Literature DB >> 32101441

Coarse-Grained Molecular Dynamics Simulations for Understanding the Impact of Short-Range Anisotropic Attractions on Structure and Viscosity of Concentrated Monoclonal Antibody Solutions.

Amjad Chowdhury1,2, Jonathan A Bollinger3, Barton J Dear1,2, Jason K Cheung4, Keith P Johnston1,3, Thomas M Truskett1,5.   

Abstract

Understanding protein-protein interactions in concentrated therapeutic monoclonal antibody (mAb) solutions is desirable for improved drug discovery, processing, and administration. Here, we deduce both the net protein charge and the magnitude and geometry of short-ranged, anisotropic attractions of a mAb across multiple concentrations and cosolute conditions by comparing structure factors S(q) obtained from small-angle X-ray scattering experiments with those from molecular dynamics (MD) simulations. The simulations, which utilize coarse-grained 12-bead models exhibiting a uniform van der Waals attraction, uniform electrostatic repulsion, and short-range attractions between specific beads, are versatile enough to fit S(q) of a wide range of protein concentrations and ionic strength with the same charge on each bead and a single anisotropic short-range attraction strength. Cluster size distributions (CSDs) obtained from best fit simulations reveal that the experimental structure is consistent with small reversible oligomers in even low viscosity systems and help quantify the impact of these clusters on viscosity. The ability to systematically use experimental S(q) data together with MD simulations to discriminate between different possible protein-protein interactions, as well as to predict viscosities from protein CSDs, is beneficial for designing mAbs and developing formulation strategies that avoid high viscosities and aggregation at high concentration.

Keywords:  antibody; coarse-grained modeling; high concentration; molecular dynamics simulations; protein−protein interactions; self-association; small-angle X-ray scattering; structure factor; viscosity

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Year:  2020        PMID: 32101441     DOI: 10.1021/acs.molpharmaceut.9b00960

Source DB:  PubMed          Journal:  Mol Pharm        ISSN: 1543-8384            Impact factor:   4.939


  7 in total

Review 1.  Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies.

Authors:  Rahmad Akbar; Habib Bashour; Puneet Rawat; Philippe A Robert; Eva Smorodina; Tudor-Stefan Cotet; Karine Flem-Karlsen; Robert Frank; Brij Bhushan Mehta; Mai Ha Vu; Talip Zengin; Jose Gutierrez-Marcos; Fridtjof Lund-Johansen; Jan Terje Andersen; Victor Greiff
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

2.  DeepSCM: An efficient convolutional neural network surrogate model for the screening of therapeutic antibody viscosity.

Authors:  Pin-Kuang Lai
Journal:  Comput Struct Biotechnol J       Date:  2022-04-29       Impact factor: 6.155

Review 3.  Unraveling protein's structural dynamics: from configurational dynamics to ensemble switching guides functional mesoscale assemblies.

Authors:  Exequiel Medina; Danielle R Latham; Hugo Sanabria
Journal:  Curr Opin Struct Biol       Date:  2020-11-24       Impact factor: 6.809

Review 4.  The Protein Folding Problem: The Role of Theory.

Authors:  Roy Nassar; Gregory L Dignon; Rostam M Razban; Ken A Dill
Journal:  J Mol Biol       Date:  2021-07-03       Impact factor: 6.151

5.  Calculation of therapeutic antibody viscosity with coarse-grained models, hydrodynamic calculations and machine learning-based parameters.

Authors:  Pin-Kuang Lai; James W Swan; Bernhardt L Trout
Journal:  MAbs       Date:  2021 Jan-Dec       Impact factor: 5.857

Review 6.  Computational models for studying physical instabilities in high concentration biotherapeutic formulations.

Authors:  Marco A Blanco
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

7.  Effects of Monovalent Salt on Protein-Protein Interactions of Dilute and Concentrated Monoclonal Antibody Formulations.

Authors:  Amy Y Xu; Nicholas J Clark; Joseph Pollastrini; Maribel Espinoza; Hyo-Jin Kim; Sekhar Kanapuram; Bruce Kerwin; Michael J Treuheit; Susan Krueger; Arnold McAuley; Joseph E Curtis
Journal:  Antibodies (Basel)       Date:  2022-03-31
  7 in total

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