AggScore: Prediction of aggregation‐prone regions in proteins based on the distribution of surface patches

Sankar, Kalyanasundaram; Krystek, Stanley R.; Carl, Stephen M.; Day, Tyler; Maier, Johannes

doi:10.1002/prot.25594

Cited by 82 publications

(105 citation statements)

References 58 publications

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“…As the ability of APRs to trigger aggregation depends upon their solvent accessibility, more recent structure-based predictors consider the three-dimensional structure of the protein and in some cases also their potential modes of partial unfolding. Examples include AGGRESCAN 3D [41], AggScore [42], SAP [43] and Solubis [44]. Here, we want to compare the solvent accessibility of APRs in Fab A33, between our MD simulations at the unfolding conditions and at the reference trajectory.…”

Section: Resultsmentioning

confidence: 99%

Insights into the stability of a therapeutic antibody Fab fragment by molecular dynamics and its stabilization by computational design

Codina

Zhang

Chakroun

et al. 2019

Preprint

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23Successful development of protein therapeutics depends critically on achieving stability 24 under a range of conditions, while retaining their specific mode of action. Gaining a deeper 25 understanding of the drivers of instability across different stress conditions, will potentially enable 26 the engineering of protein scaffolds that are inherently manufacturable and stable. Here, we 27 compared the structural robustness of a humanized antibody fragment (Fab) A33 using atomistic 28 molecular dynamics simulations under two different stresses of low pH and high temperature.29 RMSD calculations, structural alignments and contact analysis revealed that low pH unfolding 30 was initiated through loss of contacts at the constant domain interface (C L -C H 1), prior to C L domain 31 unfolding. By contrast, thermal unfolding began with loss of contacts in both the C L -C H 1 and 32 variable domain interface (V L -V H ), followed by domain unfolding of C L and also of V H , thus 33 revealing divergent unfolding pathways. FoldX and Rosetta both agreed that mutations at the C L -34 C H 1 interface have the greatest potential for increasing the stability of Fab A33. Additionally, 35 packing density calculations found these residues to be under-packed relative to other inter-36 domain residues. Two salt bridges were identified that possibly drive the conformational change 37 at low pH, while at high temperature, salt bridges were lost and reformed quickly, and not always 38 with the same partner, thus contributing to an overall destabilization. Sequence entropy analysis 39 of existing Fab sequences revealed considerable scope for further engineering, where certain 40 natural mutations agreed with FoldX and Rosetta predictions. Lastly, the unfolding events at the 41 two stress conditions exposed different predicted aggregation-prone regions (APR), which would 42 potentially lead to different aggregation mechanisms. Overall, our results identified the early 43 stages of unfolding and stability-limiting regions of Fab A33, which provide interesting targets for 44 future protein engineering work aimed at stabilizing to both thermal and pH-stresses 45 simultaneously. 46 3 47 Author Summary 48 49Currently, antibody-based products are the most rapidly growing class of pharmaceuticals 50 due to their high specificity towards their targets, such as biomarkers on the surface of cancer 51 cells. However, they tend to aggregate at all stages of product development, which leads to 52 decreased efficiency and could elicit an immunological response. Improvements in the stability of 53 therapeutic antibodies are generally made during the development phase, by trial and error of the 54 composition of the formulated product, which is both costly and time consuming. There is great 55 demand and potential for identifying the drivers of instability across different stress conditions, 56 early in the discovery phase, which will enable the rational engineering of protein scaffolds. This 57 work elucidated the stability-limiting regions of the ant...

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Section: Resultsmentioning

confidence: 99%

Insights into the stability of a therapeutic antibody Fab fragment by molecular dynamics and its stabilization by computational design

Codina

Zhang

Chakroun

et al. 2019

Preprint

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“…Jain et al addressed this need by subjecting a panel of mAbs to a broad range of typically deployed assays to create a reference dataset . These data enable the assessment of emerging techniques and their relationship to established methods, using mAbs that vary only in the variable domains in common solution conditions (hence without formulation) …”

Section: Discussionmentioning

confidence: 99%

The uniqueness of flow in probing the aggregation behavior of clinically relevant antibodies

Willis

Kumar

Jain

et al. 2020

Engineering Reports

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The development of therapeutic monoclonal antibodies (mAbs) can be hindered by their tendency to aggregate throughout their lifetime, which can illicit immunogenic responses and render mAb manufacturing unfeasible. Consequently, there is a need to identify mAbs with desirable thermodynamic stability, solubility, and lack of self-association. These behaviors are assessed using an array of in silico and in vitro assays, as no single assay can predict aggregation and developability. We have developed an extensional and shear flow device (EFD), which subjects proteins to defined hydrodynamic forces which mimic those experienced in bioprocessing. Here, we utilize the EFD to explore the aggregation propensity of 33 IgG1 mAbs, whose variable domains are derived from clinical antibodies. Using submilligram quantities of material per replicate, wide-ranging EFD-induced aggregation (9-81% protein in pellet) was observed for these mAbs, highlighting the EFD as a sensitive method to assess aggregation propensity. By comparing the EFD-induced aggregation data to those obtained previously from 12 other biophysical assays, we show that the EFD provides distinct information compared with current measures of adverse biophysical behavior. Assessing a candidate's liability to hydrodynamic force thus adds novel insight into the rational selection of developable mAbs that complements other assays. K E Y W O R D S aggregation, developability, extensional flow, monoclonal antibody, shear flowThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…The factors influencing protein A retention are mainly electrostatic and hydrophobic interactions, and conformational flexibility of the mAb during elution. The outputs encompassed hydrophobic moment, total charge, and aggregation propensity (AggScore; Sankar, Krystek, Carl, Day, & Maier, 2018). The team purified four in‐house mAbs through the Highland Games experimental conditions and compared results against homology models of these in‐house molecules.…”

Section: Prediction Methodsmentioning

confidence: 99%

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences

Coffman

Marques

Orozco

et al. 2020

Biotech & Bioengineering

Self Cite

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Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first “Highland Games” competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development‐related properties of six antibodies from their amino acid sequences alone. Predictions included purification‐influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all‐prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in‐house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.

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AggScore: Prediction of aggregation‐prone regions in proteins based on the distribution of surface patches

Cited by 82 publications

References 58 publications

Insights into the stability of a therapeutic antibody Fab fragment by molecular dynamics and its stabilization by computational design

Insights into the stability of a therapeutic antibody Fab fragment by molecular dynamics and its stabilization by computational design

The uniqueness of flow in probing the aggregation behavior of clinically relevant antibodies

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences

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