Literature DB >> 20068399

Predictive tools for stabilization of therapeutic proteins.

Vladimir Voynov1, Naresh Chennamsetty, Veysel Kayser, Bernhard Helk, Bernhardt L Trout.   

Abstract

Monoclonal antibodies represent the fastest growing class of pharmaceuticals. A major problem, however, is that the proteins are susceptible to aggregation at the high concentration commonly used during manufacturing and storage. Our recent publication describes a technology based on molecular simulations to identify aggregation-prone regions of proteins in silico. The technology, called spatial aggregation propensity (SAP), identifies hot-spots for aggregation based on the dynamic exposure of spatially-adjacent hydrophobic amino acids. Monoclonal antibodies (mAbs) in which patches with high-SAP scores are changed to patches with significantly reduced SAP scores via a single mutation are more stable than wild type, thus validating the SAP method for mapping aggregation-prone regions on proteins. We propose that the SAP technology will be useful for protein stabilization, and as a screening tool to bridge discovery and development of protein-based therapeutics by a rational assessment of the developability of candidate protein drugs.

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Year:  2009        PMID: 20068399      PMCID: PMC2791315          DOI: 10.4161/mabs.1.6.9773

Source DB:  PubMed          Journal:  MAbs        ISSN: 1942-0862            Impact factor:   5.857


  18 in total

1.  Dissecting the assembly of Abeta16-22 amyloid peptides into antiparallel beta sheets.

Authors:  Dmitri K Klimov; D Thirumalai
Journal:  Structure       Date:  2003-03       Impact factor: 5.006

2.  Gene mutations in human haemoglobin: the chemical difference between normal and sickle cell haemoglobin.

Authors:  V M INGRAM
Journal:  Nature       Date:  1957-08-17       Impact factor: 49.962

Review 3.  Challenges in the development of high protein concentration formulations.

Authors:  Steven J Shire; Zahra Shahrokh; Jun Liu
Journal:  J Pharm Sci       Date:  2004-06       Impact factor: 3.534

4.  Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins.

Authors:  Ana-Maria Fernandez-Escamilla; Frederic Rousseau; Joost Schymkowitz; Luis Serrano
Journal:  Nat Biotechnol       Date:  2004-09-12       Impact factor: 54.908

5.  Rational design of solution additives for the prevention of protein aggregation.

Authors:  Brian M Baynes; Bernhardt L Trout
Journal:  Biophys J       Date:  2004-09       Impact factor: 4.033

6.  Development of hydrophobicity parameters to analyze proteins which bear post- or cotranslational modifications.

Authors:  S D Black; D R Mould
Journal:  Anal Biochem       Date:  1991-02-15       Impact factor: 3.365

7.  Prediction of aggregation prone regions of therapeutic proteins.

Authors:  Naresh Chennamsetty; Vladimir Voynov; Veysel Kayser; Bernhard Helk; Bernhardt L Trout
Journal:  J Phys Chem B       Date:  2010-05-20       Impact factor: 2.991

8.  Role of arginine in the stabilization of proteins against aggregation.

Authors:  Brian M Baynes; Daniel I C Wang; Bernhardt L Trout
Journal:  Biochemistry       Date:  2005-03-29       Impact factor: 3.162

9.  Protein stability and surface electrostatics: a charged relationship.

Authors:  Samantha S Strickler; Alexey V Gribenko; Alexander V Gribenko; Timothy R Keiffer; Jessica Tomlinson; Tracey Reihle; Vakhtang V Loladze; George I Makhatadze
Journal:  Biochemistry       Date:  2006-03-07       Impact factor: 3.162

10.  Prediction of aggregation rate and aggregation-prone segments in polypeptide sequences.

Authors:  Gian Gaetano Tartaglia; Andrea Cavalli; Riccardo Pellarin; Amedeo Caflisch
Journal:  Protein Sci       Date:  2005-10       Impact factor: 6.725

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  18 in total

1.  Rational design of therapeutic mAbs against aggregation through protein engineering and incorporation of glycosylation motifs applied to bevacizumab.

Authors:  Fabienne Courtois; Neeraj J Agrawal; Timothy M Lauer; Bernhardt L Trout
Journal:  MAbs       Date:  2016       Impact factor: 5.857

Review 2.  Molecular basis of high viscosity in concentrated antibody solutions: Strategies for high concentration drug product development.

Authors:  Dheeraj S Tomar; Sandeep Kumar; Satish K Singh; Sumit Goswami; Li Li
Journal:  MAbs       Date:  2016-01-06       Impact factor: 5.857

Review 3.  High-throughput biophysical analysis of protein therapeutics to examine interrelationships between aggregate formation and conformational stability.

Authors:  Rajoshi Chaudhuri; Yuan Cheng; C Russell Middaugh; David B Volkin
Journal:  AAPS J       Date:  2013-10-31       Impact factor: 4.009

4.  Reduction of Nonspecificity Motifs in Synthetic Antibody Libraries.

Authors:  Ryan L Kelly; Doris Le; Jessie Zhao; K Dane Wittrup
Journal:  J Mol Biol       Date:  2017-11-26       Impact factor: 5.469

Review 5.  Structure, heterogeneity and developability assessment of therapeutic antibodies.

Authors:  Yingda Xu; Dongdong Wang; Bruce Mason; Tony Rossomando; Ning Li; Dingjiang Liu; Jason K Cheung; Wei Xu; Smita Raghava; Amit Katiyar; Christine Nowak; Tao Xiang; Diane D Dong; Joanne Sun; Alain Beck; Hongcheng Liu
Journal:  MAbs       Date:  2018-12-17       Impact factor: 5.857

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

7.  Beyond CDR-grafting: Structure-guided humanization of framework and CDR regions of an anti-myostatin antibody.

Authors:  James R Apgar; Michelle Mader; Rita Agostinelli; Susan Benard; Peter Bialek; Mark Johnson; Yijie Gao; Mark Krebs; Jane Owens; Kevin Parris; Michael St Andre; Kris Svenson; Carl Morris; Lioudmila Tchistiakova
Journal:  MAbs       Date:  2016-09-13       Impact factor: 5.857

8.  Rational engineering of antibody therapeutics targeting multiple oncogene pathways.

Authors:  Jonathan Fitzgerald; Alexey Lugovskoy
Journal:  MAbs       Date:  2011-05-01       Impact factor: 5.857

9.  Blind prediction performance of RosettaAntibody 3.0: grafting, relaxation, kinematic loop modeling, and full CDR optimization.

Authors:  Brian D Weitzner; Daisuke Kuroda; Nicholas Marze; Jianqing Xu; Jeffrey J Gray
Journal:  Proteins       Date:  2014-03-31

Review 10.  Computer-aided antibody design.

Authors:  Daisuke Kuroda; Hiroki Shirai; Matthew P Jacobson; Haruki Nakamura
Journal:  Protein Eng Des Sel       Date:  2012-06-02       Impact factor: 1.650

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