Generalized design of sequence-ensemble-function relationships for intrinsically disordered proteins.

Area of Science:

• Biochemistry
• Computational Biology
• Protein Engineering

Background:

• Recent advances in folded protein design contrast with challenges in designing intrinsically disordered proteins (IDPs).
• IDPs lack stable structures, existing as dynamic ensembles of conformations that dictate function.
• The conformational plasticity and heterogeneity of IDPs make their rational design difficult.

Purpose of the Study:

• To introduce a novel computational framework for the de novo design of intrinsically disordered proteins (IDPs).
• To enable the rational and efficient design of IDPs by inverting molecular simulations and approximating the sequence-ensemble relationship.
• To demonstrate the versatility of the framework in designing IDPs with diverse properties and specific functional requirements.

Main Methods:

• Development of a computational framework for de novo IDP design.
• Utilizing rational and efficient inversion of molecular simulations.
• Approximation of the underlying sequence-ensemble relationship for IDPs.

Main Results:

• Successful design of IDPs with diverse properties and arbitrary sequence constraints.
• Demonstrated ability to design IDPs with targeted ensemble dimensions, loops, and linkers.
• Created IDPs functioning as sensitive sensors and binders to disordered substrates with specific conformational biases.

Conclusions:

• The presented computational framework offers a general approach for designing sequence-ensemble-function relationships in biological macromolecules.
• This method overcomes key challenges in IDP design by directly addressing the sequence-ensemble relationship.
• The framework facilitates the creation of novel IDPs with tailored biological functions.