Modeling Peptide-Protein Interactions: Methods and Protocols by Ora Schueler-Furman, Nir London

By Ora Schueler-Furman, Nir London

This quantity covers an array of strategies to be had for learning peptide-protein docking and layout. The booklet is split into 4 sections: peptide binding web site prediction; peptide-protein docking; prediction and layout of peptide binding specificity; and the layout of inhibitory peptides. The chapters in Modeling Peptide-Protein Interactions: tools and Protocols hide subject matters resembling using ACCLUSTER and PeptiMap for peptide binding web site prediction; AnchorDock and allure for blind, versatile docking of peptides to proteins; versatile peptide docking utilizing HADDOCK and FlexPepDock; deciding upon loop-mediated protein-protein interactions utilizing LoopFinder; and protein-peptide interplay layout utilizing PinaColada. Written within the hugely winning Methods in Molecular Biology sequence layout, chapters comprise introductions to their respective themes, lists of the mandatory info for winning program of the various techniques and step by step, comfortably reproducible protocols, in addition to tips about troubleshooting and heading off identified pitfalls.

Cutting-edge and thorough, Modeling Peptide-Protein Interactions: tools and Protocols presents a various and unified evaluation of this swiftly advancing box of significant curiosity and applicability.

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Extra info for Modeling Peptide-Protein Interactions: Methods and Protocols

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Yan C, Zou X (2015) Predicting peptide binding sites on protein surfaces by clustering chemical interactions. Journal of computational chemistry 36(1):49–61. Yang Y, Ludwig RL, Jensen JP, Pierre SA, Medaglia MV, Davydov IV, Safiran YJ, Oberoi P, Kenten JH, Phillips AC, Weissman AM, Vousden KH (2005) Small molecule inhibitors of HDM2 ubiquitin ligase activity stabilize and activate p53 in cells. Cancer cell 7(6):547–559. Soni V, Cahir-McFarland E, Kieff E (2007) LMP1 TRAFficking activates growth and survival pathways.

A first one is the rigid docking approach.  2d). The second one is the use of a simplified representation associated with a very simple force field. The impact of such a representation can be assessed by an auto validation where the experimental conformation is docked on the holo conformation of the protein.  6. Clearly, the best poses generated can, in some cases, differ largely from the experimental one—large ligand RMSD values. However, the fraction of native contacts matching these poses looks much better.

By further structure refinement that performs energy-based optimization, structural aspects that are missing in the template structures or that are not compatible with the given protein and peptide are refined. During the refinement, flexibilities of both protein and peptide induced by binding are considered. The atomistic protein-peptide interactions predicted by GalaxyPepDock can offer important clues for designing new peptides with desired binding properties. Key words Protein-peptide interaction, Template-based modeling, Structure refinement, Peptide structure flexibility 1 Introduction Protein-peptide interactions play important roles in many biological processes such as signaling pathways, protein cellular localization, immune response, and posttranslational modifications [1–3], and are related to human diseases such as cancer.

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