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

Abstract

Solubility is a property of central importance for the use of proteins in research and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are resource-intensive and time-consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the extension of one of such methods, CamSol, to include in the predictions the effect of the pH of the solubility. We illustrate the accuracy of the pH-dependent predictions on a variety of antibodies and other proteins.

Multi-dimensional protein solubility optimization with an ultra-high-throughput microfluidic platform

“…The measured values and trend compare well to previously reported measurements carried out with standard PEG-precipitation assays ( Supplementary Figure 4 ). 23 Notably, in comparison to the previous measurements, 23 the microfluidic-based measurements shown in Figure 3 require 90% less of the protein, have an incubation time of 5 minutes instead of 2 days, have a smaller measurement error as they comprise thousands of data points instead of just tens.…”

“…In Figure 1 , we observe that the relative solubility of lysozyme is 5.7 ± 0.6% PEG at 1 mg/mL, consistent with previous measurements performed with a standard PEG-precipitation assay. 23…”

“…In Figure 1, we observe that the relative solubility of lysozyme is 5.7 ± 0.6% PEG at 1 mg/mL, consistent with previous measurements performed with a standard PEG-precipitation assay. 23 Using the microfluidic platform, the average volume per sample is just 100 pL. Droplets are created at a rate of 100 droplets/second and thus thousands of datapoints can be prepared in very minimal time.…”

“…20,21,23 Obtaining solubility data by sampling the multidimensional formulation space as exhaustively as possible is critical, as the solubility of biologics is highly formulation dependent. 20,21,23 The solubility of proteins can be estimated in silico with methods such as CamSol 7,14 and SAP 24 . However, such methods cannot be used for the exhaustive screening of formulation conditions, and it remains difficult to base critical decisions solely on computational predictions.…”

“…[20][21][22] It remains highly challenging to carry out multidimensional screenings of formulation parameters, in which solubility is measured by varying two or more parameters together (e.g., the pH and the concentrations of some excipients). 20,21,23 Obtaining solubility data by sampling the multidimensional formulation space as exhaustively as possible is critical, as the solubility of biologics is highly formulation dependent. 20,21,23 The solubility of proteins can be estimated in silico with methods such as CamSol 7,14 and SAP 24 .…”