for M.pharm Pharmaceutics 2nd sem unit 02 Active transport- P-gp, BCRp, hPEPt 1, OACT, OCT, Nucleoside transporter.

1. 1
A PRESENTATION ON
COMPUTATIONAL MODELING OF DRUG
DISPOSITION: ACTIVE TRANSPORTERS
SUBMITTED BY GUIDED BY:
SAKSHI SONI Dr. DINESH K. MISHRA
M.PHARM 2ND SEM PROFESSOR
(PHARMACEUTICS) (PHARMACEUTICS)
Department of Pharmacy, Guru Ghasidas Vishwavidyalaya Bilaspur C.G. 495001

2. TABLE OF CONTENTS:
Introduction
Active Transport
1. P-Glycoprotein (P-gp)
2. Breast Cancer Resistance Protein (BCRP)
3. Nucleoside Transporter
4. Human peptide Transporter (hPEPT1)
5. Apical Sodium dependent Bile Transporter (ASBT)
6. Organic Cation Transporter (OCT)
7. Organic Anion Transporter Polypeptides (OATP)
8. Blood Brain Barrier (BBB)- Choline Transporter
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3. INTRODUCTION:
• Computational Modeling are the computer tools used for solving the problems
by step-wise, repeated and iterative methods which could be tedious or
unsolvable by manual calculations.
• OBJECTIVES OF COMPUTATIONAL MODELS:
a. The drug Formulation requires the Optimization of bioprocesses (ADMET).
b. The clinical trail procedures are very expensive and also include the
expenditure on the clinical failures. CADD is a useful tool for evaluating
ADME-Tox processes.
c. The relationship between the structure and drug utilization pathways (in the
body) can be established.
d. The electronic effects of chemical structure are implicated for predicting the
ADMET profiles.
e. The site of metabolism and possible metabolites can be predicted.
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4. OBJECTIVES OF COMPUTATIONAL MODELING:
4
OBJECTIVES
OF
COMPUTATION
AL MODELING
Optimization
of ADMET of
drug
formulation.
Establishme
nt of drug
utilization
pathways in
the body
Determines
electronic
effects of
chemical
structure.
Determines
site of
metabolism
and types
of
metabolite.
Gives more
accurate
results.
Less time
consuming

5. DRUG DISPOSITION:
Drug disposition means the change in the position/movement of drug molecules
inside the body after administration into the system irrespective with the route of
administration.
Process: After entering the body
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Drug molecules and
internal body systems
Comes under various
p’cokinetics interactions
Observation of suitable
biological activity.
Physicochemical nature
of chemical substance &
physiological nature of
system makes this
system competitive.
In this view, p’cokinetic &
toxic properties of the
molecules regulates the
destination of the
molecules.

6. Process involved in drug disposition:
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7. Computational methods for drug distribution
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8. ACTIVE TRANSPORT (UP-HILL TRANSPORT):
1. Transportation of drug molecules against the concentration gradient and natural
thermodynamic fluidity.
2. An energy regulated step, so some suitable inorganic ions, enzymes, proteins acts
as support system.
3. Adenosine triphosphate (ATP) dependent binding cassette and solute carrier
system were the main types of active transporter system.
4. It is used for enhanced permeation of membrane whereas other system was
depend upon energy dependent sodium potassium ion gated proton pump system.
5. P-glycoprotein, BCRp (breast cancer resistance protein), nucleoside transporters,
hPEPt1 (human peptide transporter-1), ASBt (apical sodium-dependent bile acid
transporter), OCt (organic cation transporter), OATP (organic-anion-transporting
polypeptides), BBb-Choline (blood brain barrier choline system) were some
important carrier systems related to biomolecules.
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9. 9
COMPUTATIONAL
MODELING FOR
ACTIVE TRANSPORT
BBB
choline
transporter
(influx)
Multidrug
resistance
transporters (efflux)
e.g. P-gp, BCRp,
MRP
Organic ion
transporters
(efflux)
e.g. OAT, OCT,
OATP, OCTN
Monocarboxylic
acid transporters
(efflux)
e.g. MCT-1, MCT-2

10. TRANSPORTER SYSTEM FOR DISTRIBUTION:
Transporters are available in the luminal and basolateral membranes of the
enterocytes,
hepatocytes,
 renal tubular epithelium cells,
blood brain barrier (BBB),
blood placenta barrier (BPB).
These transporters either inhibit or induce the metabolism action of CYP450 enzyme. A
few transporters are reported in the following sections:
• P-gp, BCRp, OAT, OATP, BCT, MCT etc.
•
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11. 1. P-glycoprotein (P-gp) (Efflux):
• It mediates the efflux of endogenous compounds and drugs out of the cells through
ATP-dependent mechanism (expel of drugs from the cells) . It is expressed in the
a. Blood brain barrier (BBB)
b. Luminal membrane of the small intestine
c. Apical membrane of excretory cells, hepatocytes and renal proximal tubules.
d. Gastrointestinal tract, blood, brain, testes and placenta.
P-gp created a barrier in this format.
E.g Bioavailability of drugs was also affected by P-gp (inducer or inhibitor) as
rifampicin (P-gp inducer) minimized bioavailability whereas verapamil (P-gp
inhibitor) increase bioavailability of related drugs.
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12. • The expression of P-gp increases from Proximal to distal regions of the small
intestine.
• Substrates: These do not contribute to the distribution of drugs. E.g.
Anthracyclines, alkaloids, peptides, local anesthetics, immunosuppressants, HIV
protease inhibitors.
• Inhibitors: These inhibit the transporter system such that drug distribution can be
enhanced. E.g. Calcium channel blockers, Immunosuppressants, and grape fruit
juice.
• Several P-gp models were developed and found adequate for the screening the
molecular databases:
a. Robust SAR methods
b. Pharmacophore model
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13. c. SOM model
d. Homology model for P-gp
APPLICATIONS:
1. Solve the efflux related bioavailability problems.
2. P-gp novel inhibitors are co-administered which would optimize the PK profile.
3. It reduces the absorption of anti-cancer drugs, through drug itself is having anti-
cancer activity. This is also responsible for multidrug resistance to cancer
chemotherapy. Same is the case with HIV protease inhibitors.
4. The intestine P-gp may contribute to the systemic clearance of intravenously
administered drugs by active secretion into the intestine lumen.
5. P-gp enhances the excretion (renal and hepatic) and reduces the absorption (de-
toxification)
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14. • The in-silico modeling of P-gp are given in the computational methods:
A. Monocarboxylate transporter (MCT): The bidirectional movement of
monocarboxylic acids across the plasma membrane is catalysed by a family of
protein-lined monocarboxylate transporters (MCTs). 4 MCTs (MCTs 1-4) are
well characterised.
B. Blood brain barrier (BCT): these are meant for transporting the nutrients and
choline (a cation) across the BBB. Choline like compound (chemical structural
similarity) can easily penetrate through BBB. Binding studies are developed from
theoretical and empirical methodologies.
2. BCRp (Breast cancer resistance protein):
• It is composed of 655 amino acids and widely distributed in-
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15. • stem cells,
• cancerous cells,
• liver,
• intestine
• placenta.
BCRp was worked as high gradient transporting system with greater
specification for molecules with- negative or positive charge, organic anion
and conjugated sulfates.
E.g. Fumitremorgin-C was the chemical substance which can reversed the
drug resistance due to BRCp activity.
Application: This system effectively worked for
a. fetus protection,
b. biliary elimination, and
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16. 16
c. decrease in reabsorption through kidney
d. as well as protection of stem cells
e. In this fashion, anticancer drugs, toxins, endogenous substances were behave as
substrate whereas multidrug resistant modulators were the inhibitors of this
transporting system. In this text, Fumitremorgin-C was the chemical substance
which can reversed the drug resistance due to BRCp activity.
• Models for BCRp:
A. BCRP pharmacophore model: for nelfanivir, and nicardipine. The model is used
in the search against clinical drugs (500 drugs). The search identified 37 hits,
which included digoxin, indinavir, ritonavir, nicardipine, ( BCRP inhibitors).
B. BCRp 3D-QSAR model: This model was generated by analyzing the activity of
25 flavonoid analogues.

17. 3. Nucleoside transporters:
Responsible for the transportation of nucleosides (deoxyribo/ribo nucleic acid
synthesis starting material)
Also regulate the energy dependent neuronal modulation especially transportation
of blood to retina.
This system was classified into sodium ion dependent and independent
transporting systems.
 These drugs were mainly prodrug in nature, so travelling from administration to
destination, these transporter systems showed a positive impact.
 Nucleoside transporter system was further divided into concentrative:
A. Concentrative nucleoside transporters (CNT-1, CNT-2, CNT-3): high affinity and
selectivity CNTs are located on epithelia of intestine, liver, kidney, and brain.
B. Equilibrative nucleoside transporters (ENT-1, ENT-2): broad affinity, low
selective ENTs are ubiquitously located.
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18. • Applications: Anti-cancer drugs – cladribine, and anti-viral drug- zalcitabine are
nucleoside analogues and hence can be transported.
4. hPEPt1 (human peptide transporter-1):
 It belongs to peptide transporter,
It is a proton coupled, low affinity, active oligopeptide transport system.
It was mainly used for transport of oligopeptide with the exchange of sodium and
hydrogen ions, associated with transportation of antibiotics, antiviral and
antihypertensive agents as well as movement of nitrogen throughout the body.
This system mainly located in- apical membrane of small intestine. In this context oral
hypoglycemic agents (sulfonylureas, biguanides and others) inhibited the transporting
system.
 This pharmacophore model is applied to screen the CMC database with over
8000 drugs-like molecules
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19. 19
• A pharmacophore model is developed based on the high affinity substrates (Gly-
sar, bestatin and enalapril).
• Application:
a. This transporter facilitates the oral availability peptidomimetics, e.g. beta- lactum
antibiotics and valcyclovir. The weak peptide bond feature of the beta-lactum
antibiotics ionizes at the intestinal pH. This limits their intestinal absorption.
These beta-lactum antibiotics have PEPT carrier mediated transport
characteristics and their absorption is facilitated by PETP1 (Proton dependent
oligopeptide transporters).
b. The fragments of the milk proteins ( free amino acids and small peptides) in the
stomach and duodenum compete for the PETP-1 substrates. The rate of
oseltamivir absorption decreases with milk.

20. 4. ASBt (apical sodium-dependent bile acid transporter):
This carrier system observed with presence of 348 amino acids with 38 kilo dalton
of molecular weight.
 The system comprised two glycosylation sites at N10 and N328 OCt (organic
cation transporter).
 ASBt was responsible for transportation and reabsorption of bile acids from gut
lumen as well as active against liver disease, hyperglycemia and
hyperlipoproteinemia.
 The ASBt is expressed on the apical membrane of intestinal epithelia and
cholangiocytes.
 ASBt assist in the absorption of bile acids and a pivotal role in cholesterol
metabolism.
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21. 21
The pharmacophore model is developed based on the training set of 17 chemically
active diverse inhibitors of ASBt.
5. OAtp (organic-anion-transporting polypeptides):
 These are responsible for actively transporting the anions present in the plasma
and thus promoting drug excretion.
 These transporters also transport organic cation drugs.
 These transporters mediate sodium dependent transport of a diverse range of
amphiphilic organic compounds with relatively high molecular weight. It
include- bile acids, steroid conjugates, thyroid hormones, anionic peptides and
numerous drugs.
 This family mainly located in
• liver,
• intestine,
• kidney,
• brain and placenta.

22. Organic cation transporters (OCT) (influx):
This includes drugs and metabolites, carrying a net positive charge at
physiological pH.
It facilitates the uptake of many cationic drugs across the barrier membranes
from
a. kidney,
b. liver and
c. intestine epithelium.
It transport relatively hydrophilic and low molecular mass organic cations.
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23. CONCLUSION:
This chapter mainly focused on the journey of a drug molecule inside the body. In
this intriguing viewing process, various pathophysiological aspects help us to know
or visualize the path of a drug molecule in achieving the ultimate goal. When a drug
molecule enters our system, our physiological system treat the substance as foreign
material, so it always try to expel out the substance and in this expelling process
both molecule and body system comes under an iterative process and finally some
positive or negative effect is observed by the system. In this fate determining
process, physicochemical nature of the chemical substance and physiological
environment (composition) of system makes this movement more interesting. In this
context, pharmacokinetic features along with toxicity profile of the drug substance
regulate the ultimate fate of the molecule. Nowadays various computational
processes are considered such as in silico assessment of drug molecule after
absorption through biological membrane, distribute throughout the system based on
the percent ionization or partition coefficient factors followed by biologically
transformed into another entity in presence of microsomal enzymes and finally
excrete out from system using various cellular transport systems.
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24. So we focused on detailed computational studies related to Computer aided drug
development on Active transporters on drug disposition Transportation of drug
molecules against the concentration gradient and natural thermodynamic fluidity.
This is an energy regulated step, so some suitable inorganic ions, enzymes, proteins
acts as support system. Adenosine triphosphate (ATP) dependent binding cassette
and solute carrier system were the main types of active transporter system. The
energy dependent system was used energy for enhanced permeation of membrane
whereas other system was depend upon energy dependent sodium potassium ion
gated proton pump system. P-glycoprotein, BCRp (breast cancer resistance protein),
nucleoside transporters, hPEPt1 (human peptide transporter-1), ASBt (apical
sodium-dependent bile acid transporter), OCt (organic cation transporter), OATP
(organic-anion-transporting polypeptides), BBb-Choline (blood brain barrier choline
system) were some important carrier systems related to biomolecules.
24

25. REFERENCES:
1. Saha, S. U. P. R. I. Y. O., & Pal, D. I. L. I. P. K. U. M. A. R. (2021). Computational
approaches related to drug disposition. Int J Pharm Pharm Sci, 13(7), 19-27.
2. Subrahmanyam CVS, Kumar Ananda Durai T., Swathi N, Thimmasetty J. a textbook of
principles and practice of computer aided drug development published by M.K. jain for
Vallabh prakashan, New delhi 1st edition 2020,178-198.
3. Saha S, Banerjee A, Rudra A. 2D QSAR approach to develop newer generation
molecules active aganist ERBB2 receptor kinase as potential anticancer agent. Int J
Pharm Chem 2015;5:134-48.
4. Saha S, Constance V, Luv Kush, Percha V. Exploring descriptor combination by
chemometric approach to develop newer molecules active through corticosteroid binding
globulin receptor. J Appl Pharm 2015;7:223-36.
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