By Torsten Schwede, Torsten Schwede, Manuel C. Peitsch
Computational structural biology has made great development over the past 20 years, and this publication offers a up to date and huge evaluate of such computational tools in structural biology. It covers the effect of computational structural biology on protein constitution prediction tools, macromolecular functionality and protein layout, and key equipment in drug discovery. It additionally addresses the computational demanding situations of experimental techniques in structural biology. as well as reviewing the present country of computational structural biology, every one bankruptcy ends with a quick, visionary dialogue at the destiny outlook, wherein the most demanding situations for the arriving years are elucidated. Written by means of a global panel of professional individuals, this booklet can function a reference handbook for college students and practitioners alike.
Contents: constitution Prediction and evaluation tools: Protein Fold attractiveness and Threading (L J McGuffin); evaluation of Protein constitution Predictions (E Capriotti & M A Marti-Renom); From constitution to operate to layout: Evolution of Protein Folds (A N Lupas & okay ok Koretke); Atomistic Simulations of Reactions and Transition States (M Meuwly); Protein Protein Interactions and Aggregation strategies (R I Dima); Drug Discovery and Pharmacology: MD-Based loose power Simulations (M A Cuendet et al.); Structure-Based Computational ways to Drug Metabolism (M A Lill); New Frontiers in Experimental equipment: New Frontiers in X-ray Crystallography (C U Stirnimann & M G GrÃƒÂƒÃ‚Â¼tter); New Frontiers in Characterizing constitution and Dynamics by means of NMR (M Nilges et al.); chosen subject matters: Docking for ignored illnesses as group Efforts (M Podvinec et al.); Protein constitution Databases (M John et al.); Molecular photographs in Structural Biology (A M Lesk et al.); and different chapters.
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Additional resources for Computational Structural Biology: Methods and Applications
Threading became one of the most successful approaches to fold recognition during the 1990s. The popularity of the method meant that “threading” became a generic term to describe carrying out protein fold recognition (such as “googling” has become the generic term used to describe web searching) and was often used to differentiate structure-based methods for tertiary structure prediction from sequence-based methods. Technically speaking, “threading” is a specialized sub-class of fold recognition and it is now beginning to fall out of common usage.
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