Literature DB >> 23451890

Energy functions in de novo protein design: current challenges and future prospects.

Zhixiu Li1, Yuedong Yang, Jian Zhan, Liang Dai, Yaoqi Zhou.   

Abstract

In the past decade, a concerted effort to successfully capture specific tertiary packing interactions produced specific three-dimensional structures for many de novo designed proteins that are validated by nuclear magnetic resonance and/or X-ray crystallographic techniques. However, the success rate of computational design remains low. In this review, we provide an overview of experimentally validated, de novo designed proteins and compare four available programs, RosettaDesign, EGAD, Liang-Grishin, and RosettaDesign-SR, by assessing designed sequences computationally. Computational assessment includes the recovery of native sequences, the calculation of sizes of hydrophobic patches and total solvent-accessible surface area, and the prediction of structural properties such as intrinsic disorder, secondary structures, and three-dimensional structures. This computational assessment, together with a recent community-wide experiment in assessing scoring functions for interface design, suggests that the next-generation protein-design scoring function will come from the right balance of complementary interaction terms. Such balance may be found when more negative experimental data become available as part of a training set.

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Year:  2013        PMID: 23451890      PMCID: PMC3851009          DOI: 10.1146/annurev-biophys-083012-130315

Source DB:  PubMed          Journal:  Annu Rev Biophys        ISSN: 1936-122X            Impact factor:   12.981


  119 in total

Review 1.  Development of novel statistical potentials for protein fold recognition.

Authors:  N-V Buchete; J E Straub; D Thirumalai
Journal:  Curr Opin Struct Biol       Date:  2004-04       Impact factor: 6.809

2.  Energy functions for protein design: adjustment with protein-protein complex affinities, models for the unfolded state, and negative design of solubility and specificity.

Authors:  Navin Pokala; Tracy M Handel
Journal:  J Mol Biol       Date:  2005-01-20       Impact factor: 5.469

3.  High-resolution structural validation of the computational redesign of human U1A protein.

Authors:  Neil Dobson; Gautam Dantas; David Baker; Gabriele Varani
Journal:  Structure       Date:  2006-05       Impact factor: 5.006

Review 4.  Progress in computational protein design.

Authors:  Shaun M Lippow; Bruce Tidor
Journal:  Curr Opin Biotechnol       Date:  2007-07-20       Impact factor: 9.740

5.  The NMR solution structure of the artificial protein M7 matches the computationally designed model.

Authors:  Claudius Stordeur; Roman Dallüge; Olaf Birkenmeier; Hans Wienk; Rainer Rudolph; Christian Lange; Christian Lücke
Journal:  Proteins       Date:  2008-08-15

6.  Design of a 20-amino acid, three-stranded beta-sheet protein.

Authors:  T Kortemme; M Ramírez-Alvarado; L Serrano
Journal:  Science       Date:  1998-07-10       Impact factor: 47.728

7.  Designing amino acid sequences to fold with good hydrophobic cores.

Authors:  S Sun; R Brem; H S Chan; K A Dill
Journal:  Protein Eng       Date:  1995-12

8.  Design of native-like proteins through an exposure-dependent environment potential.

Authors:  Samuel DeLuca; Brent Dorr; Jens Meiler
Journal:  Biochemistry       Date:  2011-09-19       Impact factor: 3.162

9.  Surface-exposed phenylalanines in the RNP1/RNP2 motif stabilize the cold-shock protein CspB from Bacillus subtilis.

Authors:  T Schindler; D Perl; P Graumann; V Sieber; M A Marahiel; F X Schmid
Journal:  Proteins       Date:  1998-03-01

10.  Design and engineering of an O(2) transport protein.

Authors:  Ronald L Koder; J L Ross Anderson; Lee A Solomon; Konda S Reddy; Christopher C Moser; P Leslie Dutton
Journal:  Nature       Date:  2009-03-19       Impact factor: 49.962

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  24 in total

1.  Artificial Diiron Enzymes with a De Novo Designed Four-Helix Bundle Structure.

Authors:  Marco Chino; Ornella Maglio; Flavia Nastri; Vincenzo Pavone; William F DeGrado; Angela Lombardi
Journal:  Eur J Inorg Chem       Date:  2015-07-06       Impact factor: 2.524

2.  Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

Authors:  Jack B Maguire; Scott E Boyken; David Baker; Brian Kuhlman
Journal:  J Chem Theory Comput       Date:  2018-04-20       Impact factor: 6.006

3.  Toward high-resolution computational design of the structure and function of helical membrane proteins.

Authors:  Patrick Barth; Alessandro Senes
Journal:  Nat Struct Mol Biol       Date:  2016-06-07       Impact factor: 15.369

4.  Consensus sequence design as a general strategy to create hyperstable, biologically active proteins.

Authors:  Matt Sternke; Katherine W Tripp; Doug Barrick
Journal:  Proc Natl Acad Sci U S A       Date:  2019-05-20       Impact factor: 11.205

5.  Computational Design of PDZ-Peptide Binding.

Authors:  Nicolas Panel; Francesco Villa; Vaitea Opuu; David Mignon; Thomas Simonson
Journal:  Methods Mol Biol       Date:  2021

6.  Computational tools help improve protein stability but with a solubility tradeoff.

Authors:  Aron Broom; Zachary Jacobi; Kyle Trainor; Elizabeth M Meiering
Journal:  J Biol Chem       Date:  2017-07-14       Impact factor: 5.157

Review 7.  Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics.

Authors:  Tatiana Maximova; Ryan Moffatt; Buyong Ma; Ruth Nussinov; Amarda Shehu
Journal:  PLoS Comput Biol       Date:  2016-04-28       Impact factor: 4.475

8.  Deep Mutational Scans as a Guide to Engineering High Affinity T Cell Receptor Interactions with Peptide-bound Major Histocompatibility Complex.

Authors:  Daniel T Harris; Ningyan Wang; Timothy P Riley; Scott D Anderson; Nishant K Singh; Erik Procko; Brian M Baker; David M Kranz
Journal:  J Biol Chem       Date:  2016-09-28       Impact factor: 5.157

9.  Designed protein reveals structural determinants of extreme kinetic stability.

Authors:  Aron Broom; S Martha Ma; Ke Xia; Hitesh Rafalia; Kyle Trainor; Wilfredo Colón; Shachi Gosavi; Elizabeth M Meiering
Journal:  Proc Natl Acad Sci U S A       Date:  2015-11-09       Impact factor: 11.205

Review 10.  Environment-transformable sequence-structure relationship: a general mechanism for proteotoxicity.

Authors:  Jianxing Song
Journal:  Biophys Rev       Date:  2017-12-04
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