Sequence-based prediction of pH-dependent protein solubility using CamSol

Abstract

Solubility is a property of central importance for the use of proteins in research in molecular and cell biology and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are material intensive and time consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of solubility for large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the development of one such method to include in the predictions the effect of the pH on solubility. We illustrate the resulting pH-dependent predictions on a variety of antibodies and other proteins to demonstrate that these predictions achieve an accuracy comparable with that of experimental methods. We make this method publicly available at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolph, as the version 3.0 of CamSol.

Sequence-based prediction of the solubility of peptides containing non-natural amino acids

“…However, experimental methods to evaluate the developability of peptides containing mAAs are typically costly, and current computational approaches lack the capability of capturing the effects of mAAs on the solubility of peptides. To address this problem, we have presented CamSol-PTM, a software that predicts the solubility of peptides and proteins containing non-canonical amino acids based on the physico-chemical properties of their amino acid sequences [74][75][76] .…”

“…In this work we exploited the CamSol framework for the accurate prediction of the solubility of proteins [74][75][76] to introduce a method able to predict the effect of mAAs on the solubility of peptides. The original CamSol method predicts the solubility of proteins by combining tabulated values of hydrophobicity, charge, and α-helical and β-sheet propensities of the 20 standard amino acids.…”

“…To bridge this gap, here we exploited the CamSol framework for the prediction of solubility [74][75][76] to develop the CamSol-PTM method, which can handle peptides containing mAAs. CamSol-PTM is capable of assessing the effect of any kind of small-size non-canonical amino acid on the solubility of peptides by combining a range of different physico-chemical property predictors.…”

Critical Assessment of pH‐Dependent Lipophilicity Profiles of Small Molecules: Which One Should We Use and In Which Cases?

“…Despite the lack of a consensus formalism to model log D pH as a function of $${P_{{\rm{IP}}}^{{\rm{app}}} }$$ , and considering that different theoretical approaches have shown similar trends, [14,21,22] Equation 2 has been successfully used for modeling the lipophilicity of ionized compounds in many areas of basic and applied sciences. For instance, to study the aggregation of naphthenic acids in aqueous environments with different saline concentrations, [50] in log D pH calculations for lignin derivatives and small datasets of drug‐like compounds in different solvents by QM and statistical thermodynamical methods, [51] partitioning of antioxidants, [52] aquatic hazard assessment of ionizable organic chemicals, [53] sorption mechanisms of antimicrobials in the soil, [54] and physicochemical properties of peptides and proteins [15–18] …”

Automated optimisation of solubility and conformational stability of antibodies and proteins

“…Both algorithms have separately been validated on experimental data for a wide range of proteins and antibodies (CamSol Refs. 4,14,23,37,[39][40][41][42][43][44]34,[45][46][47][48]. Our method also includes an ad-hoc recipe to obtain and exploit suitable phylogenetic information for immunoglobulin variable domains, as these are a key class of biologics that, because of their modular nature, cannot be handled with standard tools for searching homologs.…”