Pharmacophore modeling improves virtual screening for novel peroxisome proliferator-activated receptor-gamma ligands

Journal of Computer-Aided Molecular Design - Peroxisome proliferator-activated receptor-gamma (PPARγ) is a nuclear hormone receptor involved in regulating various metabolic and immune...     

Pharmacophore modeling and in silico screening for new P450 19 (aromatase) inhibitors

Cytochrome P450 19 (P450 19, aromatase) constitutes a successful target for the treatment of breast cancer. This study analyzes chemical features common to P450 19 inhibitors to develop ligand-based, selective pharmacophore models for this enzyme. The HipHop and HypoRefine algorithms implemented in the Catalyst software package were employed to create both common feature and quantitative models. The common feature model for P450 19 includes two ring aromatic features in its core and two hydrogen bond acceptors at the ends. The models were used as database search queries to identify active compounds from the NCI database.     

Pharmacophore modeling,virtual screening and molecular docking of ATPase inhibitors of HSP70

Heat shock protein 70 is an effective anticancer target as it influences many signaling pathways. Hence the study investigated the important pharmacophore feature required for ATPase inhibitors of HSP70 by generating a ligand based pharmacophore model followed by virtual based screening and subsequent validation by molecular docking in Discovery studio V4.0. The most extrapolative pharmacophore model (hypotheses 8) consisted of four hydrogen bond acceptors. Further validation by external test set prediction identified 200 hits from Mini Maybridge, Drug Diverse, SCPDB compounds and Phytochemicals. Consequently, the screened compounds were refined by rule of five, ADMET and molecular docking to retain the best competitive hits. Finally Phytochemical compounds Muricatetrocin B, Diacetylphiladelphicalactone C, Eleutheroside B and 5-(3-{[1-(benzylsulfonyl)piperidin-4-yl]amino}phenyl)- 4-bromo-3-(carboxymethoxy)thiophene-2-carboxylic acid were obtained as leads to inhibit the ATPase activity of HSP70 in our findings and thus can be proposed for further in vitro and in vivo evaluation.     

Pharmacophore based 3D-QSAR modeling,virtual screening and docking for identification of potential inhibitors of β-secretase

The enzyme β-secretase-1 is responsible for the cleavage of the amyloid precursor protein, a vital step in the process of the formation of amyloid-β peptides which are known to lead to neurodegeneration causing Alzheimer’s disease. Challenges associated with toxicity and blood brain permeation inability of potential inhibitors, continue to evade a successful therapy, thus demanding the search and development of highly active and effective inhibitors. Towards these efforts, we used a ligand based pharmacophore model generation from a dataset of known inhibitors whose activities against β-secretase hovered in the nano molar range. The identified 5 feature pharmacophore model, AHHPR, was validated via three dimensional quantitative structure activity relationship as indicated by r², q² and Pearson R values of 0.9013, 0.7726 and 0.9041 respectively. For a dataset of compounds with nano molar activity, the important pharmacophore features present in the current model appear to be similar with those observed in the models resulting from much wider activity range of inhibitors. Virtual screening of the ChemBridge CNS-Set™, a database having compounds with a better suitability for central nervous system based disorders followed by docking and analysis of the ligand protein interactions resulted in the identification of eight prospective compounds with considerable diversity. The current pharmacophore model can thus be useful for the identification, design and development of potent β-secretase inhibitors which by optimization can be potential therapeutics for Alzheimer’s disease.     

Methodology for the qualitative screening of parallel arrays of potential Am ligands using a photographic film

A screening method for parallel Am³⁺ ligand libraries is presented. The method makes use of α-radiation in combination with a photographic film to detect the complexed Am³⁺. After screening and development of the film spots of varying intensities are obtained. The intensities of the spots correspond with the amount of complexed Am³⁺. This allows a fast discrimination between the Am³⁺ complexation efficiencies of ligands from large libraries. Depending on the exposure time of the film, activities as small as 5 Bq ²⁴¹Am can be detected. Using internal standards a semi-quantitative assessment can be performed.     

Synthesis and evaluation of 2-Nonylaminopyridine derivatives as PPAR ligands

To find novel PPAR ligands, we prepared several 3-{3 or 4-[2-(nonylpyridin-2-ylamino)ethoxy]phenyl}propanoic acid derivatives which were designed based on the structure of our previous PPARgamma ligand 1. In PPAR binding affinity assays, compound 4, which had an ethoxy group at the C-2 position of the propanoic acid of 1, showed selective binding affinity for PPARgamma. Compound 3, with an ethyl group at the C-2 position, was found to be a PPARalpha/gamma dual ligand. Compound 6, the meta isomer of 1, has been shown to be a PPARalpha ligand. The introduction of methyl (7) and ethyl (8) groups to the C-2 position of the propanoic acid of 6 further improved PPARalpha-binding potency. In cell-based transactivation assay, compounds 3 and 4 showed dual-agonist activity toward PPARalpha and PPARgamma. Compound 6 was found to be a triple agonist and compound 8 proved to be a selective PPARalpha agonist. In the human hypodermic preadipocyte differentiation test, it was demonstrated that the maximal activity of compounds 3 and 4 was higher than that of rosiglitazone.     

Novel isomenthone-derived 1,3-diol ligands identified through parallel synthesis and screening catalyse an asymmetric aldol reaction

A library of new (+)-isomenthone-derived 1,3-diol ligands, containing 5 contiguous stereocentres (3 fixed, 2 variable), was prepared in 2 steps by parallel synthesis. Evaluation in parallel identified several different ligands from the library for catalysing a Mukaiyama aldol reaction with 87-90% e.e.     

Solid-phase parallel synthesis of phosphite ligands

Various routes for the synthesis of polymer-bound phosphites and phosphoramidites have been investigated. In the presence of a suitable activator the supported phosphoramidites react cleanly with alcohols to give the corresponding monodentate phosphite ligands in solution. We have applied this novel solid-phase route in the parallel synthesis of several monodentate chiral and achiral phosphite ligands.     

Pharmacophore modelling,virtual screening and molecular docking studies on PLD1 inhibitors

Lipid metabolism plays a significant role in influenza virus replication and subsequent infection. The regulatory mechanism governing lipid metabolism and viral replication is not properly understood to date, but both Phospholipase D (PLD1 and PLD2) activities are stimulated in viral infection. In vitro studies indicate that chemical inhibition of PLD1 delays viral entry and reduction of viral loads. The current study reports a three-dimensional pharmacophore model based on 35 known PLD1 inhibitors. A sub-set of 25 compounds was selected as the training set and the remaining 10 compounds were kept in the test set. One hundred and twelve pharmacophore models were generated; a six-featured pharmacophore model (AADDHR.57) with survival score (2.69) produced a statistically significant three-dimensional quantitative structure–activity relationship model with r² = 0.97 (internal training set), r² = 0.71 (internal test set) and Q² = 0.64. The predictive power of the pharmacophore model was validated with an external test set (r² = 0.73) and a systematic virtual screening work-flow was employed showing an enrichment factor of 23.68 at the top 2% of the dataset (active and decoys). Finally, the model was used for screening of the filtered PubChem database to fetch molecules which can be proposed as potential PLD1 inhibitors for blocking influenza infection.     

Pharmacophore modelling,molecular docking and virtual screening for EGFR (HER 1) tyrosine kinase inhibitors

A pharmacophore model has been developed using diverse classes of epidermal growth factor receptor (EGFR) tyrosine kinase (TK) inhibitors useful in the treatment of human tumours. Among the top 10 generated hypotheses, the second hypothesis, with one hydrogen bond acceptor, one ring aromatic and three hydrophobic features, was found to be the best on the basis of Cat Scramble validation as well as test set prediction (r _training?=?0.89, r _test?=?0.82). The model also maps well to the external test set molecules as well as clinically active molecules and corroborates the docking studies. Finally, 10 hits were identified as potential leads after virtual screening of ZINC database for EGFR TK inhibition. The study may facilitate the designing and discovery of novel EGFR TK inhibitors.     

3D-QSAR and Pharmacophore modeling of 3,5-disubstituted indole derivatives as Pim kinase inhibitors

Structural Chemistry - Indole derivatives are reported in the literature for their excellent kinase inhibition activity, so understanding their structural requirement is important....     

GALAHAD: 1. Pharmacophore identification by hypermolecular alignment of ligands in 3D

Alignment of multiple ligands based on shared pharmacophoric and pharmacosteric features is a long-recognized challenge in drug discovery and development. This is particularly true when the spatial overlap between structures is incomplete, in which case no good template molecule is likely to exist. Pair-wise rigid ligand alignment based on linear assignment (the LAMDA algorithm) has the potential to address this problem (Richmond et al. in J Mol Graph Model 23:199-209, 2004). Here we present the version of LAMDA embodied in the GALAHAD program, which carries out multi-way alignments by iterative construction of hypermolecules that retain the aggregate as well as the individual attributes of the ligands. We have also generalized the cost function from being purely atom-based to being one that operates on ionic, hydrogen bonding, hydrophobic and steric features. Finally, we have added the ability to generate useful partial-match 3D search queries from the hypermolecules obtained. By running frozen conformations through the GALAHAD program, one can utilize the extended version of LAMDA to generate pharmacophores and pharmacosteres that agree well with crystal structure alignments for a range of literature datasets, with minor adjustments of the default parameters generating even better models. Allowing for inclusion of partial match constraints in the queries yields pharmacophores that are consistently a superset of full-match pharmacophores identified in previous analyses, with the additional features representing points of potentially beneficial interaction with the target.     

Pharmacophore identification by molecular modeling and chemometrics: The case of HMG-CoA reductase inhibitors

Summary A methodology based on molecular modeling and chemometrics is applied to identify the geometrical pharmacophore and the stereoelectronic requirements for the activity in a series of inhibitors of 3-hydroxy 3-methylglutaryl coenzyme A (HMG-CoA) reductase, an enzyme involved in cholesterol biosynthesis. These inhibitors present two common structural features—a 3,5-dihydroxy heptanoic acid which mimics the active portion of the natural substrate HMG-CoA and a lipophilic region which carries both polar and bulky groups. A total of 432 minimum energy conformations of 11 homologous compounds showing different levels of biological activity are calculated by the molecular mechanics MM2 method. Five atoms are selected as representatives of the relevant fragments of these compounds and three interatomic distances, selected among 10 by means of a Principal Component Analysis (PCA), are used to describe the three-dimensional disposition of these atoms. A cluster analysis procedure, performed on the whole set of conformations described by these three distances, allows the selection of one cluster whose centroid represents a geometrical model for the HMG-CoA reductase pharmacophore and the conformations included are candidates as binding conformations. To obtain a refinement of the geometrical model and to have a better insight into the requirements for the activity of these inhibitors, the Molecular Electrostatic Potential (MEP) distributions are determined by the MNDO semiempirical method.     

Pharmacophore modelling,atom-based 3D-QSAR generation and virtual screening of molecules projected for mPGES-1 inhibitory activity

COX-2 inhibitors exhibit anticancer effects in various cancer models but due to the adverse side effects associated with these inhibitors, targeting molecules downstream of COX-2 (such as mPGES-1) has been suggested. Even after calls for mPGES-1 inhibitor design, to date there are only a few published inhibitors targeting the enzyme and displaying anticancer activity. In the present study, we have deployed both ligand and structure-based drug design approaches to hunt novel drug-like candidates as mPGES-1 inhibitors. Fifty-four compounds with tested mPGES-1 inhibitory value were used to develop a model with four pharmacophoric features. 3D-QSAR studies were undertaken to check the robustness of the model. Statistical parameters such as r² = 0.9924, q² = 0.5761 and F test = 1139.7 indicated significant predictive ability of the proposed model. Our QSAR model exhibits sites where a hydrogen bond donor, hydrophobic group and the aromatic ring can be substituted so as to enhance the efficacy of the inhibitor. Furthermore, we used our validated pharmacophore model as a three-dimensional query to screen the FDA-approved Lopac database. Finally, five compounds were selected as potent mPGES-1 inhibitors on the basis of their docking energy and pharmacokinetic properties such as ADME and Lipinski rule of five.     

Pharmacophore model for neonicotinoid insecticides

An effective prediction pharmacophore model （RMS = 0.634, Correl = 0.893, Weight = 1.463, Config = 11.940） was successfully obtained by 3D-QSAR based on a series of nAChR （nicotinic acetylcholine receptors） agonists, which consists of a hydrogen- bonding acceptor, a hydrogen-bond donor, a hydrophobic aliphatic and a hydrophobic aromatic centre. This pharmacophore model may provide theoretical basis for designation and development of higher active insecticides.     

Massively parallel screening of the receptorome

The National Institute of Mental Health (NIMH) Psychoactive Drug Screening Program (PDSP) is a resource that provides free screening of novel compounds to academic investigators. This program differs from other public-sector screening programs in that compounds are screened against a large panel of transmembrane receptors, channels, and transporters, a selection that currently includes a large portion of the whole neuro-receptorome. This review discusses the research areas that can profit from this resource, exemplified by recent findings. The first area is the identification of side effects of medications. Examples include the identification of the histamine H(1) receptor as being responsible for weight gain under antipsychotic treatment and the association of 5 HT(2B) receptor agonism with cardiac valvulopathy, which led to the removal of several medications. A second area is the identification of mechanisms of actions of medications and natural products. Examples are the finding that the kappa opioid receptor is the pharmacological target of the potent hallucinogen salvinorin A, that ephedrine and related compounds are not acting through direct sympathomimetic action, the identification of a strong dopaminergic action of WAY 100635, a compound that had been used as a selective 5 HT(1A) antagonist, and the discovery that the metabolite desmethylclozapine activates M(1) muscarinic receptors, an activity that might contribute to the clinical efficacy of the antipsychotic drug clozapine. A third, relatively new area is the identification of inert compounds as agonists for engineered designer receptors that no longer respond to their natural ligand (DREADDs) but exhibit unchanged signaling properties.     

Pharmacophore identification, in silico screening, and virtual library design for inhibitors of the human factor Xa

Factor Xa inhibitors are innovative anticoagulant agents that provide a better safety/efficacy profile compared to other anticoagulative drugs. A chemical feature-based modeling approach was applied to identify crucial pharmacophore patterns from 3D crystal structures of inhibitors bound to human factor Xa (Pdb entries 1fjs, 1kns, 1eqz) using the software LIGANDSCOUT and CATALYST. The complex structures were selected regarding the criteria of high inhibitory potency (i.e. all ligands show K(i) values against factor Xa in the subnanomolar range) and good resolution (i.e. at least 2.2 A) in order to generate selective and high quality pharmacophore models. The resulting chemical-feature based hypotheses were used for virtual screening of commercial molecular databases such as the WDI database. Furthermore, a ligand-based molecular modeling approach was performed to obtain common-feature hypotheses that represent the relevant chemical interactions between 10 bioactive factor Xa inhibitors and the protein, respectively. In a next step a virtual combinatorial library was designed in order to generate new compounds with similar chemical and spatial properties as known inhibitors. The software tool ILIB DIVERSE was used for this procedure in order to provide new scaffolds of this group of anticoagulants. Finally we present the combination of these two techniques, hence virtual screening was performed with selective pharmacophore models in a focused virtual combinatorial database. De novo derived molecular scaffolds that were able to adequately satisfy the pharmacophore criteria are revealed and are promising templates for candidates for further development.     

Pharmacophore and receptor models for neurokinin receptors

Three neurokinin (NK) antagonist pharmacophore models (Models 1-3) accounting for hydrogen bonding groups in the 'head' and 'tail' of NK receptor ligands have been developed by use of a new procedure for treatment of hydrogen bonds during superimposition. Instead of modelling the hydrogen bond acceptor vector in the strict direction of the lone pair, an angle is allowed between the hydrogen bond acceptor direction and the ideal lone pair direction. This approach adds flexibility to hydrogen bond directions and produces more realistic RMS values. By using this approach, two novel pharmacophore models were derived (Models 2 and 3) and a hydrogen bond acceptor was added to a previously published NK2 pharmacophore model [Poulsen et al., J. Comput.-Aided Mol. Design, 16 (2002) 273] (Model 1). Model 2 as well as Model 3 are described by seven pharmacophore elements: three hydrophobic groups, three hydrogen bond acceptors and a hydrogen bond donor. Model 1 contains the same hydrophobic groups and hydrogen bond donor as Models 2 and 3, but only one hydrogen bond acceptor. The hydrogen bond acceptors and donor are represented as vectors. Two of the hydrophobic groups are always aromatic rings whereas the other hydrophobic group can be either aromatic or aliphatic. In Model 1 the antagonists bind in an extended conformation with two aromatic rings in a parallel displaced and tilted conformation. Model 2 has the same two aromatic rings in a parallel displaced conformation whereas Model 3 has the rings in an edge to face conformation. The pharmacophore models were evaluated using both a structure (NK receptor homology models) and a ligand based approach. By use of exhaustive conformational analysis (MMFFs force field and the GB/SA hydration model) and least-squares molecular superimposition studies, 21 non-peptide antagonists from several structurally diverse classes were fitted to the pharmacophore models. More antagonists could be fitted to Model 2 with a low RMS and a low conformational energy penalty than to Models 1 and 3. Pharmacophore Model 2 was also able to explain the NK1, NK2 and NK3 subtype selectivity of the compounds fitted to the model. Three NK 7TM receptor models were constructed, one for each receptor subtype. The location of the antagonist binding site in the three NK receptor models is identical. Compounds fitted to pharmacophore Model 2 could be docked into the NK1, NK2 and NK3 receptor models after adjustment of the conformation of the flexible linker connecting the head and tail. Models I and 3 are not compatible with the receptor models.