Multisite λ‑Dynamicsfor Protein–DNABinding Affinity Prediction

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 (ΔΔ<i>G</i>_<i>b</i>) of the WRKY transcription factor upon mutating its W-box binding site (G<u>G</u>T<u>C</u>AA) to a nonspecific sequence (G<u>A</u>T<u>A</u>AA). Among the schemes tested, the single λ per base pair protocol demonstrated the fastest convergence and highest precision. Extending this protocol to additional mutants (GGTC<u>C</u><u>G</u> and GG<u>A</u>CAA) yielded ΔΔ<i>G</i>_<i>b</i> values that successfully ranked binding affinities, showcasing its strong potential for high-throughput screening of DNA binding sites.