Computer aided molecular modeling of anti-tuberculosis ...

Ref. code: 25595522300366BZHRef. code: 25595522300366BZH

COMPUTER AIDED MOLECULAR MODELING OF

ANTI-TUBERCULOSIS DRUGS

BY

PIMONLUCK SITTIKORNPAIBOON

A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF

THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF

PHILOSOPHY (ENGINEERING AND TECHNOLOGY)

SIRINDHORN INTERNATIONAL INSTITUTE OF TECHNOLOGY

THAMMASAT UNIVERSITY

ACADEMIC YEAR 2016


ii

Abstract

COMPUTER AIDED MOLECULAR MODELING OF

ANTI-TUBERCULOSIS DRUGS

by

PIMONLUCK SITTIKORNPAIBOON

Bachelor of Engineering (Chemical Engineering), Sirindhorn International Institute of

Technology, Thammasat University, 2009

Master of Engineering (Engineering Technology), Sirindhorn International Institute of

Technology, Thammasat University, 2012

Mycobacterium tuberculosis (mtb) is a human pathogen that causes

Tuberculosis (TB). According to the rapid growth of the new multidrug-resistant TB

and the fatality of the disease, the development of high efficacy drugs for TB is needed.

Dihydrofolate reductase ( DHFR, EC 1 . 5 . 1 . 3 ) is an essential enzyme for the folate

biosynthesis pathway of eukaryotic and prokaryotic cells. An enzyme DHFR was

facilitated in the conversion of substrate dihydrofolate to the product tetrahydrofolate,

which is an important precursor for DNA synthesis. Therefore, the inhibition of

mtbDHFR enzyme can terminate the synthesis of essential proteins and molecules for

the growth of bacteria. In this study, mtbDHFR was selected as a drug target to develop

the effective inhibitor for anti-mtbDHFR.

This work focuses on the use of molecular modeling to investigate the

interactions between the selected ligands on mtbDHFR, which target to identify the

binding affinities and the mode of interaction. Quantum chemistry calculations,

molecular docking and molecular dynamics simulations were used to predict the four

ternary systems of mtbDHFR complex with NADPH and three difference inhibitors,

which are 2,4-diaminopyrimidine derivative compounds (P1, P157, and P169) and its


iii

substrate, dihydrofolate. The results provided the key interactions in the binding site

which are important for the designing of more effective compound against mtbDHFR.

Keywords: Tuberculosis, 2,4-Diaminopyrimidine derivative, Quantum Chemistry,

Molecular Dynamics Simulations, Molecular Docking, Protein-Ligand Interaction,

Dihydrofolate Reductase


iv

Acknowledgements

I would like to thank to Assoc. Prof. Dr. Luckhana Lawtrakul for being my

advisor and gives me a chance to study in this grateful environment. Especially for her

support, patience and offer valuable guidance during preparation of this dissertation.

Deepest gratitude are also due to my committee members: Assoc. Prof. Dr.

Alice Sharp, Dr. Chawanee Thongpanchang, Assoc. Prof. Dr. Pisanu Toochinda, and

Dr. Ubolsree Leartsakulpanich without their expert knowledge and advice the research

would not have been possible.

I would also like to thank Dr.Wichai Pornthanakasem and Ms.Wanwipa

Ittarat for help preparing, purified mtbDHFR and Ki measurement of P1, P157 and P169

that were mentioned in the study.

I would like to thank to all of my colleagues for their help throughout the

research. And I would like to thank to my friends for our friendship along ten years of

my university life at SIIT. Lastly, I would like to thank to my parents who take care and

support me at all times.

This project would have been impossible without the financial support of

SIIT Scholarships for Graduate Students and the Thammasat University Research Fund

under the TU Research Scholar, Contract No.TP 2/21/2559.


v

Table of Contents

Chapter Title Page

Signature Page i

Abstract ii

Acknowledgements iv

Table of Contents v

List of Tables vii

List of Figures viii

1 Introduction 1

1.1 Background 1

1.2 Scope of work 3

2 Literature Review 5

2.1 Tuberculosis 5

2.2 TB Treatment 6

2.3 Mycobacterium tuberculosis 9

2.4 Dihydrofolate reductase 9

2.5 Mycobacterium tuberculosis dihydrofolate reductase 11

3 Methodology 13

3.1 Dataset of compounds 13

3.2 Ligand structure preparation 17

3.3 Protein structure preparation 17

3.4 Molecular docking simulation 17

3.5 Molecular dynamics simulation 18

3.5.1 System preparation 18

3.5.2 MD simulation 19

3.5.3 Analysis of MD trajectories 20


vi

3.5.4 Binding free energies calculated by MM/GBSA 20

4 Result and Discussions 21

4.1 X-ray crystallographic structures of mtbDHFR 21

4.2 Molecular docking simulation 21

4.3 Molecular dynamics (MD) simulation 32

4.3.1 The system stability of MD simulation 32

4.3.2 MM/GBSA Calculations 34

4.3.3 The dynamics of loops and domains of mtbDHFR 36

4.3.4 The binding of cofactor NADPH on mtbDHFR. 41

4.3.5 The binding of substrate and inhibitor on mtbDHFR 42

5 Conclusion 50

References 52

Appendices 56

Appendix A 57


vii

List of Tables

Tables Page

2.1 FDA approved anti TB drugs and their targets. 8

2.2 Deposited mtbDHFR crystal structures with the inhibition

constant (Ki) from Protein databank. Retrieved on April 1,

2015.

12

3.1 Structures of twenty-three compounds in PYR-S1. 14

3.2 Structures of twenty-seven compounds in PYR-S2. 15

3.3 Mass, volume, density, and number of ions and water

molecules of each systems.

19

4.1 Consensus alpha carbon atoms RMSD (Å) of all mtbDHFR

structure.

21

4.2 AutoDock estimated binding free energy (ΔGb) in kcal/mol and

its inhibition constant (Ki) of PYR-S1 compounds to mtbDHFR

at temperature of 298.15 K.

24

4.3 AutoDock estimated binding free energy (ΔGb) in kcal/mol and

its inhibition constant (Ki) of PYR-S2 compounds to mtbDHFR

at temperature of 298.15 K.

27

4.4 Binding free energies (ΔGbind) and their energy components for

each mtbDHFR:NADPH:ligand complex from MM/GBSA

calculation. (Unit: kcal/mol)

36

4.5 The conformation type and the angle of nine crystal

structures of mtbDHFR.

40


viii

List of Figures

Figures Page

1.1 Chemical structures of A) P1 and B) P157. IUPAC name of P1

and P157 are (2,4-diamino-6-ethyl-5-(4-

chlorophenyl)pyrimidine)) and (2,4-diamino-6-ethyl-5-(3-(7-

fluoro-2-methylquinolin-4-yloxy)propoxy)pyrimidine)),

respectively.

2

1.2 Core scaffold of fifty 2,4 diaminopyrimidine compounds: A)

PYR-S1 series with C-5 and C-6 substitute. B) PYR-S2 series

with C-5 substitute.

3

1.3 Work flow diagram of the research. 4

2.1 Globally TB patients reported by WHO (2011). 6

2.2 Dihydrofolate reductase catalyzed reaction. The A) substrate

DHF, B) cofactor NADPH, and C) Catalysis reaction of

DHFR. For the purpose of clarity, only the pterin ring of

substrate or product and the nicotinamide ring of the cofactor

are shown.

10

2.3 Secondary structure of mtbDHFR. The secondary structural

elements assigned by DSSP [22] program.

11

4.1 Alignment of (A) fifty docked conformations and (B) fifteen

effective compounds. The PYR-S1 (blue) and PYR-S2 (pink)

compounds are represent as line. The PYR from an x-ray

structure (PDB code: 4KM0) is shown as stick.

22

4.2 Chemical structures of three compounds, A) P1, B) P157 and

C) P169, substrate D) DHF, and cofactor E) NADPH.

33


ix

4.3 Heavy atoms RMSD of mtbDHFR relative to their initial

minimized complex structures as a function of time for P1,

P157, P169, and DHF.

33

4.4 Total energy (ETOT) of each system for 20 ns of MD

simulation. Moving average of 20 ps represent as a red line.

34

4.5 The schematic structure of mtbDHFR. (A) Structure of

mtbDHFR. Coils in green, -helices in red and -strands in

yellow. (B) Sequence and secondary structure of each MD

simulations at 16 ns. The secondary structural elements

assigned by DSSP [22] program.

37

4.6 Conformations of mtbDHFR in X-ray structures. SASA of

mtbDHFR were represented as gray surface. Amino acid

residues Gly18 on loop L1 and Ser49 on helix αC are

represented as green and red sphere, respectively.

38

4.7 Overall structural comparison of mtbDHFR. (A) Superposition

of the binary mtbDHFR:NADPH crystal structures in closed

and open states. The closed conformations are 4KL9 (red line)

and 1DG8 (orange). The open conformation is 4KLX (green).

The angle θ measured from the angle between three alpha-C

atoms (ball models) of Ser49, Tyr106 and Gly18. (B)

Superposition of the ternary

mtbDHFR:NADPH:2,4diaminopyrimidine complex from MD

simulations at 16 ns: P1 (cyan), P157 (blue), P169 (pink line)

and DHF (gray).

39

4.8 The angle of mtbDHFR conformation at every 1 ns time

interval of each MD simulations systems. P1 (cyan), P157

(blue), P169 (pink), and DHF (gray). The orange shading

41


x

indicates the upper bound and lower bound of closed and open

conformation, respectively.

4.9 The NADPH (cyan) and ligand (magenta) binding sites on

mtbDHFR (gray ribbon) in MD simulations at 16 ns. (A) P1,

(B) P157, (C) P169 and (D) DHF. Two water molecules (red

spheres) are found in the substrate DHF binding site.

42

4.10 The interactions between amino acid residues in the mtbDHFR

binding site with the ligands: (A) P1, (B) P157, (C) P169 and

(D) DHF from the MD simulations. The distances of hydrogen

bond represent by green dash lines (in Å). The aromatic (π-π)

interaction represent in yellow lines and the hydrophobic

interactions are presented in blue lines.

45

4.11 Energy decompositions of each residue towards the ligand in

each of the ternary complex: P1 (cyan bars), P157 (blue bars),

P169 (pink bars), and DHF (gray bars). The total energy that

contribute from the backbone and the sidechain of each protein

residues toward the ligands (A). Energy contribute from the

sidechain (B) and from the carbon backbone (C) toward the

ligands.

49


1

Introduction

1.1 Background

Tuberculosis (TB) is a bacterial infection disease caused by Mycobacterium

tuberculosis (M. tuberculosis or mtb). Medication treatment of TB requires taking a

combination of antibiotics for at least six to nine months. Due to long time of treatment,

improper taking of the drugs can promote the development of drug-resistant mtb strains.

Nowadays, the resistance of mtb strains to isoniazid and rifampicin have been reported.

[1] In addition, the resistance of mtb strains to isoniazid and rifampicin lead to

multidrug-resistant TB (MDR-TB), which is difficult and more expensive to cure. [2]

In 2012, the World Health Organization (WHO) reported 170,000 MDR-TB patients

died and up to 450,000 new cases of MDR-TB globally. [1] MDR-TB became an

important issue worldwide therefore the development of high efficacy drug for TB is

urgently needed.

Dihydrofolate reductase (DHFR, EC 1.5.1.3) is an enzyme responsible for

catalyzing the reduction of an inactive form of 7,8-dihydrofolate (DHF) to an active

form 5,6,7,8-tetrahydrofolate (THF). All living organisms require folate as a precursor

for the synthesis of DNA to promote the cell growth and proliferation. [3] Therefore,

an inhibition of DHFR can inhibit the production of the active form of THF and leads

to the termination of the cell growth of the organisms. Moreover, various antifolates

have been studied against DHFR and DHFR is a notable drug target for the designing

of anti-malarial [4], anti-bacterial [5], and anti-cancer [6] drugs. Therefore,

Mycobacterium tuberculosis DHFR (mtbDHFR) is an attractive drug target for the

development of anti-tuberculosis drugs.

Binding affinity of three antifolates including pyrimethamine, cycloguanil, and

trimethoprim against mtbDHFR were reported by Dias et al. (2014) [7]. Among those

three antifolates, pyrimethamine have showed strongest binding to mtbDHFR. Hence,

the pyrimethamine derivative may have potential to inhibit mtbDHFR.

Pyrimethamine is a 2,4-diaminopyrimidine compound and is used as a drug for

the treatment of malaria. Malaria is a disease caused by the protozoan parasite


2

Plasmodium falciparum. [2] The drug target of pyrimethamine is a bifunctional enzyme

Plasmodium falciparum dihydrofolate reductase thymidylate synthase (pfDHFR-TS).

The derivatives of 2,4-diaminopyrimidine have been designed and synthesized earlier

to test the efficacy against pfDHFR-TS. [8, 9]

Through a personal communication with Dr. Ubolsree Leartsakulpanich at

National Center for Genetic Engineering and Biotechnology, NSTDA, Thailand,

inhibition constant (Ki) of two antifolates, P1 and P157, against mtbDHFR enzyme

were reported to be 6,000 and 22.8 nM respectively. Chemical structures of P1 and

P157 are presented in Figure 1.1. The compound P157 is shown as an effective

compound to inhibit mtbDHFR while P1 is an ineffective compound. To explain why

P157 is more effective to inhibit mtbDHFR than P1, the models of mtbDHFR:NADPH

complexed with each of P1 and P157 are required.

Figure 1.1 Chemical structures of A) P1 and B) P157. IUPAC name of P1 and P157

are (2,4-diamino-6-ethyl-5-(4-chlorophenyl)pyrimidine)) and (2,4-diamino-6-ethyl-5-

(3-(7-fluoro-2-methylquinolin-4-yloxy)propoxy)pyrimidine)), respectively.

In this study, the research focused on an enzyme mtbDHFR as a drug target for

developing anti-mtbDHFR compounds from the database of the anti-malaria

compounds. The research aims to utilize computer aided molecular modeling, including

Molecular docking and Molecular dynamics (MD) simulation, for prediction of the

models of each ternary complex. The ternary complex that predicted were used to study

the dynamics and interactions of protein-ligand upon the binding; and explores the key

characteristics that make the compound P157 effective in the inhibition of mtbDHFR.


3

1.2 Scope of work

Two series of fifty 2,4-diaminopyrimidine compounds are selected to examine the

binding affinity against mtbDHFR by computer aided molecular modeling. The

compounds in PYR-S1 series have a rigid structure, which is similar to P1. The

structures of compounds in PYR-S2 series are similar to P157 that have more structural

flexibility as a result of three-carbon linker chain between C5 of 2,4-diaminopyrimidine

ring and R-substituent. (See Figure 1.2)

Figure 1.2 Core scaffold of fifty 2,4-diaminopyrimidine compounds: A) PYR-S1 series

with rigid C-5 and C-6 substitute. B) PYR-S2 series with flexible C-5 substitute.

The scope of this research is summarized as a work flow diagram as presents in

Figure 1.3. Molecular docking simulation of fifty 2,4-diaminopyrimidine compounds

in the binding pocket of mtbDHFR were performed, based on the predicted Ki values

from AutoDock 4.2 program [10] the compounds were classified into effective and

ineffective compounds to inhibit mtbDHFR. Next, some of the effective compounds

were selected to examine the experimental binding affinity toward mtbDHFR together

with the MD simulation of the system in aqueous solution in order to investigate the

interactions of that effective compound with mtbDHFR.

In MD simulations, all atoms in the system are allowed to move freely unlike the

molecular docking simulation that allowed only the ligand (compound) to move and

rotate randomly inside the defined pocket area of mtbDHFR. The advantages of

molecular docking simulation is fast, which is suitable for primary drug screening from

library of compounds. However, molecular docking simulation ignore the solvent effect

and the protein cannot be moved. MD simulation takes higher computational times and


4

provides a lot of information in order to understand the binding behaviors of protein

and ligand in aqueous.

By utilizing the combination of these two approaches, the finding of anti-

mtbDHFR compound from library of compounds will be fast and can reveal the

important characteristics of effective compounds that required for the inhibition of

mtbDHFR.

Figure 1.3 Work flow diagram of the research.

Molecular docking simulation

of fifty 2,4-diaminopyrimidine compounds

into binding site of mtbDHFR

Obtaine Ki of 50 compounds against mtbDHFR

Two Effective compounds

(P157 and P169)

MD simulation and Experimental testing

Essential charateristics of effective compound for the inhibition of mtbDHFR.

Ineffective compounds


5

Literature Review

This chapter provide a background information of the research, including the

general information of tuberculosis and their treatment, a summary of drug targets of

current approved anti-tuberculosis drugs, and the general information of mtbDHFR,

which is the drug target for developing an anti-mtbDHFR compound in this study.

2.1 Tuberculosis

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis

(M. tuberculosis or mtb). The symptoms of TB include the following: a chronic cough

that last 3 weeks or longer, coughing up blood or mucus, weight loss, fever, night

sweats, and chest pain. [11]

TB is a global health problem. In 2011, World Health Organization (WHO)

estimated 8.7 million incident cases, 12 million prevalent cases, and 1.4 deaths from

TB. The deaths included 990,000 and 430,000 cases of HIV-negative and -positive

people, respectively. TB was the second leading cause of death from an infectious

disease, after the human immunodeficiency virus (HIV). As illustrated in Figure 2.1,

most of the TB patients are Asian (59%) and African (26%) [1].

The estimated new TB cases as incident rates by country in the year 2011 were

reported by WHO. New TB patients are found in all areas over the world. High number

of new TB patients were found in Africa and Asia, especially in South Africa,

Myanmar, and Cambodia.

In addition, the global numbers of Multidrug-resistant TB (MDR-TB) cases in

2011 were 310,000 for almost 60% of these cases were accounted in India, China and

the Russian Federation.


6

Figure 2.1 Globally TB patients reported by WHO (2011).

2.2 TB Treatment

TB is a curable disease that can be treated by taking a combination of drugs for at

least six to nine months. Currently, there are eleven drugs formally approved by the

United States Food and Drug Administration (FDA) for treating TB. The drugs are

classified into first-line and second-line drugs (Table 2.1). The first-line drugs are

Isoniazid (INH), Pyrazinamide (PZA), Ethambutol (EMB), Rifampicin (RIF), and

Rifapentine (RPT). [12] The second-line drugs are Streptomycin (SM), Para

aminosalicylate (PAS), Cycloserine (CS), Ethionamide (ETA), Capreomycin, and

Bedaquiline (TMC207).

The INH, EMB, CS, and ETA drugs are designed to terminate cell wall synthesis.

[12, 13] DNA, RNA, and protein synthesis are inhibited by RIF, RPT, Capreomycin,

SM, and PAS. [12-16] In addition, the ATP synthesis is blocked by Bedaquiline. [17]

The drug target of PZA is unclear, either disruption of plasma membrane functions or

energy metabolism. [12, 13] Bedaquiline is a newly FDA approved drug in the past 40

years, whereas other 10 drugs were approved since 1940s-1960s. The summary of TB

drugs and its drug target are shown in Table 2.1.

59%26%

8%

4%3%

TB patients

Asia

African

Eastern Mediterranean Region

European Region

Region of the Americas


7

Treatment of TB disease usually uses combined drug to reduce the probability of

the emergence of resistant bacteria. Normally, the INH, RIF, PZA and EMB drugs are

prescribed in combination for six months for TB treatment. The patients are treated with

INH, RIF, PZA and EMB for 2 months then continue to take INH and RIF for 4 months.

[12] However, if the patients do not take the drugs exactly as prescribed, this may

promote the emergence of the drug-resistant of mtb strains. MDR-TB is a strain of mtb

that is resistant to at least isoniazid and rifampicin, which are the powerful anti-TB

drugs. Treatment of MDR-TB are more complicated and expensive, its take 20 months

for taking a combination of second-line drugs. In addition, an extensively drug resistant

TB (XDR-TB) is a rare type of MDR-TB that is resistant to isoniazid and rifampicin,

plus any fluoroquinolone and at least one of three injectable second-line drugs. The

treatments for XDR-TB are less effective because the bacteria are resistant to the most

potent drugs. Since, resistance of bacteria to the first-line and second-line drug is still

increasing [18], the finding of new anti-tuberculosis is an important issue.


8

Table 2.1 FDA approved anti TB drugs and their targets. [12, 13]

Drug Discover

Year Mechanism of action Targets

First-line drugs

Isoniazid (INH) 1952 Inhibition of cell wall mycolic acid synthesis. Acyl carrier protein reductase (InhA),

β-ketoacyI synthase (KasA)

Pyrazinamide (PZA) 1954 Disruption of plasma membrane functions and

energy metabolism.

FAS I

Ethambutol (EMB) 1961 Inhibition of cell wall arabinogalactan synthesis. Arabinosyl transferase

Rifampicin (RIF) 1963 Inhibition of RNA synthesis. RNA polymerase β-subunit

Rifapentine (RPT) 1965 Inhibition of RNA synthesis. RNA polymerase [14]

Second-line drugs

Streptomycin (SM) 1943 Inhibition of protein synthesis. 16S rRNA [15]

Para aminosalicylate (PAS) 1948 Inhibition of folic acid synthesis, which are

precursors for DNA synthesis.

Thymidylate synthase (ThyA) [16]

Cycloserine (CS) 1955 Inhibition of cell wall peptidoglycan synthesis. D-alanine racemase/synthase

Ethionamide (ETA) 1960 Inhibition of cell wall mycolic acid synthesis. Acyl carrier protein reductase (InhA)

Capreomycin 1963 Inhibition of protein synthesis. 16S rRNA

Bedaquiline (TMC207) 2004 Inhibition of the proton pumps of mycobacterial

ATP synthase, which leads to inhibition of ATP

synthesis.

ATP synthase [17]


9

2.3 Mycobacterium tuberculosis

M. tuberculosis is the major pathogen that cause TB in human. Infection of the

bacteria mtb are found in one-third of world’s population. TB can be transmitted from

person to person via inhaling aerosol droplets from cough or sneeze of patient infected

with mtb. [2]

Mtb is an acid-fast bacteria, obligate aerobe, and rod shape. The bacteria can cause

disease in highly oxygenated tissues such as the lungs and kidneys. Due to the fact that

the cell wall of mtb contain high complex lipid contents, such as wax D, mycolic acid,

and phosphatides, thus mtb can ticker an immune respond; make mycobacteria to be an

acid-fast; and form a caseation necrosis in tissue. Moreover, the bacteria are tolerant to

dehydration environment therefore it can survive and transmit to human by aerosol.

Nowadays, strains of mtb resistant to isoniazid and rifampicin, which are the most

two potent first-line drugs, and have developed to MDR-TB that cause a worldwide

problem. [2]

2.4 Dihydrofolate reductase

Dihydrofolate reductase (DHFR) is an enzyme necessary for folate biosynthesis

pathway. [19] The enzyme DHFR catalyzes the reduction of an inactive form of 7,8-

dihydrofolate (DHF) to an active form 5,6,7,8-tetrahydrofolate (THF) by hydride

transfer from NADPH cofactor to the C6 atom of pterin ring and subsequently

protonation at N5. (Figure 2.2) The product THF or simple called as “folate” is a

precursor for the synthesis of RNA, DNA, and protein in order to promote the cell

growth and proliferation of living organisms. [3, 19]

Therefore, an inhibition of DHFR can inhibits the production of the active form

of THF and leads to the termination of the cell growth. Previously, various antifolate

compounds were studied against DHFR. This enzyme is a notable drug target for the

designing of anti-malarial [4], anti-bacterial [5], and anti-cancer [6] drugs.


10

Figure 2.2 Dihydrofolate reductase catalyzed reaction. The A) substrate DHF, B)

cofactor NADPH, and C) Catalysis reaction of DHFR. For the purpose of clarity, only

the pterin ring of substrate or product and the nicotinamide ring of the cofactor are

shown.


11

2.5 Mycobacterium tuberculosis dihydrofolate reductase

M. tuberculosis dihydrofolate reductase (mtbDHFR) represents an attractive drug

target for the development of anti-mtbDHFR drug. Moreover, no mutation has been

reported for mtbDHFR. The enzyme mtbDHFR is essential for folate biosynthesis

pathway of mtb. So, the inhibition of the enzyme will affect the synthesis of essential

molecules for the growth of mtb such as purines, pyrimidines and amino acids for RNA,

DNA, and protein synthesis. [19]

The structure of mtbDHFR shows the same general fold as another species that

have a central beta sheet with four alpha helices connected together. [20] The primary

structure of mtbDHFR comprises of 159 amino acids residues. The nomenclatures of

secondary elements are the same as those defined by Li et al., 2000 [21] and were shown

in Figure 2.3. The free forms of mtbDHFR consist of mtbDHFR complexes with its

cofactor NADPH (Reduced nicotinamide-adenine dinucleotide phosphate), which are

important in the DHFR-catalyzed reactions.

Figure 2.3 Secondary structure of mtbDHFR. The secondary structural elements

assigned by DSSP program [22].


12

Since 2000, ten structures of mtbDHFR in binary and ternary complexes have

been solved by x-ray diffraction technique and their coordinates information have been

deposited in the RSCB protein data bank (RSCB PDB; http://www.rcsb.org/pdb) [23].

All available crystal structures of mtbDHFR from RSCB PDB database, three binary

complex structures and seven ternary complex structures, are summarized in Table 2.2.

Three structures of mtbDHFR in binary complexes with the cofactor NADPH are

in PDB codes: 1DG8, 4KL9, and 4KLX. The other seven structures are ternary

complexes of mtbDHFR:NADP:inhibitor, which the inhibitors are methotrexate (MTX;

PDB code 1DF7), trimethoprim (TMP; PDB code: 1DG5 and 4KM2), 4-bromo

WR99210 (WRB; PDB code: 1DG7), pyrimethamine (PYR; PDB code: 4KM0),

cycloguanil (CYC; PDB code: 4KNE), and trimetrexate (TMQ; PDB code: 4M2X).

The structures of mtbDHFR were reported in “open” and “closed” conformations.

Open conformations of mtbDHFR reported by Dias et al., 2014 [7] could not detected

the electron density of nicotinamide ribose moiety of cofactor NADPH. Published

crystallographic structures of mtbDHFR were reported with the experimental inhibition

constant (Ki) values of inhibitors to mtbDHFR. (Table 2.2)

Table 2.2 Deposited mtbDHFR crystal structures with the inhibition constant (Ki)

from Protein databank. Retrieved on April 1, 2015.

PDB code Complex a Conformation Ki (nM) Res. (Å) Ref.

1DG8 NADPH closed - 2.00 [21]

1DF7 NADPH:MTX closed 11 1.70 [21]

1DG5 NADPH:TMP closed 88,000 2.00 [21]

1DG7 NADPH:WRB closed 187 1.80 [21]

4KL9 NADPH closed - 1.39 [7]

4KLX NADPH b open - 1.23 [7]

4KM0 NADPH b :PYR open 910 1.30 [7]

4KM2 NADPH b :TMP open 1,430 1.40 [7]

4KNE NADPH b :CYC open 1,260 2.00 [7]

4M2X NADPH:TMQ - n/a 2.26 - a Abbreviations: NADPH, nicotinamide adenine dinucleotide phosphate (reduced form); MTX,

methotrexate; TMP, trimethoprim; WRB, 4-BROMO WR99210; PYR, pyrimethamine; CYC,

cycloguanil; and TMQ, trimetrexate. b No electron densities of nicotinamide ribose moiety of NADPH in crystals structures.


13

Methodology

Anti-mtbDHFR compounds used in this study are antifolates that developed for

malaria treatment. In this study, fifty 2,4-diaminopyrimidine compounds were selected

to study against mtbDHFR by computer aided molecular modeling, including

Molecular docking and Molecular dynamics (MD) simulation approaches.

In order to utilize computer aided molecular modeling, the starting geometry of

all atoms in the system, including protein, cofactor, and ligands are required. The

starting geometry of mtbDHFR was retrieved from X-ray crystallographic structure that

deposited in RCSB protein databank [23]. While the structures of fifty compounds were

constructed and optimized by GaussView 05 and GAUSSIAN 09 program package

[24]. The compounds were classified into ineffective and effective compounds to

inhibit mtbDHFR based on predicted Ki value from molecular docking simulations.

Then, MD simulation was performed to predict the models of ternary complexes in

order to understand insights into the protein dynamics and its interactions with the

compounds. Details of methodology applied in this study will be described in this

section.

3.1 Dataset of compounds

Fifty 2,4-diaminopyrimidine compounds were selected to examine the binding

affinity against mtbDHFR. The compounds were divided into two series based on the

core scaffolds. The compounds in PYR series 1 (PYR-S1) have a rigid structure while

PYR series 2 (PYR-S2) have more flexibility as a result of three-carbon linker chain

that extent from C5 of pyrimidine ring.

The chemical structures of PYR-S1 were taken from the reference [8], whereas

PYR-S2 were obtained through a personal communication with Dr. Ubolsree

Leartsakulpanich at National Center for Genetic Engineering and Biotechnology,

NSTDA, Thailand. The structure of PYR-S1 and PYR-S2 compounds are shown in

Table 3.1 and Table 3.2, respectively.


14

Table 3.1 Structures of twenty-three compounds in PYR-S1. (Continued)

Compound R1 R2 R3

P1 (PYR) H Cl

P12 H Cl

P13 Cl Cl

P15

P16 H Cl

P17 H

P20 H H

P26 H H

P29 Cl H

P30 Cl H

P31 Cl H

P32 Cl H

P33 H H

P38 Cl H

P39 H H

P40 Cl H

P41 Cl H

P42 Cl H


15

Table 3.1 Structures of twenty-three compounds in PYR-S1. (Continued)

Compound R1 R2 R3

P43 Cl H

P44 Cl H

P45 H H

P46 H H

P47 H H

Table 3.2 Structures of twenty-seven compounds in PYR-S2. (Continued)

Compound R Compound R

P82

P112

P85

P113

P89

P114

P90

P115


16

Table 3.2 Structures of twenty-seven compounds in PYR-S2. (Continued)

Compound R Compound R

P91

P121

P96

P125

P98

P130

P99

P131

P102

P134

P103

P135

P105

P140

P107

P157

P108

P169

P110


17

3.2 Ligand structure preparation

The geometry of compounds were drawn using GaussView 05. The geometry

optimizations were performed using density functional calculations at B3LYP/6-

31G(d,p) level as included in the GAUSSIAN 09 program package [24]. The optimized

structures were saved as .mol2 file.

3.3 Protein structure preparation

The X-ray crystallographic structure of wild-type mtbDHFR was obtained from

the RCSB protein databank [23] (PDB website; http://www.rcsb.org/pdb/). The

mtbDHFR structure was retrieved from the PDB code 4KM0 [7]. The x-ray structures

that was downloaded from the database were edited by Discovery studio visualizer 4.0

program. [25]

Due to the incomplete structure of NADPH, which the electron density of

nicotinamide ribose moiety cannot be detected from X-ray diffraction. The incomplete

structure of NADPH was replaced with NADPH from PDB code 1DG7 by structural

alignment at adenine-ribose of NADPH. Only protein and cofactor structures were

retained. The protein structure was save as .pdb file.

3.4 Molecular docking simulation

Molecular docking simulations of each compound into the active site of

mtbDHFR structure were carried out using the AutoDock 4.2 software package [10].

All torsion angles within the small-molecules were set free to perform flexible docking.

Non-polar hydrogen atoms of the protein and ligands were merged by using the

hydrogen module in AutoDock Tools (ADT). Gasteiger charges were assigned for the

molecules. The Lamarckian Genetic Algorithm was used at 100 dockings for each

compound. The grid sizes were set at specified grid points of 65 points in all three

dimensions with a grid point spacing of 0.375 Å. The grid box center located at the

binding pocket of mtbDHFR, which is 3.576, 23.891, and 9.068 in x, y, z direction,

respectively. All other parameters were ran at the program’s default settings. One


18

hundred orientations and the calculated binding energy for each orientation were

obtained from molecular docking simulation.

The conformation that has the lowest binding energy and the orientation of 2,4-

diaminopyrimidine ring similar to those appear in the x-ray structure of 4KM0 is a best-

fit conformation. The best-fit conformations were selected as a preferred orientation of

the ligand binding to mtbDHFR in order to form a stable complex.

3.5 Molecular dynamics simulation

Molecular dynamics (MD) simulations were performed to the stable complexes

of protein-ligands from molecular docking. MD simulation were achieved using

AMBER12 software package [26], which contains several modules inside the package.

Protein and ligands were parameterized by the ff12SB force fields [27] and general

AMBER force field (GAFF) [28], respectively.

3.5.1 System preparation

All missing hydrogen atoms were added to each complex. Then,

ANTECHAMBER module was utilized to compute partial atomic charges of ligands

and cofactor with AM1-BCC method [29]. Additionally, ligands atom types and

missing force field parameters were assigned based on the GAFF [28].

Then, tLeap module was employed to prepare the systems for MD

simulation. Each ternary complex of protein-ligands was solvated with a periodic

truncated octahedral box of TIP3P water molecules with density around 1 g/cm3. The

closest distance between any atom present in solute and the edge of the periodic box is

10 Å. The dimensions of solvent unit box is 18.774 Å in x,y,z – directions. The solvated

systems randomly added counterions (Na+) to neutralize the system charge. The details

of mass, volume, density, and number of ions and water molecules of each systems are

summarized in Table 3.3.


19

Table 3.3 Mass, volume, density, and number of ions and water molecules of each

systems.

Systema Mass (amu)b Volume (Å3) Density

(g/cm3)

Water

molecules Ions

P1 145,948.378 273,502.494 0.886 7,067 4 Na+

P157 146,017.032 273,466.635 0.887 7,064 4 Na+

P169 145,927.940 273,107.349 0.887 7,056 5 Na+

DHF 145,960.916 272,679.291 0.889 7,057 4 Na+ a The system referred to ternary complexes of mtbDHFR with NADPH and ligand. b 1 amu = 1.66×10-24 g

3.5.2 MD simulation

The MD simulations were achieved by SANDER module of the AMBER12

package. All systems were performed MD simulation and the same procedure were

applied to all systems. The detailed procedures were described below.

First, the initial structure of each system was performed energy

minimization in order to relax the molecular geometry of all atoms in the system.

Energy minimization was performed to correct any atomic clashes or other irregularities

that may exist. The system was minimized with 1,000 cycles of steepest descent follow

by 1,000 cycles of conjugate gradient minimization.

Second, the system was equilibrated by slowly heating to the desired

temperature with constant volume and temperature (Canonical ensemble, NVT) from 0

K to 300 K. The system was heated for 20 ps (1 ps = 10-12 s) with time step of 0.002 ps.

Lastly, the production of MD was performed with constant pressure and

temperature (Isothermal–isobaric ensemble, NPT) at 300 K and 1atm for 20 ns (1 ns =

10-9 s) with time step of 0.002 ps. During the equilibration and production MD phases,

SHAKE algorithm was applied to all bonds involving hydrogen atom. The Langevin

thermostat with collision frequency of 2.0 ps-1 was used to control the temperature of

the systems. Moreover, the random number generator will be initialized with a random

seed. The trajectory and MD output files were written every 0.2 ps. Totally 100,000

conformations of the complexes during 20 ns MD simulation are written in trajectory

file.


20

3.5.3 Analysis of MD trajectories

The MD trajectories from production phase were visualized with Visual

Molecular Dynamics (VMD) [30] to ensure that the protein structures are folded during

the simulation. To monitor the stability of the systems, the PTRAJ module of AMBER

12 was used to calculate heavy atoms RMSD of protein, cofactor, and ligands (inhibitor

or substrate) atoms for each complexes with the minimized structure.

3.5.4 Binding free energies calculated by MM/GBSA

The binding free energy of ligands to mtbDHFR in each complexes were

estimated using Molecular Mechanics/Generalized Born Surface Area (MM/GBSA)

method as included in MMPBSA.py [31] of AmberTool 13.

In MM/GBSA, binding free energy (ΔGbind) between ligand (L) and

enzyme (E) to form a complex E:L can be calculated from the equation (1):

∆𝐺𝑏𝑖𝑛𝑑 = ∆𝐻 − 𝑇∆𝑆 ≈ ∆𝐸𝑀𝑀 + ∆𝐺𝑠𝑜𝑙𝑣 − 𝑇∆𝑆 (1)

∆𝐸𝑀𝑀 = ∆𝐸𝑖𝑛𝑡𝑒𝑟𝑛𝑎𝑙 + ∆𝐸𝑒𝑙𝑒 + ∆𝐸𝑣𝑑𝑊 (2)

∆𝐺𝑠𝑜𝑙𝑣 = ∆𝐺𝐺𝐵 + ∆𝐺𝑆𝐴 (3)

Binding free energies are calculated by subtracting the free energies of unbound E and

L state from the free energy of the bound complex E:L. The binding free energy was

estimated as a sum of ΔEMM, ΔGsolv and –TΔS; which are the changes of the gas phase

MM energy, the solvation free energy, and the conformational entropy upon protein

and ligand binding, respectively. The value of ΔEMM is the sum of ΔEinternal (bond, angle

and dihedral energies), ΔEele (electrostatic energy) and ΔEvdw (van der Waals energy).

However, in each trajectory ΔEinternal is canceled between ligand, enzyme, and complex.

ΔGsolv is the sum of ΔGGB (electrostatic solvation energy or polar contribution) and ΔGSA

(non-electrostatic solvation component or non-polar contribution). The polar

contribution is calculated using either Generalized Born (GB) model, while the non-

polar energy is estimated by solvent accessible surface area (SASA). Conformational

entropy change (−TΔS) is computed by quasi-harmonic entropy approximation on a set

of conformational taken from MD simulations.


21

Result and Discussions

4.1 X-ray crystallographic structures of mtbDHFR

Structural superposition and sequence alignment were performed on ten x-ray

crystallographic structures of mtbDHFR by using Discovery studio visualizer 4.0

program package [25]. The values of 159 α-carbon atoms root-mean-square deviation

(RMSD) of each mtbDHFR structure are shown in Table 4.1. The result indicates that

all ten mtbDHFR structures showed high similarity with an average between 0.61 to

0.82 angstrom (Å). In addition, the sequence alignment reveals that the amino acid

sequence in all mtbDHFR structures are identical.

Table 4.1 Consensus alpha carbon atoms RMSD (Å) of all mtbDHFR structure.

PDB 1DG8 4KLX 4KL9 1DF7 1DG5 1DG7 4KM0 4KM2 4KNE 4M2X

1DG8 0.00 1.14 0.63 0.31 0.27 0.24 1.14 0.98 1.11 0.61

4KLX 1.14 0.00 1.22 1.11 1.04 1.09 0.16 0.53 0.32 1.22

4KL9 0.63 1.22 0.00 0.73 0.62 0.67 1.20 1.07 1.20 0.85

1DF7 0.31 1.11 0.73 0.00 0.35 0.23 1.10 0.96 1.06 0.54

1DG5 0.27 1.04 0.62 0.35 0.00 0.27 1.04 0.92 1.01 0.57

1DG7 0.24 1.09 0.67 0.23 0.27 0.00 1.08 0.95 1.05 0.55

4KM0 1.14 0.16 1.20 1.10 1.04 1.08 0.00 0.52 0.31 1.22

4KM2 0.98 0.53 1.07 0.96 0.92 0.95 0.52 0.00 0.47 1.12

4KNE 1.11 0.32 1.20 1.06 1.01 1.05 0.31 0.47 0.00 1.18

4M2X 0.61 1.22 0.85 0.54 0.57 0.55 1.22 1.12 1.18 0.00

Avg.a 0.64 0.78 0.82 0.64 0.61 0.61 0.78 0.75 0.77 0.79

a Avg. is an average RMSD in each column.

4.2 Molecular docking simulation

Molecular docking simulations were utilized to predict the binding affinities of

fifty 2,4-diaminopyrimidine compounds against mtbDHFR in order to screening the

effective compound out of ineffective compounds. The efficiency of compounds were

classified based on the binding energy and inhibition constant that predicted by


22

AutoDock. Binding energy and inhibition constant (Ki) of PYR-S1 and PYR-S2 to

mtbDHFR from AutoDock calculations are summarized in Table 4.2 and Table 4.3,

respectively.

Based on the predicted Ki values of P1 and P157, the efficiency of these two

compound were correlated with the experimental data (1520 and 458.46 nM vs 6000

and 22.8 nM, respectively). Docked conformations of fifty compounds were aligned by

structural superposition of mtbDHFR. The structural alignment of 50 compounds are

shown in Figure 4.1A.

Figure 4.1 Alignment of (A) fifty docked conformations and (B) fifteen effective

compounds. The PYR-S1 (blue) and PYR-S2 (pink) compounds are represent as line.

The PYR from X-ray structure (PDB code: 4KM0) is shown as stick.

Since P157 was defined as an effective compound to inhibit mtbDHFR by using

an Enzyme binding affinity data, the Ki value of P157 was used as a criteria to judge

the effectiveness of the compounds in this study. Therefore, fifteen compounds

including P32, P43, P31, P44, P12, P40, P33, P47, P42, P16, P29, P169, P140, P98,

and P157 showed predicted Ki values less than or equal to 458.46 nM (predicted Ki of

P157) and are considered as possible compounds to inhibit the activity of mtbDHFR.

Structural alignment of effective compounds are presented in Figure 4.1B.

The PYR-S1 compounds with m-chlorophenyl or p-chlorophenyl, Cl atom was at

R1 or R2 position of PYR-S1, showed stronger binding affinity than those of

unsubstituted compounds. (Table 4.2) The Cl atom in m-chlorophenyl and p-


23

chlorophenyl interacted with nicotinamide moiety of the cofactor NADPH and

exhibited hydrophobic interactions with Ile20 and Ile50, respectively. In addition, the

R3 substituent at C6 of PYR-S1 compounds promoted the stronger binding as compared

to PYR-S2 that has a small ethyl substituent at C6 of 2,4-diaminopyrimidine ring.

(Figure 4.1)

According to the problem statement of the research, which aimed to investigate

the reasons why P157 was inhibited mtbDHFR better than P1. The compound P169,

which is the compound in the same category with P157 and shown stronger binding

affinity to mtbDHFR, will be selected to perform Enzyme binding affinity testing with

mtbDHFR together with MD simulation.


24

Table 4.2 AutoDock estimated binding free energy (ΔGb) in kcal/mol and inhibition constant (Ki) of PYR-S1

compounds to mtbDHFR at temperature of 298.15 K.

(Continued)

Compound R1 R2 R3 Average ΔGb ± SD Lowest ΔGb Ki (nM)

P38 Cl H -7.73 ± 0.06 -7.85 1,770.00

P20 H H -7.49 ± 0.08 -7.64 2,530.00

P30 Cl H -7.95 ± 0.07 -8.09 1,180.00

P1 H Cl -7.88 ± 0.05 -7.94 1,520.00

P13 Cl Cl -8.36 ± 0.06 -8.43 661.83

P17 H -7.81 ± 0.06 -7.94 1,520.00

P15 -8.03 ± 0.08 -8.19 991.35

P39 H H -7.99 ± 0.30 -8.46 632.90

P41 Cl H -7.67 ± 0.13 -8.19 999.69

P45 H H -7.20 ± 0.18 -7.73 2,150.00

P26 H H

-7.98 ± 0.25 -8.39 712.50

P29 Cl H

-8.38 ± 0.27 -8.74 389.49


25



(Continued)


P16 H Cl

-8.41 ± 0.27 -8.77 375.78

P46 H H

-8.03 ± 0.26 -8.49 602.50

P42 Cl H

-8.42 ± 0.29 -8.86 320.29

P47 H H

-9.02 ± 0.48 -9.79 66.48

P43 Cl H

-9.62 ± 0.36 -10.45 21.81

P44 Cl H

-9.25 ± 0.52 -10.14 36.89

P40 Cl H

-9.17 ± 0.46 -9.91 54.62

P33 H H

-9.02 ± 0.45 -9.80 65.38

P31 Cl H

-9.24 ± 0.56 -10.15 36.38


26



(Continued)


P12 H Cl

-9.19 ± 0.59 -10.11 39.10

P32 Cl H

-9.99 ± 0.33 -10.55 18.36


27



(Continued)

Compound R Average ΔGb ± SD Lowest ΔGb Ki (nM)

P131

-6.67 ± 0.28 -7.14 5,800.00

P102

-6.84 ± 0.30 -7.37 3,960.00

P110

-6.95 ± 0.31 -7.43 3,580.00

P103

-6.98 ± 0.26 -7.59 2,740.00

P115

-7.49 ± 0.24 -7.89 1,650.00

P82

-7.18 ± 0.29 -7.8 1,920.00


28



(Continued)


P85

-7.53 ± 0.36 -8.18 1,010.00

P91

-7.80 ± 0.40 -8.46 626.30

P135

-7.56 ± 0.55 -8.44 655.87

P96

-7.62 ± 0.33 -8.13 1,100.00

P125

-7.32 ± 0.28 -7.78 2,000.00

P90

-7.61 ± 0.35 -8.18 1,010.00


29



(Continued)


P89

-7.58 ± 0.35 -8.01 1,350.00

P108

-7.45 ± 0.35 -7.88 1,680.00

P105

-7.48 ± 0.46 -8.52 565.06

P121

-7.89 ± 0.37 -8.40 701.92

P98

-8.08 ± 0.52 -8.81 347.87

P130

-7.88 ± 0.36 -8.50 584.30

P99

-7.68 ± 0.33 -8.18 1,010.00


30



(Continued)


P107

-7.68 ± 0.33 -8.36 740.36

P114

-7.58 ± 0.78 -8.16 1,050.00

P112

-7.68 ± 0.27 -8.16 1,040.00

P113

-7.68 ± 0.34 -8.25 902.60

P134

-7.89 ± 0.39 -8.41 685.71

P140

-8.43 ± 0.23 -8.84 331.03


31



(Continued)


P157

-8.21 ± 0.25 -8.65 458.46

P169

-7.81 ± 0.60 -9.07 226.01


32

4.3 Molecular dynamics (MD) simulation

Molecular dynamics simulations of mtbDHFR in ternary complexes with

NADPH and ligand in aqueous solution were performed in order to predict the mode of

protein-ligand binding. The predicted models can be utilized to investigate deeply into

the interactions and effect of ligand binding to the enzyme mtbDHFR.

In this study, MD simulation was used as a tool to construct four systems of P1,

P157, P169, or DHF in ternary complexes with mtbDHFR and cofactor NADPH. The

chemical structures of ligand and cofactor in each complex are shown in Figure 4.2.

IUPAC name of the compound P169 is 2,4-diamino-6-ethyl-5-(3-(6-

(carboxylatemethoxy)-2-methylquinolin-4-yloxy)propoxy) pyrimidine.

4.3.1 The system stability of MD simulation

The stability of each systems were monitored from the heavy atoms RMSD

of mtbDHFR along 20 ns MD simulations. Heavy atoms RMSD of mtbDHFR in all

systems were plotted against the minimized structure along 20 ns as shown in Figure

4.3. The RMSD of protein heavy atoms of P1, P157, P169, and DHF systems remained

stable after 3 ns, 12 ns, 3 ns, and 10 ns, respectively. The RMSD values of mtbDHFR

in all complexes showed no significant fluctuation after 12 ns MD simulations and

seemed to be stable around 1 Å. In addition, the stability of the systems can be

monitored from the total energy (kcal/mol) of each system. The total energy of all

systems during 20 ns MD simulation are shown in Figure 4.4 with the moving average

of 20 ns. The total energy of all systems were stable throughout the simulations.

Therefore, the trajectory after 12 ns will be used to calculate the binding free energy of

each ligand to mtbDHFR.


33

Figure 4.2 Chemical structures of three compounds, A) P1, B) P157 and C) P169,

substrate D) DHF, and cofactor E) NADPH.

Figure 4.3 Heavy atoms RMSD of mtbDHFR relative to their initial minimized

complex structures as a function of time for P1, P157, P169, and DHF.


34

Figure 4.4 Total energy (ETOT) of each system for 20 ns of MD simulation. Moving

average of 20 ps represent as a red line.

4.3.2 MM/GBSA Calculations

In this section, the binding free energies of ligands to mtbDHFR in four

complexes were calculated using Molecular Mechanics/Generalized Born Surface Area

(MM/GBSA) method as included in MMPBSA.py [31] of AmberTool 13. Five

thousand snapshots with 1.6 ps interval from 12 to 20 ns of MD simulation were

collected.

An average binding free energies of ligands to mtbDHFR and their energy

components in four complexes are listed in Table 4.4. More negative values of binding

free energy (ΔGbind) implied the tighter binding of ligands to the enzyme. According to

the ΔGbind values, the binding affinity of ligands to mtbDHFR were ranking in the

following order: P169 > DHF > P157 > P1. The compound P169 showed a stronger

binding to mtbDHFR than the substrate DHF. Therefore, P169 should be the potent


35

inhibitor that is more competitively binding to mtbDHFR compared to P1 and P157.

The compound P169 showed the strongest binding affinity to mtbDHFR.

From the experimental data, the Ki values of P1, P157, and P169 are 6000,

22.80, and 15.40 nM, respectively. Therefore, the results from our simulation were

correlated with the experimental data, which indicated that P169 and P157 have higher

binding affinity to mtbDHFR than P1.

As shown in Table 4.4, favorable binding energy of P1 and P157 were

mainly contributed from the van der Waals energy changes (ΔEvdw). However, majority

of favorable binding of the substrate DHF and compound P169 were largely contributed

from electrostatic energy changes ( ΔEele) due to their carboxylate anions ( R-COO-) .

The van der Waals energy changes (ΔEvdw) was revealed to be a significant contribution

upon the binding affinity of P169 to mtbDHFR as well as the non-electrostatic solvation

component or non- polar contribution ( ΔGSA) , which was estimated by the solvent

accessible surface area.

The entropy term (TΔS) indicated the positional change of the system. The

more negative value of TΔS demonstrated the decrease in the disorder of the system.

The data indicated that the less disorder of the systems resulted from the strong binding

with P169 or DHF molecules.

MD simulations directed that the binding of all ternary mtbDHFR

complexes in this study were energetically favorable and spontaneously occurring

based on the negative sign of their ΔGbind. Moreover, the results from MM/ GBSA

calculation suggest P169 was a promising anti-mtbDHFR inhibitor, which was

consistent with the experimental data.


36

Table 4.4 Binding free energies (ΔGbind) and their energy components for each

mtbDHFR:NADPH:ligand complex from MM/GBSA calculation. (Unit: kcal/mol)

Energy Component P1 P157 P169 DHF

ΔEvdw -31.93 -46.23 -52.60 -46.65

ΔEele -6.77 -14.98 -85.70 -127.65

ΔGGB 19.83 32.78 86.52 128.08

ΔGSA -3.96 -5.51 -7.09 -6.44 aΔGgas -38.71 -61.21 -138.31 -174.30 bΔGsolv 15.87 27.27 79.44 121.63

ΔGgas + ΔGsolv -22.84 -33.94 -58.87 -52.67

TΔS -21.48 -26.04 -30.27 -30.17 cΔGbind -1.36 -7.90 -28.60 -22.50

aΔGgas (gas-phase interaction energy) = ΔEMM = ΔEvdw + ΔEele bΔGsolv (solvation free energy) = ΔGGB + ΔGSA cΔGbind = ΔGgas + ΔGsolv – TΔS

4.3.3 The dynamics of loops and domains of mtbDHFR

The secondary structures of mtbDHFR from MD simulations were

exhibited the same general fold as appeared in X-ray structures. (Figure 4.5) X-ray

crystal structures of mtbDHFR were reported in two conformations, corresponding to

“open” and “closed” forms as presented in Figure 4.6. The surface area of mtbDHFR

(gray surface) in Figure 4.6 was determined by Solvent Accessible Surface Area

(SASA) method with a probing solvent ball radius of 1.4 Å.

Loop L1 of mtbDHFR was corresponding to loop Met20 of E. coli and the

fluctuation of this loop caused the different conformations in DHFR. Molecular

investigation was performed on X-ray structures of closed and open conformations of

mtbDHFR. The largest difference between open and closed conformations of

mtbDHFR was observed at the position of loop L1 which comprises of amino acid

residues Arg16 to Leu24. Loop L1 of closed conformations was closed into the binding

pocket and closer to helix αC whereas the L1 of open conformations shown wider

distance to the helix αC. In closed conformation, the closest points between loop L1

and helix αC were located at residues Gly18 (green sphere) and Ser49 (red sphere),

respectively. (Figure 4.6)


37

Figure 4.5 The schematic structure of mtbDHFR. (A) Structure of mtbDHFR. Coils in

green, -helices in red and -strands in yellow. (B) Sequence and secondary structure

of each MD simulations at 16 ns. The secondary structural elements assigned by DSSP

[22] program.


38

Figure 4.6 Conformations of mtbDHFR in X-ray structures. SASA of mtbDHFR were represented as gray surface. Amino acid residues

Gly18 on loop L1 and Ser49 on helix αC are represented as green and red sphere, respectively.


39

Figure 4.7 Overall structural comparison of mtbDHFR. (A) Superposition of the binary mtbDHFR: NADPH crystal structures in closed

and open states. The closed conformations are 4KL9 (red line) and 1DG8 (orange). The open conformation is 4KLX (green). The angle θ

measured from the angle between three alpha-C atoms (ball models) of Ser49, Tyr106 and Gly18. (B) Superposition of the ternary

mtbDHFR: NADPH:2,4-diaminopyrimidine complex from MD simulations at 16 ns: P1 (cyan), P157 (blue), P169 (pink line) and DHF

(gray).


40

Therefore, the angle was defined in order to compare the open and closed

conformations of mtbDHFR. The angle measured from three alpha-C atoms of three

amino acid residues Ser49, Tyr106, and Gly18 on helix C, turn T7, and loop L1,

respectively. The superposition of the open and closed forms of the binary

mtbDHFR:NADPH complexes is presented in Figure 4.7A.

Table 4.5 The conformation type and the angle of nine crystal structures of mtbDHFR.

Complex PDB code Conformation (degrees)

mtbDHFR:NADPH 4KLX open 18.34

4KL9 closed 13.57

1DG8 closed 15.07

mtbDHFR:NADPH:Methotrexate 1DF7 closed 15.81 mtbDHFR:NADPH:Br-WR99210 1DG7 closed 14.72

mtbDHFR:NADPH:Trimethoprim 1DG5 closed 14.54

4KM2 open 18.79

mtbDHFR:NADPH:Cycloguanil 4KNE open 17.88

mtbDHFR:NADPH:Pyrimethamine 4KM0 open 18.64

From the value of angle of nine crystal structures of mtbDHFR

complexes, the 99% confidential interval of the average values of for the closed

conformation is 14.74 ± 1.68 degrees and the open conformation is 18.41 ± 1.17

degrees.

The dynamics motions of loop L1 of mtbDHFR for each MD system were

monitored by θ angle during 20 ns of MD simulation and values of θ angle were plotted

in Figure 4.8. The previous simulations of the catalysis pathway of E.coli DHFR

demonstrated that the ternary complex comprised of NADPH cofactor and substrate

DHF underwent transitions between a closed state and an occluded state via an

intermediate open conformation. [32] The motion of loop L1 of

mtbDHFR:NADPH:DHF in our MD system as indicated by angle (Figure 5, gray

line) also supported this catalysis pathway for mtbDHFR. The graph demonstrated that

at the last 8 ns of MD simulations, the loop L1 of mtbDHFR:NADPH complexed with

either P1 (cyan) or P157 (blue) were mostly opened whereas in the complexed with

P169 (pink) and DHF (gray) were frequently closed. This may explained why P1 and

P157 had lower mtbDHFR affinities than P169. Moreover, from our MM/GBSA

calculations (Table 4.4) showed more negative values of ΔGbind when


41

mtbDHFR:NADPH binding with either P169 or DHF. The results were in agreement

with the previous report that the closed conformation was thermodynamically most

favored. [32]

Figure 4.8 The angle of mtbDHFR conformation at every 1 ns time interval of each

MD simulations systems. P1 (cyan), P157 (blue), P169 (pink), and DHF (gray). The

orange shading indicates the upper bound and lower bound of closed and open

conformation, respectively.

4.3.4 The binding of cofactor NADPH on mtbDHFR.

The mode of binding of NADPH on mtbDHFR in MD systems selected at

16 ns MD simulation time (the median of the last 8 ns of simulation period) are

illustrated in Figure 4.9. The alignment of NADPH molecules in each ternary complex

were almost identical. The adenine ribose-5-phosphate and diphosphate moiety of

NADPH in all systems were stayed in the same region and reveled similar

configuration. The adenine ribose-5-phosphate of NADPH bound to the C-terminus of

βC, N-terminus of αC and L2 of mtbDHFR. The adenine moiety was shown

hydrophobic interactions with Leu65 (βC), Arg67 (L2), and Val99 (αF). The ribose-5-

phosphate of NADPH was formed hydrogen bonds to Arg44, Ser66 and Arg67. The


42

diphosphate group in the middle part of NADPH bound near helices αC and αF and

formed many hydrogen bonds to mtbDHFR. One significant difference observed

between the structure of NADPH in complex with inhibitors and substrate was its

nicotinamide ribose moiety. In a nonreactive ternary complexes (P1, P157, and P169),

the nicotinamide ribose of NADPH formed H-bonds with Ala7 and Ile14 on βA and

βP, respectively. Due to the occurrence of the hydrogen bond with Ser49 on αC, the

nicotinamide ribose moiety of reactive ternary complex with DHF bended outward

from the binding site and moved closer to αC helix. (Figure 4.9D).

Figure 4.9 The NADPH (cyan) and ligand (magenta) binding sites on mtbDHFR (gray

ribbon) in MD simulations at 16 ns. (A) P1, (B) P157, (C) P169 and (D) DHF. Two

water molecules (red spheres) are found in the substrate DHF binding site.

4.3.5 The binding of substrate and inhibitor on mtbDHFR

The conformation at 16 ns of MD simulation was taken in order to

investigate the interactions of each Protein-ligand in each complex. The interactions of


43

inhibitors or substrate with the surrounding amino acid residues are depicted in 2D-

interaction as shown in Figure 4.10. The substrate DHF which located at the active site

on mtbDHFR showed the strong hydrogen bonds between hydrogen atoms from the

amino groups of substrate’s pterin ring with the carboxylic groups of Ile5 and Asp27

residues. In addition, pairwise energy decomposition of the same selected interval used

in free binding energy calculation was used to investigate the significance between the

interaction of amino acid residues and the compounds or the substrate in each system

as depicted in Figure 4.11. Two hydrogen bonds between the amino and the carbonyl

groups of DHF and Gln28 residue on B (Figure 4.10D, green lines) made the DHF

molecule staying in the pucker V shape, as seen in Figure 4.9D. Two water molecules

found in the active site formed hydrogen bonds with the carbonyl groups of DHF

molecule. The pucker V shape of DHF molecule was also stabilized by the π-π

interactions of its pterin ring and its benzyl ring with the phenyl ring of Phe31 residue

Figure 4.10D, yellow lines). The strong hydrogen bonds between the O-carboxylate of

DHF with the H-amine of Arg60 residues (Figure 4.10 and Figure 4.11, gray bars)

enhanced the binding affinity between them.

Three inhibitors (P1, P157 and P169) were located at the same binding site

of DHF on mtbDHFR (Figure6). The pyrimidine ring of inhibitors were held in the

interior of a deep cleft through hydrogen bonds and van der Waals interactions as

shown in Figure 4.10 (A-C). 2,4-diamino groups interacted with the carbonyl group of

three amino acid residues; Ile5, Ile94, and Asp27 via hydrogen bonding. The π- π

interactions between the pyrimidine ring of inhibitors and the phenyl ring of Phe31

contributed to stabilize the complex conformation (Figure 4.11). Many van der Waals

interactions between substituent at C5 on the pyrimidine ring of inhibitors with amino

acid residues 50-54 on mtbDHFR were presented (Figure 4.10, blue lines and Figure

4.11). These interactions resulted in the loss of the spiral conformation (C) of the

enzyme, which was observed in mtbDHFR:NADPH:DHF’s configuration (as

represented in Figure 4.5B), and caused the P157 and P169 molecules possessing the

pucker V shape (Figure 4.9B-C). The substitution at C5 on pyrimidine ring of inhibitor

molecules with the propoxy-(fluoro-methylquinolin) moiety in P157 and with the

propoxy-(carboxylatemethoxy-methylquinolin) moiety in P169 increased the stability

of ternary complex systems and significantly improved their anti-mtbDHFR efficiency


44

compared to P1, the parent molecule that has a rigid chlorophenyl substituent at C5.

Moreover, the hydrogen bonds between the O-carboxylate of P169 and the amine group

of Arg32 and Arg60 residues (Figure 4.10C and Figure 4.11, pink bars) enhanced the

binding between them which explained the lowest value of Gbind for this system and

the highest anti-mtbDHFR efficiency of this compound.

The simulations suggest that P1, P157, and P169 were competitively

binding to the same binding site of substrate DHF in mtbDHFR. The substitution at C5

on pyrimidine ring of the molecule with different functional group yielded the

significant changes within the anti-mtbDHFR affinity of compounds.


45

Figure 4.10 The interactions between amino acid residues in the mtbDHFR binding site with the ligands: (A) P1, (B) P157, (C) P169 and

(D) DHF from the MD simulations. The distances of hydrogen bond represent by green dash lines (in Å). The aromatic (π-π) interaction

represent in yellow lines and the hydrophobic interactions are presented in blue.


46



represent in yellow lines and the hydrophobic interactions are presented in blue. (Continued)


47





48





49

Figure 4.11 Energy decompositions of each residue towards the ligand in each of the

ternary complex: P1 (cyan bars), P157 (blue bars), P169 (pink bars), and DHF (gray

bars). The total energy that contributes from the backbone and the sidechain of each

protein residues toward the ligands (A). Energy contributes from the sidechain (B) and

from the carbon backbone (C) toward the ligands.


50

Conclusion

The models of mtbDHFR in ternary complexes with NADPH and P1, P157, and

P169 compounds (as inhibitors) or the substrate DHF have been predicted by twenty

nanoseconds MD simulations. The results were demonstrated the prediction of binding

affinity of three compounds to mtbDHFR from MM/GBSA method were correlated

with the experimental data. The compounds P157 and P169 were shown to be potent

inhibitors of mtbDHFR, indicate by a strong binding affinity toward mtbDHFR than

that of P1. Therefore, the MD simulation was a reliable method to predict the binding

mode and affinity between compounds and the enzyme. From MM/GBSA calculation,

the electrostatic and van der Waals energy changed (Table 4.4) played major role in the

binding of effective compound P169 and the substrate DHF. In addition, the binding of

the compound P169 allowed the enzyme to adopting in the more order conformation

and had strong binding affinity with the enzyme which was similar to the natural

substrate DHF. In addition, the enzyme mtbDHFR preferred to adopt the closed

conformation of loop L1 when binding to the effective compound P169 or the substrate

DHF. However, the loop L1 of mtbDHFR in ineffective compound P1 tended to open

along the simulation, resulting from the less binding affinity between the P1 and

mtbDHFR.

The pairwise energy decomposition together with the interactions analysis were

performed to investigate deep insights into the interactions of the protein-cofactor-

ligand in reactive and nonreactive complexes. For the reactive complex of

mtbDHFR:NADPH:DHF, the substrate DHF formed a strong binding to the enzyme

via numerous H-bonds and hydrophobic interactions. Because DHF was a natural

substrate of DHFR, therefore, these molecule had a highly precise binding into the

binding pocket of the enzyme via the hydrogen bonding to Asp72, Gln28, Arg32, and

Arg60 of mtbDHFR. In nonreactive complexes of enzyme and inhibitors, the amino

groups of all 2,4-diaminopyrimidine compounds were highly specific hydrogen

bonding to the carbonyl group of Ile5 and Ile94 amino acid residues. The compound

P169 mimicked the ability of the binding of DHF through the carboxylate group and


51

the amino groups from 2,4-diaminopyrimidine. Therefore, the compound P169 was a

potent compound that can be developed as an inhibitor of mtbDHFR. Moreover,

molecular docking simulation also suggest fifteen compound that have strong binding

affinity to mtbDHFR.

In addition, anti-Mycobacterium tuberculosis (anti-TB) activity of the compounds

P1, P157, and P169 were tested against the cell culture of M. tuberculosis H37Ra strain

(see Appendix A). The compound P1 cannot inhibited the cell growth of M.

tuberculosis. However, two potent compounds P157 and P169 can be inhibited the cell

growth of M. tuberculosis with minimum inhibitory concentration (MIC) of 1 μM.

These compounds shown strong bound affinity with the enzyme DHFR of M.

tuberculosis and it can passed through the cell membrane in order to inhibit the cell

growth of bacteria. Therefore, the compounds P157 and P169 shown high possibility

to develop as anti-TB drugs in the future.


52

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Appendices


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Appendix A

Experimental inhibition constant (Ki)

Binding affinity of P1, P157, and P169 testing on an enzyme mtbDHFR reported

by Protein-Ligand Engineering and Molecular Biology Laboratory (Medical Molecular

Biology Research Unit, NASTDA, Thailand) is shown in Figure A1. The inhibition

constant (Ki) of P1, P157, and P169 against mtbDHFR are 6000 nM, 22.8 nM, and 15.4

nM, respectively.

In vitro studies, an anti-Mycobacterium tuberculosis (Anti-TB) activity of P1,

P157, and P169 were tested against Mycobacterium tuberculosis H37Ra strain by Green

fluorescent protein microplate assay (GFPMA) and the results are present in Figure A2

and Figure A3. A negative control in the testing is 0.5% DMSO as well as positive

controls are Rifampicin, Ofloxacin, Streptomycin, Isoniazid, and Ethambutol.

Anti-TB activity of P1 and P157 against H37Ra strain is present in Figure A2, the

concentration of compounds varied as 0.1, 1, 10, and 100 μM. From Figure A2, the

compound P1 at concentration rang of 0.1 to 100 μM cannot inhibits the activity of M.

tuberculosis while P157 shown a minimum inhibitory concentration (MIC) at 1 μM and

this MIC value of P157 is correlated with the second test (Figure A3) that varied the

concentrations of P157 from 0.1 to 1 μM, the result still be the same. The Anti-TB

activity of P169 is shown in Figure A3, the MIC of P169 is 1 μM.


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Figure A1 Binding affinity of P1, P157, and P169 to mtbDHFR from experimental

testing. Please note that the notation P168 in the figure is the compound P169 in this

study.


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Figure A2 Anti-Mycobacterium tuberculosis activity of PYR (P1) and P157 against

H37Ra strain. Positive control samples are Rifampicin, Ofloxacin, Streptomycin,

Isoniazid, and Ethambutol. The concentrations of P1 and P157 are varies as 0.1, 1, 10,

and 100 μM.


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Figure A2 Anti-Mycobacterium tuberculosis activity of PYR (P1) and P157 against

H37Ra strain. Positive control samples are Rifampicin, Ofloxacin, Streptomycin,

Isoniazid, and Ethambutol. The concentrations of P1 and P157 are varies as 0.1, 1, 10,

and 100 μM. (Continued)


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Figure A3 Anti-Mycobacterium tuberculosis activity of P157 and P169 against H37Ra

strain. Positive control samples are Rifampicin, Ofloxacin, Streptomycin, Isoniazid,

and Ethambutol. Please note that the notation P168 in the figure is the compound

P169 in this study.


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Figure A3 Anti-Mycobacterium tuberculosis activity of P157 and P169 against H37Ra

strain. Positive control samples are Rifampicin, Ofloxacin, Streptomycin, Isoniazid,

and Ethambutol. Please note that the notation P168 in the figure is the compound

P169 in this study. (Continued)

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