Literature DB >> 35282775

Computational models for studying physical instabilities in high concentration biotherapeutic formulations.

Marco A Blanco1.   

Abstract

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Entities:  

Keywords:  Biotherapeutics; aggregation; drug formulation; high concentration; molecular modeling; phase separation; physical instabilities; viscosity

Mesh:

Year:  2022        PMID: 35282775      PMCID: PMC8928847          DOI: 10.1080/19420862.2022.2044744

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


  217 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2003-12-22       Impact factor: 11.205

2.  Intermolecular interactions of IgG1 monoclonal antibodies at high concentrations characterized by light scattering.

Authors:  Thomas M Scherer; Jun Liu; Steven J Shire; Allen P Minton
Journal:  J Phys Chem B       Date:  2010-10-14       Impact factor: 2.991

3.  Surface effects on aggregation kinetics of amyloidogenic peptides.

Authors:  Robert Vácha; Sara Linse; Mikael Lund
Journal:  J Am Chem Soc       Date:  2014-08-07       Impact factor: 15.419

4.  Patchy Particle Models to Understand Protein Phase Behavior.

Authors:  Nicoletta Gnan; Francesco Sciortino; Emanuela Zaccarelli
Journal:  Methods Mol Biol       Date:  2019

5.  Concentration dependent viscosity of monoclonal antibody solutions: explaining experimental behavior in terms of molecular properties.

Authors:  Li Li; Sandeep Kumar; Patrick M Buck; Christopher Burns; Janelle Lavoie; Satish K Singh; Nicholas W Warne; Pilarin Nichols; Nicholas Luksha; Davin Boardman
Journal:  Pharm Res       Date:  2014-06-07       Impact factor: 4.200

6.  Interplay between secondary and tertiary structure formation in protein folding cooperativity.

Authors:  Tristan Bereau; Michael Bachmann; Markus Deserno
Journal:  J Am Chem Soc       Date:  2010-09-29       Impact factor: 15.419

7.  Lumry-Eyring nucleated-polymerization model of protein aggregation kinetics. 2. Competing growth via condensation and chain polymerization.

Authors:  Yi Li; Christopher J Roberts
Journal:  J Phys Chem B       Date:  2009-05-14       Impact factor: 2.991

8.  Probing the early stages of prion protein (PrP) aggregation with atomistic molecular dynamics simulations.

Authors:  Francesca Collu; Enrico Spiga; Nesrine Chakroun; Human Rezaei; Franca Fraternali
Journal:  Chem Commun (Camb)       Date:  2018-07-12       Impact factor: 6.222

9.  Sequence determinants of protein phase behavior from a coarse-grained model.

Authors:  Gregory L Dignon; Wenwei Zheng; Young C Kim; Robert B Best; Jeetain Mittal
Journal:  PLoS Comput Biol       Date:  2018-01-24       Impact factor: 4.475

10.  Amyloidogenic motifs revealed by n-gram analysis.

Authors:  Michał Burdukiewicz; Piotr Sobczyk; Stefan Rödiger; Anna Duda-Madej; Paweł Mackiewicz; Małgorzata Kotulska
Journal:  Sci Rep       Date:  2017-10-11       Impact factor: 4.379

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