking study of hit compounds with Pim-2 crystal structure 4X7Q (which prepared as mentioned previously) showed that compounds Benz53 and Benz58 could be a promise Pim-2 inhibitors where they form important bonds with the active site and have high –CDocker energy values of 58.3202 and 56.6249, respectively (as shown in table 13).

Table (8): The Hits/Pim-2 docking study results.

Pim-2		Compounds
-CDocker Energy	Interactions	Compounds
37.879	-	Benz30
48.2679	Glu167, Arg118	Benz41
25.3206	Arg118, Ala122	Benz43
20.8514	Arg118, Ala122	Benz44
29.7824	Arg118, Glu167	Benz46
25.3735	Arg118, Glu167	Benz47
35.8978	Arg118, Glu117	Benz50
58.3202	Arg118, Glu117, Glu167, Phe43	Benz53
56.6249	Arg118, Glu167, Lys61	Benz58
64.6027	Glu167	Benz62
67.7701	Glu167	Benz64
58.1545	Arg118, Glu167	Benz60

CONCLUSION:

Based upon the docking study and In-silico ADMET prediction results, we recommend the synthesis and In-vivo evaluation of compounds Benz30 and Benz53 which exhibited the highest affinity proved by CDocker and Ligand fit docking methods and characterized with good ADMET values and low toxicity.

CONFLICT OF INTEREST:

The authors declare no conflict of interest.

ABREVIATIONS:

Pim-1=Proviral Insertion site of Molony Murine Leukemia virus

CAMK group= Calcium/calmoduline-dependent protein kinase

CDC25= cell division cycle

BAD= Bcl-2-associated death promoter

P53= Tumor Suppressor Protein

DLBCL= diffuse large B cell lymphoma

CADD= Computer Aided Drug Design

SBDD= Structure-Based drug design

LBDD= Ligand-Based drug design

PDB= Protein Data Bank

ADMET=Absorption, Distribution, Metabolism, Excretion and Toxicity

REFERENCES:

1. Matthews, D.J. and M.E. Gerritsen, Targeting protein kinases for cancer therapy. 2011: John Wiley & Sons.

2. Eichmann, A., et al., Developmental expression of pim kinases suggests functions also outside of the hematopoietic system. Oncogene, 2000. 19(9): p. 1215.

3. Alvarado, Y., F.J. Giles, and R.T. Swords, The PIM kinases in hematological cancers. Expert review of hematology, 2012. 5(1): p. 81-96.

4. Nawijn, M.C., A. Alendar, and A. Berns, For better or for worse: the role of Pim oncogenes in tumorigenesis. Nature reviews Cancer, 2011. 11(1): p. 23.

5. Banerjee, S., et al., EBNA3C augments Pim-1 mediated phosphorylation and degradation of p21 to promote B-cell proliferation. PLoS pathogens, 2014. 10(8): p. e1004304.

6. Qian, K.C., et al., Structural basis of constitutive activity and a unique nucleotide binding mode of human Pim-1 kinase. Journal of Biological Chemistry, 2005. 280(7): p. 6130-6137.

7. Kumar, A., et al., Crystal structures of proto-oncogene kinase Pim1: a target of aberrant somatic hypermutations in diffuse large cell lymphoma. Journal of molecular biology, 2005. 348(1): p. 183-193.

8. Amaravadi, R. and C.B. Thompson, The survival kinases Akt and Pim as potential pharmacological targets. The Journal of clinical investigation, 2005. 115(10): p. 2618-2624.

9. Bachmann, M. and T. Möröy, The serine/threonine kinase Pim-1. The international journal of biochemistry & cell biology, 2005. 37(4): p. 726-730.

10. Kim, K.-T., et al., Pim-1 is up-regulated by constitutively activated FLT3 and plays a role in FLT3-mediated cell survival. Blood, 2005. 105(4): p. 1759-1767.

11. Stout, B.A., et al., IL-5 and granulocyte-macrophage colony-stimulating factor activate STAT3 and STAT5 and promote Pim-1 and cyclin D3 protein expression in human eosinophils. The Journal of Immunology, 2004. 173(10): p. 6409-6417.

12. Shay, K.P., et al., Pim-1 kinase stability is regulated by heat shock proteins and the ubiquitin-proteasome pathway. Molecular Cancer Research, 2005. 3(3): p. 170-181.

13. Mizuno, K., et al., Regulation of pim-1 by hsp90. Biochemical and biophysical research communications, 2001. 281(3): p. 663-669.

14. Tursynbay, Y., et al., Pim-1 kinase as cancer drug target: an update. Biomedical reports, 2016. 4(2): p. 140-146.

15. Magnuson, N.S., et al., Why target PIM1 for cancer diagnosis and treatment? Future oncology, 2010. 6(9): p. 1461-1478.

16. Fang, X., et al., Regulation of BAD phosphorylation at serine 112 by the Ras-mitogen-activated protein kinase pathway. Oncogene, 1999. 18(48): p. 6635.

17. Bachmann, M., et al., The oncogenic serine/threonine kinase Pim-1 directly phosphorylates and activates the G2/M specific phosphatase Cdc25C. The international journal of biochemistry & cell biology, 2006. 38(3): p. 430-443.

18. Warfel, N.A. and A.S. Kraft, PIM kinase (and Akt) biology and signaling in tumors. Pharmacology & therapeutics, 2015. 151: p. 41-49.

19. Gu, J.J., et al., PIM1 phosphorylates and negatively regulates ASK1-mediated apoptosis. Oncogene, 2009. 28(48): p. 4261.

20. Blanco-Aparicio, C. and A. Carnero, Pim kinases in cancer: diagnostic, prognostic and treatment opportunities. Biochemical pharmacology, 2013. 85(5): p. 629-643.

21. Sutrakar, S., et al., Pure Leiomyoma of prostate: A Case Report. Research Journal of Pharmacology and Pharmacodynamics, 2011. 3(6): p. 297-298.

22. Chen, L.S., et al., Pim kinase inhibitor, SGI-1776, induces apoptosis in chronic lymphocytic leukemia cells. Blood, 2009. 114(19): p. 4150-4157.

23. Dakin, L.A., et al., Discovery of novel benzylidene-1, 3-thiazolidine-2, 4-diones as potent and selective inhibitors of the PIM-1, PIM-2, and PIM-3 protein kinases. Bioorganic & medicinal chemistry letters, 2012. 22(14): p. 4599-4604.

24. Kapoor, S., Effect of inhibiting Pim-1 kinase in acute myeloid leukemia with FLT3 internal tandem duplication. 2016.

25. Xiang, Y., et al., The discovery of novel benzofuran-2-carboxylic acids as potent Pim-1 inhibitors. Bioorganic & medicinal chemistry letters, 2011. 21(10): p. 3050-3056.

26. Sliman, F., et al., Identification and structure–activity relationship of 8-hydroxy-quinoline-7-carboxylic acid derivatives as inhibitors of Pim-1 kinase. Bioorganic & medicinal chemistry letters, 2010. 20(9): p. 2801-2805.

27. Nishiguchi, G.A., et al., Discovery of novel 3, 5-disubstituted indole derivatives as potent inhibitors of Pim-1, Pim-2, and Pim-3 protein kinases. Bioorganic & medicinal chemistry letters, 2011. 21(21): p. 6366-6369.

28. Wurz, R.P., et al., Discovery of imidazopyridazines as potent Pim-1/2 kinase inhibitors. Bioorganic & medicinal chemistry letters, 2016. 26(22): p. 5580-5590.

29. Hu, H., et al., Discovery of 3, 5-substituted 6-azaindazoles as potent pan-Pim inhibitors. Bioorganic & medicinal chemistry letters, 2015. 25(22): p. 5258-5264.

30. Nisha, H. and B. Karavadi, Computational analysis to identify the drug targets and their lead molecules in pancreatic cancer. Research Journal of Pharmacy and Technology, 2017. 10(6): p. 1708.

31. Karavadi, B. and S. Shivashankari, Computational study on receptors related to aggressive conduct. Research Journal of Pharmacy and Technology, 2018. 11(5): p. 1729-1733.

32. Sandeep, G., et al., Synthesis and biological screening of some novel coumarin derivatives. Asian Journal of Research in Chemistry, 2009. 2(1): p. 46-48.

33. Hassan Baig, M., et al., Computer aided drug design: success and limitations. Current pharmaceutical design, 2016. 22(5): p. 572-581.

34. Gao, C., Computer-aided drug design approaches in developing anti-cancer inhibitors. 2016.

35. Karavadi, B. and V. Martina, Insilico Analysis of Inhibitors Related to Aggressive Behavior in Human Beings. Research Journal of Pharmacy and Technology, 2018. 11(4): p. 1436-1441.

36. Arunkumar, T., A.F. Ebby, and G. Narendrakumar, Docking studies of benzisoxazole analogues in white spot syndrome virus. Research Journal of Pharmacy and Technology, 2017. 10(8): p. 2497-2500.

37. Karavadi, B. and H. Nisha, Homology Modeling and Docking Studies to Identify the Targets in Pancreatic Cancer. Research Journal of Pharmacy and Technology, 2017. 10(7): p. 2032-2040.

38. Suresh, M.X., J. Mahalakshmi, and G. Vinisha, Computational Modeling of Novel Drug Targets ftsE and mpt83 for MDRTB and Molecular Docking of Selected Compounds from Medicinal Plants. Research Journal of Pharmacy and Technology, 2018. 11(4): p. 1413-1420.

39. Venkatachalam, C.M., et al., LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites. Journal of Molecular Graphics and Modelling, 2003. 21(4): p. 289-307.

40. Kim, J.-H., et al., Ligand supported homology modeling and docking evaluation of CCR2: docked pose selection by consensus scoring. Journal of molecular modeling, 2011. 17(10): p. 2707-2716.

41. Reddy, S.C., et al., Insilico Design and Discovery of Some Novel Ache Inhibitors for Treatment of Alzheimer's Disorder. Research Journal of Pharmacy and Technology, 2012. 5(3): p. 425.

42. Chelamalla, R. and A. Makula, Molecular docking studies and ADMET predictions of pyrimidine coumarin scaffolds as potential IDO inhibitors. Asian Journal of Research in Chemistry, 2017. 10(3): p. 331-340.

43. Nishiguchi, G.A., et al., Design, synthesis and structure activity relationship of potent pan-PIM kinase inhibitors derived from the pyridyl carboxamide scaffold. Bioorganic & medicinal chemistry letters, 2016. 26(9): p. 2328-2332.

44. Deng, G., et al., Pim-2 kinase influences regulatory T cell function and stability by mediating Foxp3 protein N-terminal phosphorylation. Journal of Biological Chemistry, 2015. 290(33): p. 20211-20220.

Received on 28.03.2019 Modified on 30.04.2019

Research J. Pharm. and Tech. 2019; 12(11):5413-5423.

DOI: 10.5958/0974-360X.2019.00939.9