PhosIDP: a web tool to visualize the location of phosphorylation sites in disordered regions.

Charge is a key determinant of intrinsically disordered protein (IDP) and intrinsically disordered region (IDR) properties. IDPs and IDRs are enriched in sites of phosphorylation, which alters charge. Visualizing the degree to which phosphorylation modulates the charge profile of a sequence would assist in the functional interpretation of IDPs and IDRs.

Protein-sol pKa: prediction of electrostatic frustration, with application to coronaviruses.

Motivation: Evolution couples differences in ambient pH to biological function through protonatable groups, in particular, those that switch from buried to exposed and alter protonation state in doing so. We present a tool focusing on structure-based discovery and display of these groups.

Results: Since prediction of buried group pKas is computationally intensive, solvent accessibility of ionizable groups is displayed, from which the user can iteratively select pKa calculation centers.

Modelling of pH-dependence to develop a strategy for stabilising mAbs at acidic steps in production.

Engineered proteins are increasingly being required to function or pass through environmental stresses for which the underlying protein has not evolved. A major example in health are antibody therapeutics, where a low pH step is used for purification and viral inactivation. In order to develop a computational model for analysis of pH-stability, predictions are compared with experimental data for the relative pH-sensitivities of antibody domains.

Charge and hydrophobicity are key features in sequence-trained machine learning models for predicting the biophysical properties of clinical-stage antibodies.

Unlabelled: Improved understanding of properties that mediate protein solubility and resistance to aggregation are important for developing biopharmaceuticals, and more generally in biotechnology and synthetic biology. Recent acquisition of large datasets for antibody biophysical properties enables the search for predictive models. In this report, machine learning methods are used to derive models for 12 biophysical properties.

Web-based display of protein surface and pH-dependent properties for assessing the developability of biotherapeutics.

Protein instability leads to reversible self-association and irreversible aggregation which is a major concern for developing new biopharmaceutical leads. Protein solution behaviour is dictated by the physicochemical properties of the protein and the solution. Optimising protein solutions through experimental screens and targeted protein engineering can be a difficult and time consuming process.

Self-Interaction of Human Serum Albumin: A Formulation Perspective.

In the present study, small-angle X-ray scattering (SAXS) and static light scattering (SLS) have been used to study the solution properties and self-interaction of recombinant human serum albumin (rHSA) molecules in three pharmaceutically relevant buffer systems. Measurements are carried out up to high protein concentrations and as a function of ionic strength by adding sodium chloride to probe the role of electrostatic interactions. The effective structure factors ( ) as a function of the scattering vector magnitude have been extracted from the scattering profiles and fit to the solution of the Ornstein-Zernike equation using a screened Yukawa potential to describe the double-layer force.

Models for Antibody Behavior in Hydrophobic Interaction Chromatography and in Self-Association.

Monoclonal antibodies (mAbs) form an increasingly important sector of the pharmaceutical market, and their behavior in production, processing, and formulation is a key factor in development. With data sets of solution properties for mAbs becoming available, and with amino acid sequences, and structures for many Fabs, it is timely to examine what features correlate with measured data. Here, previously published data for hydrophobic interaction chromatography and the formation of high molecular weight species are studied.

Sequence composition predicts immunoglobulin superfamily members that could share the intrinsically disordered properties of antibody CH1 domains.

Antibodies are central to the growing sector of protein therapeutics, and increasingly they are being manipulated as fragments and combinations. An improved understanding of the properties of antibody domains in isolation would aid in their engineering. We have conducted an analysis of sequence and domain interactions for IgG antibodies and Fab fragments in the structural database.

Coarse-Grained Modeling of Antibodies from Small-Angle Scattering Profiles.

Predicting the concentrated solution behavior for monoclonal antibodies requires developing and using minimal models to describe their shape and interaction potential. Toward this end, the small-angle X-ray scattering (SAXS) profiles for a monoclonal antibody (COE-03) have been measured under solution conditions chosen to produce weak self-association. The experiments are complemented with molecular simulations of a three-bead antibody model with and without interbead attraction.

Protein-Sol: a web tool for predicting protein solubility from sequence.

Motivation: Protein solubility is an important property in industrial and therapeutic applications. Prediction is a challenge, despite a growing understanding of the relevant physicochemical properties.

Results: Protein-Sol is a web server for predicting protein solubility.

The Use of Antibodies in Small-Molecule Drug Discovery.

Antibodies are powerful research tools that can be used in many areas of biology to probe, measure, and perturb various biological structures. Successful drug discovery is dependent on the correct identification of a target implicated in disease, coupled with the successful selection, optimization, and development of a candidate drug. Because of their specific binding characteristics, with regard to specificity, affinity, and avidity, coupled with their amenability to protein engineering, antibodies have become a key tool in drug discovery, enabling the quantification, localization, and modulation of proteins of interest.

Detection of salt bridges to lysines in solution in barnase.

We show that salt bridges involving lysines can be detected by deuterium isotope effects on NMR chemical shifts of the sidechain amine. Lys27 in the ribonuclease barnase is salt bridged, and mutation of Arg69 to Lys retains a partially buried salt bridge. The salt bridges are functionally important.