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Cover Image, Volume 37, Issue 12
Publication year - 2016
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Reports
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.24366
Subject(s) - cover (algebra) , computer science , sequence (biology) , image (mathematics) , volume (thermodynamics) , citation , stability (learning theory) , function (biology) , theoretical computer science , information retrieval , algorithm , artificial intelligence , world wide web , machine learning , chemistry , mechanical engineering , physics , engineering , biochemistry , quantum mechanics , evolutionary biology , biology
The cover picture highlights the use of cost function networks (CFN) in computational protein design (CPD). These methods provide important speedups to explore large sequence‐conformation spaces and provably identify the sequence with the conformation of optimal stability, i.e., the global minimum energy conformation (GMEC). On page 1048 (DOI: 10.1002/jcc.24290 ), Seydou Traoré et al. show that, in addition to quickly finding the GMEC in highly complex protein design problems, CFN‐based methods also enable the efficient enumeration of sub‐optimal sequences. These approaches offer an attractive alternative to the usual CPD methods.