Prediction of Ligand−Receptor Binding Thermodynamics by Free Energy Force Field (FEFF) 3D-QSAR Analysis:  Application to a Set of Peptidometic Renin Inhibitors

Abstract

A methodology is presented and applied in which the accurate estimation of ligand-receptor binding thermodynamics is achieved by formulating the calculation as a QSAR problem. When the receptor geometry is known, the free energy force field (FEFF) ligand-receptor binding energy terms can be calculated and used as independent variables in constructing FEFF 3D-QSARs. The FEFF 3D-QSAR analysis of a series of transition state inhibitors of renin was carried out. From a statistical analysis of the free energy contributions to the binding process, FEFF 3D-QSARs were constructed that reveal the change in solvation free energy upon binding and the intramolecular vacuum internal energy of the ligand in the unbound state are the most significant FEFF terms in determining the binding free energy, delta G. Other terms, such as ligand stretching, bending, and torsion energy changes, the intermolecular van der Waals interaction energy, and change in ligand conformational entropy upon binding, are also found to make significant contributions in some FEFF 3D-QSAR delta G models and in delta H and delta S binding models. Overall, a relatively small number of the thermodynamic contributions to the ligand-receptor binding process dominates the thermodynamics of binding in a given model.

Novel Capsaicin Analogues as Potential Anticancer Agents: Synthesis, Biological Evaluation, and In Silico Approach

“…MD simulations of 1 ns (step size of 1 fs) at 310 K were performed for each molecular model. Dielectric constant of 3.5 was used to simulate the environment of biological membranes and enzyme or receptor binding sites [35]. It was assigned a fictitious atomic mass of 5000 u.m.a.…”

Ligand solvation in molecular docking

“…Dividing the solvation and interaction terms into electrostatic and non-electrostatic components is not rigorously correct, 13 but the approximation is often reasonable. 24 The binding energy score equation becomes:…”

Quantized Surface Complementarity Diversity (QSCD): A Model Based on Small Molecule−Target Complementarity

“…The latter assignment is based on an assumption that hydrophobic effects are, on average, the largest single component contributing to ligand/target interaction. 17 In sum, the above process implies as a basis set for molecular diversity 1.1 × 10 14 theoretical target surfaces of negative volume between 460 and 1070 cubic Å and having four sites of specific molecular property characteristics P [1][2][3][4][5][6][7] . The numerical breakdown of these 110 trillion surfaces is listed in Table 1.…”

“…In a pharmaceutical setting, it follows that molecular diversity can be defined as the measure, based on biological criteria, of the difference or similarity between small molecules. Largely due to continuing advances in our understanding of the principles of molecular recognition, [14][15][16][17][18][19][20][21][22][23][24] there exist today many methods of calculating biologically relevant diversity of small molecules. 25,26 Each method defines slightly different criteria for molecular comparison, and each thereby presents a different configuration of diversity space as a whole.…”