Biological Activity Prediction of an Ethno
Medicinal Plant Cinnamomum camphora
Through Bio-informatics
D. Abiya Chelliah
PG & Research Department of Plant Biology and
Biotechnology
St.Xavier’s College (Autonomous), Tirunelveli – 627 002, Tamilnadu, India
E-mail: abiya@scientist.com
Tel:
9976106111
Received
Introduction
The camphor tree (Cinnamomum camphora) is a
broad-leaved, evergreen tree. The alternate leaves are shiny dark green above
and lighter green below and have wavy margins with three distinct yellow veins.
A distinctive odor of camphor is emitted when the leaves are crushed. The
flowers are inconspicuous and the fruit is a black pea-sized berry. The camphor
tree grows in full sun or partial shade and it is drought tolerant but not
particularly cold tolerant. It invades hardwood forests, upland pine and scrub
woods, fence rows and urban green spaces.
The traditional oils are obtained from the wood and
bark of this plant (Stahl, 1957; Pandey et al.,
1997). The oil, with a high content of camphor, has an important antifungal
activity ( Sattar et al.,
1991). C. camphora has several chemical
varieties which have different essential oil compositions (Moellenbeck
et al., 1997). Two varieties have been exploited commercially, C. camphora Nees & Eberm., the most valuable for the presence of camphor, and
(C. camphora Nees
& Eberm var. linaloolifera)
for its high content of linalool. These varieties are morphologically similar,
but they show different essential oil compositions and for this reason are
considered physiological varieties (Guenther, 1950). The oils obtained from the
leaves by steam distillation have economic importance as their main components
are camphor and linalool.
The pahrmacognosy of the phytols in the C. camphora are given below:
Cinnamon
bark oil possesses the delicate aroma of
the spice and a sweet and pungent taste. Its major constituent is cinnamaldehyde, but other, minor components impart the
characteristic odour and flavour.
It is employed mainly in the flavouring industry
where it is used in meat and fast food seasonings, sauces and pickles, baked
goods, confectionery, cola-type drinks, tobacco flavours
and in dental and pharmaceutical preparations. Perfumery applications are far
fewer than in flavours because the oil has some
skin-sensitizing properties, but it has limited use in some perfumes.
Cinnamon
leaf oil has a warm, spicy, but rather
harsh odour, lacking the rich body of the bark oil.
Its major constituent is eugenol rather than cinnamaldehyde. It is used as a flavouring
agent for seasonings and savory snacks. As a cheap fragrance, it is added to
soaps and insecticides. The oil's high eugenol
content also makes it valuable as a source of this chemical for subsequent
conversion into iso-eugenol, another flavouring agent.
Cassia
oil is distilled from a mixture of
leaves, twigs and fragments of bark. Cinnamaldehyde
is the major constituent and it is used mainly for flavouring
cola-type drinks, with smaller amounts used in bakery products, sauces,
confectionery and liqueurs. Like cinnamon bark oil, its use as a fragrance is
limited by its skin sensitizing properties. (FAO)
An FAO listing of the cinnamomum
species that yield the chemical isolates which are of therapeutic, medicinal
and economic importance is given below:
Cinnamomum species with actual or potential use as sources of chemical
isolates (FAO).
|
Species |
Major oil constituent |
|
C. camphora |
Camphor,
linalool, safrole and cineole |
|
C.camphora
var.linaloolifera |
Linalool |
|
C. sulphuratum |
Linalool |
|
C. petrophilum |
Safrole |
|
C. mollissimum |
Safrole |
|
C. mollissimum |
Benzyl
benzoate |
|
C. pubescens |
Eugenol |
|
C. tamala |
Cinnamaldehyde or eugenol |
Camphor
has a long history of herbal use. It has been used internally in the treatment
of hysteria, but in modern day herbalism it is mainly
used as an essential oil and internal use is not advised [1]. The wood and
leaves are analgesic, antispasmodic, odontalgic, rubefacient, and are also used as a stimulant. An infusion
is used as an inhalant in the treatment of colds and diseases of the lungs [2,
3, 4]. The essential oil, which can
be obtained by distillation of the chipped branches, trunk and wood of the
tree, or from the leaves and twigs, is the most suitable form of usage.
Wood 24 - 40 years old is normally used [5]. The essential oil is anthelmintic, antirheumatic,
antispasmodic, cardiotonic, carminative, diaphoretic,
sedative and tonic [6, 7, 8, 9]. It is used externally
in liniments for treating joint and muscle pains, balms for chilblains, chapped
lips, cold sores, skin diseases, etc., and as an inhalant for bronchial
congestion [8]. Some caution is advised, excessive use causes vomiting,
palpitations, convulsions and death [8]. It is possible that the oil can be
absorbed through the skin, causing systemic poisoning [8]. The essential oil is
used in aromatherapy. Its keyword is 'Piercing' [9]. It is used in the
treatment of digestive complaints and depression [8].
Sassafras oils from Cinnamomum camphora and
Ocotea pretiosa,
respectively, are both sources of safrole, which is
used to manufacture heliotropin, a valuable flavour and fragrance compound. C. camphora
is also a source of natural camphor (FAO).
Rosewood oil was once an important
source of linalool, an aroma chemical in its own right but also a precursor for
other fragrance compounds. Although cheaper sources of linalool are now
utilized (still of plant origin), Cinnamomum spp. are also proving its
best to add it to the content (FAO).
Having established that there is a
market for a particular chemical substance and an opportunity for new or
improved production, the action is necessary to put these ideas into practice
in the field of its activity prediction. Biological Activity Spectrum (BAS) of
a compound represents the complex of pharmacological effects, physiological
& biochemical mechanisms of action, specific toxicity (mutagenicity,
carcinogenicity, teratogenicity & embryotoxicity) which can be revealed in a compound's
interaction with the biological system. Biological Activity Spectrum describes
the intrinsic properties of the compound dependent on it's
structural particularities. It may be revealed in experiment under any
conditions (dosage, route of administration, biological object, age, sex,
etc.).
The objective of our work was to
screen the five major phytols of C. camphora which are very much of
medicinal importance. For our work, we have used computational techniques with
the internet source as a backend.
Materials
and Methods
The structures of the phytochemicals present in the C. camphora are (Camphor, linalool, safrole and cineole) are obtained from the pubchem compound repository. The structures are drawn using
the Chem skech package 11.0
belonging to the ACD Chem laboratory. The biological
activity spectrum was drawn using the acticvity
prediction
Multilevel
Neighborhoods of Atoms (MNA) structure descriptors of a molecule are generated
on the basis of connection between (C) and of atoms types (A) presented in the
compound. Connection table contains data on the valent
bonds in a molecule. Various bond types are not specified (topological
approximation). All hydrogens based on valencies and partial charges of atoms are taken into
account. The structure of a molecule is represented as the set of multilevel
neighborhoods of atom's descriptors calculated iteratively. Zero-level's
descriptor is presented by the type of atom and special dash label if the atom
is not included into the cycle. This process is extended from the 1st
level to the 2nd, 3rd, etc. neighborhoods of the atom.
Biological activity is the result of a chemical compound's
interaction with a biological entity. In clinical study, a biological entity is
represented by a human organism. In preclinical testing, it is the experimental
animals (in vivo) and experimental models (in vitro). Biological activity
depends on the peculiarities of a compound (structure and physico-chemical
properties), biological entity (species, sex, age, etc.), mode of treatment
(dose, route, etc.).
Any biologically active compound reveals a wide spectrum of
different effects. Some of them are useful in the treatment of definite
diseases, but the others cause various side and toxic effects. Total complex of
activities caused by the compound in biological entities is called the
"biological activity spectrum of the substance".
The algorithm used for the
activity prediction is as follows:
Algorithm Prediction: (The
source is obtained from the PASS description through its server in the training
set).
The compound under prediction in
structural descriptors are generated. For each activity the following
values are calculated:
uj = a i ArcSin{ri(2pij-1)},
u0j = a i ArcSin{ri(2pj-1)}
where,
n is the total amount of
compounds in the training set;
ni is the
amount of compounds, that have the descriptor i;
nj is the
amount of compounds, that reveal the activity j;
nij is the
amount of compounds, that have both the descriptor i
and the activity j;
pj = a i nij/a i
ni is the estimate of a priori probability of
activity j;
pij = nij/ni is the estimate of the conditional probability of
the activity j for the
descriptor i;
m is the number of
descriptors for the compound under prediction;
ri = ni/(ni + 7.7/m) is the regulating
factor;
Prj is the initial estimate
of the probability of the activity j for the compound
under prediction;
CPj is the cutting point;
E1j(CPj) is the estimate of 1st
kind error probability;
E2j(CPj) is the estimate of 2nd
kind error probability;
The 1st
kind error is observed when the compound under prediction actually is
active but Prj
< CPj;
The 2nd
kind error is observed when the compound under prediction is
considered as
inactive but Prj > CPj;
LOO is the
leave-one-out procedure:
for each
compound in the training set the values n, ni, nj, nij are changed for n-1,
ni-1, and nj-1, nij-1 when
it has activity j, and the estimates Prj are
calculated
based on the other compounds
in the training set.
MEP is the
maximal error of prediction.
sj = Sin(uj/m), s0j = Sin(u0j/m)
Prj = (1+(sj-s0j)/(1-sjs0j))/2
Validation
criterion:
For each compound in the training set the LOO estimates of Prj are calculated.For each
activity the estimates of E1j(CPj) and E2j(CPj) are calculated. The cutting
points CPj* which provides equality
E1j(CPj*) = E2j(CPj*)
are
calculated. The maximal error of prediction MEP is:
MEPj = E1j(CPj*) = E2j(CPj*)
Results
Camphor
17
Possible activities at Pa > 70%
Pa Pi Activity
0,841
0,025 Antidiabetic
0,841
0,025 Phosphatase inhibitor
0,841
0,025 Antineoplastic
0,841
0,025 Phosphatase inhibitor
0,728
0,008 Neuroprotector
0,728
0,008 Nerve growth factor agonist
0,728
0,008 Antiparkinsonian
0,728
0,008 Nerve growth factor agonist
0,977
0,002 Analeptic
0,762
0,028 Cardiovascular analeptic
0,942
0,002 Respiratory analeptic
0,753
0,007 Cognition disorders treatment
0,753
0,007 Alzheimer's disease treatment
0,753
0,007 Neurotrophic factor enhancer
0,728
0,008 Nerve growth factor agonist
0,753
0,007 Neurotrophic factor enhancer
0,728
0,008 Nerve growth factor agonist
0,902
0,007 Dermatologic
0,739
0,008 Antiacne
0,739
0,008 Antipruritic
0,739
0,008 Antieczematic atopic
0,739
0,008 Antipruritic
0,902
0,012 Antiseborrheic
0,728
0,008 Psychotropic
0,728
0,008 Nootropic
0,728
0,008 Nerve growth factor agonist
0,739
0,008 Antipruritic, non-allergic
0,739
0,008 Antipruritic
0,728
0,008 Antiischemic, cerebral
0,728
0,008 Nerve growth factor agonist
0,728
0,008 Amyotrophic lateral sclerosis treatment
0,728
0,008 Nerve growth factor agonist
0,739
0,008 Allergic conjunctivitis treatment
0,739
0,008 Antipruritic
0,768
0,006 Tocolytic
Linalool
16
Possible activities at Pa > 70%
Pa Pi Activity
0,776
0,018 Hypolipemic
0,776
0,018 Lipid metabolism regulator
0,763
0,022 Cholesterol synthesis inhibitor
0,763
0,022 Anticholelithogenic
0,763
0,022 Cholesterol synthesis inhibitor
0,763
0,022 Atherosclerosis treatment
0,763
0,022 Cholesterol synthesis inhibitor
0,969
0,004 Antiulcerative
0,969
0,004 Mucomembranous protector
0,825
0,006 Skin irritations, moderate
0,714
0,008 Eye irritation, weak
Safrole
18
Possible activities at Pa > 70%
Pa Pi Activity:
0,951
0,006 Antiviral
0,951
0,006 Antiviral (HIV)
0,951
0,006 Membrane integrity agonist
0,951
0,006 Membrane integrity agonist
0,951
0,006 Antipruritic
0,951
0,006 Membrane integrity agonist
0,951
0,005 Antiinflammatory
0,951
0,006 Membrane integrity agonist
0,918
0,005 Integrin antagonist
0,918
0,005 Antineoplastic
0,814
0,013 Antineoplastic (brain cancer)
0,918
0,005 Integrin antagonist
0,869
0,004 Antiparkinsonian
0,869
0,004 Neurotransmitter uptake inhibitor
0,765
0,007 Cognition disorders treatment
0,765
0,007 Alzheimer's disease treatment
0,765
0,007 Neurotrophic factor enhancer
0,765
0,007 Neurotrophic factor enhancer
0,951
0,006 Dermatologic
0,951
0,006 Antieczematic
0,951
0,006 Membrane integrity agonist
0,951
0,006 Antiseborrheic
0,951
0,006 Membrane integrity agonist
0,951
0,004 Psychotropic
0,781
0,008 Anxiolytic
0,781
0,008 GABA A receptor antagonist
0,781
0,008 Antidepressant
0,781
0,008 GABA A receptor antagonist
0,951
0,004 Antiepileptic
0,951
0,006 Membrane integrity agonist
0,869
0,004 Neurotransmitter uptake inhibitor
0,781
0,008 GABA A receptor antagonist
0,918
0,005 Antiasthmatic
0,918
0,005 Integrin antagonist
0,918
0,005 Inflammatory Bowel disease treatment
0,918
0,005 Integrin antagonist
0,918
0,005 Antiosteoporotic
0,918
0,005 Integrin antagonist
0,918
0,005 Antithrombotic
0,918
0,005 Integrin antagonist
0,779
0,021 Neuroprotector
0,768
0,015 Antiischemic
0,869
0,007 Pulmonary hypertension treatment
0,707
0,018 Antiischemic, cerebral
Cineole
12
Possible activities at Pa > 70%
Pa Pi Activity
0,758
0,006 Antitoxic
0,758
0,006 Hepatoprotectant
0,758
0,006 Liver fibrosis treatment
0,758
0,006 Hepatoprotectant
0,944
0,004 Hypolipemic
0,944
0,004 Cholesterol antagonist
0,715
0,082 Antidiabetic
0,715
0,082 Phosphatase inhibitor
0,781
0,006 Cardiotonic
0,781
0,006 Heart failure treatment
0,781
0,006 Adenylate cyclase
stimulant
0,781
0,006 Adenylate cyclase
stimulant
0,742
0,008 Autoimmune disorders treatment
0,742
0,008 Multiple sclerosis treatment
0,715
0,082 Antineoplastic
0,715
0,082 Phosphatase inhibitor
0,781
0,006 Ophthalmic drug
0,781
0,006 Antiglaucomic
0,781
0,006 Adenylate cyclase
stimulant
0,944
0,004 Atherosclerosis treatment
0,944
0,004 Cholesterol antagonist
0,721
0,009 Cognition disorders treatment
0,721
0,009 Alzheimer's disease treatment
0,721
0,009 Neurotrophic factor enhancer
0,721
0,009 Neurotrophic factor enhancer
0,781
0,006 Myocardial ischemia treatment
0,781
0,006 Adenylate cyclase
stimulant
0,781
0,006 Antithrombotic
0,781
0,006 Adenylate cyclase
stimulant
0,877
0,004 Choleretic
0,715
0,007 Hepatic disorders treatment
0,807
0,006 Antidyskinetic
Discussion
PASS Inet predicts biological
activity spectrum on the basis of structural formula of the compound. The
compounds are considered equivalent in PASS if they have the same molecular
formulae and the same set of MNA descriptors. Since the MNA descriptors do not
represent the stereochemical peculiarities of a
molecule, the compounds, which have only stereochemical
differences in the structure, are formally considered equivalent. The
equivalent structures are excluded from the training set during the PASS Inet prediction. The result of prediction is presented as
the list of activities with appropriate Pa and Pi, sorted in descending order
of the difference (Pa-Pi)>0.
Pa and Pi are the estimates of
probability for the compound to be active and inactive respectively for each
type of activity from the biological activity spectrum. Their values vary from
0.000 to 1.000. It is reasonably that only those types of activities may be
revealed by the compound, which Pa > Pi and so they are put into the
biological activity spectrum.
If Pa > 0.7 the compound is
very likely to reveal this activity in experiments, but in this case the chance
of being the analogue of the known pharmaceutical agents for this compound is
also high.
If 0.5 < Pa < 0.7 the
compound is likely to reveal this activity in experiments, but this probability
is less, and the compound is not so similar to the known pharmaceutical agents.
If Pa < 0.5 the compound is
unlikely to reveal this activity in experiments, but if the presence of this
activity is confirmed in the experiment the compound might be a New Chemical
Entity.
Thus, in planning experiments and
choosing the activities on which the compound has to be tested, one should have
in mind the necessity of balancing between the novelty of pharmacological
action and the risk to obtain negative results in experimental testing.
Certainly, one will also take into account the particular interest in some
kinds of activity, experimental facilities, etc. We may use PASS for the prediction of the biological
activity spectrum for existing compounds and compounds, which are only planned
to synthesize.
References
1.
Chevallier. A. The
Encyclopedia of Medicinal Plants Dorling Kindersley.
2.
Uphof.
J. C. Th. Dictionary of
Economic Plants. Weinheim 1959.
3.
Schery.
R. W. Plants for
4.
Yeung.
Him-Che.
Handbook of Chinese Herbs and Formulas.
5.
Stuart.
M. (Editor) The Encyclopedia of Herbs and Herbalism Orbis Publishing.
6.
Grieve. A Modern Herbal. Penguin 1984
ISBN 0-14-046-440-9.
7.
Duke.
J. A. and Ayensu. E. S. Medicinal Plants of China
Reference Publications, Inc. 1985 ISBN 0-917256-20-4.
8.
Bown.
D. Encyclopaedia
of Herbs and their Uses. Dorling Kindersley,
9.
Chopra.
R. N., Nayar. S. L. and Chopra. I. C. Glossary of Indian Medicinal Plants
(Including the Supplement). Council of Scientific and Industrial Research,
10.
Westwood.
C. Aromatherapy - A
guide for home use. Amberwood Publishing Ltd
1993 ISBN 0-9517723-0-9.
11.
Stahl, E.. Chemical varieties of plants containing terpenoids. Essenze deriv. Agrumari 27,
208-220 (1957)
12.
Pandey,
A.K., Bora, H.R.,
13.
Sattar,
A., Gilani, A.M. and Saed,
M. A. Gas
chromatographic examination of the essential oil of Cinnamomum
camphora. Pak. J. Sci.
Ind. Res. 34, 135-136 (1991)
14.
Moellenbeck, S., Koening, T., Schreirer, P., Schwab, W., Rajaonarivony,
J. and Ranarivelo, L. Chemical composition and analyses of enantiomers of essential oils from Madagascar. Flav.Fragr.J. 12, 63-69 (1997)
15.
http://www.invasive.org/browse/subject.cfm?sub=3014
16.
http://www.fao.org/docrep/V5350E/V5350e03.htm
17.
http://195.178.207.233/PASS/Pe.html#3