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LUTE (Local Unpruned Tuple Expansion): Accurate Continuously Flexible Protein Design with General Energy Functions and Rigid Rotamer-Like Efficiency.
Hallen, Mark A; Jou, Jonathan D; Donald, Bruce R.
Afiliação
  • Hallen MA; 1 Department of Computer Science, Levine Science Research Center, Duke University , Durham, North Carolina.
  • Jou JD; 1 Department of Computer Science, Levine Science Research Center, Duke University , Durham, North Carolina.
  • Donald BR; 1 Department of Computer Science, Levine Science Research Center, Duke University , Durham, North Carolina.
J Comput Biol ; 24(6): 536-546, 2017 Jun.
Article em En | MEDLINE | ID: mdl-27681371
Most protein design algorithms search over discrete conformations and an energy function that is residue-pairwise, that is, a sum of terms that depend on the sequence and conformation of at most two residues. Although modeling of continuous flexibility and of non-residue-pairwise energies significantly increases the accuracy of protein design, previous methods to model these phenomena add a significant asymptotic cost to design calculations. We now remove this cost by modeling continuous flexibility and non-residue-pairwise energies in a form suitable for direct input to highly efficient, discrete combinatorial optimization algorithms such as DEE/A* or branch-width minimization. Our novel algorithm performs a local unpruned tuple expansion (LUTE), which can efficiently represent both continuous flexibility and general, possibly nonpairwise energy functions to an arbitrary level of accuracy using a discrete energy matrix. We show using 47 design calculation test cases that LUTE provides a dramatic speedup in both single-state and multistate continuously flexible designs.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Software / Desenho de Fármacos / Engenharia de Proteínas / Proteínas / Biologia Computacional Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Software / Desenho de Fármacos / Engenharia de Proteínas / Proteínas / Biologia Computacional Idioma: En Ano de publicação: 2017 Tipo de documento: Article