Literature DB >> 27681371

LUTE (Local Unpruned Tuple Expansion): Accurate Continuously Flexible Protein Design with General Energy Functions and Rigid Rotamer-Like Efficiency.

Mark A Hallen1, Jonathan D Jou1, Bruce R Donald1,2,3.   

Abstract

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.

Keywords:  algorithms; combinatorial optimization; drug design; machine learning; protein structure

Mesh:

Substances:

Year:  2016        PMID: 27681371      PMCID: PMC5467149          DOI: 10.1089/cmb.2016.0136

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  39 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-12       Impact factor: 11.205

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4.  Predicting resistance mutations using protein design algorithms.

Authors:  Kathleen M Frey; Ivelin Georgiev; Bruce R Donald; Amy C Anderson
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5.  Dead-End Elimination with a Polarizable Force Field Repacks PCNA Structures.

Authors:  Stephen D LuCore; Jacob M Litman; Kyle T Powers; Shibo Gao; Ava M Lynn; William T A Tollefson; Timothy D Fenn; M Todd Washington; Michael J Schnieders
Journal:  Biophys J       Date:  2015-08-18       Impact factor: 4.033

6.  A natural linear scaling coupled-cluster method.

Authors:  N Flocke; Rodney J Bartlett
Journal:  J Chem Phys       Date:  2004-12-08       Impact factor: 3.488

7.  An improved pairwise decomposable finite-difference Poisson-Boltzmann method for computational protein design.

Authors:  Christina L Vizcarra; Naigong Zhang; Shannon A Marshall; Ned S Wingreen; Chen Zeng; Stephen L Mayo
Journal:  J Comput Chem       Date:  2008-05       Impact factor: 3.376

8.  comets (Constrained Optimization of Multistate Energies by Tree Search): A Provable and Efficient Protein Design Algorithm to Optimize Binding Affinity and Specificity with Respect to Sequence.

Authors:  Mark A Hallen; Bruce R Donald
Journal:  J Comput Biol       Date:  2016-01-13       Impact factor: 1.479

9.  Conformation of amino acid side-chains in proteins.

Authors:  J Janin; S Wodak
Journal:  J Mol Biol       Date:  1978-11-05       Impact factor: 5.469

10.  Antibodies VRC01 and 10E8 neutralize HIV-1 with high breadth and potency even with Ig-framework regions substantially reverted to germline.

Authors:  Ivelin S Georgiev; Rebecca S Rudicell; Kevin O Saunders; Wei Shi; Tatsiana Kirys; Krisha McKee; Sijy O'Dell; Gwo-Yu Chuang; Zhi-Yong Yang; Gilad Ofek; Mark Connors; John R Mascola; Gary J Nabel; Peter D Kwong
Journal:  J Immunol       Date:  2014-01-03       Impact factor: 5.422

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  8 in total

1.  BBK* (Branch and Bound Over K*): A Provable and Efficient Ensemble-Based Protein Design Algorithm to Optimize Stability and Binding Affinity Over Large Sequence Spaces.

Authors:  Adegoke A Ojewole; Jonathan D Jou; Vance G Fowler; Bruce R Donald
Journal:  J Comput Biol       Date:  2018-03-13       Impact factor: 1.479

2.  Minimization-Aware Recursive K*: A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape.

Authors:  Jonathan D Jou; Graham T Holt; Anna U Lowegard; Bruce R Donald
Journal:  J Comput Biol       Date:  2019-12-06       Impact factor: 1.479

3.  Protein Design by Provable Algorithms.

Authors:  Mark A Hallen; Bruce R Donald
Journal:  Commun ACM       Date:  2019-10       Impact factor: 4.654

Review 4.  Algorithms for protein design.

Authors:  Pablo Gainza; Hunter M Nisonoff; Bruce R Donald
Journal:  Curr Opin Struct Biol       Date:  2016-04-14       Impact factor: 6.809

5.  Perturbing the energy landscape for improved packing during computational protein design.

Authors:  Jack B Maguire; Hugh K Haddox; Devin Strickland; Samer F Halabiya; Brian Coventry; Jermel R Griffin; Surya V S R K Pulavarti; Matthew Cummins; David F Thieker; Eric Klavins; Thomas Szyperski; Frank DiMaio; David Baker; Brian Kuhlman
Journal:  Proteins       Date:  2020-12-11

6.  A critical analysis of computational protein design with sparse residue interaction graphs.

Authors:  Swati Jain; Jonathan D Jou; Ivelin S Georgiev; Bruce R Donald
Journal:  PLoS Comput Biol       Date:  2017-03-30       Impact factor: 4.475

7.  CATS (Coordinates of Atoms by Taylor Series): protein design with backbone flexibility in all locally feasible directions.

Authors:  Mark A Hallen; Bruce R Donald
Journal:  Bioinformatics       Date:  2017-07-15       Impact factor: 6.937

Review 8.  Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering.

Authors:  Bartłomiej Surpeta; Carlos Eduardo Sequeiros-Borja; Jan Brezovsky
Journal:  Int J Mol Sci       Date:  2020-04-14       Impact factor: 5.923

  8 in total

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