Monoclonal antibodies are the fastest growing class of therapeutics. However, aggregation limits their shelf life and can lead to adverse immune responses. Assessment and optimization of the long-term antibody stability are therefore key challenges in the biologic drug development. Here, we present a platform based on the analysis of temperature-dependent aggregation data that can dramatically shorten the assessment of the long-term aggregation stability and thus accelerate the optimization of antibody formulations. For a set of antibodies used in the therapeutic areas from oncology to rheumatology and osteoporosis, we obtain an accurate prediction of aggregate fractions for up to three years using the data obtained on a much shorter time scale. Significantly, the strategy combining kinetic and thermodynamic analysis not only contributes to a better understanding of the molecular mechanisms of antibody aggregation but has already proven to be very effective in the development and production of biological therapeutics.

Circular dichroism (CD) spectroscopy is an established biophysical technique to study chiral molecules. CD allows investigating conformational changes under varying experimental conditions and has been used to understand secondary structure, folding, and binding of proteins and nucleic acids. Here, we present ChiraKit, a user-friendly, online, and open-source tool to process raw CD data and perform advanced analysis. ChiraKit features include the calculation of protein secondary structure with the SELCON3 and SESCA algorithms, estimation of peptide helicity using the helix-ensemble model, the fitting of thermal/chemical unfolding or user-defined models, and the decomposition of spectra through singular value decomposition or principal component analysis. ChiraKit can be accessed at https://spc.embl-hamburg.de/.

Significance: Intrinsically disordered proteins (IDPs) do not possess a stable three-dimensional structure but populate partially folded, transient structures. They are involved in numerous cellular processes, often in cooperation with globular proteins. In such complexes, the protein-bound IDPs can be structurally very heterogeneous ranging from folded, stable conformations to those that are dynamic and disordered. The underlaying principles governing this heterogeneity, known also as fuzziness, are obscure. We developed a simple statistical thermodynamic model based on the helix–coil theory that rationalizes diversity of the target-bound IDP ensembles. The model successfully reproduces bound-state IDP dynamics and explains how ensembles modulate their structure and interaction affinity due to mutations. Collectively, this sheds light on the sequence–ensemble relationship of fuzzy IDP–protein complexes.

An established method for the quantitation of the helix content in peptides using circular dichroism (CD) relies on the linear spectroscopic model. This model assumes an average value of the helix-length correction for all peptide conformers, irrespective of the length of the helical segment. Here we assess the validity of this approximation and introduce a more physically realistic ensemble-based analysis of the CD signal in which the length correction is assigned specifically to each ensemble conformer. We demonstrate that the linear model underestimates peptide helicity, with the difference depending on the ensemble composition. We developed a computer program that implements the ensemble model to estimate the peptide helicity. Using this model and the CD data set covering a broad range of helicities, we recalibrate CD baseline parameters and redetermine helix-coil parameters for the alanine-rich peptide. We show that the ensemble model leverages small differences in signal between conformers to extract more information from the experimental data, enabling the determination of several poorly defined quantities, such as the nucleation constant and heat capacity change associated with helix folding. Overall, the presented ensemble-based treatment of the CD signal, together with the recalibrated values of the spectroscopic baseline parameters, provides a coherent framework for the analysis of the peptide helix content.

A non-redundant data set of nanobody-antigen crystal structures is presented. The data set consists of a collection of cleaned pdb files which can be readily used as an input with most automatic analysis software. The accompanying data also include nanobody amino acid sequences with the annotated CDR regions. In the tabular format, we provide data on the interaction properties for each complex such as number of intermolecular interactions, experimental affinity and changes of the solvent accessible area. We also include the data regarding the surface composition of all nanobody and antigen molecules (surface occurrence of each amino acid type and its secondary structure). The data may be used for further structural bioinformatic studies of nanobodies and as the reference data when performing comparisons with the conventional antibodies.