THEORETICAL INVESTIGATION OF
ENANTIOSELECTIVE LIGAND-HOST BINDING
INTERACTIONS
BY
SURIYAWUT KULATEE
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE
(ENGINEERING AND TECHNOLOGY)
SIRINDHORN INTERNATIONAL INSTITUTE OF TECHNOLOGY
THAMMASAT UNIVERSITY
ACADEMIC YEAR 2017
Ref. code: 25605922040059HVU
THEORETICAL INVESTIGATION OF
ENANTIOSELECTIVE LIGAND-HOST BINDING
INTERACTIONS
BY
SURIYAWUT KULATEE
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE
(ENGINEERING AND TECHNOLOGY)
SIRINDHORN INTERNATIONAL INSTITUTE OF TECHNOLOGY
THAMMASAT UNIVERSITY
ACADEMIC YEAR 2017
Ref. code: 25605922040059HVU
ii
Acknowledgements
I would like to thank Assoc. Prof. Dr. Luckhana Lawtrakul for designing,
conceiving, and analyzing the experiments. Special thanks to Assoc. Prof. Dr. Pisanu
Toochinda and Col. Asst. Prof. Dr. Anotai Suksangpanomrung for analyzing and co-
writing the publication.
Special acknowledgements to my beloved advisor, Assoc. Prof. Dr. Luckhana
Lawtrakul for her invaluable encouragement and guidance throughout the study. I
would like to convey my utmost gratitude to her understandings in both the academic
and personal activities of mine. Without her special care and support, this study would
not be a success.
I would love to dedicate my integrity towards my parents, Mr. Yuwachart
Kulatee and Mrs. Pornthip Sukchuen, for their endless encouragements and supports
throughout the study.
Suriyawut Kulatee was financially supported by the Excellent Thai Student
(ETS) scholarship program of Sirindhorn International Institute of Technology (SIIT).
The author gratefully acknowledges the Center of Nanotechnology, Kasetsart
University for the Gaussian 09 program package.
Mr. Suriyawut Kulatee
Ref. code: 25605922040059HVU
iii
Abstract
THEORETICAL INVESTIGATION OF ENANTIOSELECTIVE
LIGAND-HOST BINDING INTERACTIONS
by
SURIYAWUT KULATEE
Bachelor of Engineering (Chemical Engineering), Sirindhorn International Institute of
Technology, Thammasat University, 2016.
Master of Science (Engineering and Technology), Sirindhorn International Institute of
Technology, Thammasat University, 2018.
Enantiomerically pure compounds are highly demanded by the pharmaceutical,
agrochemical, food additives, fragrances, and catalysts industries. Their separations
require appropriate technique and the problem arise with the selection of appropriate
systems of chiral selector-selectand combinations. The identification of suitable
selectors for separating enantiomers requires considerable experimentation which is
highly demanding with respect to time, material and labor. With the help of molecular
modeling, the researchers can visualize three-dimensional structures of any chemical
compounds in any kind of simulated environment, allowing them to study their physical
and chemical properties. In this study, two chiral systems are studied; the chemical
system consisting of beta-cyclodextrin (chiral host) and nicotine enantiomers (chiral
guests), and the biological system consisting of wild-type and mutant pfDHFR (chiral
hosts) and cycloguanil derivatives enantiomers (chiral ligands). The research aims to
study the effect of stereochemistry in chiral hosts on the chiral guests and to predict
their enantioselectivity as the potential chiral selector. The findings indicate the
potential use of both beta-cyclodextrin and pfDHFR as the chiral selectors in separating
nicotine and cycloguanil derivatives enantiomers, respectively.
Keywords: Enantioselectivity, enantiomer, chiral resolution, and molecular modeling
Ref. code: 25605922040059HVU
iv
Table of Contents
Chapter Title Page
Signature Page i
Acknowledgements ii
Abstract iii
Table of Contents iv
List of Figures vi
List of Tables vii
1 Introduction 1
1.1 Background 1
1.2 Scope of the study 4
1.3 Objectives of the study 5
2 Literature Review 6
2.1 Chemical system (beta-cyclodextrin and nicotine enantiomers) 6
2.1.1 Beta-cyclodextrin 9
2.1.2 Nicotine enantiomers 10
2.2 Biological system (Plasmodium falciparum Dihydrofolate 11
Reductase and cycloguanil derivatives enantiomers)
2.2.1 Plasmodium falciparum Dihydrofolate Reductase (pfDHFR) 13
2.2.2 Cycloguanil (Cyc) enantiomers 14
3 Methodology 16
Ref. code: 25605922040059HVU
v
3.1 Guest/ligand structures preparation 16
3.2 Host structures preparation 16
3.3 Molecular docking calculation setup 16
3.4 Complex optimization setup 17
3.5 ∆E calculation 17
4 Result and discussion 20
4.1 Enantioselectivity of nicotine by beta-cyclodextrin 20
4.2 Enantioselectivity of Cycloguanil derivatives by pfDHFR 25
5 Conclusions and Recommendations 29
References 30
Appendices 35
Appendix A 36
Ref. code: 25605922040059HVU
vi
List of Tables
Tables Page
2.1 Properties of alpha-, beta-, and gamma-cyclodextrin [16] 6
2.2 Chiral resolution studies using BCD or its derivatives as the chiral
selector
8
2.3 General properties of nicotine enantiomers 11
2.4 Cycloguanil derivatives substituents (R1, R2) dataset. Compound
names and substituent details are taken from [38]
15
4.1 Binding energy (kcal mol-1) calculation of (R)-nicotine from
molecular docking calculations and ∆E (kcal mol-1) calculation of
nicotine/BCD inclusion complex from PM6 calculations
20
4.2 Binding energy (kcal mol-1) calculation of (S)-nicotine from
molecular docking calculations and ∆E (kcal mol-1) calculation of
nicotine/BCD inclusion complex from PM6 calculations
20
4.3 Binding energy (kcal mol-1) comparison of enantiomeric Cyc
derivatives between molecular docking calculation and experimental
data [38]
25
Ref. code: 25605922040059HVU
vii
List of Figures
Figures Page
1.1 Diagrammatic representation of two non-superimposable mirror
images of (R)- and (S)-enantiomer
1
1.2 Optical activities of (R)- and (S)-enantiomer, respectively 1
1.3 Examples of racemic drugs that exert different biological responses
[1]
2
1.4 Chiral resolution techniques in both the analytic and preparative
scale [3]
3
1.5 Lock and key mechanism of binding interaction. (R)- and (S)-
enantiomer are shown as left and right compound, respectively. (R)-
enantiomer binds to the host while (S)-enantiomer cannot
5
2.1 Chemical structure of beta-cyclodextrin. Image source: Sci.
Pharm. 2018,86(2), 20; doi:10.3390/scipharm86020020
7
2.2 Stereocenters of a single glucose unit in beta-cyclodextrin (BCD)
structure. A total of five chiral centers are located at C-1 to C-5, each
depicted by R and S symbols. R and S stands for chiral center in that
configuration, respectively
9
2.3 Chemical structures of nicotine enantiomers (a) (R)-nicotine; (b) (S)-
nicotine, respectively. Chiral center is shown as black asterisk. (R)-
nicotine has hydrogen atom pointed inside the plane of paper (hollow
wedge), while (S)-nicotine has hydrogen atom pointing outside the
paper (bold wedge)
10
2.4 Conversion of dihydrofolate (DHF) to tetrahydrofolate (THF) by
Dihydrofolate Reductase (DHFR) [32]
11
2.5 Chemical structures of (a) cycloguanil; (b) the general structure of
its derivatives. Cyc consists of a chlorophenyl ring and a 1,3,5-
dihydrotriazine ring. Chiral center is shown as black asterisk. X and
X’ are meta-positions, while Y is para-position
12
Ref. code: 25605922040059HVU
viii
2.6 Three-dimensional structures of wild-type pfDHFR crystal, obtained
from Protein Data Bank (PDB ID: 3UM8 [33])
13
2.7 Amino acid comparisons within the binding pockets of (a) wild-type;
(b) mutant pfDHFR (right), respectively. Cycloguanil and amino
acids are shown as stick and line model, respectively. Dark grey,
blue, red, green, and yellow represents carbon, nitrogen, oxygen,
chlorine, and sulfur atoms, respectively. Hydrogen atoms were
removed for clarity. Asterisk represents chiral centers
14
3.1 Summary of methodological flowchart for chemical system 18
3.2 Summary of methodological flowchart for biological system 19
4.1 ∆E calculation for determining the favorability of nicotine/BCD
inclusion complex formation
21
4.2 Structure of nicotine/BCD inclusion complex from molecular
docking (left side) and PM6 calculations (right side). (a), (b), and (c)
represents (R)-nicotine/BCD inclusion complex of ranking 1,2, and
3, respectively. (d) and (e) represents (S)-nicotine/BCD inclusion
complex of ranking 1 and 2, respectively
23
4.3 The minimized structure of nicotine/BCD inclusion complex’s
binding interactions of (a) (R)-nicotine; (b) (S)-nicotine
24
4.4 Simplified view of the binding interactions of Cyc derivatives inside
the wild-type and mutant pfDHFR binding pockets
26
4.5 Superposition image of Cyc derivatives (p- and m-chlorophenyl
substituent) with the reference structure in the wild-type pfDHFR
binding pocket. Cyc24, 25, 26, 27, 28, 29, 30, 31, and 42 (R2 is alkyl
chain) in: (a) R configuration; (b) S configuration. Cyc32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 43, 44, 45, and 46 (R2 is phenol chain) in: (c)
R configuration; (d) S configuration. Cyc derivatives and the
reference structure are shown as line model and stick model,
respectively. Black, blue and green indicates carbon, nitrogen, and
chlorine atom, respectively
27
Ref. code: 25605922040059HVU
ix
4.6 Superposition image of Cyc derivatives (p- and m-chlorophenyl
substituent) with the reference structure in the mutant pfDHFR
binding pocket. Cyc24, 25, 26, 27, 28, 29, 30, 31, and 42 (R2 is alkyl
chain) in: (a) R configuration; (b) S configuration. Cyc32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 43, 44, 45, and 46 (R2 is phenol chain) in: (c)
R configuration; (d) S configuration. Cyc derivatives and the
reference structure are shown as line model and stick model,
respectively. Black, blue and green indicates carbon, nitrogen, and
chlorine atom, respectively
28
Ref. code: 25605922040059HVU
1
Chapter 1
Introduction
1.1 Background
Enantiomers are isomeric compounds containing at least one asymmetric chiral
center (C, N, F, etc.) that have two non-superimposable images. These compounds exist
in two enantiopure forms; (R)- and (S)-enantiomer, with optical activity. Enantiomers
have identical physical and chemical properties, except they rotate plane polarized light
in opposite directions (Figure 1.1 and 1.2).
Figure 1.1 Diagrammatic representation of two non-superimposable mirror images of
(R)- and (S)-enantiomer.
Figure 1.2 Optical activities of (R)- and (S)-enantiomer, respectively.
4
1
2
3
1
4
3
2
(+) or D = Clockwise
(-) or L = Anti-clockwise
R configuration S configuration
Absolute configuration Optical Activity
(+) or D = Clockwise
(-) or L = Anti-clockwise
Optical Activity
S
Ref. code: 25605922040059HVU
2
Enantiomeric drugs (or chiral drugs) are gaining immeasurable importance in
the field of pharmaceutical industry, as well as in the field of therapeutic applications.
On a molecular level, chirality represents an intrinsic property of the building blocks of
life [1]. Most of the functional enzymes in living organisms are chiral compounds, e.g.
amino acids, sugars, proteins and nucleic acids [2-3]. For some therapeutics, single-
enantiomer formulations can provide greater desirable effects than a mixture of
racemates (equal mixture of two pure enantiomers) [2-4]. This would, in theory, only
require half of the effective dose of 50:50 racemic mixture [2-3]. In fact, very often one
of them represents the more active isomer (eutomer), while the other one might be
active (distomer) in a different way, contributing to side-effects, displaying toxicity, or
acting as antagonist [1]. Taking a mixture of a eutomer and a distomer (in the form of
racemates) may lead to different biological responses like: (i) distomer is inactive when
compared to eutomer, (ii) distomer has the same biological activity as eutomer, (iii)
distomer is less potent than eutomer, (iv) distomer acts as an antagonist to eutomer, (v)
distomer exerts an adverse effect on eutomer, and (vi) distomer exerts different
therapeutic effects than eutomer [1,5]. A few examples of racemic drugs that exert
different therapeutic effects are shown in Figure 1.3 [1].
Figure 1.3 Examples of racemic drugs that exert different biological responses [1].
* *
****
Ref. code: 25605922040059HVU
3
The impact of chirality on almost any pharmacological and biological process
is well recognized and is finding strong repercussion on many fields of economic
interests, such as the development of drugs, agrochemicals, food additives, fragrances,
new materials, and catalysts [3]. The increasing demands in enantiomerically pure
compounds, techniques that are robust, cost-effective, and capable of parallelism are
required for both the analytical and preparative scales [3]. The process of separating
pure enantiomers from racemic mixture is called chiral resolution. Until date, chiral
resolution is achieved via three main techniques; (i) chiral resolution by crystallization,
(ii) chiral resolution by chiral derivatizing agents, and (iii) chiral resolution by chiral
column chromatography. New emerging methods like capillary electrophoresis, liquid-
liquid extraction, sensors, membranes, and biotransformation asymmetric catalysis are
still developing and have been studied extensively [3, 6-9]. A summarized information
about chiral resolution techniques is shown in Figure 1.4. Problems, however, arise
with the selection of appropriate systems chiral selector-selectand combinations from
the constantly growing repertoire of chiral selectors [10]. The identification of suitable
selectors for a specific pair of enantiomers requires considerable experimentation and
might be, therefore, highly demanding with respect to time, material and labor [3].
Clearly, there is a need for empirical and/or rational strategies to facilitate this tedious
selection procedure and to avoid to some extent the “trial-and-error” approach [3].
Figure 1.4 Chiral resolution techniques in both the analytic and preparative scale [3].
ENANTIOSEPERATIONTECHNIQUES
BiotransformationAsymmetric catalysis
Liquid-liquidextraction
Sensors
Capillary electrophoresis Chromatography
Crystallization
Membranes
Analytical Analytical/Preparative Frequently used Emerging techniques
Ref. code: 25605922040059HVU
4
In order to reduce such inconveniences, chiral resolution of racemic compounds
can be investigated by computational chemistry; molecular modeling approach.
Molecular modeling is a computer-based means of representing, visualizing and
investigating the three-dimensional structures and related properties of molecules.
Modern biochemical texts are resplendent with marvelous computer-generated pictures
representing chemical and biological molecules [11]. This technique aids the
researchers to visualize three-dimensional structures of any chemical and biological
molecules in any kind of simulated environment, allowing them to study their physical
and chemical properties, for example shape, size and charge; to simulate the dynamic
behavior of atoms and molecules, such as their vibrational, twisting and rotational
movements; to explore their interactions with other molecules; to design rationally
molecules of biological and clinical interest; and, perhaps most importantly, to greatly
improve scientific communication and the teaching of all aspects of biomolecular
sciences [11]. With the help of molecular modeling, enantioselectivity of the chiral
hosts towards chiral guests can be investigated. Such measures can help reduce the
experimental work load, by generating hypotheses of the subsequent experiment
testing, which is quicker and cost-effective.
1.2 Scope of the study
In this study, two systems (chemical and biological) of chiral molecules are
investigated by molecular modeling. Chemical system of compounds consists of beta-
cyclodextrin (BCD) and nicotine enantiomers; (R)- and (S)-nicotine. While biological
system of compounds consists of Plasmodium falciparum Dihydrofolate Reductase
(pfDHFR) and cycloguanil (Cyc) derivatives enantiomers; (R)- and (S)-cycloguanil
derivatives. The hosts and guests in both the systems are chiral. Based on the lock and
key mechanism of binding interaction, compounds that can fit in perfectly inside the
host’s binding cavity, will results in binding interaction and thus, the formation of
chemical/or biological complexes (Figure 1.5).
Three-dimensional structures of nicotine and Cyc derivatives enantiomers were
constructed using GaussView 5 [12]. The resulting structures were further optimized
for the lowest energy state via Gaussian 09 [13]. While the three-dimensional structures
of BCD and pfDHFR (wild and mutant type) can be obtained from central database.
Ref. code: 25605922040059HVU
5
The downloaded structures were optimized via Discovery Studio Visualizer 4.0 [14].
Then, nicotine enantiomers were docked into the BCD’s binding cavity and Cyc
derivatives enantiomers were docked into the pfDHFR’s binding site via AutoDock 4.2,
using default settings at a hundred docking frequencies [15]. In this calculation, ligands
were freely flexible while hosts were kept rigid. The results obtained from AutoDock
calculation were reported in terms of binding energies (BE). A hundred docking
calculations were classified into many clusters depending on the structural
conformations of ligands within the hosts’ molecules. The best BE were selected from
the cluster with highest frequencies and were further analyzed. From the analysis,
binding interactions of chemical and biological complexes can be studied and predicted
using hypotheses, as whether the chiral hosts can be used to separate pure enantiomers
from racemic mixture or not.
Figure 1.5 Lock and key mechanism of binding interaction. (R)- and (S)-enantiomer are
shown as left and right compound, respectively. (R)-enantiomer binds to the host while
(S)-enantiomer cannot.
1.3 Objectives of the study
This study aims at understanding the relationship of stereochemistry of chiral
hosts on chiral guests. The scope is to investigate the enantioselective properties of
chiral hosts towards chiral guests, using molecular modeling approach. The obtained
results then will be used for predicting the potential chiral hosts which will be beneficial
for other researchers and experimentalists.
Host
SR
Ref. code: 25605922040059HVU
6
Chapter 2
Literature Review
2.1 Chemical system (beta-cyclodextrin and nicotine enantiomers)
Cyclodextrins (CDs) are membered rings of glucose units connected to each
other by (alpha-1,4)-glycosidic bondage. Three primary types of CDs are alpha-, beta-
, and gamma-cyclodextrin (ACD, BCD, and GCD, respectively), each containing six,
seven, and eight glucose units. Summarized details of CDs are given in Table 2.1.
Table 2.1 Properties of alpha-, beta-, and gamma-cyclodextrin [16].
Properties ACD BCD GCD
No. of glucopyranose units 6 7 8
Chemical formula C36H60O30 C42H70O35 C48H80O40
Molar mass in Dalton units 972.8 1134.9 1297.1
Water molecules in cavity 6 11 17
Water solubility (w/v at 25℃) 14.5 1.8 23.2
Inner diameter in Å 5 ± 0.3 6.3 ± 0.3 7.9 ± 0.4
Outer diameter in Å 14.6 ± 0.5 15.4 ± 0.1 17.5 ± 0.6
Height of structure in Å 7.9 ± 0.1 7.9 ± 0.1 7.9 ± 0.1
Melting range in ˚C 255-260 255-265 240-245
Water of crystallization 10.2 13-15 8-18
Cavity volume (ml/mol) 174 262 472
Price 1.0 0.025 0.8
(USD/g of pharmaceutical grade)
What sets CDs apart from other compounds is that, CDs exhibit intrinsic
property of both hydrophobicity and hydrophilicity. The interior of CDs is joined by
glycosidic bonds (or ethereal linkages), resulting in the internal cavity of all CDs to
have hydrophobic property. Whereas the outer edges of CDs are occupied with primary
and secondary hydroxyl (-OH) functional groups. Primary -OH groups are located at
C-2 and C-3 of the wider rim while secondary -OH group is located at C-6 of the narrow
Ref. code: 25605922040059HVU
7
rim. The presence of -OH groups on the outer edges of CDs resulted in the hydrophilic
property. Three-dimensional structure of BCD showing seven membered-ring,
glycosidic linkage, and -OH functional groups is shown in Figure 2.1.
Figure 2.1 Chemical structure of beta-cyclodextrin. Image source: Sci. Pharm. 2018,
86(2), 20; doi:10.3390/scipharm86020020.
Cyclodextrins (CDs) are the most popular of the many chiral selectors used in
capillary electrophoresis (CE); a chiral resolution technique used for analytical purpose.
CE is an analytical technique used for separation of charges/ionic analytes based on their
electrophoretic mobility, under the influence of applied voltage. During the process,
positively charged analytes are reduced (gain e-) at cathode and negatively charged
analytes are oxidized (loss e-) at anode, via the capillary tube of the size 20 to 100 μm.
Due to their good enantioselective property towards a wide range of analytes, their good
water solubility, and their transparency towards UV light down to low wavelengths, CDs
closely resemble the ideal chiral selector and they are used in about two-thirds of the
literature applications (refer to Table 2.2) [17-18].
Ref. code: 25605922040059HVU
8
Table 2.2 Chiral resolution studies using BCD or its derivatives as the chiral selector.
Method Selector Selectant Year Ref.
CE Sulfobutyl-BCD Ephedrine, and pseudo- 1994 [19]
ephedrine enantiomers
CE Carboxymethyl-BCD Neurotransmitters 2001 [20]
Membrane BCD Tryptophan enantiomers 2007 [21]
CE BCD derivatives Higenamine enantiomers 2017 [22]
MM BCD Isopulegol enantiomers 2013 [23]
MM BCD Propranolol enantiomers 2014 [24]
MM BCD Valine enantiomers 2015 [25]
MM, NMR BCD Asenapine enantiomers 2016 [26]
MM BCD Leucine enantiomers 2017 [27]
Sensors BCD Tyrosine enantiomers 2017 [28]
MM BCD Mansonone enantiomers 2018 [29]
CE = capillary electrophoresis, Membrane = membrane technology,
Sensors = enantioselectivity sensing, MM = molecular modeling,
NMR = nuclear magnetic resonance spectroscopy.
CDs are available in many sizes. They give fast kinetics for the formation and
breakdown of complexes with enantiomers and are relatively cheap [17]. Successful
application of CDs in CE, has followed their use as chiral stationary phases in gas
chromatography (GC), thin-layered chromatography (TLC), and high-performance liquid
chromatography (HPLC), and as mobile phase additives in TLC and HPLC. Most early
workers used the parent ACD, BCD, and GCD but most interest has now shifted to the
substituted cyclodextrin derivatives, particularly those of BCD and its derivatives
because of its low cost and accessibility [17-18]. However, these techniques require
considerable experimentation and might be, therefore, highly demanding with respect to
time, material and labor [3]. To reduce such inconveniences, theoretical investigation
using molecular modeling can be quite handful, as seen in later studies shown in Table
2.2 [23-29]. Therefore, preliminary analysis via molecular modeling can be useful in
Ref. code: 25605922040059HVU
9
predicting possible hypotheses before conducting real experiments and thus, saves time
and cost.
2.1.1 Beta-cyclodextrin (BCD)
Figure 2.2 Stereocenters of a single glucose unit in beta-cyclodextrin (BCD) structure.
A total of five chiral centers are located at C-1 to C-5, each depicted by R and S
symbols. R and S stands for chiral center in that configuration, respectively.
Beta-cyclodextrin is a seven-membered glucose ring, joined by (alpha-1,4)-
glycosidic bonds. BCD is known for its cheap price and high productivity in the field of
chiral resolution [19-29]. Each glucose unit has five chiral centers as shown in Figure 2.2.
Therefore, BCD is a chiral host. As mentioned earlier, BCD and its derivatives are
gaining popularity among researchers due to its lower cost and higher efficiency in its
fast kinetic for inclusion complex formation with the chiral molecules [23-29]. The use
of BCD in forming inclusion complex with guest enantiomers will provide greater
insights towards its enantioselectivity towards guest enantiomers, as well as providing us
with the in-depth molecular interactions that are responsible for higher affinity of BCD
towards one of the guest enantiomers. From these findings, the possibility of using BCD
in separating nicotine enantiomers can be concluded. Please be noted that such
predictions are derived from preliminary analysis. In order to reduce biases from fixed
host flexible guest calculation, molecular dynamics calculation where both the host and
guest are flexible, should be further performed.
Ref. code: 25605922040059HVU
10
2.1.2 Nicotine enantiomers
Nicotine is a volatile alkaloid that can be extracted from the tobacco leaves.
Nicotine forms a very stable complex with hemoglobin, allowing them to be transported
from the lungs to the brain. Nicotine indirectly stimulates the release of neurotransmitters
in various parts of the brain, which collectively resulted in the feeling of relaxation,
sustained attention, stimulation, alertness, and calmness [30]. Nicotine is an optically
active stereoisomer. Due to its structural arrangement, the molecule has one chiral center
at C-1. Nicotine enantiomer compositions in naturally occurring tobacco leaves is
dominated by ~99.0-99.9% of (S)-nicotine and ~0.1-1.2% of (R)-nicotine [31]. The
structure of nicotine is made up of the covalent linkage between pyrimidine ring and
methylpyrrolidine ring. The chiral center exists at the position of carbon atom of
methylpyrrolidine ring that is linked to the pyrimethamine ring. Molecular structures of
nicotine enantiomers and its properties are shown in Figure 2.3 and Table 2.3,
respectively. In this study, the enantioselectivity of BCD towards nicotine enantiomers
were investigated.
Figure 2.3 Chemical structures of nicotine enantiomers (a) (R)-nicotine; (b) (S)-nicotine,
respectively. Chiral center is shown as black asterisk. (R)-nicotine has hydrogen atom
pointed inside the plane of paper (hollow wedge), while (S)-nicotine has hydrogen atom
pointing outside the paper (bold wedge).
Pyrimethamine ring
(R)-nicotine (S)-nicotine
Methylpyrrolidine ring
Ref. code: 25605922040059HVU
11
Table 2.3 General properties of nicotine enantiomers.
Properties (R)-nicotine (S)-nicotine
Chemical formula C10H14N2 C10H14N2
Molar mass in g/mol 162.236 162.236
Polarization effect Rotate clockwise (+) Rotate anti-clockwise (-)
Melting point in ˚C -79 -79
Boiling point in ˚C 247 247
No. of H bond donor 0 0
No. of H bond acceptor 2 2
No. of chiral center 1 1
Rotatable bond count 1 1
2.2 Biological system (Plasmodium falciparum Dihydrofolate Reductase and
cycloguanil derivatives enantiomers)
Figure 2.4 Conversion of dihydrofolate (DHF) to tetrahydrofolate (THF) by
Dihydrofolate Reductase (DHFR) [32].
Ref. code: 25605922040059HVU
12
Plasmodium falciparum Dihydrofolate Reductase (pfDHFR) is a key enzyme
responsible for the livelihood of Plasmodium falciparum parasites [5]. This parasite
contributes up to 87% of all the Plasmodium population in Thailand (based on reports
from Thailand’s Center of Disease Control). The enzyme Dihydrofolate Reductase
(DHFR) is responsible for the reproductive cycle of the Plasmodium parasite, which is
responsible for the malaria infection in human. DHFR converts dihydrofolate to
tetrahydrofolate, which is the building blocks of nucleic acids (refer to Figure 2.4).
Cycloguanil (Cyc), a kind of the anti-folate, is used to tackle DHFR enzymatic
activity by inhibiting DHFR’s activation and thus, no conversion of dihydrofolate.
However, prolong use of same line of drug resulted in pfDHFR resistance towards anti-
folate. Among various types of mutated pfDHFR, double-point mutations at residue 16
(alanine mutates to valine) and at residue 108 (serine mutates to threonine) confer
cycloguanil (Cyc) resistance in the double mutant variant pfDHFR (A16V + S108T) [5,
34-35]. Cyc derivatives (a new line of anti-folate) are designed and experimentally tested
against both the wild-type and mutant pfDHFR (A16V + S108T) [34-35]. The structure
of Cyc derivatives contain one chiral center at the C-2 position of chlorophenyl ring,
resulting them to be enantiomers (Figure 2.5).
Figure 2.5 Chemical structures of (a) cycloguanil; (b) the general structure of its
derivatives. Cyc consists of a chlorophenyl ring and a 1,3,5-dihydrotriazine ring. Chiral
center is shown as black asterisk. X and X’ are meta-positions, while Y is para-position.
Ref. code: 25605922040059HVU
13
So far, there is no reports about which type of Cyc derivatives enantiomers; the
(R)- or (S)-enantiomer is more potent towards mutant pfDHFR. This is important because
the pure enantiomeric form of a chiral drug can exert desirable or non-desirable responses
on the body or both [1-2,4-5]. Important living enzymes are mostly made up of chiral
molecules. Chances are that, they will exhibit “lock and key” mechanism as illustrated in
Figure 1.2. Since both pfDHFR and cycloguanil derivatives are chiral molecules, we can
investigate the enantioselectivity of chiral host (wild-type and mutant pfDHFR) towards
chiral ligands (Cyc derivatives enantiomers) via molecular modeling.
2.2.1 Plasmodium falciparum Dihydrofolate Reductase (pfDHFR)
Figure 2.6 Three-dimensional structures of wild-type pfDHFR crystal, obtained from
Protein Data Bank (PDB ID: 3UM8 [33]).
In this study, two types of pfDHFR are being studies; the wild-type pfDHFR
(PDB ID: 3UM8 [33]) and double mutant variant (A16V+S108T) pfDHFR (PDB ID:
3UM6 [34]). The crystal structure of pfDHFR is shown in Figure 2.6. The three-
dimensional protein network is made up of two domains; the dihydrofolate (DHFR)
DHFR domain
(N-terminal)
TS domain
(C-terminal)
pfDHFR
binding site
-helix -helix -loop
Ref. code: 25605922040059HVU
14
domain and the thymidylate synthase (TS) domain. A total of 608 amino acid residues
with 231 residues belonged to DHFR domain and 288 residues belonged to the TS
domain. The remaining 89 residues belonged to the junction region that serves as the
bridge joining the DHFR to TS domain [35]. The enantioselectivity of both the wild-type
and mutant pfDHFR will be investigated in the region of interests i.e., the DHFR’s
binding site. From exterior view of both types of pfDHFR, it is not possible to notice their
differences. For better perspectives, the comparison of binding pockets of both the wild-
type and mutant pfDHFR is shown in Figure 2.7.
Figure 2.7 Amino acid comparisons within the binding pockets of (a) wild-type; (b)
mutant pfDHFR (right), respectively. Cycloguanil and amino acids are shown as stick
and line model, respectively. Dark grey, blue, red, green, and yellow represents carbon,
nitrogen, oxygen, chlorine, and sulfur atoms, respectively. Hydrogen atoms were
removed for clarity. Asterisk represents chiral centers.
2.2.2 Cycloguanil (Cyc) derivatives enantiomers
Cyc is well known for its inhibiting potential against DHFR enzyme. Lately,
pfDHFR mutated and became resistant to Cyc. One of the type i.e., the double mutant
variant (A16V+S108T) was found to be directly associated with the Cyc resistance
[5,36-37]. Chemical structures of Cyc and Cyc derivatives are shown in Figure 2.5. Cyc
consists of a 1,3,5-dihydrotriazine ring with a 2,2-dimethyl substitution at the C-2
position and p-chlorophenyl substitution at the N-1 position. In this study, there are two
Ref. code: 25605922040059HVU
15
types of R1, R2 substituents; the non-bulky alkyl chains and the bulky phenolic chains.
The substitution of R1, R2 substituents into the general structure of Cyc derivatives
gives the R-enantiomer. On the other hand, switching the position of R1, R2 substituents
constitute the S-enantiomer. The substitution of flexible substituents at C-2 gives rise
to asymmetric carbon chiral center. As a result, Cyc derivatives can exist as (R)- or (S)-
enantiomers. The dataset of Cyc derivatives are presented in Table 2.4.
Table 2.4 Cycloguanil derivatives substituents (R1, R2) dataset. Compound names and
substituent details are taken from [38].
Comp. X Y R1 R2
Cyc H Cl Me Me
23 Cl H Me Me
24 H Cl Me nPr
25 Cl H Me iPr
26 H Cl Me iPr
27 Cl H Me nPr
28 H Cl Me nHex
29 Cl H Me nHex
30 H Cl H Me
31 Cl H H Me
32 H Cl H C6H5
33 Cl H H C6H5
34 H Cl H 4-C6H5OC6H4
35 Cl H H 4-C6H5OC6H4
36 H Cl H 3-C6H5OC6H4
37 Cl H H 3-C6H5OC6H4
38 H Cl H 3-C6H5CH2OC6H4
39 Cl H H 3-C6H5CH2OC6H4
40 H Cl H 3-(4-ClC6H4O)C6H4
41 Cl H H 3-(4-ClC6H4O)C6H4
42 Cl H H nC7H15
43 Cl H H 4-PrOC6H4
44 Cl H H 3-(3,5-Cl2C6H3O)C6H4
45 Cl H H 3-[2,4,5-Cl3C6H2O(CH2)3O]C6H4
46 Cl H H 3-(3-CF3C6H4O)C6H4
X and X’: m-positions; Y: p-position; green: chlorine atom.
Ref. code: 25605922040059HVU
16
Chapter 3
Methodology
In this study, there are two types of molecular systems; the chemical and
biological system. In chemical system, the host is beta-cyclodextrin (BCD) and the
guests are nicotine enantiomers. In biological system, the host is wild-type and double
mutant variant (A16V+S108T) Plasmodium falciparum Dihydrofolate Reductase
(pfDHFR) and the guests are cycloguanil (Cyc) derivatives enantiomers.
3.1 Guest/Ligand structures preparation
Three dimensional structures of nicotine (guests) and Cyc derivatives
enantiomers (ligands) are constructed using GaussView 0 5 [ 12]. Chemical structures
of nicotine enantiomers are submitted to geometry optimization with the basis set PM6,
gaseous state, by Gaussian 09 [13]. Similarly, Cyc derivatives underwent geometry
optimization but with the different basis set i.e., Hatree-Fock/6-31G (d,p), gaseous
environment by Gaussian 09 [13].
3.2 Host structures preparation
The crystal structures of BCD is downloaded from Cambridge Crystallographic
Data Center (CCDC). The reference code for BCD is BCDEXD03 [39]. pfDHFR’s
crystal structure is download from RCSB Protein Data Bank; Wild-type pfDHFR (PDB
ID: 3UM8) [33] and double-mutant variant (A16V+S108T) pfDHFR (PDB ID: 3UM6)
[34]. The downloaded crystal structures are then optimized in Discovery Studio
Visualizer by removing water of crystallization molecules and add polar hydrogen
atoms [14]. The final structures of both the optimized ligands and hosts are docked in
together using AutoDock 4.2.6 tools [15].
3.3 Molecular docking calculation setup
The optimized structures of nicotine enantiomers are docked into the crystal
structure of BCD while Cyc derivatives enantiomers are docked into the crystal
structure of wild-type and mutant pfDHFR, using AutoDock 4.2.6 [15]. The small
Ref. code: 25605922040059HVU
17
molecules (guests or ligands) are kept flexible, while the hosts are kept rigid. Gasteiger
charges are assigned to the system before performing molecular docking simulation. A
grid size of 40 × 40 × 20 (chemical system) and 60 x 60 x 60 (biological system) with
0.375 Å spacing was assigned. The dimensions and coordinates of grid boxes are kept
constant throughout the docking process. One hundred docking calculations are
performed on each guest-host complex using the Lamarckian genetic algorithm with
remaining parameters run at default settings [40]. The results obtained are classified
into different clusters with different binding energies which are used for further
analysis.
3.4 Complex optimization setup
The results obtained from molecular docking calculations predict the
configuration of guests/ligands within the host’s binding site. Each configuration is
saved from the results and then embedded into the host’s structure to form binding
complex. The inclusion complex of biological system (Cyc derivatives/pfDHFR
complex) is rather big and cannot be optimize due to computational limitations.
Therefore, smaller complex like nicotine/BCD is furthered optimized using PM6,
gaseous state basis set, by Gaussian 09 [13].
3.5 ∆E calculation
After performing nicotine/BCD complex optimization, ∆E is calculated. The
negative and positive value of ∆E indicates that inclusion complex formation is
favorable and non-favorable, respectively.
The equilibrium equation is described by the equation:
Guest + Host ↔ Guest/Host inclusion complex)
Guest = (R)- and (S)-nicotine
Host = BCD
∆E calculation: ∆E (kcal mol-1) = EINCLUSION COMPLEX – (EHOST + EGUEST)
Ref. code: 25605922040059HVU
18
Figure 3.1 Summary of methodological flowchart for chemical system
Ref. code: 25605922040059HVU
19
Figure 3.2 Summary of methodological flowchart for biological system
Ref. code: 25605922040059HVU
20
Chapter 4
Result and Discussion
4.1 Enantioselectivity of nicotine by beta-cyclodextrin
Table 4.1 Binding energy (kcal mol-1) calculation comparison of (R)-nicotine from
molecular docking calculations and ∆E (kcal mol-1) calculation of nicotine/BCD
inclusion complex from PM6 calculations.
Docking Calculation ∆E Calculation
Rank Freq. BE S.D. EBCD E(R)-NICOTINE ECOMPLEX ∆E
1 76 -4.16 ± 0.02 -1572.31 27.76 -1557.33 -12.78
2 16 -4.10 ± 0.00 -1572.31 27.76 -1561.91 -17.37
3 8 -4.08 ± 0.00 -1572.31 27.76 -1556.06 -11.51
Freq. = frequency; BE = binding energy; S.D. = standard deviation
Table 4.2 Binding energy (kcal mol-1) calculation comparison of (S)-nicotine from
molecular docking calculations and ∆E (kcal mol-1) calculation of nicotine/BCD
inclusion complex from PM6 calculations.
Docking Calculation ∆E Calculation
Rank Freq. BE S.D. EBCD E(S)-NICOTINE ECOMPLEX ∆E
1 60 -4.15 ± 0.01 -1572.31 27.72 -1554.31 -9.72
2 40 -4.13 ± 0.00 -1572.31 27.72 -1553.58 -8.98
Freq. = frequency; BE = binding energy; S.D. = standard deviation
The results obtained from molecular docking calculation of (R)- and (S)-
nicotine enantiomers into the beta-cyclodextrin (BCD) binding site is shown in Table
4.1 and 4.2, respectively. From one hundred docking frequencies, rankings of the
clusters are classified as rank 1, 2, and 3. One rank classification represents one
structural conformation of the nicotine enantiomer within the BCD’s binding site. It is
observed that (R)- and (S)-nicotine has three and two rankings, respectively. To obtain
∆E, the inclusion complexes were re-optimized by Gaussian 09 using PM6 calculation
by Gaussian 09 [13].
Ref. code: 25605922040059HVU
21
Figure 4.1 ∆E calculation for determining the favorability of nicotine/BCD inclusion
complex formation.
The results in Table 4.1 and 4.2 indicate the enantioselectivity of BCD towards
(R)-nicotine is more than the (S)-nicotine. In terms of molecular docking calculations,
clear difference could not be established to predict the enantioselectivity of BCD
towards one of the nicotine enantiomers. In order to observe the movement of nicotine
inside BCD’s binding site, nicotine/BCD inclusion complex optimization was
performed using PM6 gas phase calculation. From PM6 calculation, we obtain ∆E
values which are calculated by subtracting the energy of reactants i.e., nicotine and
BCD from the energy of nicotine/BCD inclusion complex, as shown in Figure 4.1. In
equilibrium perspective, negative and positive ∆E means that the formation of inclusion
complex is favorable and non-favorable, respectively.
From the results, BCD is more enantioselective towards the (R)-nicotine than
the (S)-nicotine. To support the claim, ∆E values of each nicotine/BCD inclusion
complex were compared and the comparison shows that (R)-nicotine of ranking 2 has
the lowest ∆E value of -17.37 kcal mol-1 while (S)-nicotine of ranking 2 has the highest
∆E value of -8.98 kcal mol-1. This value shows that the formation of nicotine/BCD
inclusion complex is more favorable by the (R)-nicotine than the (S)-nicotine. The
lower ∆E values corresponds not only to the favorability of inclusion complex, they
also indicate the distribution of retention time of each nicotine enantiomer within the
BCD Nicotine Nicotine/BCD inclusion complex
∆E= EINCLUSION COMPLEX - (EBCD + ENICOTINE)
- ∆E means formation of inclusion complex is favorable
+∆E means formation of inclusion complex is not favorable
Ref. code: 25605922040059HVU
22
chromatography column. The lower the ∆E value, the longer that inclusion complex
retentate within the column.
In order to understand the phenomena of higher and lower ∆E values, binding
interactions of nicotine enantiomers with BCD were investigated. As previously stated,
one ranking obtained from molecular docking calculation represents one structural
conformation of nicotine within the BCD’s binding pocket. The comparison of
nicotine/BCD inclusion complex conformation obtained from molecular docking
calculation and PM6 calculation is shown in Figure 4.2. In the figure, the structure of
nicotine is shown as stick model while BCD is shown as line model. The gray opaque
surface surrounding the BCD’s structure is the Van der Waals surface. From the figure,
it is observed that the structure of nicotine experiences minor shift from its original
position after performing nicotine/BCD inclusion optimization via PM6 gaseous phase
calculation. The minor shift in the structure of nicotine was the response to avoid steric
hindrance between the nicotine and the BCD molecule.
Nicotine molecule consists of methylpyrrolidine and pyrimethamine ring (refer
to Figure 2.3). The pyrimethamine ring is aromatic because of the presence of
delocalized electrons. One torsional point is present at the chiral carbon, allowing the
methylpyrrolidine to rotate freely. From Figure 4.2, the methylpyrrolidine ring of both
the (R)- and (S)-nicotine rotated itself to avoid steric hindrance, while the
pyrimethamine ring remained rigid, except in Figure 4.2c and 4.2d where the
pyrimethamine did actually move. From Figure 4.2, nicotine/BCD inclusion complex
of 4.2b (lowest ∆E; (R)-nicotine/BCD) and 4.2d (lowest ∆E; (S)-nicotine/BCD) were
further evaluated for the effect of BCD’s stereoselectivity on nicotine enantiomers.
Their binding interactions are shown in Figure 4.3a and 4.3b, respectively.
Ref. code: 25605922040059HVU
23
Figure 4.2 Structure of nicotine/BCD inclusion complex from molecular docking (left
side) and PM6 calculations (right side). (a), (b), and (c) represents (R)-nicotine/BCD
inclusion complex of ranking 1,2, and 3, respectively. (d) and (e) represents (S)-
nicotine/BCD inclusion complex of ranking 1 and 2, respectively.
Ref. code: 25605922040059HVU
24
Figure 4.3 The minimized structure of nicotine/BCD inclusion complex’s binding
interactions of (a) (R)-nicotine; (b) (S)-nicotine.
From binding interaction analysis of Figure 4.3, (R)- and (S)-nicotine were
primarily driven into BCD’s binding pocket by van der Waals forces and hydrophobic
interactions. In (R)-nicotine/BCD inclusion complex, one hydrogen bonding of the
distance 2.53 Å was present. This hydrogen bonding is formed between nitrogen atom
of methylpyrrolidine ring of nicotine and a secondary -OH group of BCD. The bond
length of 2.53 Å represents medium strong hydrogen bonding with the bond energy of
the range 4-14 kcal mol-1 [41]. The formation of hydrogen bond in (R)-nicotine/BCD
inclusion complex, results it to have more negative ∆E value than the (S)-nicotine/BCD
inclusion complex by (-17.37) - (-9.72) = -7.65 kcal mol-1. Hydrogen bonding formed
also prevented (R)-nicotine from being rejected from the nicotine/BCD inclusion
complex. As a result, the folding of secondary -OH groups of the wider rim, furthermore
strengthened the inclusion complex formed between (R)-nicotine of ranking 2 and
BCD.
The stereochemistry of BCD is dominated by 80% (R)-chiral carbon centers and
20% (S)-chiral carbon centers. The stereochemistry of both the BCD and nicotine
enantiomers were well preserved after molecular docking and PM6 calculations. No
special relationship between BCD’s stereochemistry and nicotine enantiomers were
observed. Despite the presence of high majority of (R)-chiral centers in BCD, BCD
still bind to both nicotine enantiomers but BCD binds more preferably with the (R)-
nicotine due to the formation of hydrogen bonding.
Ref. code: 25605922040059HVU
25
4.2 Enantioselectivity of Cycloguanil derivatives by pfDHFR
The results in Table 4.3 are selected according to the guideline of essential
binding characteristics of a good pfDHFR inhibitor (Figures 4.4) [42]. The selected
results are compared with the experimental data by superimposing the structural
conformations of the selected results with the Cyc structure present in the parent x-ray
crystal structure. The good superposition indicates that Cyc derivatives have similar
binding interaction characteristics to the guideline (Figure 4.4) and the bad
superposition indicates some internal steric hindrance.
Table 4.3 Binding energy (kcal mol-1) comparison of enantiomeric Cyc derivatives
between molecular docking calculation and experimental data [38].
a m-Cl at X flips to X’ position; b Poor conformation; X: m-position; Y: p-position; R1,
R2: substituents; R: Cyc derivatives in R configuration; S: Cyc derivatives in S
configuration; Exp.: Experimental data; Comp.: Compound; Bold: Enantiomer
configuration with the lowest BE.
3UM8 3UM6
Comp X Y R1 R2 R S Exp R S Exp
Cyc H Cl Me Me -8.12
-7.98
-12.04 -7.70
-7.70
-8.02
23 Cl H Me Me -11.63 -8.88
24 H Cl Me nPr -8.07 -6.85b -11.54 -8.08 -7.09b -6.87
25 Cl H Me iPr -8.59 -7.30b -10.36 -8.20a -7.41b -7.72
26 H Cl Me iPr -8.72 -7.12b -10.15 -7.70 -7.37b -5.93
27 Cl H Me nPr -8.14 -8.01 -11.37 -8.07 -7.57a -8.63
28 H Cl Me nHex -7.75b -8.26 -12.58 -7.81 -7.79 -8.21
29 Cl H Me nHex -7.85 -8.17 -11.76 -7.65a -7.62a -9.54
30 H Cl H Me -8.34 -7.76 -11.44 -7.98 -7.53 -9.41
31 Cl H H Me -8.26a -7.83 -10.90 -8.40a -7.48 -10.11
32 H Cl H C6H5 -8.97 -8.39 -11.39 -9.18 -7.21b -9.97
33 Cl H H C6H5 -8.80a -8.67 -10.82 -9.34a -7.19 -10.88
34 H Cl H 4-C6H5OC6H4 -8.57b -9.47 -12.82 -9.19 -9.04b -11.49
35 Cl H H 4-C6H5OC6H4 -8.47b -9.97 -12.49 -9.01a -7.22b -11.69
36 H Cl H 3-C6H5OC6H4 -8.60 -9.49 -12.69 -8.91 -6.81 -11.69
37 Cl H H 3-C6H5OC6H4 -8.73b -9.85 -12.22 -8.50 -8.55b -11.73
38 H Cl H 3-C6H5CH2OC6H4 -8.12 -8.82 -12.49 -8.40 -6.74 -11.20
39 Cl H H 3-C6H5CH2OC6H4 -9.31b -9.82 -11.78 -8.14 -7.01 -11.59
40 H Cl H 3-(4-ClC6H4O)C6H4 -8.82 -10.04 -12.08 -8.96 -7.27 -11.08
41 Cl H H 3-(4-ClC6H4O)C6H4 -9.25b -10.40 -12.12 -8.79 -7.39 -11.54
42 Cl H H nC7H15 -8.39a -8.03 -11.69 -8.33a -7.59 -11.49
43 Cl H H 4-PrOC6H4 -7.43b -8.87 -11.57 -9.43a -8.05b -10.96
44 Cl H H 3-(3,5-Cl2C6H3O)C6H4 -8.90b -10.09 -11.93 -8.62 -6.93b -11.36
45 Cl H H 3-[2,4,5-Cl3C6H2O(CH2)3O]C6H4 -9.18b -10.20 -11.46 -7.68 -3.49b -11.71
46 Cl H H 3-(3-CF3C6H4O)C6H4 -8.20b -9.98 -11.69 -8.62 -6.74 -11.17
Ref. code: 25605922040059HVU
26
Figure 4.4 Simplified view of the binding interactions of Cyc derivatives inside the
wild-type and mutant pfDHFR binding pockets.
The presence of poor conformations in the results were analyzed. The outcomes
indicated that chiral binding pocket of both the wild-type and mutant pfDHFR have
preferential binding towards one form of enantiomer. The non-preferred enantiomer
cannot bind property due to its failure to comply with the “lock and key” mechanism,
thereby, making them experiencing steric hindrance with one or more of the pfDHFR
side chains. For better insights, the structures of enantiomeric Cyc derivatives were
superimposed inside the wild and mutant pfDHFR binding pocket as shown in Figure
4.5 (wild-type pfDHFR) and 4.6 (mutant pfDHFR).
In wild-type pfDHFR, Cyc derivatives with alkyl chains (except Cyc28 and 29)
are preferred for the (R)-enantiomer and Cyc derivatives with phenol chains (except
Cyc32 and 33) are preferred for the (S)-enantiomer. (R)-Cyc derivatives with alkyl
chains have better binding activity than (S)-Cyc derivatives because they can avoid
steric hindrance with the Phe58 side chains. (S)-Cyc derivatives with phenol chains
have better binding activity than (R)-Cyc derivatives because they can avoid steric
hindrance with the Leu46 and Met55 side chains. Cyc28, 29, 32, and 33 are exceptions
because the size of their substituents is the transition between non-bulky alkyl chains
and bulky phenol chains.
Ref. code: 25605922040059HVU
27
Figure 4.5 Superposition image of Cyc derivatives (p- and m-chlorophenyl substituent)
with the reference structure in the wild-type pfDHFR binding pocket. Cyc24, 25, 26,
27, 28, 29, 30, 31, and 42 (R2 is alkyl chain) in: (a) R configuration; (b) S configuration.
Cyc32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 45, and 46 (R2 is phenol chain) in: (c)
R configuration; (d) S configuration. Cyc derivatives and the reference structure are
shown as line model and stick model, respectively. Black, blue and green indicates
carbon, nitrogen, and chlorine atom, respectively.
In mutant pfDHFR, the BE values have similar trend to the experimental data.
Cyc derivatives, irrespective of the substituent type, are preferred for the (R)-
enantiomer. Mutant pfDHFR is made up of chiral centers. The chirality within mutant
pfDHFR are similar to that of wild-type, except for Thr108 that contains two chiral
centers (R and S). The highest available enantiomers are in S configuration (refer to
Figure 2.6). The increase in the bulkiness of Val16 and Thr108 results in the reduction
of binding pocket volume around them. Mutation at residue 108 results in Cyc
derivatives with p-Cl (except Cyc28, 34, 36, 38 and 40) to experience steric hindrance
Ref. code: 25605922040059HVU
28
with Thr108 side chains. Val16 is situated in front Phe58 (refer to Figure 2.6). Because
Val16 is bulkier than Ala16, the pocket volume Val16 and Phe58 is reduced, resulting
in the (R)-Cyc derivatives to have better binding activity than the (S)-Cyc derivatives.
The superposition images show that poor conformation or the non-preferred enantiomer
configurations have binding interactions that are different from the reference structure.
This is because they have steric hindrance with one or more of the amino acid side
chains within the binding pocket, resulting them to have higher energy state and
therefore higher BE as shown in Table 4.3.
Figure 4.6 Superposition image of Cyc derivatives (p- and m-chlorophenyl substituent)
with the reference structure in the mutant pfDHFR binding pocket. Cyc24, 25, 26, 27,
28, 29, 30, 31, and 42 (R2 is alkyl chain) in: (a) R configuration; (b) S configuration.
Cyc32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 45, and 46 (R2 is phenol chain) in: (c)
R configuration; (d) S configuration. Cyc derivatives and the reference structure are
shown as line model and stick model, respectively. Black, blue and green indicates
carbon, nitrogen, and chlorine atom, respectively.
Ref. code: 25605922040059HVU
29
Chapter 5
Conclusions and Recommendations
The theoretical investigation of enantioselective ligand-host binding
interactions in chemical and biological systems reveals that both the chiral hosts of
these two systems were capable of separating pure enantiomers from the racemic
mixture. In the chemical system, BCD binds more preferably towards (R)-nicotine than
the (S)-nicotine, due to the formation of hydrogen bonding. In the biological system,
both the wild-type and mutant pfDHFR are enantioselective towards Cyc derivatives
enantiomers because they cannot satisfy the lock and key mechanism, together with the
steric hindrance that one enantiomeric form of Cyc derivative experienced within the
pfDHFR binding pocket. The enantioselectivity of chiral hosts i.e. BCD and pfDHFR
from both systems demonstrated good activity in selective binding with one form of
enantiomer over another form. Both hosts are the potential chiral selectors to be used
in real environment for enantiomer separations. Therefore, theoretical investigation of
enantioselective ligand-host binding interaction by molecular modeling approach
proves to be a very powerful tool towards understanding the three-dimensional aspects
of chiral ligands-hosts binding interactions, which is very beneficial to the
experimentalist, not only in saving time and cost, but also provide them with the general
idea of selecting a good chiral selector.
For in-depth understanding of the molecular interactions of chiral hosts and
guests (or ligands) and to obtain the docking-based binding energies that are sufficiently
accurate to discriminate the preferred ligand stereochemistry, more accurate methods
for binding energy prediction as well as incorporating protein flexibility may be
required to improve the quality of the predicted binding energies. These could be done
by molecular dynamics simulations (MD) in the real aqueous environment.
Ref. code: 25605922040059HVU
30
References
1. Sekhon, B.S. (2013). Exploiting the power of stereochemistry in drugs: an
overview of racemic and enantiopure drugs. Journal of Modern Medicinal Chemistry,
1, 10–36.
2. Nguyen, L. A., He, H., & Pham-Huy, C. (2006). Chiral drugs: an overview.
International Journal of Biomedical Science: IJBS, 2(2), 85–100.
3. Maier, N. M., Franco, P., & Lindner, W. (2001). Separation of enantiomers:
needs, challenges, perspectives. Journal of Chromatography A, 906(1), 3-33.
4. McConathy, J., & Owens, M. J. (2003). Stereochemistry in drug action. Primary
Care Companion to The Journal of Clinical Psychiatry, 5(2), 70–73.
5. Kulatee, S., Toochinda, P., Suksangpanomrung, A., & Lawtrakul, L. (2017).
Theoretical investigation of the enantioselective complexations between pfDHFR and
cycloguanil derivatives. Scientia Pharmaceutica, 85(4), 37.
6. Chankvetadze, B., Lindner, W., & Scriba, G. K. E. (2004). Enantiomer
separations in capillary electrophoresis in the case of equal binding constants of the
enantiomers with a chiral selector: commentary on the feasibility of the concept.
Analytical Chemistry, 76(14), 4256-4260.
7. Keurentjes, J. T. F., Nabuurs, L. J. W. M., & Vegter, E. A. (1996). Liquid
membrane technology for the separation of racemic mixtures. Journal of Membrane
Science, 113(2), 351-360.
8. Buser, H. R., & Mueller, M. D. (1992). Enantiomer separation of chlordane
components and metabolites using chiral high-resolution gas chromatography and
detection by mass spectrometric techniques. Analytical Chemistry, 64(24), 3168-3175.
9. Collet, A., Brienne, M. J., & Jacques, J. (1980). Optical resolution by direct
crystallization of enantiomer mixtures. Chemical Reviews, 80(3), 215-230.
10. Pirkle, W. H., & Pochapsky, T. C. (1989). Considerations of chiral recognition
relevant to the liquid chromatography separation of enantiomers. Chemical Reviews,
89(2), 347-362.
Ref. code: 25605922040059HVU
31
11. Sansom, C. E., & Smith, C. A. (1998). Computer applications in the
biomolecular sciences. Part 1: Molecular modelling. Biochemical Education,
GaussView, version 5; Semichem Inc.: Shawnee Mission, KS, USA.
13. Frisch, M.J., Trucks, G.W., Schlegel, H.B., Scuseria, G.E., Robb, M.A.,
Cheeseman, J.R., Scalmani, G., Barone, V., Petersson, G.A., Nakatsuji, H., & et al.
(2016). Gaussian 09; Revision A.02; Gaussian, Inc.: Wallingford, CT, USA.
14. Accelrys (2016). Discovery Studio Modeling Environment Release 4.0;
Accelrys Inc.: San Diego, CA, USA.
15. Morris, G.M., Huey, R., Lindstrom, W., Sanner, M.F., Belew, R.K., Goodsell,
D.S., & Olson, A.J (2009). Autodock4 and AutoDockTools4: Automated docking with
selective receptor flexibility, Journal of Computational Chemistry. 16, 2785–2791.
16. Kurkov, S. V., & Loftsson, T. (2013). Cyclodextrins. International Journal of
Pharmaceutics, 453(1), 167-180.
17. Wren S., & et al. (2001) The Use of Cyclodextrins as Chiral Selectors, An
International Journal for Rapid Communication in Chromatography, Electrophoresis,
and Associated Techniques, 6, 59-77.
18. Gübitz, G., & Schmid, M.G (1997). Chiral separation principles in capillary
electrophoresis, Journal of Chromatography A, 792(1), 179–225.
19. Tait, R. J., Thompson, D. O., Stella, V. J., & Stobaugh, J. F. (1994). Sulfobutyl
ether beta-cyclodextrin as a chiral discriminator for use with capillary electrophoresis.
Analytical Chemistry, 66(22), 4013-4018.
20. Maruszak, W., Trojanowicz, M., Margasinska, M., & Engelhardt, H. (2001).
Application of carboxymethyl-beta-cyclodextrin as a chiral selector in capillary
electrophoresis for enantiomer separation of selected neurotransmitters. Journal of
Chromatography A, 926(2), 327-336.
21. Xiao, Y., & Chung, T.-S. (2007). Functionalization of cellulose dialysis
membranes for chiral separation using beta-cyclodextrin immobilization. Journal of
Membrane Science, 290(1), 78-85.
22. Liu, Y., Yu, H., Zhang, H., Yu, L., & Xu, W. (2017). Use of various beta-
cyclodextrin derivatives as chiral selectors for the enantiomeric separation of
higenamine by capillary electrophoresis. Microchemical Journal, 134, 289-294.
Ref. code: 25605922040059HVU
32
23. Ceborska, M., Szwed, K., & Suwinska, K. (2013). Beta-Cyclodextrin as the
suitable molecular container for isopulegol enantiomers. Carbohydrate Polymers,
97(2), 546-550.
24. Ghatee, M. H., & Sedghamiz, T. (2014). Chiral recognition of Propranolol
enantiomers by beta-Cyclodextrin: Quantum chemical calculation and molecular
dynamics simulation studies. Chemical Physics, 445, 5-13.
25. Alvira, E. (2015). Theoretical study of the separation of valine enantiomers by
beta-cyclodextrin with different solvents: a molecular mechanics and dynamics
simulation. Tetrahedron: Asymmetry, 26(15), 853-860.
26. Szabó, Z.-I., Tóth, G., Völgyi, G., Komjáti, B., Hancu, G., Szente, L., & et al.
(2016). Chiral separation of asenapine enantiomers by capillary electrophoresis and
characterization of cyclodextrin complexes by NMR spectroscopy, mass spectrometry
and molecular modeling. Journal of Pharmaceutical and Biomedical Analysis, 117,
398-404.
27. Alvira, E. (2017). Influence of solvent polarity on the separation of leucine
enantiomers by beta-cyclodextrin: a molecular mechanics and dynamics simulation.
Tetrahedron: Asymmetry, 28(10), 1414-1422.
28. Xuanping, T., Qin, L., Yizhong, S., Huan, W., Yanmei, Z., & Jidong, Y. (2015).
Chiral recognition of tyrosine enantiomers based on decreased resonance scattering
signals with silver nanoparticles as optical sensor. Chirality, 27(3), 194-198.
29. Mahalapbutr, P., Nutho, B., Wolschann, P., Chavasiri, W., Kungwan, N., &
Rungrotmongkol, T. (2018). Molecular insights into inclusion complexes of
mansonone E and H enantiomers with various beta-cyclodextrins. Journal of Molecular
Graphics and Modelling, 79, 72-80.
30. W., A. D., Xiande, W., & Nuran, E. (1998). Enantiomeric composition of
nicotine in smokeless tobacco, medicinal products, and commercial reagents. Chirality,
10(7), 587-591.
31. Ernst, M., Matochik, J. A., Heishman, S. J., Van Horn, J. D., Jons, P. H.,
Henningfield, J. E., & London, E. D. (2001). Effect of nicotine on brain activation
during performance of a working memory task. Proceedings of the National Academy
of Sciences of the United States of America, 98(8), 4728–4733.
Ref. code: 25605922040059HVU
33
32. Schnell, J. R., Dyson, H. J., & Wright, P. E. (2004). Structure, dynamics, and
catalytic function of Dihydrofolate Reductase. Annual Review of Biophysics and
Biomolecular Structure, 33(1), 119-140.
33. RCSB PDB-3UM8: Wild-Type Plasmodium falciparum DHFR-TS Complexed
with Cycloguanil and NADPH Structure Summary Page. Available online:
https://www.rcsb.org/pdb/explore.do?structureId=3UM8 (accessed on 30 May 2017).
34. RCSB PDB-3UM6: Double Mutant (A16V + S108T) Plasmodium falciparum
DHFR-TS (T9/94) Complexed with Cycloguanil, NADPH and dUMP Structure
Summary Page. Available online: https://www.rcsb.org/pdb/explore.do?structureId=
3UM6 (accessed on 30 May 2017).
35. Yuvaniyama, J., Chitnumsub, P., Kamchonwongpaisan, S., Vanichtanankul, J.,
Sirawaraporn, W., Taylor, P., & et al. (2003). Insights into antifolate resistance from
malarial DHFR-TS structures. Nature Structural Biology, 10, 357.
36. Yuthavong, Y., Vilaivan, T., Chareonsethakul, N., Kamchonwongpaisan, S.,
Sirawaraporn, W., Quarrell, R., & Lowe, G. (2000). Development of a lead inhibitor
for the A16V+S108T mutant of Dihydrofolate Reductase from the cycloguanil resis-
tant strain (T9/94) of Plasmodium falciparum†. Journal of Medicinal Chemistry,
43(14), 2738-2744.
37. Vanichtanankul, J., Taweechai, S., Uttamapinant, C., Chitnumsub, P., Vilaivan,
T., Yuthavong, Y., & Kamchonwongpaisan, S. (2012). Combined Spatial Limitation
around Residues 16 and 108 of Plasmodium falciparum Dihydrofolate Reductase
Explains Resistance to Cycloguanil. Antimicrobial Agents and Chemotherapy, 56(7),
3928–3935.
38. Kamchonwongpaisan, S., Quarrell, R., Charoensetakul, N., Ponsinet, R.,
Vilaivan, T., Vanichtanankul, J., & et al. (2004). Inhibitors of multiple mutants of
Plasmodium falciparum Dihydrofolate Reductase and their antimalarial activities.
Journal of Medicinal Chemistry, 47(3), 673-680.
39. CSD Entry-BCDEXD03: Beta-Cyclodextrin hydrate clathrate. Available
online:https://www.ccdc.cam.ac.uk/structures/search?sid=iucr&id=doi:10.1021%2Fja
00091a014 (accessed on 22 November, 2017).
Ref. code: 25605922040059HVU
34
40. Morris, G. M., Goodsell, D. S., Halliday, R. S., Huey, R., Hart, W. E., Belew,
R. K., & Olson, A. J. (1998). Automated docking using a Lamarckian genetic algorithm
and an empirical binding free energy function. Journal of Computational Chemistry,
19(14), 1639-1662.
41. Grabowski, S.J. (2006). Theoretical studies of strong hydrogen bonds. Annual
Reports Section “C” (Physical Chemistry), 102, 131–165.
42. Yuthavong, Y. (2002). Basis for antifolate action and resistance in malaria.
Microbes and Infection, 4(2), 175-182.
Ref. code: 25605922040059HVU
35
Appendices
Ref. code: 25605922040059HVU
36
Appendix A
List of abbreviations
Abbreviation Meaning
ACD
BCD
BE
CCDC
CDs
CE
Cyc
DHFR
GC
Alpha-cyclodextrin
Beta-cyclodextrin
Binding energy
Cambridge Crystallographic Data Center
Cyclodextrins
Capillary electrophoresis
Cycloguanil
Dihydrofolate reductase
Gas chromatography
GCD
HPLC
Gamma-cyclodextrin
High-performance liquid chromatography
Membrane Membrane technology
MM Molecular modeling
NMR
PDB
pfDHFR
Sensors
Nuclear magnetic resonance spectroscopy
Protein Data Bank
Plasmodium falciparum Dihydrofolate Reductase
Enantioselectivity sensing
TLC Thin-layered chromatography
TS Thymidylate synthase
Ref. code: 25605922040059HVU
Top Related