Published 12/2022Created by Abdul Rehman IkramMP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 6 Lectures ( 1h 20m ) | Size: 741 MB
Protein basic Concepts Understanding different techniques for protein prediction Understanding Comparative or Homology modeling Protein Modeling Using GUI Interface Swiss Model hands on training Protein Modeling Using CLI Interface Protein Modeling Using Modeller Background knowledge of Biology and genetics Knowledge of the composition and function of Proteins Molecular modeling tools can model a protein's structure based on a previously known homologous structure, so it is possible to use the structural information to design ligands for proteins for which no structure is known.Protein modeling methods could speed up drug development and reposition by predicting the effects of existing medication on new viruses. Pharma companies could generate their own antibody sequences in response to specific targets, use models for drug screening, and so on.So You want to learn how to model a protein? In this course, we are going to do so We are going to learn Protein Basic ConceptsUnderstanding different techniques for protein predictionUnderstanding Comparative or Homology modelingProtein Modeling Using GUI InterfaceSwiss Model hands-on trainingProtein Modeling Using CLI InterfaceProtein Modeling Using ModellerThe three-dimensional structure of a protein is essential to the understanding of its biological function and the design of drug candidates. In recent years, tremendous progress has been achieved in structural biology and a large number of new macromolecular structures have been deteed using expental methods such as X-ray crystallography, NMR, and cryo-EM. Despite the impressive advances, it is still generally difficult and -consuming to obtain structures for every protein of interest. This is why computational approaches come into play as a powerful alternative and supplement to expental methods.Homology modeling (also known as comparative modeling) is, to date, the most reliable and well-established computational approach for predicting protein structures. In this method, one or more expental three-dimensional structures of related homologous proteins are identified and used as templates, based on which an atomic-resolution model of the "target" protein is built from its amino acid sequence. It has been shown that three-dimensional protein structure is evolutionarily more conserved than would be expected on the basis of sequence conservation alone. Thus, even proteins that have diverged appreciably in sequence but still share detectable similarities will also share common structural properties, particularly the overall folding. People generally interested in new research methodologies and would like to try them themselves! Bner Bioinformaticians looking to understand the process of Proteins HomePage:
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