Rapid and accurate in silico solubility screening of a monoclonal antibody library

Abstract Antibodies represent essential tools in research and diagnostics and are rapidly growing in importance as therapeutics. Commonly used methods to obtain novel antibodies typically yield several candidates capable of engaging a given target. The development steps that follow, however, are usu...

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Autores principales:	Pietro Sormanni, Leanne Amery, Sofia Ekizoglou, Michele Vendruscolo, Bojana Popovic
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/022e023f1b4041a69a12e49083c3e5d9
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spelling	oai:doaj.org-article:022e023f1b4041a69a12e49083c3e5d92021-12-02T16:06:25ZRapid and accurate in silico solubility screening of a monoclonal antibody library10.1038/s41598-017-07800-w2045-2322https://doaj.org/article/022e023f1b4041a69a12e49083c3e5d92017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-07800-whttps://doaj.org/toc/2045-2322Abstract Antibodies represent essential tools in research and diagnostics and are rapidly growing in importance as therapeutics. Commonly used methods to obtain novel antibodies typically yield several candidates capable of engaging a given target. The development steps that follow, however, are usually performed with only one or few candidates since they can be resource demanding, thereby increasing the risk of failure of the overall antibody discovery program. In particular, insufficient solubility, which may lead to aggregation under typical storage conditions, often hinders the ability of a candidate antibody to be developed and manufactured. Here we show that the selection of soluble lead antibodies from an initial library screening can be greatly facilitated by a fast computational prediction of solubility that requires only the amino acid sequence as input. We quantitatively validate this approach on a panel of nine distinct monoclonal antibodies targeting nerve growth factor (NGF), for which we compare the predicted and measured solubilities finding a very close match, and we further benchmark our predictions with published experimental data on aggregation hotspots and solubility of mutational variants of one of these antibodies.Pietro SormanniLeanne AmerySofia EkizoglouMichele VendruscoloBojana PopovicNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Pietro Sormanni Leanne Amery Sofia Ekizoglou Michele Vendruscolo Bojana Popovic Rapid and accurate in silico solubility screening of a monoclonal antibody library
description	Abstract Antibodies represent essential tools in research and diagnostics and are rapidly growing in importance as therapeutics. Commonly used methods to obtain novel antibodies typically yield several candidates capable of engaging a given target. The development steps that follow, however, are usually performed with only one or few candidates since they can be resource demanding, thereby increasing the risk of failure of the overall antibody discovery program. In particular, insufficient solubility, which may lead to aggregation under typical storage conditions, often hinders the ability of a candidate antibody to be developed and manufactured. Here we show that the selection of soluble lead antibodies from an initial library screening can be greatly facilitated by a fast computational prediction of solubility that requires only the amino acid sequence as input. We quantitatively validate this approach on a panel of nine distinct monoclonal antibodies targeting nerve growth factor (NGF), for which we compare the predicted and measured solubilities finding a very close match, and we further benchmark our predictions with published experimental data on aggregation hotspots and solubility of mutational variants of one of these antibodies.
format	article
author	Pietro Sormanni Leanne Amery Sofia Ekizoglou Michele Vendruscolo Bojana Popovic
author_facet	Pietro Sormanni Leanne Amery Sofia Ekizoglou Michele Vendruscolo Bojana Popovic
author_sort	Pietro Sormanni
title	Rapid and accurate in silico solubility screening of a monoclonal antibody library
title_short	Rapid and accurate in silico solubility screening of a monoclonal antibody library
title_full	Rapid and accurate in silico solubility screening of a monoclonal antibody library
title_fullStr	Rapid and accurate in silico solubility screening of a monoclonal antibody library
title_full_unstemmed	Rapid and accurate in silico solubility screening of a monoclonal antibody library
title_sort	rapid and accurate in silico solubility screening of a monoclonal antibody library
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/022e023f1b4041a69a12e49083c3e5d9
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Rapid and accurate in silico solubility screening of a monoclonal antibody library

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