Multisite λ-Dynamics for Protein-DNA Binding Affinity Prediction

Abstract

Transcription factors (TFs) regulate gene expression by binding to specific DNA sequences, playing critical roles in cellular processes and disease pathways. Computational methods, particularly λ-Dynamics, offer a promising approach for predicting TF relative binding affinities. This study evaluates the effectiveness of different λ-Dynamics perturbation schemes in determining binding free energy changes (ΔΔGb) of the WRKY transcription factor upon mutating its W-box binding site (GGTCAA) to a nonspecific sequence (GATAAA). Among the schemes tested, the single λ per base pair protocol demonstrated the fastest convergence and highest precision. Extending this protocol to additional mutants (GGTCCG and GGACAA) yielded ΔΔGb values that successfully ranked binding affinities, showcasing its strong potential for high-throughput screening of DNA binding sites.