PWD/SE-COMBINE

QuantumBio now offers the latest approach for computing protein-ligand interaction energies in the PWD/SE-COMBINE Application (semiempirical pairwise decomposition, along with comparative binding energy analysis). PWD/SE-COMBINE improves overall accuracy and provides new mechanistic insight into protein-ligand interactions.

The PairWise energy Decomposition (PWD) scheme for evaluating the electrostatic interaction energy uses the neglect of nonbonded differential overlap (NNDO) formalism applied to study protein-ligand interaction using the linear scaling QM methods implemented within the DivCon package. This scheme permits the calculation of the self-energy of the atom, core-electron interactions, electron-electron repulsion, and exchange between atoms from the molecular electron density.

Simulations using PWD yield raw atom-by-atom pairwise values which can be difficult to interpret. Therefore, included with the tool is a receptor-based QSAR method, comparative binding energy analysis (COMBINE), which is able to process the data using statistical methods to better understand the active site. This method is coupled with the semi-empirical (SE) QM implementation within DivCon and is referred to as SE-COMBINE.

To ensure QuantumBio's application meets your needs, PWD/SE-COMBINE has been expanded to include molecular mechanics (MM) pairwise energy terms derived from the Lennard-Jones potential in addition to QM energy terms. The MM terms include dispersive/attractive, repulsive, and electrostatic.

Additionally, QuantumBio includes a protein alignment tool to perform PWD/SE-COMBINE analysis on more than one protein.

PWD/SE-COMBINE offers several post analysis datasets that can be selected:

  • PLS Results Table: a table that shows the following statistical results for each number of latent variables (1 to number of components) used in the construction of the PLS models:
    • X_Expl: percent explanation of X variance
    • Act_Expl: percent explanation of activity
    • R2: correlation coefficient (R2)
    • Q2: cross-validated correlation coefficient (Q2)
    • SDEC: standard deviation of error of calculation
    • SDEP: standard deviation of error of prediction
    • SDEP_Ext: standard deviation of error of prediction, external data set
    • R2_Ext: correlation coefficient, external data set
  • Interaction Heat Map: a heat map that makes it easy to identify the residues that have the largest absolute effect on ligand binding.
  • SAR Heat Map: a heat map that highlights residues that are most critical to discriminating between more and less potent ligands.

 

Example Data Results utilizing PWD/SE-COMBINE:

 

SAR Heat Map                                                     Visualization utilizing MOE/DivCon GUI

 

Analysis of the interaction energies, heat maps, and structures show that PWD/SE-COMBINE provides a predictive model for affinity, a clear indication of the most critical residues for binding, and a meaningful indication of the many structural trade-offs necessary to design potent ligands.

To learn more about QMScore, please contact QuantumBio.