Understanding and predicting molecular binding kinetics remains one of
the central challenges in computational biophysics and drug discovery. The
Simulation-Enabled Estimation of Kinetic Rates (SEEKR) framework provides
a powerful multiscale approach that integrates molecular dynamics
(MD) and Brownian dynamics (BD) simulations to model key biomolecular
processes. By leveraging both atomistic and continuum regimes, SEEKR
enables accurate and efficient estimation of association and dissociation rate
constants (kon and koff) for protein–ligand systems. SEEKR has demonstrated
strong performance across diverse targets, including kinases and chaperone
proteins such as Janus Kinase, Heat Shock Protein 90, and Threonine
Tyrosine Kinase. Crucially, its multiscale design circumvents the limitations
of traditional BD simulations, replacing the empirical “reaction criteria”
with collective variables and MD-based sampling that reveal realistic binding
pathways. Ongoing work focuses on addressing challenges such as charge polarization
upon binding, defining optimal MD/BD interface placement, and
refining the representation of complex reaction pathways. Together, these
developments continue to expand SEEKR’s potential as a general framework
for simulating and understanding molecular recognition dynamics.