Ligand‐based pharmacophore modelling and screening of DNA minor groove binders targeting Staphylococcus aureus

The recognition of DNA by small molecules is of special importance in the design of new drugs. Many natural and synthetic compounds have the ability to interact with the minor groove of DNA. In the present study, identification of minor groove binding compounds was attained by the combined approach of pharmacophore modelling, virtual screening and molecular dynamics approach. Experimentally reported 32 minor groove binding compounds were used to develop the pharmacophore model. Based on the fitness score, best three pharmacophore hypotheses were selected and used as template for screening the compounds from drug bank database. This pharmacophore‐based screening provides many compounds with the same pharmacological properties. All these compounds were subjected to four phases of docking protocols with combined Glide‐quantum‐polarized ligand docking approach. Molecular dynamics results indicated that selected compounds are more active and showed good interaction in the binding site of DNA. Based on the scoring parameters and energy values, the best compounds were selected, and antibacterial activity of these compounds was identified using in vitro antimicrobial techniques. Copyright © 2014 John Wiley & Sons, Ltd.     

Design of the influenza virus inhibitors targeting the PA endonuclease using 3D-QSAR modeling,side-chain hopping,and docking

With the emergence of drug resistance and the structural determination of the PA N-terminal domain (PA_N), influenza endonucleases have become an attractive target for antiviral therapies for influenza infection. Here, we combined 3D-QSAR with side-chain hopping and molecular docking to produce novel structures as endonuclease inhibitors. First, a new molecular library was generated with side-chain hopping on an existing template molecule, L-742001, using an in-house fragment library that targets bivalent-cation-binding proteins. Then, the best 3D-QSAR model (AAAHR.500), with q² = 0.76 and r² = 0.97 from phase modeling, was constructed from 23 endonuclease inhibitors and validated with 17 test compounds. The AAAHR.500 model was then used to select effective candidates from the new molecular library. Combining 3D-QSAR with docking using Glide and Autodock, 13 compounds were considered the most likely candidate inhibitors. Docking studies showed that the binding modes of these compounds were consistent with the crystal structures of known inhibitors. These compounds could serve as potential endonuclease inhibitors for further biological activity tests.     

Exploring docking methods for virtual screening: application to the identification of neuraminidase and Ftsz potential inhibitors

Virtual screenings based on molecular docking play a major role in medicinal chemistry for the identification of new bioactive molecules. For this purpose, several docking methods can be used. Here, using Arguslab as software and a Gold Platinum subset library of commercially available compounds from Asinex, two docking methods associated to the scoring function Ascore were employed to investigate virtual screenings. One method is based on a genetic algorithm and the other based on a shape-based method. As case studies, both docking techniques were explored by targeting the PC190723 binding site of FtsZ protein from Staphylococcus aureus and the active site of N8 neuraminidase from Influenza virus. Following four docking sequences for each docking engine, the genetic algorithm led to multiple docking results, whereas the shape-based method gave reproducible results. The present study shows that the stochastic nature of the genetic algorithm will require the biological evaluation of more compounds than the shape-based method. This study showed that both methods are complementary and also led to the identification of neuraminidase and FtsZ potential inhibitors.     

N-(thiazol-2-yl)-2-thiophene carboxamide derivatives as Abl inhibitors identified by a pharmacophore-based database screening of commercially available compounds

Suggestions derived from a previous ligand-based ligand design approach and docking calculations aimed at finding compound with affinity toward Abl and molecular scaffolds previously untested as Abl inhibitors, led to the identification of commercially available N-(thiazol-2-yl)-2-thiophene carboxamide derivatives with affinity in a cell-free assay up to low nanomolar concentrations, significantly enhanced with respect to that of their parent compounds previously reported. In particular, among compounds of the Asinex database, molecular docking simulations guided the choice of high-affinity ligands, predicting their binding mode and their interaction pattern with the Abl catalytic binding site. Moreover, affinity of the new compounds was also rationalized in terms of their interactions with the enzyme.     

Compound prioritization from inverse docking experiment using receptor‐centric and ligand‐centric methods: a case study on Plasmodium falciparum Fab enzymes

Prioritization of compounds using inverse docking approach is limited owing to potential drawbacks in its scoring functions. Classically, molecules ranked by best or lowest binding energies and clustering methods have been considered as probable hits. Mining probable hits from an inverse docking approach is very complicated given the closely related protein targets and the chemically similar ligand data set. To overcome this problem, we present here a computational approach using receptor‐centric and ligand‐centric methods to infer the reliability of the inverse docking approach and to recognize probable hits. This knowledge‐driven approach takes advantage of experimentally identified inhibitors against a particular protein target of interest to delineate shape and molecular field properties and use a multilayer perceptron model to predict the biological activity of the test molecules. The approach was validated using flavone derivatives possessing inhibitory activities against principal antimalarial molecular targets of fatty acid biosynthetic pathway, FabG, FabI and FabZ, respectively. We propose that probable hits can be retrieved by comparing the rank list of docking, quantitative‐structure activity relationship and multilayer perceptron models. Copyright © 2014 John Wiley & Sons, Ltd.     

Homology modeling,molecular docking and spectra assay studies of sterol 14α-demethylase from <Emphasis Type="Italic">Penicillium digitatum</Emphasis>

Sterol 14α-demethylase from Penicillium digitatum (PdCYP51) is a prime target of antifungal drugs for citrus disease in plants. To design novel antifungal compounds, a homology model of PdCYP51 was constructed using the recently reported crystal structure of human CYP51 as the template. Molecular docking was performed to investigate the interaction of four commercial fungicides with the modeled enzyme. The side chain of these compounds interplayed with PdCYP51 mainly through hydrophobic and van der Waals interactions. Biochemical spectra analysis of inhibitors combined with PdCYP51 are also compatible with the docking results. This is the first molecular modeling for PdCYP51 based on the eukaryotic crystal structure of CYP51. The structural information and binding site mapping of PdCYP51 for different inhibitors obtained from this study could aid in screening and designing new antifungal compounds targeting this enzyme.     

Developing novel approaches to improve binding energy estimation and virtual screening: a PARP case study

Poly-(ADP-ribose)-polymerase (PARP) is a promising anti-cancer target as it plays a crucial role in the cellular reparation and survival mechanisms. However, the development of a robust and cost effective experimental technique to screen PARP inhibitors is still a scientific challenge owing to the difficulties in quantitative detection of the enzyme activity. In this work we demonstrate that the computational chemistry tools including molecular docking and scoring can perform on par with the experimental studies in assessing binding constants and in the recovery of active compounds in virtual screening. Using the recently introduced Lead Finder software we were able to dock a set of 142 well characterized PARP inhibitors and obtain a good correlation between the calculated and experimentally measured binding energies with the rmsd of 1.67 kcal mol⁻¹. Additionally, fine-tuning of the energy scaling coefficients within the Lead Finder scoring function has further decreased rmsd to the value of 0.88 kcal mol⁻¹. Moreover, we were able to reproduce the selectivity of ligand binding between the two isoforms of the enzyme-PARP1 and PARP2-suggesting that the Lead Finder software can be used to design isoform-selective inhibitors of PARP. An impressive enrichment was obtained in the virtual screening experiment, in which the mentioned set of PARP inhibitors was mixed with a commercial library of 300,000 compounds. We also demonstrate that the virtual screening performance can be significantly improved by an additional structural filtration of the docked ligand poses through detection of the crucial hydrogen bonding interactions with the enzyme.     

A crystallographic and theoretical study of an (E)-2-Hydroxyiminoethanone derivative: prediction of cyclooxygenase inhibition selectivity of stilbenoids by MM-PBSA and the role of atomic charge

We recently reported that the hydroxyiminoethanone derivative, (E)-OXM, behaves as a highly selective COX-1 inhibitor (COX-1 SI = 833), and also an interesting scaffold with unique characteristics. In the current study, a comprehensive crystallographic and computational study was performed to elucidate its conformational stability and pharmacological activity. Its conformational energy was studied at the B3LYP/6-311G** level of theory and compared to the single-crystal X-ray diffraction data. In addition, computational studies of three structurally different stilbenoid derivatives used as selective COX-1 or COX-2 inhibitors were undertaken to predict their COX selectivity potentials. Flexible docking was performed for all compounds at the active site of both COX-1 and COX-2 enzymes by considering some of the key residues as flexible during the docking operation. In the next step, molecular dynamic simulation and binding free energy calculations were performed by MM-PBSA. Final results were found to be highly dependent on the atomic charges of the inhibitors and the choice of force field used to calculate the atomic charges. The binding conformation of the hydroxyiminoethanone derivative is highly correlated with the type of COX isoform inhibited. Our predictive approach can truly predict the cyclooxygenase inhibition selectivity of stilbenoid inhibitors.     

Design,synthesis, and molecular modelling of pyridazinone and phthalazinone derivatives as protein kinases inhibitors

The design and synthesis of pyridazinone and phthalazinone derivatives are described. Newly synthesized compounds were tested on a panel of four kinases in order to evaluate their activity and potential selectivity. In addition, the promising compounds were tested on four cancer cell lines to examine cytotoxic effects. The compounds inhibited DYRK1A and GSK3 with different activity. SAR analysis and docking calculations were carried out to aid in the interpretation of the results. Taken together, our findings suggest that pyridazinone and phthalazinone scaffolds are interesting starting points for design of potent GSK3 and DYRK1A inhibitors.     

Integrative computational protocol for the discovery of inhibitors of the <Emphasis Type="Italic">Helicobacter pylori</Emphasis> nickel response regulator (NikR)

In order to identify novel inhibitors of the Helicobacter pylori nickel response regulator (HpNikR) an integrative protocol was performed for half a million compounds retrieved from the ZINC database. We firstly implement a structure-based virtual screening to build a library of potential inhibitors against the HpNikR using a docking analysis (AutoDock Vina). The library was then used to perform a hierarchical clustering of docking poses, based on protein-contact footprints calculation from the multiple conformations given by the AutoDock Vina software, and the drug-protein interaction analyses to identify and remove potential promiscuous compounds likely interacting with human proteins, hence causing drug side effects. 250 drug-like compounds were finally proposed as non-promicuous potential inhibitors for HpNikR. These compounds target the DNA-binding sites of HpNikR so that HpNikR-compound binding could be able to mimic key interactions in the DNA-protein recognition process. HpNikR inhibitors with promising potential against H. pylori could also act against other human bacterial pathogens due to the conservation of targeting motif of NikR involved in DNA-protein interaction.     

New molecular scaffolds for the design of Mycobacterium tuberculosis type II dehydroquinase inhibitors identified using ligand and receptor based virtual screening

Using ligand and receptor based virtual screening approaches we have identified potential virtual screening hits targeting type II dehydroquinase from Mycobacterium tuberculosis, an effective and validated anti-mycobacterial target. Initially, we applied a virtual screening workflow based on a combination of 2D structural fingerprints, 3D pharmacophore and molecular docking to identify compounds that rigidly match specific aspects of ligand bioactive conformation. Subsequently, the resulting compounds were ranked and prioritized using receptor interaction fingerprint based scoring and quantitative structure activity relationship model developed using already known actives. The virtual screening hits prioritized belong to several classes of molecular scaffolds with several available substitution positions that could allow chemical modification to enhance binding affinity. Finally, identified hits may be useful to a medicinal chemist or combinatorial chemist to pick up the new molecular starting points for medicinal chemistry optimization for the design of novel type II dehydroquinase inhibitors.     

Computational Design of New Peptide Inhibitors for Amyloid Beta (Aβ) Aggregation in Alzheimer's Disease: Application of a Novel Methodology

Alzheimer''s disease is the most common form of dementia. It is a neurodegenerative and incurable disease that is associated with the tight packing of amyloid fibrils. This packing is facilitated by the compatibility of the ridges and grooves on the amyloid surface. The GxMxG motif is the major factor creating the compatibility between two amyloid surfaces, making it an important target for the design of amyloid aggregation inhibitors. In this study, a peptide, experimentally proven to bind Aβ40 fibrils at the GxMxG motif, was mutated by a novel methodology that systematically replaces amino acids with residues that share similar chemical characteristics and subsequently assesses the energetic favorability of these mutations by docking. Successive mutations are combined and reassessed via docking to a desired level of refinement. This methodology is both fast and efficient in providing potential inhibitors. Its efficiency lies in the fact that it does not perform all possible combinations of mutations, therefore decreasing the computational time drastically. The binding free energies of the experimentally studied reference peptide and its three top scoring derivatives were evaluated as a final assessment/valuation. The potential of mean forces (PMFs) were calculated by applying the Jarzynski‚s equality to results of steered molecular dynamics simulations. For all of the top scoring derivatives, the PMFs showed higher binding free energies than the reference peptide substantiating the usage of the introduced methodology to drug design.     

Ligand-induced conformational changes: improved predictions of ligand binding conformations and affinities

A computational docking strategy using multiple conformations of the target protein is discussed and evaluated. A series of low molecular weight, competitive, nonpeptide protein tyrosine phosphatase inhibitors are considered for which the x-ray crystallographic structures in complex with protein tyrosine phosphatase 1B (PTP1B) are known. To obtain a quantitative measure of the impact of conformational changes induced by the inhibitors, these were docked to the active site region of various structures of PTP1B using the docking program FlexX. Firstly, the inhibitors were docked to a PTP1B crystal structure cocrystallized with a hexapeptide. The estimated binding energies for various docking modes as well as the RMS differences between the docked compounds and the crystallographic structure were calculated. In this scenario the estimated binding energies were not predictive inasmuch as docking modes with low estimated binding energies corresponded to relatively large RMS differences when aligned with the corresponding crystal structure. Secondly, the inhibitors were docked to their parent protein structures in which they were cocrystallized. In this case, there was a good correlation between low predicted binding energy and a correct docking mode. Thirdly, to improve the predictability of the docking procedure in the general case, where only a single target protein structure is known, we evaluate an approach which takes possible protein side-chain conformational changes into account. Here, side chains exposed to the active site were considered in their allowed rotamer conformations and protein models containing all possible combinations of side-chain rotamers were generated. To evaluate which of these modeled active sites is the most likely binding site conformation for a certain inhibitor, the inhibitors were docked against all active site models. The receptor rotamer model corresponding to the lowest estimated binding energy is taken as the top candidate. Using this protocol, correct inhibitor binding modes could successfully be discriminated from proposed incorrect binding modes. Moreover, the ranking of the estimated ligand binding energies was in good agreement with experimentally observed binding affinities.     

The molecular basis of urokinase inhibition: from the nonempirical analysis of intermolecular interactions to the prediction of binding affinity

Urokinase-type plasminogen activator (uPA) is a trypsin-like serine protease that plays a crucial role in angiogenesis process. In addition to its physiological role in healthy organisms, angiogenesis is extremely important in cancer growth and metastasis, resulting in numerous attempts to understand its control and to develop new approaches to anticancer therapy. The α-aminoalkylphosphonate diphenyl esters are well known as highly efficient serine protease inhibitors. However, their mode of binding has not been verified experimentally in details. For a group of average and potent phosphonic inhibitors of urokinase, flexible docking calculations were performed to gain an insight into the active site interactions responsible for observed enzyme inhibition. The docking results are consistent with the previously suggested mode of inhibitors binding. Subsequently, rigorous ab initio study of binding energy was carried out, followed by its decomposition according to the variation–perturbation procedure to reveal stabilization energy constituents with clear physical meaning. Availability of the experimental inhibitory activities and comparison with theoretical binding energy allows for the validation of theoretical models of inhibition, as well as estimation of the possible potential for binding affinity prediction. Since the docking results accompanied by molecular mechanics optimization suggested that several crucial active site contacts were too short, the optimal distances corresponding to the minimum ab initio interaction energy were also evaluated. Despite the deficiencies of force field-optimized enzyme-inhibitor structures, satisfactory agreement with experimental inhibitory activity was obtained for the electrostatic interaction energy, suggesting its possible application in the binding affinity prediction. Figure The comparison of an arrangement of inhibitors within uPA active. Amino acid residues form S1 pocket that binds the variable part of inhibitor molecules     

Design,Synthesis and Evaluation of Fe-S Targeted Adenosine 5′-Phosphosulfate Reductase Inhibitors

Adenosine 5′-phosphosulfate reductase (APR) is an iron-sulfur enzyme that is vital for survival of Mycobacterium tuberculosis during dormancy and is an attractive target for the treatment of latent tuberculosis (TB) infection. The 4Fe-4S cluster is coordinated to APR by sulfur atoms of four cysteine residues, is proximal to substrate, adenosine 5′-phopsphosulfate (APS), and is essential for catalytic activity. Herein, we present an approach for the development of a new class of APR inhibitors. As an initial step, we have employed an improved solid-phase chemistry method to prepare a series of N⁶-substituted adenosine analogues and their 5′-phosphates as well as adenosine 5′-phosphate diesters bearing different Fe and S binding groups, such as thiols or carboxylic and hydroxamic acid moieties. Evaluation of the resulting compounds indicates a clearly defined spacing requirement between the Fe-S targeting group and adenosine scaffold and that smaller Fe-S targeting groups are better tolerated. Molecular docking analysis suggests that the S atom of the most potent inhibitor may establish a favorable interaction with an S atom in the cluster. In summary, this study showcases an improved solid-phase method that expedites the preparation of adenosine and related 5′-phosphate derivatives and presents a unique Fe-S targeting strategy for the development of APR inhibitors.