Performance Evaluation of Docking Programs- Glide, GOLD, AutoDock & SurflexDock, Using Free Energy Perturbation Reference Data: A Case Study of Fructose-1, 6-bisphosphatase-AMP Analogs.

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.

Advances in binding free energies calculations: QM/MM-based free energy perturbation method for drug design.

Multiple approaches have been devised and evaluated to computationally estimate binding free energies. Results using a recently developed Quantum Mechanics (QM)/Molecular Mechanics (MM) based Free Energy Perturbation (FEP) method suggest that this method has the potential to provide the most accurate estimation of binding affinities to date. The method treats ligands/inhibitors using QM while using MM for the rest of the system. The method has been applied and validated for a structurally diverse set of fructose 1,6- bisphosphatase (FBPase) inhibitors suggesting that the approach has the potential to be used as an integral part of drug discovery for both lead identification lead optimization, where there is a structure available. In addition, this QM/MM-based FEP method was shown to accurately replicate the anomalous hydration behavior exhibited by simple amines and amides suggesting that the method may also prove useful in predicting physical properties of molecules. While the method is about 5-fold more computationally demanding than conventional FEP, it has the potential to be less demanding on the end user since it avoids development of MM force field parameters for novel ligands and thereby eliminates this time-consuming step that often contributes significantly to the inaccuracy of binding affinity predictions using conventional FEP methods. The QM/MM-based FEP method has been extensively tested with respect to important considerations such as the length of the simulation required to obtain satisfactory convergence in the calculated relative solvation and binding free energies for both small and large structural changes between ligands. Future automation of the method and parallelization of the code is expected to enhance the speed and increase its use for drug design and lead optimization.

Virtual screening of cathepsin k inhibitors using docking and pharmacophore models.

Cathepsin K is a lysosomal cysteine protease that is highly and selectively expressed in osteoclasts, the cells which degrade bone during the continuous cycle of bone degradation and formation. Inhibition of cathepsin K represents a potential therapeutic approach for diseases characterized by excessive bone resorption such as osteoporosis. In order to elucidate the essential structural features for cathepsin K, a three-dimensional pharmacophore hypotheses were built on the basis of a set of known cathepsin K inhibitors selected from the literature using catalyst program. Several methods are used in validation of pharmacophore hypothesis were presented, and the fourth hypothesis (Hypo4) was considered to be the best pharmacophore hypothesis which has a correlation coefficient of 0.944 with training set and has high prediction of activity for a set of 30 test molecules with correlation of 0.909. The model (Hypo4) was then employed as 3D search query to screen the Maybridge database containing 59,000 compounds, to discover novel and highly potent ligands. For analyzing intermolecular interactions between protein and ligand, all the molecules were docked using Glide software. The result showed that the type and spatial location of chemical features encoded in the pharmacophore are in full agreement with the enzyme inhibitor interaction pattern identified from molecular docking.

Calculation of relative binding affinities of fructose 1,6-bisphosphatase mutants with adenosine monophosphate using free energy perturbation method.

The free energy perturbation (FEP) methodology is the most accurate means of estimating relative binding affinities between inhibitors and protein variants. In this article, the importance of hydrophobic and hydrophilic residues to the binding of adenosine monophosphate (AMP) to the fructose 1,6-bisphosphatase (FBPase), a target enzyme for type-II diabetes, was examined by FEP method. Five mutations were made to the FBPase enzyme with AMP inhibitor bound: 113Tyr --> 113Phe, 31Thr --> 31Ala, 31Thr --> 31Ser, 177Met --> 177Ala, and 30Leu --> 30Phe. These mutations test the strength of hydrogen bonds and van der Waals interactions between the ligand and enzyme. The calculated relative free energies indicated that: 113Tyr and 31Thr play an important role, each via two hydrogen bonds affecting the binding affinity of inhibitor AMP to FBPase, and any changes in these hydrogen bonds due to mutations on the protein will have significant effect on the binding affinity of AMP to FBPase, consistent to experimental results. Also, the free energy calculations clearly show that the hydrophilic interactions are more important than the hydrophobic interactions of the binding pocket of FBPase.