Accurate prediction of the binding affinities of protein–ligand complexes is an extremely challenging task. Typically, the protein–ligand binding affinities are estimated based on scores obtained from knowledge-based or empirical scoring functions, or from energy functions based on molecular mechanics (MM) force-fields. Although such methods are extensively used in predicting protein–ligand binding affinities, they inherently lack a rigorous description of the underlying intermolecular interactions (e.g., charge-transfer, π-π interactions, many-body effects, etc.), and do not provide a reliable quantification of such interactions critical to design a potent drug. In such cases, a high-level quantum mechanical (QM) treatment can be very useful to correct for the deficiencies in the classical description of such interactions. Unfortunately, the steep computational scaling of traditional quantum mechanical methods limits their applicability for large molecules. We have developed the Molecules-in-Molecules (MIM) fragment-based approach to overcome these bottlenecks and to enable accurate calculations on such systems.<br/>            In this study, we present the first application of our MIM method for the computation of interaction energies associated with protein–ligand binding. The performance of our approach has been assessed using the diverse sets of ligands bound to different proteins where experimental binding affinities are available, and compared with other theoretical methods. We also present an energy decomposition analysis protocol within our MIM framework (MIM-EDA) to break down the contributions from individual ligand-residue pairs into four physically important interaction components, viz., electrostatics, exchange-repulsion, polarization, and dispersion. MIM-EDA provides a quantitative description of the residue-specific interactions responsible for the observed difference in binding potencies of seemingly identical ligands. Using a representative set of ligand-receptor complexes, we demonstrate that MIM-EDA provides a fundamental understanding of ligand-residue interactions crucial to analyze the observed biological activities. Our protocol offers a reliable estimate of relative binding potencies of protein–ligand complexes and, in conjunction with interaction energy partitioning, can be an effective tool for structure-based drug design.<br/>

Exploring protein–ligand interactions using molecules-in-molecules (MIM) fragment-based approach

256th National Meeting (2018)

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