Predicting the potency of hERG K<Superscript>+</Superscript> channel inhibition by combining 3D-QSAR pharmacophore and 2D-QSAR models

Blockade of the hERG K⁺ channel has been identified as the most important mechanism of QT interval prolongation and thus inducing cardiac risk. In this work, an ensemble of 3D-QSAR pharmacophore models was constructed to provide insight into the determinants of the interactions between the hERG K⁺ channel and channel inhibitors. To predict hERG inhibitory activities, the predicted values from the ensemble of models were averaged, and the results thus obtained showed that the predictive ability of the combined 3D-QSAR pharmacophore model was greater that those of the individual models. Also, using the same training and test sets, a 2D-QSAR model based on a heuristic machine-learning method was developed in order to analyze the physicochemical characters of hERG inhibitors. The models indicated that the inhibitors have certain key inhibitory features in common, including hydrophobicity, aromaticity, and flexibility. A final model was developed by combining the combined 3D-QSAR pharmacophore with the 2D-QSAR model, and this final model outperformed any other individual model, showing the highest predictive ability and the lowest deviation. This model can not only predict hERG inhibitory potency accurately, thus allowing fast cardiac safety evaluation, but it provides an effective tool for avoiding hERG inhibitory liability and thus enhanced cardiac risk in the design and optimization of new chemical entities.     

Identification of novel, less toxic PTP-LAR inhibitors using in silico strategies: pharmacophore modeling, SADMET-based virtual screening and docking

Human leukocyte antigen-related (PTP-LAR) is a receptor-like transmembrane phosphatase and a potential target for diabetes, obesity and cancer. In the present study, a sequence of in silico strategies (pharmacophore mapping, a 3D database searching, SADMET screening, and docking and toxicity studies) was performed to identify eight novel nontoxic PTP-LAR inhibitors. Twenty different pharmacophore hypotheses were generated using two methods; the best (hypothesis 2) consisted of three hydrogen-bond acceptor (A), one ring aromatic (R), and one hydrophobic aliphatic (Z) features. This hypothesis was used to screen molecules from several databases, such as Specs, IBS, MiniMaybridge, NCI, and an in-house PTP inhibitor database. In order to overcome the general bioavailability problem associated with phosphatases, the hits obtained were filtered by Lipinski’s rule of five and SADMET properties and validated by molecular docking studies using the available crystal structure 1LAR. These docking studies suggested the ligand binding pattern and interactions required for LAR inhibition. The docking analysis also revealed that sulfonylurea derivatives with an isoquinoline or naphthalene scaffold represent potential LAR drugs. The screening protocol was further validated using ligand pharmacophore mapping studies, which showed that the abovementioned interactions are indeed crucial and that the screened molecules can be presumed to possess potent inhibitory activities.     

Farnesyltransferase pharmacophore model derived from diverse classes of inhibitors

A three-dimensional pharmacophore model was developed based on 25 currently available inhibitors, which were carefully selected with great diversity in both molecular structure and bioactivity as required by HypoGen program in the Catalyst software, for discovering new farnesyltransferase (FTase) inhibitors. The best hypothesis (Hypo1), consisting of four features, namely, two hydrogen-bond acceptors, one hydrophobic point, and one ring aromatic feature, has a correlation coefficient of 0.949, a root-mean-square deviation of 1.321, and a cost difference of 163.15, suggesting that a highly predictive pharmacophore model was successfully obtained. The application of the model shows great success in predicting the activities of 227 known FTase inhibitors in our test set with a correlation coefficient of 0.776 with a cross-validation of 98% confidence level. Accordingly, our model should be reliable in identifying structurally diverse compounds with desired biological activity.     

Virtual screening and QSAR study of some pyrrolidine derivatives as α-mannosidase inhibitors for binding feature analysis

Virtual screening and QSAR analysis were carried out to investigate the binding features of (2R, 3R, 4S)-2-aminomethylpyrrolidine 3,4-diol and the functionalized pyrrolidine derivatives to the α-mannosidase I and II enzymes. The QSAR models (possessed considerable R², Q² values, etc.) suggested that the presence of polar property on the vdW surface (vsurf_W, vsurf_Wp, etc.) of the molecules is important along with the presence of aromatic rings (opr_violation) in the molecules (which also provide hydrophobicity to the molecules). The docking study performed on α-mannosidase I and II enzymes pointed that the main interactions occur by hydrogen bonds, hydrophobic π–π stacking contacts and salt bridges with the cation calcium (for α-mannosidase I) and close interaction with zinc ion (α-mannosidase II), respectively. The bond flexibility orientates the aromatic ring in the molecules toward the hydrophobic cavity for π–π stacking contacts with the aromatic amino acids (Phe528, Phe329 and Phe659 for α-mannosidase I and Trp95, Tyr269, Phe312, Tyr102 for α-mannosidase II). The pharmacophore analysis also supports the results derived from the docking and QSAR studies. Our results suggest that the best compound to inhibit both classes of α-mannosidase is the compound 30, which may be used to design similar and better inhibitors to next generation drugs.     

Molecular dynamic simulations and structure-based pharmacophore development for farnesyltransferase inhibitors discovery

Farnesyltransferase is one of the enzyme targets for the development of drugs for diseases, including cancer, malaria, progeria, etc. In the present study, the structure-based pharmacophore models have been developed from five complex structures (1LD7, 1NI1, 2IEJ, 2ZIR and 2ZIS) obtained from the protein data bank. Initially, molecular dynamic (MD) simulations were performed for the complexes for 10?ns using AMBER 12 software. The conformers of the complexes (75) generated from the equilibrated protein were undergone protein–ligand interaction fingerprint (PLIF) analysis. The results showed that some important residues, such as LeuB96, TrpB102, TrpB106, ArgB202, TyrB300, AspB359 and TyrB361, are predominantly present in most of the complexes for interactions. These residues form side chain acceptor and surface (hydrophobic or π–π) kind of interactions with the ligands present in the complexes. The structure-based pharmacophore models were generated from the fingerprint bits obtained from PLIF analysis. The pharmacophore models have 3–4 pharmacophore contours consist of acceptor and metal ligation (Acc & ML), hydrophobic (HydA) and extended acceptor (Acc2) features with the radius ranging between 1–3?Å for Acc & ML and 1–2?Å for HydA. The excluded volumes of the pharmacophore contours radius are between 1–2?Å. Further, the distance between the interacting groups, root mean square deviation (RMSD), root mean square fluctuation (RMSF) and radial distribution function (RDF) analysis were performed for the MD-simulated proteins using PTRAJ module. The generated pharmacophore models were used to screen a set of natural compounds and database compounds to select significant HITs. We conclude that the developed pharmacophore model can be a significant model for the identification of HITs as FTase inhibitors.     

Are hERG channel blockers also phospholipidosis inducers?

Both pharmacophore models of the human ether-à-go-go-related gene (hERG) channel blockers and phospholipidosis (PLD) inducers contain a hydrophobic moiety and a hydrophilic motif/positively charged center, so it is interesting to investigate the overlap between the ligand chemical spaces of both targets. We have assayed over 4000 non-redundant drug-like compounds for both their hERG inhibitory activity and PLD inducing potential in a quantitative high throughput screening (qHTS) format. Seventy-seven percent of PLD inducing compounds identified from the screening were also found to be hERG channel blockers, and 96.9% of the dually active compounds were positively charged. Among the 48 compounds that induced PLD without inhibiting hERG channel, 24 compounds (50.0%) carried steroidal structures. According to our results, hERG channel blockers and PLD inducers share a large chemical space. In addition, a positively charged hERG channel blocker will most likely induce PLD, while a steroid PLD inducer is less likely a hERG channel blocker.     

A profound computational study to prioritize the natural compound inhibitors against the P. falciparum orotidine-5-monophosphate decarboxylase enzyme

Abstract

In the current contribution, a multicomplex-based pharmacophore modeling approach was employed on the structural proteome of Plasmodium falciparum orotidine-5-monophosphate decarboxylase enzyme (PfOMPDC). Among the constructed pharmacophore models, the representative hypotheses were selected as the primary filter to screen the molecules with the complementary features responsible for showing inhibition. Thereafter, auxiliary evaluations were performed on the screened candidates via drug-likeness and molecular docking studies. Subsequently, the stability of the docked protein-ligand complexes was scrutinized by employing molecular dynamics simulations and molecular mechanics-Poisson Boltzmann surface area based free binding energy calculations. The stability the docked candidates was compared with the highly active crystallized inhibitor (3S9Y-FNU) to seek more potential candidates. All the docked molecules displayed stable dynamic behavior and high binding free energy in comparison to 3S9Y-FNU. The employed workflow resulted in the retrieval of five drug-like candidates with diverse scaffolds that may show inhibitory activity against PfOMPDC and could be further used as the novel scaffold to develop novel antimalarials.

Communicated by Ramaswamy H. Sarma     

Identification of novel inhibitor of protein tyrosine phosphatases delta: structure-based pharmacophore modeling,virtual screening,flexible docking,molecular dynamics simulation,and post-molecular dynamics analysis

Abstract

Owing to their unique functions in regulating the synapse activity of protein tyrosine phosphatases delta (PTPδ) that has drawn special attention for developing drugs to autism spectrum disorders (ASDs). In this study, the PTPδ pharmacophore was first established by the structure-based pharmacophore method. Subsequently, 10 compounds contented Lipinski’s rule of five was acquired by the virtual screening of the PTPδ pharmacophore against ZINC and PubChem databases. Then, the 10 identified molecules were discovered that had better binding affinity than a known PTPδ inhibitors compound SCHEMBL16375396. Two compounds SCHEMBL16375408 and ZINC19796658 with high binding score, low toxicity were gained. They were observed by docking analysis and molecular dynamics simulations that the novel potential inhibitors not only possessed the same function as SCHEMBL16375396 did in inhibiting PTPδ, but also had more favorable conformation to bind with the catalytic active regions. This study provides a new method for identify PTPδ inhibitor for the treatment of ASDs disease.

Communicated by Ramaswamy H. Sarma     

QSAR analysis of meclofenamic acid analogues as selective COX-2 inhibitors

The use of quantitative structure-activity relationships, since its advent, has become increasingly helpful in understanding many aspects of biochemical interactions in drug research. This approach was utilized to explain the relationship of structure with biological activity of selective COX-2 inhibitors. The enormity of the COX-2 discovery is reflected in the unprecedented speed at which research laboratories have sought to validate its clinical implications. Presented herein is a series of 21 derivatives of meclofenamic acid with selective COX-2 inhibitory activity. Several statistically significant regression expressions were obtained for both COX-1 and COX-2 inhibition using sequential multiple linear regression analysis method. Two of these models were selected and validated further, which revealed the importance of Kier molecular flexibility index for COX-2 inhibitory activity and the number of hydrogen bond donor atoms for COX-1 inhibitory activity. Additionally, linear correlation of molecular flexibility with COX-1 and COX-2 inhibitory activities revealed that flexibility of molecules at COX-2 active site can improve the selectivity of COX-2 inhibitors.     

Three-dimensional pharmacophore hypotheses of octopamine/tyramine agonists which inhibit [1-14C]acetate incorporation in Plodia interpunctella

Three-dimensional pharmacophore hypotheses were built from a set of 36 octopamine (OA)/tyramine (TA) agonists responsible for the inhibition of sex-pheromone production in Plodia interpunctella. Among the ten chemical-featured models generated by a program Catalyst/Hypo, hypotheses including hydrogen-bond acceptor (HBA), hydrogen-bond acceptor aliphatic (HBAl), hydrophobic (Hp), hydrophobic aromatic (HpAr) and hydrophobic aliphatic (HpAl) features were considered to be important and predictive in evaluating OA/TA agonists. Active agonists mapped well onto all the features of the hypothesis such as HBA, HBAl, Hp, HpAr and HpAl features. On the other hand, inactive compounds were shown to be poorly capable of achieving an energetically favorable conformation shared by the active molecules in order to fit the 3-D chemical-feature pharmacophore models. Those hypotheses are considered to be used in designing new leads for hopefully more active compounds. Further research on the comparison of models from the agonists may help elucidate the mechanisms of OA/TA receptor-ligand interactions.     

Stepwise development of structure–activity relationship of diverse PARP-1 inhibitors through comparative and validated in silico modeling techniques and molecular dynamics simulation

Inhibitors of poly (ADP-ribose) polymerase-1 (PARP-1) enzyme are useful for the treatment of various diseases including cancer. Comparative in silico studies were performed on different ligand-based (2D-QSAR, Kernel-based partial least square (KPLS) analysis, Pharmacophore Search Engine (PHASE) pharmacophore mapping), and structure-based (molecular docking, MM-GBSA analyses, Gaussian-based 3D-QSAR analyses on docked poses) modeling techniques to explore the structure–activity relationship of a diverse set of PARP-1 inhibitors. Two-dimensional (2D)-QSAR highlighted the importance of charge topological index (JGI7), fractional polar surface area (Jurs_FPSA3), and connectivity index (CIC2) along with different molecular fragments. Favorable and unfavorable fingerprints were demonstrated in KPLS analysis, whereas important pharmacophore features (one acceptor, one donor, and two ring aromatic) along with favorable and unfavorable field effects were demonstrated in PHASE-based pharmacophore model. MM-GBSA analyses revealed significance of different polar, non-polar, and solvation energies. Docking-based alignment of ligands was used to perform Gaussian-based 3D-QSAR study that further demonstrated importance of different field effects. Overall, it was found that polar interactions (hydrogen bonding, bridged hydrogen bonding, and pi–cation) play major roles for higher activity. Steric groups increase the total contact surface area but it should have higher fractional polar surface area to adjust solvation energy. Structure-based pharmacophore mapping spotted the positive ionizable feature of ligands as the most important feature for discriminating highly active compounds from inactives. Molecular dynamics simulation, conducted on highly active ligands, described the dynamic behaviors of the protein complexes and supported the interpretations obtained from other modeling analyses. The current study may be useful for designing PARP-1 inhibitors.     

Inhibitory effect of carboxylic acid group on hERG binding

Drug-induced QT prolongation arising from drugs' blocking of hERG channel activity presents significant challenges in drug development. Many, but not all, of our benzamidine-containing factor Xa inhibitors were found to have high hERG binding propensity. However, incorporation of a carboxylic acid group into these benzamidine molecules generally leads to hERG inactive compounds regardless where the carboxyl group is tethered within the molecules. The inhibitory effect of a carboxylic acid group on hERG binding has also been observed in many series of diverse structural scaffolds (including non-amidines). These findings suggest that the negatively charged carboxylate group causes unfavorable interaction within hERG channel binding cavity by electrostatic interaction.     

Pharmacophore modeling for hERG channel facilitation

Human ether-a-go-go-related gene (hERG) channels play a critical role in cardiac action potential repolarization. The unintended block of hERG channels by compounds can prolong the cardiac action potential duration and induce arrhythmia. Several compounds not only block hERG channels but also enhance channel activation after the application of a depolarizing voltage step. This is referred to as facilitation. In this study, we tried to extract the property of compounds that induce hERG channel facilitation. We first examined the facilitation effects of structurally diverse hERG channel blockers in Xenopus oocytes. Ten of 13 assayed compounds allowed facilitation, suggesting that it is an effect common to most hERG channel blockers. We constructed a pharmacophore model for hERG channel facilitation. The model consisted of one positively ionizable feature and three hydrophobic features. Verification experiments suggest that the model well describes the structure-activity relationship for facilitation. Comparison of the pharmacophore for facilitation with that for hERG channel block showed that the spatial arrangement of features is clearly different. It is therefore conceivable that two different interactions of a compound with hERG channels exert two pharmacological effects, block and facilitation.