GWOVina: A grey wolf optimization approach to rigid and flexible receptor docking

Protein–ligand docking programs are indispensable tools for predicting the binding pose of a ligand to the receptor protein. In this paper, we introduce an efficient flexible docking method, GWOVina , which is a variant of the Vina implementation using the grey wolf optimizer (GWO) and random walk for the global search, and the Dunbrack rotamer library for side‐chain sampling. The new method was validated for rigid and flexible‐receptor docking using four independent datasets. In rigid docking, GWOVina showed comparable docking performance to Vina in terms of ligand pose RMSD, success rate, and affinity prediction. In flexible‐receptor docking, GWOVina has improved success rate compared to Vina and AutoDockFR. It ran 2 to 7 times faster than Vina and 40 to 100 times faster than AutoDockFR. Therefore, GWOVina can play a role in solving the complex flexible‐receptor docking cases and is suitable for virtual screening of compound libraries. GWOVina is freely available at https://cbbio.cis.um.edu.mo/software/gwovina for testing.     

A New,Improved Hybrid Scoring Function for Molecular Docking and Scoring Based on AutoDock and AutoDock Vina

Automated docking is one of the most important tools for structure‐based drug design that allows prediction of ligand binding poses and also provides an estimate of how well small molecules fit in the binding site of a protein. A new scoring function based on AutoDock and AutoDock Vina has been introduced. The new hybrid scoring function is a linear combination of the two scoring function components derived from a multiple linear regression fitting procedure. The scoring function was built on a training set of 2412 protein–ligand complexes from pdbbind database ( www.pdbbind.org.cn , version 2012). A test set of 313 complexes that appeared in the 2013 version was used for validation purposes. The new hybrid scoring function performed better than the original functions, both on training and test sets of protein–ligand complexes, as measured by the non‐parametric Pearson correlation coefficient, R, mean absolute error (MAE), and root‐mean‐square error (RMSE) between the experimental binding affinities and the docking scores. The function also gave one of the best results among more than 20 scoring functions tested on the core set of the pdbbind database. The new AutoDock hybrid scoring function will be implemented in modified version of AutoDock.     

Metabolism of captopril carboxyl ester derivatives for percutaneous absorption

Objectives To determine the metabolism of captopril n‐carboxyl derivatives and how this may impact on their use as transdermal prodrugs. The pharmacological activity of the ester derivatives was also characterised in order to compare the angiotensin converting enzyme inhibitory potency of the derivatives compared with the parent drug, captopril. Methods The metabolism rates of the ester derivatives were determined in vitro (using porcine liver esterase and porcine ear skin) and in silico (using molecular modelling to investigate the potential to predict metabolism). Key findings Relatively slow pseudo first‐order metabolism of the prodrugs was observed, with the ethyl ester displaying the highest rate of metabolism. A strong relationship was established between in‐vitro methods, while in‐silico methods support the use of in‐vitro methods and highlight the potential of in‐silico techniques to predict metabolism. All the prodrugs behaved as angiotensin converting enzyme inhibitors, with the methyl ester displaying optimum inhibition. Conclusions In‐vitro porcine liver esterase metabolism rates inform in‐vitro skin rates well, and in‐silico interaction energies relate well to both. Thus, in‐silico methods may be developed that include interaction energies to predict metabolism rates.     

Molecular docking studies of novel palmitoyl-ligands for cyclooxygenase-2

An in silico approach was adopted to identify potential cyclooxygenase-2 inhibitors through molecular docking studies. The in vivo studies indicated that synthetic palmitoyl derivatives of salicylic acid, para amino phenol, para amino benzoic acid, and anthranilic acid possessed significant pharmacological activities like anti-inflammatory, analgesic, and antipyretic activities. None of the tested substances produced any significant gastric lesions in experimental animals. In an attempt to understand the ligand-protein interactions in terms of the binding affinity, the above synthetic molecules were subjected to docking analysis using AutoDock. The palmitoyl derivatives palmitoyl anthranilic acid, palmitoyl para amino benzoic acid, palmitoyl para amino phenol, and palmitoyl salicylic acid showed better binding energy than the known inhibitor diclofenac bound to 1PXX. All the palmitoyl derivatives made similar interactions with the binding site residues of cyclooxygenase-2 as compared to that of the known inhibitor. Thus, structure-based drug discovery approach was successfully employed to identify some promising pro-drugs for the treatment of pain and inflammation.     

Optimization and computational evaluation of a series of potential active site inhibitors of the V82F/I84V drug-resistant mutant of HIV-1 protease: an application of the relaxed complex method of structure-based drug design

The Relaxed Complex method, an approach to structure-based drug design that incorporates the flexibilities of both the ligand and target protein, was applied to the immunodeficiency virus protease system. The control cases used AutoDock3.0.5 to dock a fully flexible version of the prospective drug JE-2147 (aka SM-319777 or KNI-764) to large ensembles of conformations extracted from conventional, all atom, explicitly solvated molecular dynamic simulations of the wild type, and the V82F/I84V drug-resistant mutant of HIV-1 protease. The best set of run parameters from the control cases produced robust results when used against 2200 different conformations of the wild-type HIV-1 protease or against 2200 conformations of the mutant. The results of the control cases, the published advice from experts, and structural intuition were used to design a new series of 23 potential active site inhibitors. The compounds were evaluated by docking them against 700 different conformations of the V82F/I84V mutant. The results of this first round of lead optimization were quite promising. Approximately one-third of that series performed at least slightly better than the parent compound, and four of those compounds displayed significantly better binding affinities against that drug-resistant mutant (within our computational model).     

Structure-based design of a potent and selective small peptide inhibitor of Mycobacterium tuberculosis 6-hydroxymethyl-7, 8-dihydropteroate synthase: a computer modelling approach

In an attempt to design novel anti-TB drugs, the target chosen is the enzyme 6-hydroxymethyl-7,8-dihydropteroate synthase (DHPS), which is an attractive target since it is present in microorganisms but not in humans. The existing drugs for this target are the sulfa drugs, which have been used for about seven decades. However, single mutations in the DHPS gene can cause resistance to sulfa drugs. Therefore, there is a need for the design of novel drugs. Based on the recently determined crystal structure of Mycobacterium tuberculosis (M.tb) DHPS complexed with a known substrate analogue, and on the crystal structures of E. coli DHPS and Staphylococcus aureus DHPS, we have identified a dipeptide inhibitor with the sequence WK. Docking calculations indicate that this peptide has a significantly higher potency than the sulfa drugs. In addition, the potency is 70-90 times higher for M.tb DHPS as compared to that for the pterin and folate-binding sites of key human proteins. Thus, the designed inhibitor is a promising lead compound for the development of novel antimycobcaterial agents.     

Identification of ssDNA aptamers specific for anti-neuroexcitation peptide III and molecular modeling studies: Insights into structural interactions

Twelve ssDNA aptamers specific for a novel recombinant anti-neuroexcitation peptide (ANEPIII) were identified using the SELEX method from a 79-nucleotide ssDNA pool to purify ANEPIII in a more efficient way. To further understand the binding modes between ssDNA and ANEPIII, fully flexible dinucleotides were docked onto the homology-modeled ANEPIII structure. AutoDocking identified favorable binding sites on ANEPIII for nucleotides, which was valuable for designing more potent ligands.     

Rational Discovery of Dengue Type 2 Non‐Competitive Inhibitors

Various works have been carried out in developing therapeutics against dengue. However, to date, no effective vaccine or anti‐dengue agent has yet been discovered. The development of protease inhibitors is considered as a promising option, but most previous works have involved competitive inhibition. In this study, we focused on rational discovery of potential anti‐dengue agents based on non‐competitive inhibition of DEN‐2 NS2B/NS3 protease. A homology model of the DEN‐2 NS2B/NS3 protease (using West Nile Virus NS2B/NS3 protease complex, 2FP7, as the template) was used as the target, and pinostrobin, a flavanone, was used as the standard ligand. Virtual screening was performed involving a total of 13 341 small compounds, with the backbone structures of chalcone, flavanone, and flavone, available in the ZINC database. Ranking of the resulting compounds yielded compounds with higher binding affinities compared with the standard ligand. Inhibition assay of the selected top‐ranking compounds against DEN‐2 NS2B/NS3 proteolytic activity resulted in significantly better inhibition compared with the standard and correlated well with in silico results. In conclusion, via this rational discovery technique, better inhibitors were identified. This method can be used in further work to discover lead compounds for anti‐dengue agents.