Biology subjects

Waibl, F.

Publications and source records attributed to Waibl, F..

3 recordsLinked to original sources

bioRxiv2023

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity and Antibody Developability

The electrostatic properties of proteins arise from the number and distribution of polar and charged residues. Due to their long-ranged nature, electrostatic interactions in proteins play a critical role in numerous processes, such as molecular recognition, protein solubility, viscosity, and antibody developability. Thus, characterizing and quantifying electrostatic properties of a protein is a pre-requisite for understanding these processes. Here, we present PEP-Patch, a tool to visualize and quantify the electrostatic potential on the protein surface and showcase its applicability to elucidate protease substrate specificity, antibody-antigen recognition and predict heparin column retention times of antibodies as an indicator of pharmacokinetics.

biophysics↗

bioRxiv2022

Challenges in antibody structure prediction

The tremendous advances in structural biology and the exponential increase of high-quality experimental structures available in the PDB motivated numerous studies to tackle the grand challenge of predicting protein structures. AlphaFold2 revolutionized the field of protein structure prediction, by combining artificial intelligence with evolutionary information. Antibodies are one of the most important classes of biotherapeutic proteins. Accurate structure models are a prerequisite to advance biophysical property predictions and consequently antibody design. Various specialized tools are available to predict antibody structures based on different principles and profiting from current advances in protein structure prediction based on artificial intelligence. Here, we want to emphasize the importance of reliable protein structure models and highlight the enormous advances in the field. At the same time, we want to raise the awareness that protein structure models--and in particular antibody models--may suffer from structural inaccuracies, namely incorrect cis-amid bonds, wrong stereochemistry or clashes. We show that these inaccuracies affect biophysical property predictions such as surface hydrophobicity. Thus, we stress the significance of carefully reviewing protein structure models before investing further computing power and setting up experiments. To facilitate the assessment of model quality, we provide a tool "TopModel" to validate structure models.

bioinformatics↗

bioRxiv2021

OCD.py - Characterizing immunoglobulin inter-domain orientations

SummaryInter-domain orientations between immunoglobulin domains are important for the modeling and engineering of novel antibody therapeutics. Previous tools to describe these orientations are applicable only to the variable domains of antibodies and T-cell receptors. We present the "Orientation of Cylindrical Domains (OCD)" tool, which employs a transferable approach to calculate inter-domain orientations for all immunoglobulin domains. Based on a reference structure, the OCD tool automatically builds a suitable reference coordinate system for each domain. Through alignment, the reference coordinate systems are transferred onto the sample to calculate six measures which fully characterize the inter-domain orientation. Availability and implementationThe OCD approach is implemented as a stand-alone Python script, OCD.py, which can handle multiple types of data input for the analysis of single structures and molecular dynamics trajectories alike. OCD.py is available at https://github.com/liedllab/OCD under MIT license. Supplementary InformationSupplementary information and data are available at Bioinformatics online.

bioinformatics↗