Mapping polymerization and allostery of hemoglobin S using point mutations.

Area of Science:

• Biophysics
• Computational Biology
• Molecular Modeling

Background:

• Hemoglobin (Hb) exhibits complex conformational dynamics influenced by oxygen, allosteric effectors, mutations, and environmental factors.
• Understanding these dynamics is crucial for deciphering Hb function and dysfunction, particularly in diseases like sickle cell disease.

Purpose of the Study:

• To investigate allostery and polymerization in hemoglobin and its variants using advanced computational methods.
• To predict the impact of numerous mutations on Hb's oxygen binding and polymerization propensity.

Main Methods:

• Application of AllosMod for simulating allosteric dynamics between different Hb structures.
• Utilizing a machine-learning approach for predicting mutation effects on Hb allostery, extended to multi-site systems.
• Analysis of 866 annotated mutations and a subset of 30 mutations associated with sickle cell disease.

Main Results:

• Predicted relative stabilities of Hb substates and microstates, primarily driven by entropy.
• Identified 866 mutations impacting Hb oxygen binding equilibrium.
• Seven sickle cell-related mutations identified within three potential druggable pockets that could inhibit polymerization; one pocket emerged only in simulated structures.

Conclusions:

• Mutation-induced conformational changes within a single Hb tetramer have limited impact on polymerization; direct perturbation of the polymerization interface is more significant.
• The study provides insights into the evolution of Hb's multi-subunit structure and the persistence of the sickle cell mutation.
• Identified potential therapeutic strategies targeting specific binding pockets to inhibit Hb polymerization.