Literature DB >> 25512516

In silico selection of therapeutic antibodies for development: viscosity, clearance, and chemical stability.

Vikas K Sharma1, Thomas W Patapoff1, Bruce Kabakoff1, Satyan Pai1, Eric Hilario1, Boyan Zhang2, Charlene Li2, Oleg Borisov2, Robert F Kelley3, Ilya Chorny4, Joe Z Zhou4, Ken A Dill5, Trevor E Swartz6.   

Abstract

For mAbs to be viable therapeutics, they must be formulated to have low viscosity, be chemically stable, and have normal in vivo clearance rates. We explored these properties by observing correlations of up to 60 different antibodies of the IgG1 isotype. Unexpectedly, we observe significant correlations with simple physical properties obtainable from antibody sequences and by molecular dynamics simulations of individual antibody molecules. mAbs viscosities increase strongly with hydrophobicity and charge dipole distribution and decrease with net charge. Fast clearance correlates with high hydrophobicities of certain complementarity determining regions and with high positive or high negative net charge. Chemical degradation from tryptophan oxidation correlates with the average solvent exposure time of tryptophan residues. Aspartic acid isomerization rates can be predicted from solvent exposure and flexibility as determined by molecular dynamics simulations. These studies should aid in more rapid screening and selection of mAb candidates during early discovery.

Entities:  

Keywords:  degradation; monoclonal antibodies; pharmacokinetics; prediction; viscosity

Mesh:

Substances:

Year:  2014        PMID: 25512516      PMCID: PMC4284567          DOI: 10.1073/pnas.1421779112

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  28 in total

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

2.  Design of therapeutic proteins with enhanced stability.

Authors:  Naresh Chennamsetty; Vladimir Voynov; Veysel Kayser; Bernhard Helk; Bernhardt L Trout
Journal:  Proc Natl Acad Sci U S A       Date:  2009-07-01       Impact factor: 11.205

3.  Weak interactions govern the viscosity of concentrated antibody solutions: high-throughput analysis using the diffusion interaction parameter.

Authors:  Brian D Connolly; Chris Petry; Sandeep Yadav; Barthélemy Demeule; Natalie Ciaccio; Jamie M R Moore; Steven J Shire; Yatin R Gokarn
Journal:  Biophys J       Date:  2012-07-03       Impact factor: 4.033

4.  Entanglement model of antibody viscosity.

Authors:  Jeremy D Schmit; Feng He; Shradha Mishra; Randal R Ketchem; Christopher E Woods; Bruce A Kerwin
Journal:  J Phys Chem B       Date:  2014-05-02       Impact factor: 2.991

5.  Neighboring side chain effects on asparaginyl and aspartyl degradation: an ab initio study of the relationship between peptide conformation and backbone NH acidity.

Authors:  J L Radkiewicz; H Zipse; S Clarke; K N Houk
Journal:  J Am Chem Soc       Date:  2001-04-18       Impact factor: 15.419

6.  Minipig as a potential translatable model for monoclonal antibody pharmacokinetics after intravenous and subcutaneous administration.

Authors:  Yanan Zheng; Devin B Tesar; Lisa Benincosa; Herbert Birnböck; C Andrew Boswell; Daniela Bumbaca; Kyra J Cowan; Dimitry M Danilenko; Ann L Daugherty; Paul J Fielder; Hans Peter Grimm; Amita Joshi; Nicole Justies; Gerry Kolaitis; Nicholas Lewin-Koh; Jing Li; Sami McVay; Jennifer O'Mahony; Michael Otteneder; Michael Pantze; Wendy S Putnam; Zhihua J Qiu; Jane Ruppel; Thomas Singer; Oliver Stauch; Frank-Peter Theil; Jennifer Visich; Jihong Yang; Yong Ying; Leslie A Khawli; Wolfgang F Richter
Journal:  MAbs       Date:  2012-03-01       Impact factor: 5.857

7.  A strategy for risk mitigation of antibodies with fast clearance.

Authors:  Isidro Hötzel; Frank-Peter Theil; Lisa J Bernstein; Saileta Prabhu; Rong Deng; Leah Quintana; Jeff Lutman; Renuka Sibia; Pamela Chan; Daniela Bumbaca; Paul Fielder; Paul J Carter; Robert F Kelley
Journal:  MAbs       Date:  2012 Nov-Dec       Impact factor: 5.857

8.  Development of motavizumab, an ultra-potent antibody for the prevention of respiratory syncytial virus infection in the upper and lower respiratory tract.

Authors:  Herren Wu; David S Pfarr; Syd Johnson; Yambasu A Brewah; Robert M Woods; Nita K Patel; Wendy I White; James F Young; Peter A Kiener
Journal:  J Mol Biol       Date:  2007-02-20       Impact factor: 5.469

9.  Structure-based prediction of asparagine and aspartate degradation sites in antibody variable regions.

Authors:  Jasmin F Sydow; Florian Lipsmeier; Vincent Larraillet; Maximiliane Hilger; Bjoern Mautz; Michael Mølhøj; Jan Kuentzer; Stefan Klostermann; Juergen Schoch; Hans R Voelger; Joerg T Regula; Patrick Cramer; Apollon Papadimitriou; Hubert Kettenberger
Journal:  PLoS One       Date:  2014-06-24       Impact factor: 3.240

10.  Probing antibody internal dynamics with fluorescence anisotropy and molecular dynamics simulations.

Authors:  Ekaterine Kortkhonjia; Relly Brandman; Joe Zhongxiang Zhou; Vincent A Voelz; Ilya Chorny; Bruce Kabakoff; Thomas W Patapoff; Ken A Dill; Trevor E Swartz
Journal:  MAbs       Date:  2013-02-08       Impact factor: 5.857

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  62 in total

1.  Computational tool for the early screening of monoclonal antibodies for their viscosities.

Authors:  Neeraj J Agrawal; Bernhard Helk; Sandeep Kumar; Neil Mody; Hasige A Sathish; Hardeep S Samra; Patrick M Buck; Li Li; Bernhardt L Trout
Journal:  MAbs       Date:  2015-09-23       Impact factor: 5.857

2.  Scale-up of a physiologically-based pharmacokinetic model to predict the disposition of monoclonal antibodies in monkeys.

Authors:  Patrick M Glassman; Yang Chen; Joseph P Balthasar
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-09-12       Impact factor: 2.745

Review 3.  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

4.  Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.

Authors:  Derek M Mason; Simon Friedensohn; Cédric R Weber; Christian Jordi; Bastian Wagner; Simon M Meng; Roy A Ehling; Lucia Bonati; Jan Dahinden; Pablo Gainza; Bruno E Correia; Sai T Reddy
Journal:  Nat Biomed Eng       Date:  2021-04-15       Impact factor: 25.671

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.  In vitro and in silico assessment of the developability of a designed monoclonal antibody library.

Authors:  Adriana-Michelle Wolf Pérez; Pietro Sormanni; Jonathan Sonne Andersen; Laila Ismail Sakhnini; Ileana Rodriguez-Leon; Jais Rose Bjelke; Annette Juhl Gajhede; Leonardo De Maria; Daniel E Otzen; Michele Vendruscolo; Nikolai Lorenzen
Journal:  MAbs       Date:  2019-01-18       Impact factor: 5.857

7.  In-silico prediction of concentration-dependent viscosity curves for monoclonal antibody solutions.

Authors:  Dheeraj S Tomar; Li Li; Matthew P Broulidakis; Nicholas G Luksha; Christopher T Burns; Satish K Singh; Sandeep Kumar
Journal:  MAbs       Date:  2017-01-26       Impact factor: 5.857

Review 8.  Pharmacokinetic de-risking tools for selection of monoclonal antibody lead candidates.

Authors:  Miroslav Dostalek; Thomayant Prueksaritanont; Robert F Kelley
Journal:  MAbs       Date:  2017-05-02       Impact factor: 5.857

9.  Biophysical properties of the clinical-stage antibody landscape.

Authors:  Tushar Jain; Tingwan Sun; Stéphanie Durand; Amy Hall; Nga Rewa Houston; Juergen H Nett; Beth Sharkey; Beata Bobrowicz; Isabelle Caffry; Yao Yu; Yuan Cao; Heather Lynaugh; Michael Brown; Hemanta Baruah; Laura T Gray; Eric M Krauland; Yingda Xu; Maximiliano Vásquez; K Dane Wittrup
Journal:  Proc Natl Acad Sci U S A       Date:  2017-01-17       Impact factor: 11.205

10.  Evaluating the Use of Antibody Variable Region (Fv) Charge as a Risk Assessment Tool for Predicting Typical Cynomolgus Monkey Pharmacokinetics.

Authors:  Daniela Bumbaca Yadav; Vikas K Sharma; Charles Andrew Boswell; Isidro Hotzel; Devin Tesar; Yonglei Shang; Yong Ying; Saloumeh K Fischer; Jane L Grogan; Eugene Y Chiang; Konnie Urban; Sheila Ulufatu; Leslie A Khawli; Saileta Prabhu; Sean Joseph; Robert F Kelley
Journal:  J Biol Chem       Date:  2015-10-21       Impact factor: 5.157

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