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220 Chapter 9 Molecular docking and drug–receptor interactions
Chapter 10
ADMET analysis in CADD
ADMET properties can make or break a drug candidate, so integrating ADMET analysis early in
drug design is crucial for success in drug discovery. – Dr. A. N. Jain
10.1 Introduction
Absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis is a
pivotal component of CADD, playing a crucial role in the drug discovery and develop-
ment process [1]. This multidisciplinary approach combines computational methods
with experimental data to assess the pharmacokinetic and pharmacodynamic proper-
ties of potential drug candidates. ADMET analysisbeginswiththeassessmentofa
compound’s absorption, determining its ability to enter the bloodstream through vari-
ous routes such as oral ingestion or injection. Distribution focuses on how a drug
spreads throughout the body, affecting different tissues and organs [2, 3]. Metabolism
evaluates the compound’s susceptibility to enzymatic transformation, which can im-
pact its bioavailability and activity. Excretion assesses how efficiently the body elimi-
nates the drug, influencing its duration of a ction. Finally, toxicity analysis aims to
predict any adverse effects a compound may have on the body. CADD utilizes a range
of computational tools and databases to predict these ADMET properties, helping re-
searchers filter out potential drug candidates with undesirable characteristics early in
the drug development pipeline. This accelerates the discovery process, reduces costs,
and minimizes the likelihood of adverse effects in clinical trials. Overall, ADMET anal-
ysis in CADD is a crucial step in optimizing the safety and efficacy of new drug candi-
dates, ultimately benefiting patients and the pharmaceutical industry [4–6].
It is indispensable for any drug molecule that its sufficient concentration should
reach its site of action for executing the desired pharmacological action. In achieving
this, absorption, distribution, metabolism, and excretion (ADME) properties play a very
crucial role whenever a new drug molecule is designed for any target disease. This
study of the ADME properties of the drug molecules is often referred to as the pharma-
cokinetics of the drug molecule. The importance of studying the ADME properties can
be understood by the fact that approximately 40% of the drugs demonstrating good
pharmacological activity fail because of their poor ADME properties. This failure rate
can be reduced if the ADME properties of any new potential drug moiety are studied
and optimized simultaneously with its pharmacological profile. The overall representa-
tion of the journey of a drug molecule inside the body is given in Fig. 10.1. Therefore, to
design new drug molecules, one should have a clear understanding of the ADME pa-
rameters, which should be considered at the time of the drug designing process [7].
https://doi.org/10.1515/9783111434858-010
Fig. 10.1: A complete overview of the processes of absorption, distribution, metabolism, and excretion of a drug inside the body.
222 Chapter 10 ADMET analysis in CADD
ADME analysis in CADD is crucial for selecting promising drug candidates, reduc-
ing toxicity risks, speeding up drug development, improving drug efficacy, and ensur-
ing compliance with regulato ry standards. This integrated approach harnesses the
power of computational methods to revolutionize the way pharmaceuticals are dis-
covered and developed, ultimately leading to safer and more effective medicines for
patients worldwide [8, 9].
10.2 Importance of ADME studies in CADD
– Optimizing drug candidates: ADME analysis helps identify molecules with favor-
able properties, ensuring that drugs are effectively absorbed into the bloodstream,
distributed to target tissues, metabolized efficiently, and excreted appropriately.
This streamlines the drug development process by focusing efforts on compounds
with the greatest potential for success.
– Reducing toxicity and side effects: Poorly metabolized or excreted drugs can
lead to toxic effects or unwanted side effects. By predicting ADME properties
early in the drug discovery process, researchers can eliminate or modify com-
pounds with unfavorable profiles, minimizing risks to patients.
– Cost and time efficiency: Traditional drug development is time-consuming and
expensive, with many potential candidates failing due to ADME issues late in the
process. CADD, with ADME analysis, allows researchers to screen and prioritize
compounds in silico, significantly reducing the cost and time associated with ex-
perimental testing.
– Enhancing drug efficacy: ADME analysis is not just about avoiding problems; it
is also about improving drug performance. By optimizing a drug’s pharmacoki-
netic properties, it is possible to enhance its efficacy, ensuring that it reaches its
target in the right concentration and for the right duration.
– Meeting regulatory requirements: Regulatory agencies like the FDA require
comprehensive ADME data during the drug approval processes. CADD can pro-
vide a wealth of predictive ADME information, helping companies meet these re-
quirements more effectively.
10.3 Absorption parameters of the drug molecule
Entry of the drug inside the systemic circulation from the site of administration is
known as the process of absorption. Absorption is a critical phase in the pharmacoki-
netic profile of a drug molecule, influencing how efficiently it enters the bloodstream
and reaches its target site within the body [10, 11]. Several key parameters govern this
process, which include lipophilicity, molecular size, ionization, etc. Lipophilicity,
often measured as LogP, represents the drug’s affinity for lipids or fats. A higher LogP
10.3 Absorption parameters of the drug molecule 223
suggests greater fat solubility, which can enhance absorption as many biological
membranes consist of lipid bilayers. Likewise, smaller molecules can permeate biolog-
ical barriers more easily than larger ones, facilitating absorption. The charge state of
a drug molecule is another determinant. Drugs with a balanced charge are typically
better absorbed due to their ability to traverse aqueous and lipid environments. Ioni-
zation, which is dependent on pH, impacts absorption. A drug’s ionization state can
change along the gastrointesti nal tract, affecting its ability to cross biological mem-
branes. Collectively, these absorption parameters guide drug design, ensuring that po-
tential candidates possess the characteristics necessary for effective absorption into
the bloodstream, a crucial step in the development of pharmaceuticals [12].
The majority of the clinically available drugs are administered through the oral
route and, therefore, are absorbed through the gastrointestinal tract (GIT). GIT is con-
sidered as the major site of the drug absorption, although it can also take place through
skin, lungs, etc., which are considered as minor sites of drug absorption. Regardless of
the site of absorption, any drug that is administered inside the body has to cross the
bilayered cell membrane to reach the systemic circulation. The cell membrane consists
of a bilayer of phospholipids, which contains a hydrophilic head and lipophilic tail part
(Fig. 10.2). Absorption of the drugs mostly occurs by passive diffusion through this cell
membrane. This passive diffusion of the small drug molecules is totally dependent on
the concentration gradient along the cell membrane and the partition coefficient value
of the drug molecule (lipid/water partition coefficient). Thus for designing any drug
molecule, it is important to consider its partition coefficient value and it is the very first
parameter to be considered in the drug-designing process.
10.3.1 Partition coefficient/log P
Partition coefficient (log P or log D) is a fundamental parameter in ADME studies, par-
ticularly in the field of pharmaceutical research. It quantifies the distribution of a
drug molecule between two immiscible phases, typically a li pid-like organic solvent
and water [13]. This parameter offers valuable insights into a compound’s lipophilic-
ity, which plays a pivotal role in its pharmacokinetics. A higher LogP value indicates
Fig. 10.2: Bilayered phospholipid cell membrane of the gastrointestinal tract (GIT) through which
absorption of the drug takes place inside the body. It consists of a hydrophilic head and a lipophilic tail.
224 Chapter 10 ADMET analysis in CADD
greater lipophilicity, suggesting that the molecule has an affinity for lipid-rich envi-
ronments, such as biological membranes. This property can enhance a drug’s absorp-
tion and distribution within the body, enabling it to traverse cellular barriers more
effectively. Conversely, a lower LogP value implies higher hydrophilicity, indicating
that the drug is more soluble in water. While hydrophilicity can be advantageous for
certain aspects of drug development, such as solubility, an optimal balance is often
sought to ensure efficient absorption and distribution while maintaining a suitabl e
aqueous solubility. Therefore, the partition coefficient is a vital parameter in ADME
analysis, aiding researchers in the selection and optimization of drug candidates. It
guides the design of molecules with the appropriate balance of lipophilicity and hy-
drophilicity, ultimately contributing to the development of safe and effective pharma-
ceuticals [14].
Mathematically, the partition coefficient can be defined as in the following equation:
Partition coefficient PðÞ=
The concentration of a drug in the lipid phase
The concentration of a drug in aqueous phase
(10:1)
The logarithmic form, log P, is commonly used because it simplifies the expression of
the data and is more convenient for comparisons. The LogP value can be positive, neg-
ative, or zero, indicating whether a compound is more soluble in the organic phase,
aqueous phase, or equally distributed between the two, respectively. Generally, an op-
timum value of partition coefficient is required for a drug molecule so that it can
cross the cell membrane and reach systemic circulation. A too-low partition coeffi-
cient value w ill result in a highly aqueous soluble drug that will not cross the cell
membrane. Likewise, too high a partition coefficient value results in a drug molecule
that has high lipid solubility, making it to be entrapped in the lipid layer of the mem-
brane and, therefore, will not reach the aqueous systemic circulation.
There are numerous tools available through which this parameter of the pro-
posed drug molecule can be calculated through in silico approaches. Any drug mole-
cule having a logP value less than 0 is considered aqueous soluble with poor lipid
solubility, whereas the molecule having a logP value more than 0 is considered lipid-
soluble. As per Lipinski’s rule, an ideal drug molecule should have a LogP value of
less than 5 [15, 16].
10.3.2 Acid–base dissociation constant (pK
a
)
Acid–base dissociation constant, often referred to as pK
a
, is a fundamental parameter
in drug development that plays a crucial role in understanding and manipulating a
drug’s pharmacological properties. This constant quantifies the degree of ionization of
a compound in a solution, specifically indicating the equilibrium between its proton-
ated (acidic) and deprotonated (basic) forms [15]. The solubility of a drug in physiologi-
cal fluids is strongly influenced by its pK
a
. Compounds with pK
a
values close to the
10.3 Absorption parameters of the drug molecule 225
physiological pH (around 7.4) are typically more soluble, ensuring their effective disso-
lution and absorption within the body. The ionization state of a drug significantly im-
pacts its ability to traverse biological barriers. A compound’s charge (resulting from its
pK
a
) affects its transport across cell membranes and its distribution within tissues. Like-
wise, the pK
a
of a drug can influence its binding to target receptors or enzymes. Varia-
tions in pH at different physiological sites can modulate a drug’s affinity for its target,
impacting its therapeutic effectiveness. Moreover, the enzymatic processes in the body
often depend on the ionization state of a drug. Knowledge of a drug’spK
a
can aid in
predicting its metabolic fate and designing prodrugs that become active through enzy-
matic transformations. Therefore, the acid–base dissociation constant (pK
a
) is a critical
parameter in drug development, influencing drug solubility, transport, receptor in-
teractions, metabolism, and formulation. Understanding and manipulating the pK
a
of a drug candidate is essential for designing pharmaceuticals with the desired phar-
macokinetic and pharmacodynamic properties, ultimately leading to safer and more
effective medications.
It is estimated that overall 75% of the drugs are weak bases, 20% are weak acids,
and the remaining are either neutral substances or ampholytic in nature. This type of
chemical behavior of the drugs also affects their absorption inside the body. It is a
universal fact that a unionized drug is lipophilic in nature and is absorbed easily
through the cell membrane, whereas, a drug in the ionic form is considered polar and
is not absorbed through the cell membrane. As already discussed, most of the drugs
available are weak electrolytes. Their dissociation into ions is dependent on the pH of
the system. Hence, the pK
a
value of any drug molecule gives a fair idea about the pH-
dependent dissociation of the drug inside the body, and ultimately about its absorp-
tion. pK
a
is defined as the negative logarithm of the dissociation constant (K
a
) of the
drug molecule [17, 18]. Consider an example of an acidic drug HA whose dissociation
will be given by the following equation:
pH = pK
a
+ log
A
−
½
HA½
(10:2)
where [A
–
] is the concentration of the ionic (non-protonated) state and [HA] is the
concentration of the acid in the unionized (protonated) state.
If at any stage, [A
–
] = [HA], then log [A
–
]/[HA] will become 0 and pH will be equal
to pKa(pH=pK
a
). From here, it can be determined that the pK
a
is equal to the pH
value when half of the drug is ionized. From equation (10.2) it becomes evident that if
the value of pH is increased by 1, the concentration of ionized or non-protonated state
([A
–
]) will be increased by 10 folds. Similarly, for the decrease in the pH value by 1,
there will be a 10-fold increase in the concentration of unionized or protonated state
([HA]). Since the unionized form of the drug is absorbed readily from the cellular
membrane, acidic drugs are absorbe d more readily in the acidic medium (stomach)
and basic drugs are absorbed more readily in the basic environment (intestine) inside
the body
226 Chapter 10 ADMET analysis in CADD
Considering a similar example for the basic drug B, the dissociation of the basic
drug will be given by the following equation:
pH = pK
a
+ log
B½
HB
+
½
(10:3)
where [B] is the concentration of the unionized basic drug and [HB
+
] is the concentra-
tion of the basic drug in its protonated or ionized form.
The value of pK
a
will be equal to the pH when half of this basic drug is ionized,
that is, [B] = [HB
+
]. However, in the case of the basic drugs, the situation will be totally
opposite as compared to the acidic drug. If there is an increase in the pH value by 1,
the concentration of the unionized drug will increase 10-fold. Likewise, for a decrease
in the pH by a value of 1, the concentration of ionized form will increase by 10 folds.
Therefore, it can be said that basic drugs that increase in pH will increase the concen-
tration of the unionized form of the drug and therefore will enhance their absorption
in the basic medium. This dependence of absorption on the pK
a
of the drug can b e
best understood with the example given in Fig. 10.3. Log P and pK
a
values of some of
the commonly prescribed drugs are given in Tab. 10.1, which was calculated through
the Marvin Sketch of Chemaxon [19].
10.3.3 Bioavailability (F)
Bioavailability plays a pivotal role in the field of CADD when analyzing the ADME proper-
ties of potential drug candidates. Understanding bioavailability is essential in predicting a
Fig. 10.3: The dependence of the drug absorption on its pK
a
value, which determines whether the drug
will be absorbed in the stomach or the intestine.
10.3 Absorption parameters of the drug molecule 227
drug’s effectiveness and safety in vivo. In the context of CADD, bioavailability refers to
the fraction of an orally administered drug that reaches the bloodstream and is available
to interact with the target receptor. It serves as a critical parameter for assessing drug
candidates’ viability and optimizing their pharmacokinetic profiles. CADD models take
into account a compound’s physicochemical properties, such as lipophilicity and solubil-
ity, to estimate its likelihood of being absorbed through biological membranes. This pre-
diction helps identify compounds with favorable bioavailability profiles. Bioavailability
impacts the distribution of drugs within the body. By considering factors like protein
binding and tissue permeability, CADD helps assess a drug’s ability to reach its target site
effectively. Bioavailability also affects a drug’s susceptibility to metabolic processes in the
liverandothertissues.CADDtoolspredictpotential metabolites and their impact on bio-
availability, aiding in drug design to minimize unwanted transformations. Predicting a
drug’s elimination rate and potential excretion routes, such as renal or hepatic clearance,
is also crucial in optimizing bioavailability and overall pharmacokinetics. Therefore, bio-
availability serves as a critical parameter in CADD’s ADME analysis, guiding drug design
efforts to develop compounds that maximize their therapeutic potential while minimizing
adverse effects. By leveraging computational techniques, researchers can efficiently
screen and prioritize potential drug candidates with improved bioavailability, ultimately
accelerating the drug discovery process [20–23]. Table 10.2 depicts the values of bioavail-
ability of the commonly marketed drugs calculated through the SwissADME server [24].
Tab. 10.1: LogP and pK
a
values of some of the commonly prescribed drugs
calculated through the Marvin Sketch of Chemaxon.
S. no. Name of drug Calculated log P value Calculated pK
a
value
Paracetamol . .
Clonazepam . .
Captopril . .
Rosuvastatin . .
Cetirizine . .
Pantoprazole . .
Glimepride . .
Donepezil . .
Quinine . .
Lidocaine . .
Tab. 10.2: Values of bioavailability of the commonly marketed drugs
calculated through the SwissADME server.
S. no. Name of drug Calculated F value
Paracetamol .
Clonazepam .
228 Chapter 10 ADMET analysis in CADD
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