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Ethnobotanical Leaflets 12: 181-190.
2008. 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 Issued 2 April 2008 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).
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 ( 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
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Stuart.
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Grieve. A Modern Herbal. Penguin 1984
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Duke.
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Reference Publications, Inc. 1985 ISBN 0-917256-20-4. 8.
Bown.
D. Encyclopaedia
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Pandey,
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