Related Experiment Video
Updated: Jan 2, 2026
05:08
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
Published on: July 8, 2025
863
Advancing Therapeutic Protein Discovery and Development through Comprehensive Computational and Biophysical
Lorenzo Gentiluomo1,2, Hristo L Svilenov2, Dillen Augustijn3
1Wyatt Technology Europe GmbH , Hochstrasse 18 , 56307 Dernbach , Germany.
Molecular Pharmaceutics
|December 3, 2019
Summary
Developing effective therapeutic proteins requires guidelines for early selection. This study suggests using computational and biophysical characterization across various conditions to assess protein stability and predict aggregation risk for drug development.
Area of Science:
- Biopharmaceutical Development
- Protein Chemistry
- Analytical Chemistry
Background:
- Establishing guidelines for selecting therapeutic protein candidates with optimal drug-like properties is crucial for early-stage development.
- Current characterization methods for therapeutic proteins often lack standardization, hindering efficient selection processes.
- Orthogonal techniques applied to diverse protein formulations are needed to build a robust knowledge base for protein developability.
Purpose of the Study:
- To investigate correlations between computational and biophysical parameters of diverse therapeutic protein candidates.
- To evaluate the impact of formulation conditions (pH, ionic strength) on protein stability and aggregation.
- To develop and validate risk scores for early-stage developability assessment of therapeutic proteins.
Main Methods:
- Characterization of diverse protein candidates including primary sequences, purity, and computational/biophysical properties.
- Assessment of protein behavior across varying pH and ionic strength conditions.
- Calculation of stability risk scores based on analytical effort and correlation with storage-induced protein aggregation.
Main Results:
- Weak linear correlations were observed between many biophysical parameters.
- Protein stability is significantly influenced by solution conditions, determining stability thresholds.
- Developed stability risk scores showed correlation with protein aggregation during storage.
Conclusions:
- A comprehensive stability assessment of therapeutic protein candidates requires characterization under multiple formulation conditions.
- Combined risk scores, informed by stability data across different solutions, are essential for accurate early-stage developability assessment.
- The proposed approach using computational and biophysical characterization can enhance the prediction accuracy of protein aggregation and improve therapeutic protein selection.
