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A common and significant goal in the design and optimization of biologic drugs is the reliable prediction of the impact of specific residue mutations on protein stability, binding affinity, selectivity, and functional attributes that are correlated with these properties. Exploration of such mutational effects through lab experiments can be costly and time-consuming.

The need to accelerate the design and optimization of biotherapeutics has thus led to renewed interest in computational protein engineering, especially in light of recent remarkable advances in the development of new algorithms and gains in processing power. However, the accuracy of many standard computational approaches for protein engineering is still limited by reliance on biased datasets for training, as well as inadequate representations of essential characteristics of the complex molecular systems being studied.

Free energy perturbation (FEP) offers a rigorous, physics-based approach for accurately computing free energy changes induced by protein residue mutation. FEP incorporates conformational sampling using explicit solvent molecular dynamics and a robust underlying force field for modeling interactions between atoms in the system.

This webcast will highlight a new FEP technology, called FEP+, and presents recent affinity and stability prediction results illustrating the applicability of FEP+ to protein engineering.

You will learn:

• How the FEP+ computational chemistry software platform can accelerate your research and development projects
• How to improve the accuracy of your in silico predictions with proven methodologies
• How to streamline your protein engineering research workflows with integrated software solutions