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PHARMACODYNAMICS

'Pharmacodynamics' is the study of the biochemical and physiological effects of drugs and the mechanisms of drug action and the relationship between drug concentration and effect. One dominant example being drug-receptor interactions as modeled by:
:L + R leftrightarrow L! cdot !R
where ''L''=ligand (drug), ''R''=receptor (attachment site), reaction dynamics that can be studied mathematically through tools such as free energy maps. Pharmacodynamics is often summarized as the study of what a drug does to the body, whereas pharmacokinetics is the study of what the body does to a drug. Pharmacodynamics is sometimes abbreviated as "PD", and when referred to in conjunction with pharmacokinetics can be referred to as "PKPD".

Contents
Effects on the body
Desired activity
Undesirable effects
Receptor binding
Multicellular pharmacodynamics
See also

Effects on the body


There are 4 main drug actions:

depressing

stimulating

destroying cells

replacing substances
Desired activity

The desired activity of a drug is mainly due to one of the following:

Cellular membrane disruption

Chemical reaction

★ Interaction with enzyme proteins

★ Interaction with structural proteins

★ Interaction with carrier proteins

★ Interaction with ion channels

Ligand binding to receptors:


Hormone receptors


Neuromodulator receptors


Neurotransmitter receptors
General anesthetics were once thought to work by disordering the neural membranes, thereby altering the Na+ influx. Antacids and chelating agents combine chemically in the body. Enzyme-substrate binding is a way to alter the production or metabolism of key endogenous chemicals, for example aspirin irreversibly inhibits the enzyme prostaglandin synthetase (cyclooxygenase) thereby preventing inflammatory response. Colchicine, a drug for gout, interferes with the function of the structural protein tubulin, while Digitalis, a drug still used in heart failure, inhibits the activity of the carrier molecule, Na-K-ATPase pump. The widest class of drugs act as ligands which bind to receptors which determine cellular effects. Upon drug binding, receptors can elicit their normal action (agonist), blocked action (antagonist), or even action opposite to normal (inverse agonist).
In principle, a pharmacologist would aim for a targetplasma concentration of the drug for a desired level of response. In reality, there are many factors affecting this goal. Pharmacokinetic factors determine peak concentrations, and concentrations cannot be maintained with absolute consistency because of metabolic breakdown and excretory clearance. Genetic factors may exist which would alter metabolism or drug action itself, and a patient's immediate status may also affect indicated dosage.
Undesirable effects

Undesirable effects of a drug include:

★ Increased probability of cell mutation (carcinogenic activity)

★ A multitude of simultaneous assorted actions which may be deleterious

★ Interaction (additive, multiplicative, or metabolic)

★ Induced physiological damage, or abnormal chronic conditions

Receptor binding


The binding of ligands (drug) to receptors is governed by the ''law of mass action'' which relates the large-scale status to the rate of numerous molecular processes. The rates of formation and un-formation can be used to determine the equilibrium concentration of bound receptors. The ''equilibrium dissociation constant'' is defined by:
:::::::L + R leftrightarrow L! cdot !R                      K_d = rac{[L][R]}{[L! cdot !R]}
where ''L''=ligand, ''R''=receptor, square brackets [] denote concentration. The fraction of bound receptors is found as ''(1+[R]/[L·R])-1'' , which can then be expressed using Kd as,
Semi-log plots of two agonists with different Kd.

:::Fraction Bound = rac{1}{1+ rac{K_d}{[L]}}
This expression is one way to consider the effect of a drug, in which the response is related to the fraction of bound receptors. The fraction of bound receptors is known as occupancy. The relationship between occupancy and pharmacological response is usually non-linear. This explains the so called ''receptor reserve'' phenomenon i.e. the concentration producing 50% occupancy is typically higher than the concentration producing 50% of maximum response.
Often the response is determined as a function of ''log[L]'' to consider many orders of magnitude of concentration. However, there is no biological or physical theory which relates effects to the log of concentration. It is just convenient for graphing purposes. It is useful to note that 50% of the receptors are bound when ''[L]=Kd'' .
The graph shown represents the conc-response for two hypothetical receptor agonists, plotted in a semi-log fashion. The curve toward the left represents a higher potency (potency arrow does not indicate direction of increase) since lower concentrations are needed for a given response. The effect increases as a function of concentration.

Multicellular pharmacodynamics


The concept of pharmacodynamics has been expanded to include 'Multicellular Pharmacodynamics' (MCPD). MCPD is the study of the static and dynamic properties and relationships between a set of drugs and a dynamic and diverse multicellular 4 dimensional organization. It is the study of the workings of a drug on a minimal multicellular system (mMCS), both ''in vivo'' and ''in silico''. 'Networked Multicellular Pharmacodynamics' (Net-MCPD) further extends the concept of MCPD to model regulatory genomic networks together with signal transduction pathways, as part of a complex of interacting components in the cell. For a fuller explanation of these concepts see the articles:

★ Jackson, R.C. (2003) Predictive software for drug design and development. Pharmaceutical Development and Regulation 1 ((3)), 159-168.

★ Werner, E., In silico multicellular systems biology and minimal genomes, DDT vol 8, no 24, pp 1121-1127, Dec 2003. (Introduces the concepts MCPD and Net-MCPD)
A good source for further information and posting to experts can be found courtesy of Dr. David W. A. Bourne, OU College of Pharmacy [1].

See also



Dose-response relationship

Pharmacokinetics

ADME

Pharmaceutical company

Schild regression

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