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Related Concept Videos

Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

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Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
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Multicompartment Models: Overview01:14

Multicompartment Models: Overview

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Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
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Adrenergic Agonists: Chemistry and Structure-Activity Relationship01:16

Adrenergic Agonists: Chemistry and Structure-Activity Relationship

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Adrenergic agonists' structure-activity relationship (SAR) determines their selectivity and efficacy. These agonists comprise a phenylethylamine moiety with an aromatic ring and an ethylamine side chain.
Aromatic ring substitutions: Substituting the aromatic ring with –OH groups at positions 3 and 4 yields catecholamines (e.g., epinephrine), which have a high affinity for adrenoceptors. Hydrogen bonding between –OH groups and receptors enhances adrenergic activity.
Separation of...
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Agonism and Antagonism: Quantification01:14

Agonism and Antagonism: Quantification

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When drugs are administered, they can elicit either an agonist or antagonist effect on the body. Agonism occurs when a drug activates a specific receptor, triggering a biological response. On the other hand, antagonism happens when a drug binds to the same receptors but blocks their activation, thereby preventing a biological response.
To quantify these effects, researchers use a dose-response curve, which provides valuable information about the potency and efficacy of a drug. Potency refers to...
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Principles of Drug Action01:24

Principles of Drug Action

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Drugs are chemical substances that modify biological responses by interacting with macromolecular targets such as receptors, ion channels, transporters, and enzymes. Pharmacodynamics describes the course of action of drugs leading to the physiological effect at a specific site in the body.
Drugs can be agonists or antagonists. Like the endogenous ligands, agonists always bind and activate the target to produce a cellular response. Agonist binding induces a conformational change which in turn...
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Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

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Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
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Toward structure-multiple activity relationships (SMARts) using computational approaches: A polypharmacological

Edgar López-López1, José L Medina-Franco2

  • 1Department of Chemistry and Graduate Program in Pharmacology, Center for Research and Advanced Studies of the National Polytechnic Institute, Section 14-740, Mexico City 07000, Mexico; DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.

Drug Discovery Today
|May 29, 2024
PubMed
Summary

In silico polypharmacology drug design decodes structure-multiple activity relationships (SMARts) using computational methods. These approaches aid molecule optimization and repurposing, with potential for automated drug discovery and interaction prediction.

Keywords:
bioinformaticschemoinformaticscomputer-aided drug designmultiobjectivemultitarget

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Area of Science:

  • Computational chemistry
  • Pharmacology
  • Bioinformatics

Background:

  • The era of biological big data necessitates advanced computational approaches for drug discovery.
  • In silico polypharmacology is crucial for decoding structure-multiple activity relationships (SMARts).

Purpose of the Study:

  • To highlight the role of in silico polypharmacology in modern drug design.
  • To discuss the impact of computational methods on various scientific fields.
  • To explore the future potential of computer-guided drug discovery and repurposing.

Main Methods:

  • Utilizing computational methods for simultaneous prediction and categorization of molecular properties.
  • Analyzing structure-multiple activity relationships (SMARts) for molecule generation and optimization.

Main Results:

  • Computational methods facilitate the generation, identification, curation, prioritization, optimization, and repurposing of molecules.
  • These methods present both opportunities and challenges across medicinal chemistry, pharmacology, food chemistry, toxicology, bioinformatics, and chemoinformatics.

Conclusions:

  • Computer-guided SMARts are poised to automate drug design and repurposing campaigns.
  • Future applications include predicting novel biological targets, side effects, off-target effects, and drug-drug interactions.