Monoamine Oxidase ( MAO ) is a flavinadenosine dinucleotide incorporating enzyme located at the outer membranes of chondriosome in the encephalon, liver, enteric mucous membrane, and other variety meats. It catalyzes the oxidative deaminization of biogenic aminoalkanes ( neuroamines, vasoactive and exogenic aminoalkanes ) , including Dopastat, 5-hydroxytryptamine, norephinephrine, tyramine, tryptamine, and MPTP neurolysin. The terminal merchandises are aldehydes and H2O2 that are involved in oxidative cellular processes25,69. MAO exists in two isoforms, i.e. , MAO-A and MAO-B in worlds and both are 60 kDa outer-mitochondrial membrane-bound flavoenzymes that portion 70 % sequence identities70,23. Due to distinct and overlapping specificities of MAO-A and MAO-B in the oxidative deaminization of neurotransmitters and dietetic aminoalkanes, the development of specific reversible inhibitors has been a long sought end. Expression degrees of MAO-B in neural tissue addition 4-fold with age,45,71 ensuing in an increased degree of dopamine metamorphosis and the production of higher degrees of H peroxide, which are thought to play a function in the etiology of neurodegenerative diseases such as Parkinson ‘s and Alzheimer ‘s diseases.45,72 MAO inhibitors demonstrated singular antidepressant action but their clinical value was earnestly compromised with side effects like ”cheese reaction ” 18,73. These serious side effects stimulated a hunt for antidepressants that are non MAO inhibitors and to their eventual replacing utilizing the uptake inhibitors, the tricyclic antidepressants and more late the 5-hydroxytryptamine selective re-uptake inhibitors ( Prozac ) . Despite the general deficiency of involvement, Knoll & A ; Magyar persisted in their survey with an irreversible MAO inhibitor, l-Deprenyl, derived from propargylamine37-39,45,74. It is a selective MAO-B inhibitor at low doses and inhibited the oxidative deaminization of Dopastat, phenylethylamine and benzylamine but at higher doses the selectivity of the compound was lost. The compound besides was evaluated as an antidepressant, devoid of the ”cheese reaction ” 18,45. Therefore, the development of specific, reversible MAO-B inhibitors could take to clinically utile neuroprotective agents. Compounds with similar structural motives can take to the same biological consequence. It is besides good accepted that bioactive ligands that bind to a common receptor must carry through certain chemical and geometric standards. For this intent a knowledge-based attack is based on another popular technique applied in the drug find, known as scaffold-hopping75,76 where the end is to ‘jump ‘ in chemical science infinite, i.e. , to detect a new construction get downing from a known active compound via the alteration of the cardinal nucleus of this molecule.77 In the old surveies pharmacophore theoretical account was generated with the consideration of Thiazole derived functions and Thiosemicarbazide derived functions with characteristics like three H bond acceptors, one hydrophobic characteristic and one aromatic ring.78 In the present survey, the ligand and construction based design surveies were done utilizing Catalyst and Glide to plan selective MAO-B inhibitors.79-82 We have considered diverse set of structural motives like Thio- and semicarbazides, beta-Carbolines, cis- and trans-resveratrol derived functions, Eugenol derived functions, Pyrazoles, Oxazolidinones, Phenylcyclopropylamines, and Indan derived functions to depict the knowledge-based design, designation and optimisation of a new lead.83-93 Most of the rationally designed and clinically utile inhibitors ( revesible or irreversible ) are competitory inhibitors. We have included both reversible and irreversible inhibitors in the preparation set to acquire the optimized characteristics necessary for the enzyme suppression.

Plan of work

The work done shows how chemical characteristics for Selective MAO-B inhibitors along with their activities runing over several orders of magnitudes can be used to bring forth pharmacophore hypotheses and can successfully foretell the activity. The validated pharmacophore theoretical account is used to recover molecules from a practical library and the retrieved hits/leads were farther refined utilizing the docking surveies to cut down the figure of false positives and false negatives. This practical showing attack can be used to place and plan inhibitors with greater selectivity.

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3.2 Computational Surveies

Catalyst 4.11 package was used to bring forth pharmacophore theoretical accounts. GLIDE ( Schrodinger, L.L.C. , New York ) docking plans were used for the construction based surveies.

3.2.1 Database Mining and Training Set

The compound choice procedure implemented is shown as a flow chart in Figure 3.1. The pharmacophore theoretical account ( Hypo2 ) was used as a question to test an in house database dwelling of 80,000 compounds which were passed drug like filters. The hunt retrieved 5500 compounds were selected for bunch analysis and a set of 530 bunch representative hits with predicted IC50 value of less than 10 AµM were chosen for docking onto the active site of MAO-B. Highly scored compounds were selected to transport out the docking analysis onto the active site of MAO-A.

Figure 3.1: Conventional representation of in silico testing protocol implemented in the designation of MAO-B inhibitors.

Figure 3.2: Structurally diverse set of compounds retrieved from the database and proposed for synthesis.

3.2.2 Pharmacophore Model Generation and Validation

Pharmacophore patterning correlatives activities with the spacial agreement of assorted chemical characteristics in a set of active parallels. A set of 70 human MAO-B inhibitors83-92 with an activity scope ( IC50 ) crossing over 5 orders of magnitude, i.e. , 0.014-980 AµM were selected. Molecules were chosen based on the MAO-B inhibitory check tested under similar experimental conditions. This initial group was so divided into the preparation and trial sets. The preparation set of 22 molecules was designed to be structurally diverse with a broad activity scope. The preparation set molecules play a critical function in the pharmacophore coevals procedure and the quality of the end point pharmacophore theoretical accounts relies entirely on the preparation set molecules. The trial set of staying 48 molecules is designed to measure prognostic ability of the end point pharmacophore. Highly active ( +++ or & lt ; 20 AµM ) , reasonably active ( ++ or 20-50 AµM ) and inactive ( + or & gt ; 50 AµM ) compounds were added to the preparation set to obtain critical information on pharmacophore demands for MAO-B suppression. The molecules selected as the preparation set are given in Figure 3.3. This preparation set was so used to bring forth quantitative pharmacophore theoretical accounts.

Qualitative pharmacophore theoretical accounts were generated utilizing a set of extremely active molecules. To corroborate indispensable characteristics predominating among the MAO-B inhibitors, 10 common characteristic hypotheses were generated utilizing the most active molecules 1-6 ( Figure 3.3 ) . The common characteristics for all 10 hypotheses are hydrogen bond giver, H bond acceptor and pealing aromatic characteristics. However, these theoretical accounts can non be straight used to foretell biological activity of the compounds retrieved from a database. We have generated quantitative pharmacophore theoretical accounts to foretell the biological activities of fresh compounds. While bring forthing the quantitative theoretical account, a lower limit of 0 to a upper limit of 5 characteristics affecting HBA, HBD, and RA characteristics were selected and used to construct a series of hypotheses utilizing a default uncertainness value of 3. The quality of HypoGen theoretical accounts are best described by Debnath and Vadivelan93-96 in footings of Fixed Cost, Null Cost and entire Cost and other statistical parametric quantities. Harmonizing to which, a big difference between the fixed cost and void cost, and a value of 40-60 spots for the unit of cost would connote 75-90 % chance for experimental and predicted activity correlativity. In general, pharmacophore theoretical accounts should be statistically important, predict the activity of molecules accurately, and recover active compounds from a database. The derived pharmacophore theoretical accounts were validated utilizing a set of parametric quantities including cost analysis, trial set anticipation, enrichment factor, and goodness of hit. HipHop and HypoGen faculties within Catalyst were so used to bring forth qualitative pharmacophore and quantitative pharmacophore theoretical accounts, severally.

Figure 3.3: Training set molecules for MAO-B inhibitors. IC50 values of each molecule are given in parentheses.

3.2.3 Docking Surveies

Crystal construction of MAO-A ( PDB codification: 2BXR ) and MAO-B ( PDB codification: 2V5Z ) 24 were used for the moorage studies97. The protein 3D constructions were downloaded from the protein databank ( PDB ) . The H atoms were added to the proteins and farther minimisation was performed utilizing protein readying ace. A set of 70 human MAO-B inhibitors were docked on to the active site of MAO-A and MAO-B utilizing Glide docking plan. During the moorage procedure, Glide ab initio performs a complete systematic hunt of the conformation, orientation, and place of a compound in the defined binding site and eliminates unwanted airss utilizing marking and energy optimisation. Finally the conformations were farther refined via a Monte Carlo trying. The MAO-A and MAO-B grid boxes were defined by the centre of the edge inhibitors of the MAO-A and MAO-B proteins severally. The enveloping box and binding box dimensions were fixed to 14 and 10 A , severally. The top 20 airss were collected for each compound. Docking airss were energy minimized utilizing the OPLS-2001 force field. The best airs was selected based on Glide mark and the favourable interactions formed between the compound and amino acid residues of the MAO-A and MAO-B active site. The selectivity index of the compoundwas calculated utilizing the Glide score ofMAO-A and MAO-B ( MAO-B Glide score/MAO-A Glide mark & gt ; 1 ) .

3.3 Consequences and Discussion

3.3.1 Pharmacophore Surveies

The best common characteristic pharmacophore model18 indicated the importance of H-bond acceptor ( HBA ) , H-bond giver ( HBD ) and pealing aromatic ( RA ) characteristics, which were further confirmed in the quantitative theoretical accounts. Several quantitative theoretical accounts were generated using the preparation set ( 1-22 ) along with MAO-B inhibitory activities ( Figure 3.3 and Table 3.1 ) . The top 10 hypotheses were composed of HBA, HBD, and RA characteristics. The values of 10 hypotheses such as cost, correlativity ( R ) , and root-mean-square divergences ( rmsd ) are statistically important ( Table 3.2 ) . It is apparent that as mistake, weight and constellation constituents are really low and non deterministic to the theoretical account, the entire pharmacophore cost is besides low and close to the fixed cost. Besides, as entire cost is less than the void cost, this theoretical account accounts for all the pharmacophore characteristics and has good prognostic ability. In add-on to an appraisal of activity of the preparation set molecules, the pharmacophore theoretical account should besides accurately predict the activity of the trial set molecules. Two statistical methods were employed to rank the 10 attendant hypotheses. In the first method, all ten hypotheses were evaluated utilizing a trial set of 48 known MAO-B inhibitors, which are non included in the preparation set. Predicted activities of the trial set were calculated utilizing all 10 hypotheses and correlated with experimental activities. Of the 10 hypotheses, Hypo2 showed a better correlativity coefficient ( 0.945 ) compared to the other nine hypotheses. A 2nd statistical trial includes computation of false positives, false negatives, enrichment, and goodness of hit to find hardiness of hypotheses. Under all proof conditions, Hypo2 performed superior as compared to the other nine hypotheses. Hypo2 demonstrated first-class anticipation of MAO-B repressive activities of the preparation set compounds ( Table 3.1 ) . Analyzing the consequences, it was observed that out of the 9 extremely active molecules, all were predicted right as extremely active. Among the 6 reasonably active molecules, except one, which was predicted as extremely active and the remainder were right predicted. Out of the 6 low active molecules, 3 were predicted as reasonably active and the remainder was predicted as low active. Activities of the compounds were non merely right predicted but besides the tantrum values confer a good step of how good the pharmacophoric characteristics of Hypo2 were mapped onto the chemical characteristics of the compounds. Figure 3.4A shows the HypoGen pharmacophore characteristics with their geometric parametric quantities, all characteristics of Hypo2 ( HBA, HBD and RA ) were mapped onto the extremely active compounds of the preparation set ( 2 ) every bit good as the moderate compound ( 8 ) shown in Figure 3.4B and Figure 3.5C severally. Many of the low active compounds in the preparation set ( 22 ) were mapped partly by the characteristics of Hypo2 ( Figure 3.4D ) .

The correlativity values along with the anticipations above make the pharmacophore suited to foretell molecular belongingss good. The secret plan demoing the correlativity between the existent and predicted activities for the trial set and the preparation set molecules is given in Figure 3.5

The intent of the pharmacophore theoretical account coevals is non merely to foretell the activity of the preparation set compounds accurately but besides to verify whether the pharmacophore theoretical accounts are capable of foretelling the activities of external compounds of the trial set series and sorting them right as active or inactive. The molecules were classified as extremely active ( +++ or & lt ; 20 AµM ) , reasonably active ( ++ or 20-50 AµM ) and inactive ( + or & gt ; 50 AµM ) . Hypo2 was used to seek the trial set of known MAO-B inhibitors. Database excavation was performed utilizing the BEST flexible searching technique. The consequences were analyzed utilizing a set of parametric quantities such as hit list ( Ht ) , figure of active per centum of outputs ( % Y ) , percent ratio of actives in the hit list ( % A ) , enrichment factor ( E ) , false negatives, false positives, and goodness of hit mark ( GH ) ( Table 3.3 ) 98. Hypo2 succeeded in the retrieval of 84 % of the active compounds. In add-on, the pharmacophore besides retrieved 6 inactive compounds ( false positives ) and predicted 2 active compounds as inactive ( false negatives ) . An enrichment factor of 1.76 and a GH mark of 0.73 indicate the quality of the theoretical account. Overall, a strong correlativity was observed between the Hypo2 predicted activity and the experimental MAO-B inhibitory activity ( IC50 ) of the preparation and trial set compounds ( Figure 3.5 ) . However, the Hypo2 theoretical account has a greater inclination to demo false positives. This could be attributed to high structural similarity in active and inactive MAO-B inhibitors, ensuing in an inability to know apart this form by the pharmacophore theoretical account. We farther extended this survey to construction based design and to restrict the figure of false positive and false negative hits and to further understand the binding of inhibitors to the active site of MAO-B composite.

Table 3.1: Experimental and Predicted IC50 informations of 22 preparation set molecules against Hypo2 theoretical account.

Molecule

Exp.

IC50, I?M

Predicted

IC50, I?M

Mistake a

Fit value B

Experimental

graduated table degree Celsius

Predicted

graduated table degree Celsius

1

0.06

0.114

2.4

4.81

+++

+++

2

0.08

0.11

2.6

5.41

+++

+++

3

2.6

7.2

5.9

3.54

+++

+++

4

3

11.2

6.8

3.41

+++

+++

5

6.7

9.8

1.5

3.73

+++

+++

6

8.9

19

2.7

3.34

+++

+++

7

13

14

1.1

3.57

+++

+++

8

17

8.2

-6

4.27

+++

+++

9

19

14

-1.3

3.57

+++

+++

10

20

13

-1.6

3.62

++

+++

11

22

24

1.1

3.35

++

++

12

25

21

-1.2

3.4

++

++

13

30

25

-1.2

3.32

++

++

14

38

21

-1.8

3.41

++

++

15

40

35

-2

3.43

++

++

16

50

21

-2.4

3.41

++

++

17

61

38

-1.6

3.14

+

++

18

65

34

-1.9

3.2

+

++

19

88

190

2.15

2.26

+

+

20

92

39

-2.4

3.14

+

++

21

140

210

1.5

2.24

+

+

22

240

148

-5

3.05

+

+

a + Indicates that the Predicted IC50 is higher than the Experimental IC50 ; – indicates that the Predicted IC50 is lower than the Experimental IC50 ; a value of 1 indicates that the predicted IC50 is equal to the Experimental IC50.

B Fit value indicates how good the characteristics in the Pharmacophore overlap the chemical characteristics in the molecule. Fit = weight* [ soap ( 0,1-SSE ) ] where SSE = ( D/T ) 2, D= supplanting of the characteristic from the centre of the location restraint and T=the radius of the location restraint domain for the characteristic ( tolerance ) .

hundred Activity graduated table – IC50 & lt ; 20 AµM = +++ ( Highly active ) – IC50 20-50 AµM = ++ ( Moderately active ) – IC50 & gt ; 50 AµM = + ( Low active ) .

Table 3.2: 10 Pharmacophore theoretical accounts generated by the HypoGen for MAO-B inhibitors.

Hypo No.

Entire cost

Cost difference $

Mistake cost

RMS divergence

Training set

( R )

Features #

1

100.46

55.42

83.92

0.941

0.772

HBAHBDRA

2

99.04

56.84

82.42

0.875

0.961

HBAHBDRA

3

99.58

56.3

82.8

0.894

0.892

HBAHBDRA

4

99.64

56.24

82.87

0.898

0.851

HBAHBDRA

5

100.06

55.82

83.23

0.916

0.812

HBAHBDRA

6

100.11

55.77

83.54

0.931

0.783

HBAHBDRA

7

100.77

55.11

84.11

0.958

0.769

HBAHBDRA

8

100.99

54.89

83.45

0.927

0.79

HBAHBDRA

9

101.12

54.76

84.36

0.97

0.763

HBAHBDRA

10

101.19

54.69

83.35

0.922

0.793

HBAHBDRA

Hypo 2 showed a better correlativity coefficient ( 0.945 ) compared to the other nine hypotheses.

a ( Null costTotal cost ) , Null cost = 155.88, Fixed cost = 90.53, For the Hypo-2 Weight = 1.28, Configuration = 15.41. All cost units are in spots.

B HBA – Hydrogen Bond Acceptor, HBD – Hydrogen bond giver, RA – Ringing aromatic.

Figure 3.4: Pharmacophore theoretical account for MAO-B inhibitors. ( A ) Three-dimensional agreement of pharmacophore characteristics in the quantitative pharmacophore theoretical account ( Hypo2 ) . Pharmacophore characteristics are: H-bond acceptor ( HBA ) as green, Ring aromatic ( RA1 ) as orange and H-bond giver ( HBD ) as magenta. ( B ) Hypo2 is mapped onto high active compound ( 2 ) . ( C ) Mapping of Hypo2 onto a reasonably active compound 8. ( D ) Mapping of Hypo2 onto an inactive compound 22.

Figure 3.5: Scatter secret plan shows correlativity between experimental and Hypo2 predicted activities of known MAO-B inhibitors.

Table 3.3: Statistical parametric quantities from testing of preparation and trial set molecules.

S. No

Parameter

MAO B

1

Entire molecules in database ( D )

70

2

Entire Number of actives in database ( A )

34

3

Entire Hits ( Ht )

38

4

Active Hits ( Ha )

32

5

% Output of actives [ ( Ha/Ht ) *100 ]

84.21

6

% Ratio of actives [ ( Ha/A ) *100 ]

94.12

7

Enrichment factor ( E ) [ ( Ha*D ) / ( Ht*A ) ]

1.76

8

False Negatives [ A – Ha ]

2

9

False Positives [ Ht – Ha ]

6

10

Good of Hit Score $

0.73

$ [ ( Ha/4HtA ) ( 3A+Ht ) ) * ( 1- ( ( Ht-Ha ) / ( D-A ) ) ] ; GH Score of 0.7 – 0.8 indicates a really good theoretical account

3.3.2 Docking Surveies

A set of 70 MAO-B inhibitors were docked onto MAO-B active site utilizing Glide in order to place their binding sites. A general tendency was observed, in which the more active compound composites scored higher than moderate active and low active compounds. Overall, there was no important correlativity between the fittingness tonss and MAO-B repressive activities of the compounds. Figure 3.6 depicts a comparing between the edge conformation of representative extremely active ( 2 ) , reasonably active ( 8 ) and low active ( 22 ) compounds inside the active site of MAO-B. The predicted binding countries of extremely active compound Figure 3.6B and moderate Figure 3.6C in the MAO-B active site were similar to that of crystal ligand Figure 3.6A. Hydrogen adhering interactions and the interacting amino acid residues at the active site are besides shown. These compounds normally occupy a broad pit surrounded by the undermentioned amino acids: Y60, P102, L171, I198, I199, Q206, I316, Y326, F343, Y398, and Y435. It was observed that the active compound established strong interactions with cardinal amino acid residues and the amide N of extremely active is engaged in two H bonds with Gln206 and an ordered H2O molecule and the amide O is H-bonded to a H2O molecule. In the moderate active compound merely one H bond formation was observed with H2O molecule where in low active compound neither demoing any H adhering nor busying the crystal ligand active site topographic point. This analysis concludes the impartment interaction between the MAO-B protein and ligand and besides correlated these interactions with pharmacophore characteristics.

Figure 3.6: GLIDE docking surveies on MAO-B inhibitors. ( A ) The bound conformation of compounds 2 ( white ) and Crystal ligand ( xanthous ) on the Active Site of MAO-B. ( B ) The bound conformation of compounds 8 ( white ) and Crystal ligand ( xanthous ) on the Active Site of MAO-B. ( C ) The bound conformation of compounds 22 ( white ) and Crystal ligand ( xanthous ) on the Active Site of MAO-B.

3.4 Decision

Several structurally diverse compounds possessing MAO-B selective inhibitory activity were identified utilizing pharmacophore and docking surveies. These compounds bearing conformable chemical and structural characteristics are possible leads for drug design schemes aiming MAO-B. Finally, 15 hits ( Figure 3.2 ) were proposed for synthesis and proving. Based on selectivity index ( MAO-B Glide Score/MAO-A Glide Score & gt ; 1 ) of the compounds, structural freshness and man-made feasibleness and handiness of chemicals, eventually, we synthesized 10 substituted Aryl or Pyridine Pyrazoline derived functions and tested for the pharmacological activity.

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