Locuaz: an in silico platform for protein binders optimization

Area of Science:

• Biochemistry
• Computational Biology
• Protein Engineering

Background:

• Engineering high-affinity protein binders for specific targets is experimentally intensive.
• Computational methods offer potential for accelerating binder optimization but require broad applicability and efficiency.

Purpose of the Study:

• To introduce a novel computational platform for optimizing protein binders.
• To enhance the efficiency and reduce the cost of designing high-affinity binders.

Main Methods:

• A modular computational platform for protein binder optimization.
• Includes modules for mutation selection, molecular dynamics simulations, and affinity scoring.
• Supports parallel processing for in silico high-throughput screening on High Performance Computing (HPC) systems.

Main Results:

• The platform enables efficient exploration of mutations and affinity evaluation.
• Facilitates parallel exploration of mutation pathways for accelerated screening.
• Offers a customizable framework for implementing user-defined protocols.

Conclusions:

• The developed platform significantly accelerates the optimization of protein binders.
• Reduces the need for extensive experimental screening in binder design.
• Provides a flexible and efficient computational tool for protein engineering.