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Peptidoglycan Synthesis

Peptidoglycan Synthesis

Structure of PeptidoglycanPeptidoglycan is a vital structural component of the bacterial cell wall, providing mechanical strength and shape to the cell. It consists of repeating units of two sugars—N-acetylglucosamine (NAG) and N-acetylmuramic acid (NAM)—linked by β-1,4 glycosidic bonds. These sugar chains are cross-linked by short peptide chains, forming a mesh-like polymer that surrounds the bacterial plasma membrane.Cytoplasmic Phase – Precursor SynthesisPeptidoglycan...

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Related Experiment Video

Updated: Dec 8, 2025

Split-and-pool Synthesis and Characterization of Peptide Tertiary Amide Library

Split-and-pool Synthesis and Characterization of Peptide Tertiary Amide Library

Published on: June 20, 2014

Peptidomimetics in Silico.

Cristina Tomasella¹, Matteo Floris², Salvatore Guccione¹

¹Dipartimento di Scienze del Farmaco, University of Catania, V.le A. Doria 6, I-95125, Catania (CT), Italy.

Molecular Informatics

|September 21, 2020

Summary

This summary is machine-generated.

Researchers are exploring computational methods to discover novel peptidomimetics. These peptide-like molecules offer therapeutic potential by mimicking endogenous peptides for modulating molecular interactions.

Keywords:

CADD drugability in silico peptidomimetics peptides pharmacophoric screening

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Solid-phase Submonomer Synthesis of Peptoid Polymers and their Self-Assembly into Highly-Ordered Nanosheets

Solid-phase Submonomer Synthesis of Peptoid Polymers and their Self-Assembly into Highly-Ordered Nanosheets

Published on: November 2, 2011

Area of Science:

Medicinal Chemistry
Computational Biology
Drug Discovery

Background:

Endogenous peptides play crucial roles in physiological processes and are attractive therapeutic targets.
Peptides face limitations as drugs, including poor stability and bioavailability.
Peptidomimetics offer a promising alternative to overcome these limitations.

Purpose of the Study:

To review recent advancements in the computational discovery of peptidomimetics.
To highlight the utility of in silico approaches for identifying novel therapeutic agents.
To understand the molecular basis of physiological processes modulated by peptides.

Main Methods:

Utilizing computational methods for peptidomimetic discovery.
Employing pharmacophore modeling and simulations.
Conducting molecular dynamic simulations.

Main Results:

Recent works demonstrate the successful application of computational strategies for identifying peptidomimetics.
Pharmacophore and molecular dynamic simulations provide insights into molecular interactions.
These methods aid in understanding the determinants of physiological processes.

Conclusions:

Computational approaches are effective for discovering peptidomimetics with therapeutic potential.
In silico methods enhance the understanding of molecular mechanisms underlying peptide function.
This research facilitates the development of novel therapeutics targeting molecular interactions.