Natural and synthetic small molecules from the NCI Developmental Therapeutics Program (DTP) were employed in molecular dynamics-based docking with DNA repair proteins whose RNA-Seq based expression was associated with overall cancer survival (OS) after adjustment for the PCNA metagene. The compounds employed were required to elicit a sensitive response (vs. resistance) in more than half of the cell lines tested for each cancer. Methodological approaches included peptide sequence alignments and homology modeling for 3D protein structure determination, ligand preparation, docking, toxicity and ADME prediction. Docking was performed for unique lists of DNA repair proteins which predict OS for AML, cancers of the breast, lung, colon, and ovaries, GBM, melanoma, and renal papillary cancer. Results indicate hundreds of drug-like and lead-like ligands with best-pose binding energies less than -6 kcal/mol. Ligand solubility for the top 20 drug-like hits approached lower bounds, while lipophilicity was acceptable. Most ligands were also blood-brain barrier permeable with high intestinal absorption rates. While the majority of ligands lacked positive prediction for Herg channel blockage and Ames carcinogenicity, there was considerable variation for predicted fathead minnow, honey bee, and Tetrahymena pyriformis toxicity. The computational results suggest the potential for new targets and mechanisms of repair inhibition and can be directly employed for in vitro and in vivo confirmatory laboratory experiments to identify new targets of therapy for cancer survival. polar hydrogens, lone pairs, and water molecules were removed using the .NET assembly of OpenBabel (OB) [47].
Molecular Ligand-Receptor Docking.Ligand-receptor docking is an MD approach for reproducing chemical potentials which determine the bound conformation preference and free energy of binding between a ligand and its receptor. The MD technique seeks to establish the optimal receptor binding pocket (pose) with a minima in the energy profile, shape, and temperature [48], while assuming consistency in the ligand charge distribution and protonation states for the bound and unbound forms. At each receptor pocket identified, several poses are evaluated while iterating through alternative conformations of the ligand at its rotatable covalent bonds.Prior to docking, ligand SMILES strings were converted to 3-dimensional SDF format containing partial charges of each atom. The .NET OB assembly was used for adding hydrogens to ligands and performing energy minimization of ligands and receptors using the Merck MMFF94 force field [49], with 250 iterations during conjugate gradient convergence. Energy-minimized ligands and receptors were saved in PDBQT format. Vina [50] was used for ligand-receptor docking on Amazon AWS cloud formations with Linux high-performance compute clusters. A total of 10 ligand poses were assessed at each receptor pocket identified, and the best pose was assumed to have the lowest binding energy (BE) in kcal/mol. BE values less than -6 kcal/mol are c...