Computational stabilization of human growth hormone.
Anton Filikov,Robert J. Hayes,Peizhi Luo,Diane M. Stark,Cheryl Chan,Anirban Kundu,Bassil I. Dahiyat +6 more
TLDR
The redesigned hGH computationally to improve its thermostability was redesigned using a previously developed combinatorial optimization algorithm based on the dead‐end elimination theorem and shows the utility of the free energy function in automated protein design.Abstract:
Recombinant human growth hormone (hGH) is used worldwide for the treatment of pediatric hypopituitary dwarfism and in children suffering from low levels of hGH. It has limited stability in solution, and because of poor oral absorption, is administered by injection, typically several times a week. Development has therefore focused on more stable or sustained-release formulations and alternatives to injectable delivery that would increase bioavailability and make it easier for patients to use. We redesigned hGH computationally to improve its thermostability. A more stable variant of hGH could have improved pharmacokinetics or enhanced shelf-life, or be more amenable to use in alternate delivery systems and formulations. The computational design was performed using a previously developed combinatorial optimization algorithm based on the dead-end elimination theorem. The algorithm uses an empirical free energy function for scoring designed sequences. This function was augmented with a term that accounts for the loss of backbone and side-chain conformational entropy. The weighting factors for this term, the electrostatic interaction term, and the polar hydrogen burial term were optimized by minimizing the number of mutations designed by the algorithm relative to wild-type. Forty-five residues in the core of the protein were selected for optimization with the modified potential function. The proteins designed using the developed scoring function contained six to 10 mutations, showed enhancement in the melting temperature of up to 16°C, and were biologically active in cell proliferation studies. These results show the utility of our free energy function in automated protein design.read more
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Patent
Albumin Fusion Proteins
TL;DR: The present invention encompasses albumin fusion proteins as discussed by the authors, as well as vectors containing these nucleic acids, host cells transformed with the nucleic acid vectors, and methods of making the fusion proteins of the invention.
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Rational engineering of enzyme stability.
Vincent G. H. Eijsink,Alexandra Bjørk,Sigrid Gåseidnes,Reidun Sirevåg,Bjørnar Synstad,Bertus van den Burg,Gert Vriend +6 more
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Inactivation of TNF signaling by rationally designed dominant-negative TNF variants.
Paul Michael Steed,Malú G. Tansey,Jonathan Zalevsky,Eugene Zhukovsky,John R. Desjarlais,David E. Szymkowski,Christina Abbott,David F. Carmichael,Cheryl Chan,Lisa Cherry,Peter Cheung,Arthur J. Chirino,Hyo H. Chung,Stephen K. Doberstein,Araz Eivazi,Anton Filikov,Sarah X. Gao,Rend S. Hubert,Marian Hwang,Linus Hyun,Sandhya Kashi,Alice Kim,Esther Kim,James Kung,Sabrina P. Martinez,T. Umesh S. Muchhal,Duc-Hanh T. Nguyen,C. O'Brien,Donald O'keefe,Karen Singer,Omid Vafa,Jost Vielmetter,Sean Yoder,Bassil I. Dahiyat +33 more
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References
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TL;DR: The DREIDING force field as discussed by the authors uses general force constants and geometry parameters based on simple hybridization considerations rather than individual force constants or geometric parameters that depend on the particular combination of atoms involved in the bond, angle, or torsion terms.
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Human Growth Hormone and Extracellular Domain of Its Receptor: Crystal Structure of the Complex
TL;DR: Examination of the 2.8 angstrom crystal structure of the complex between the hormone and the extracellular domain of its receptor (hGHbp) showed that the complex consists of one molecule of growth hormone per two molecules of receptor.
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De novo protein design: fully automated sequence selection.
TL;DR: The first fully automated design and experimental validation of a novel sequence for an entire protein is described, and a BLAST search shows that the designed sequence, full sequence design 1 (FSD-1), has very low identity to any known protein sequence.
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Backbone-dependent Rotamer Library for Proteins Application to Side-chain Prediction
TL;DR: A backbone-dependent rotamer library for amino acid side-chains is developed and used for constructing protein side-chain conformations from the main-chain co-ordinates and it is evident from the results that a single protein does not adequately test a prediction scheme.
Journal ArticleDOI
Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins.
Ruben Abagyan,Maxim Totrov +1 more
TL;DR: An efficient way to make a random step in a Monte Carlo procedure given knowledge of the energy or statistical properties of conformational subspaces is found, and the BPMC procedure is applied to the structure prediction of 12- and 16-residue synthetic peptides and the determination of protein structure from NMR data.