Cover Image, Volume 35, Issue 12. Issue 12 (5th May 2014)

• Record Type: Journal Article
• Is Part Of: Journal of computational chemistry. Volume 35:Issue 12(2014)
• Page Start: i
• Page End: ii
• Publication Date: 2014-05-05
• Subjects: Chemistry -- Data processing -- Periodicals; 542.85
• DOI: 10.1002/jcc.23600
• Languages: English
• ISSNs: 0192-8651

Abstract

<abstract abstract-type="graphical"> <title> <x xml:space="preserve">Abstract</x> </title> <p> <boxed-text content-type="graphic" position="anchor" orientation="portrait"> <graphic position="anchor" mimetype="image" xlink:href="ark:/27927/pgg537mkmtk" orientation="portrait" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink" /> </boxed-text> On page 932 (DOI: <ext-link ext-link-type="doi" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink">10.1002/jcc.23579</ext-link>), Sam Z. Grinter and Xiaoqin Zou introduce a new method of handing the sparse data problem in knowledge‐based scoring functions and present the approach in a scoring function called STScore. This Bayesian statistical approach, though presented in the context of protein‐ligand docking, may be used with other knowledge‐based scoring functions for protein‐protein docking and protein structure prediction. The cover compares the native binding mode of PDB:2cgr, correctly identified by STScore, with the binding mode predicted by a rudimentary potential of mean force. The cover also shows three example curves for the probability density function used in the derivation of STScore.</p> </abstract>