ABSTRACT
BACKGROUND: The accurate ranking of analogs of lead molecules with respect to their estimated binding free energies to drug targets remains highly challenging in molecular docking due to small relative differences in their free energy values. METHODS: Free energy perturbation (FEP) method, which provides the most accurate relative binding free energy values were earlier used to calculate free energies of many ligands for several important drug targets including Fructose-1,6-BisphosPhatase (FBPase). The availability of abundant structural and experimental binding affinity data for FBPase inhibitors provided an ideal system to evaluate four widely used docking programs, AutoDock, Glide, GOLD and SurflexDock, distinct from earlier comparative evaluation studies. RESULTS: The analyses suggested that, considering various parameters such as docking pose, scoring and ranking accuracy, sensitivity analysis and newly introduced relative ranking score, Glide provided reasonably consistent results in all respects for the system studied in the present work. Whereas GOLD and AutoDock also demonstrated better performance, AutoDock results were found to be significantly superior in terms of scoring accuracy compared to the rest. CONCLUSION: Present analysis serves as a useful guide for researchers working in the field of lead optimization and for developers in upgradation of the docking programs.
Subject(s)
Adenosine Monophosphate/analogs & derivatives , Fructose-Bisphosphatase/chemistry , Molecular Docking Simulation , Software , Adenosine Monophosphate/metabolism , Binding Sites , Drug Design , Fructose-Bisphosphatase/metabolism , Ligands , Protein Binding , ThermodynamicsABSTRACT
A wide range of benzo[c]cinnolines are prepared through a sequential C-C and C-N bond formation by means of an oxidative C-H functionalization. The reaction proceeds via the C-arylation of 1-arylhydrazine-1,2-dicarboxylate with aryl iodide using Pd(OAc)2/AgOAc followed by an oxidative N-arylation in the presence of PhI/oxone in trifluoroacetic acid. It is entirely a new strategy to generate the benzo[c]cinnoline libraries with a diverse substitution pattern.
ABSTRACT
Post-genomic era has led to the discovery of several new targets posing challenges for structure-based drug design efforts to identify lead compounds. Multiple computational methodologies exist to predict the high ranking hit/lead compounds. Among them, free energy methods provide the most accurate estimate of predicted binding affinity. Pathway-based Free Energy Perturbation (FEP), Thermodynamic Integration (TI) and Slow Growth (SG) as well as less rigorous end-point methods such as Linear interaction energy (LIE), Molecular Mechanics-Poisson Boltzmann./Generalized Born Surface Area (MM-PBSA/GBSA) and λ-dynamics have been applied to a variety of biologically relevant problems. The recent advances in free energy methods and their applications including the prediction of protein-ligand binding affinity for some of the important drug targets have been elaborated. Results using a recently developed Quantum Mechanics (QM)/Molecular Mechanics (MM) based Free Energy Perturbation (FEP) method, which has the potential to provide a very accurate estimation of binding affinities to date has been discussed. A case study for the optimization of inhibitors for the fructose 1,6- bisphosphatase inhibitors has been described.
