Design, Synthesis and Biological Evaluation of Novel Antitubercular Agents by Combining Pyrazoline and Benzoxazole Pharmacophores

Various recent reports on Tuberculosis have alarmed an increase in the patient class and subsequent death rates across the globe. Over and above the spread of more dangerous and fatal forms of tuberculosis like MDR-TB i.e. multiple-drug resistance tuberculosis, XDR-TB i.e. extensively-drug resistance tuberculosis & TDR-TB i.e. total-drug resistance tuberculosis has forwarded an urgent need to discover novel antitubercular agents. The current work is aimed at combining two previously well-known pharmacophores (pyrazoline and benzoxazole nucleus) in order to design and synthesize a series of novel benzoxazole-based pyrazoline derivatives. The synthesized target compounds were structurally confirmed by LCMS, 1H-NMR and 13C-NMR analysis. The target compounds were In vitro evaluated against M. tuberculosis H37Rv strain, multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) strains. The In vitro screening results depicted that majority of the target compounds displayed potent activity with MIC in a range of ~0.8 to 6.25 μg/mL. Many compounds were found to be more potent than isoniazid against MDR-TB with MIC value 3.12 μg/mL and XDR-TB with MIC value 12.5 μg/mL. Cytotoxicity assay of these active compounds on VERO cell lines also displayed good selectivity index.

Expanding the Boundaries of the Chemical Space of DNA Methyltransferase 1 Modulators

DNA methyltransferase 1 (DNMT1), one of the main epigenetic targets, is involved in the duplication of the DNA methylation pattern during replication, and it is essential for proper mammalian development. Small molecule DNMT1 modulators are attractive for biochemical epigenetic studies and have the potential to become drugs. So far, more than five hundred small molecules have been reported as DNMT1 inhibitors. However, only a limited number of DNMT1 activators have been disclosed because, at least in part, DNMT1 activators are typically regarded as negative data in virtual screening campaigns or optimization projects. This manuscript aims to report the chemical structures and biological activity of small molecules that increase the enzymatic activity of DNMT1. Results of the biochemical experimental assays are discussed. It was found that small molecule activators have a large variety of chemical scaffolds but share pharmacophore features. Visual analysis of the chemical space and multiverse based on molecular fingertips supported that activators are structurally diverse. This is the first report of eight small molecules that increase the enzymatic activity of DNMT1 by more than 400% in an enzymatic-based assay. The outcome warrants further investigation of the epigenetic activity of the compounds in a counter-screen assay, e.g., cell-based and in vivo context.

Trisubstituted Aryl Cyclohexanecarboxylates (TACC): A Simple, New Molecular Scaffold for Antibiotics Design

A new class of potential antibacterial agents has been synthesized on a new molecular scaffold of cyclohexane carboxylate. We have tagged this new class of compounds TACCs (Trisubstituted Aryl Cyclohexanecarboxylate). These new molecules are structural analogues of an Activators of Self-Compartmentalizing Proteases 4 and 5 (ACP 4 and 5), and were synthesized to circumvent the drug-like property (drug-ability) challenges and liability noted in ACP 4 and 5. A pseudo-Robinson annulation protocol was used to furnish this new class of potential antibiotics. Structure-activity relationship (SAR) study was done to identify the pharmacophore(s) in this molecular scaffold. A selection of these compounds was used in our preliminary antibacterial inhibitory activities’ studies on Bacillus mycoides and Bacillus subtilis. These preliminary studies show that the TACCs exhibited equal, and in some cases better, antibacterial activity than ACP 4 and 5.

In Silico Docking of Rhodanine Derivatives and 3D-QSAR Study to Identify Potent Prostate Cancer Inhibitors

The 3VHE protein is considered as a potential target for the treatment of prostate cancer. In order to find new 3VHE inhibitors, pharmacophore models based on the molecular structure of rhodanine derivatives and a three-dimensional quantitative structure-activity relationship model (3D-QSAR) have been developed and validated by different methods. The 3D-QSAR model was evaluated for its predictive performance on a diverse test set containing 18 prostate cancer inhibitors. It presents very interesting internal and external statistical validation parameters (SD = 0.081;R2 = 0.903;Q2 = 0.869;;F = 247.2). This result suggests that the 3D-QSAR combinatorial model can be used to search for new 3VHE inhibitors and predict their potential activity. Based on the combinatorial pharmacophore model, a virtual screening of the Enamine database was performed. Compounds selected after virtual screening were subjected to molecular docking protocols (HTVS, SP, XP and IFD). Twenty new active compounds have been identified and their absorption, distribution, metabolism and excretion (ADME) property calculated using Schr?dinger’s Qikprop module. These results suggest that these new compounds could constitute new chemical starting points for further structural optimization of 3VHE inhibitors.

Building the Pharmacophore Model of HIV-1 Integrase Strand Transfer Inhibitors and Studying Their Inhibition Mechanism

The replication of HIV-1 requires the integration of its cyclic DNA into host DNA by HIV-1 integrase （IN）, which includes two important reactions, 3＇-processing and strand transfer, both catalyzed by HIV-1 IN. Disrupting either of the reactions will fulfill the purpose of inhibiting the replication of HIV-1. In this paper, pharmacophore modeling and molecular docking are employed to investigate the inhibition mechanism of the HIV-1 IN strand transfer inhibitors （INSTIs）. Based on the results, we suggest that the inhibition mechanism of INSTIs involves the inhibitor chelating the cofactors Mg2＋ and its forming hydrogen bonds with some crucial residues adjacent to the DDE active center.

Three-dimensional pharmacophore screening for fentanyl derivatives

Fentanyl is a highly selective u-opioid receptor agonist with high analgesic activity. Three-dimensional pharmacophore models were built from a set of 50 fentanyl derivatives. These were employed to elucidate ligand-receptor interactions using information derived only from the ligand structure to identify new potential lead compounds. The present studies demonstrated that three hydrophobic regions, one positive ionizable region and two hydrogen bond acceptor region sites located on the molecule seem to be essential for analgesic activity. The results of the comparative molecular field analysis model suggested that both steric and electrostatic interactions play important roles. The contributions from steric and electrostatic fields for the model were 0.621 and 0.379, respectively. The pharmacophore model provides crucial information about how well the common features of a subject molecule overlap with the hypothesis model, which is very valuable for designing and optimizing new active structures.

Discovery of Novel N-Glycoside and Non-Glycoside hSGLT2 Inhibitors for the Treatment of Type 2 Diabetes Mellitus

Human sodium-glucose cotransporter 2 (hSGLT2) is a membrane protein responsible for glucose reabsorption from the glomerular filtrate in the proximal tubule. Inhibition of hSGLT2 has been regarded as a brand new therapeutic approach for the treatment of type 2 diabetes mellitus (T2DM) due to its non-insulin related characteristics with less side effects. Current commercially available hSGLT2 inhibitors are all C-glycoside inhibitors. Previous studies have reported that N-glycoside inhibitors have better potential to serve as new drugs due to their good metabolic stability. In addition, non-glycoside inhibitors have been shown to exhibit the capability to overcome the existing problems of current glycoside inhibitors, including low tissue permeability, poor stability and short serum half-time. Here, we aimed to discover novel N-glycoside and non-glycoside hSGLT2 inhibitors by a combination of several computational approaches. A ligand-based pharmacophore model was generated, well validated and subsequently utilized as a 3D query to identify novel hSGLT2 inhibitors from National Cancer Institute (NCI) and Traditional Chinese Medicine (TCM) databases. Finally, one N-glycoside (NSC679207) and one non-glycoside (TCM_Piperenol_A) hSGLT2 inhibitors were successfully identified, which were proven to exhibit excellent binding affinities, pharmacokinetic properties and less toxicity than the commercially available hSGLT2 inhibitor, canagliflozin, via molecular docking, ADMET prediction, molecular dynamics (MD) simulations and binding free energy calculations. All together, our results strongly suggest that these two compounds have great potential to serve as novel hSGLT2 inhibitors for the treatment of T2DM and their efficacies may be further examined by a series of in vitro and/or in vivo bioassays.

Pharmacophore modeling for the identification of small-molecule inhibitors of TACE

OBJECTIVE To employ pharmacophore modeling to identify a TACE inhibitor from an inhouse database of 66 organic compounds.METHODS To identify the common features required for TACE inhibition,we generated a pharmacophore model from a set of TACE-selective inhibitor using the Common Feature Pharmacophore Model protocol implemented in Discovery Studio 3.1.1.A fluorimetric assay was used to investigate the potential ability of compounds to inhibit TACE enzymatic activity.The ability of compound 1 to inhibit TACE activity in a human monocyte THP-1 cell line was evaluated by ELISA.RESULTS In this study,apharmacophore model constructed from a training set of TACE inhibitors was used to screen an in-house database of organic compounds,from which compound 1 emerged as a top candidate.In a cell-free assay,compound 1inhibited TACE enzymatic activity in a dose-dependent manner.Moreover,compound 1 inhibited the production of soluble TNF-αin human acute monocytic leukemia THP-1 cells without impacting nitric oxide production,and exhibited anti-proliferative activity against THP-1cells.CONCLUSION Compound 1 was found to inhibit TACE enzymatic activity in a cell-free system and LPS-induced TNF-αsecretion in cellulo.We envisage that compound 1 may be employed as a useful scaffold for the development of more potent TACE inhibitors.

Network pharmacology-based analysis of Chinese herbal NaoDeSheng formula for application to Alzheimer disease

OBJECTIVE To predict the potential targets and uncover the mechanisms of Nao De Sheng formula for the treatment of Alzheimer disease.METHODS Firstly,we collected the constituents in Nao De Sheng formula and key targets toward Alzheimer disease.Then,druglikeness,oral bioavailability and blood-brain barrier permeability were evaluated to find drug-like and lead-like constituents for central nervous system diseases treatment.Finallly,we were attempted to predict the targets of constituents and find potential multi-target compounds from Nao De Sheng formula by combining the advantages of machine learning,molecular docking and pharmacophore mapping together.RESULTS Constituenttarget network,constituent-target-target network and targetbiological pathway network were built to explain the network pharmacology of the constituents in NaoD eS heng formula.CONCLUSION To the best of our knowledge,we were the first to study the mechanism of Nao De Sheng formula for potential efficacy for Alzheimer disease treatment by means of the virtual screening and network pharmacology methods.

Common Pharmacophore Model and 3D-QSAR Analysis of Two Different Tyrphostin Families

In the present study we investigated two groups of small molecular tyrosine kinase phosphorylation inhibitors (tyrphostins) with quite different structures (19 compounds of the benzylidene malononitrile famliy and 13 compounds of the 3-substituted indolin-2-ones family). With the aid of a pharmacophore analysis method (CATALYST). a common three-dimensional pharmacophore model to these two kinds of molecules has been discovered. A better 3D-QSAR analysis based on the generated pharmacophore model was conducted (correlate coeffcient R=0.956) and the model shows very good predictive ability.

Discovery of a Novel 5-HT_(2A) Inhibitor by Pharmacophore-based Virtual Screening

The serotonin 2A（5-HT2A） receptor has been implicated in several neurological conditions and potent 5-HT2A antagonists have therapeutic effects in the treatment of schizo phrenia and depression.In this study,a potent novel 5-HT2A inhibitor 05245768 with a Ki value of （593.89±34.10） nmol/L was discovered by integrating a set of computational approaches and experiments（protein structure prediction,pharmacophore-based virtual screening,automated molecular docking and pharmacological bioassay）.The 5-HT2A receptor showed a negatively charged bin-ding pocket.The binding mode of compound 05245768 with 5-HT2A was obtained by GOLD docking procedure,which revealed the conserved interaction between protonated nitrogen in compound 05245768 and carboxylate group of D3.32 at the active site of 5-HT2A.

A Convenient Synthesis of the Substituted 2,3-Diarylindole the Potent Selective COX-2 Inhibitors

Phenyl sulfone-containing 2, 3-diarylindole derivatives were designed and identified to be selective COX-2 inhibitors. A convenient synthetic route was also developed for the synthesis of the novel inhibitors.

In silico Discovery of Novel FXa Inhibitors by Pharmacophore Modeling and Molecular Docking

Coagulation Factor Xa(FXa)is the crucial enzyme at the convergent point of the intrinsic and extrinsic coagulation pathways.The inhibition of FXa is an effective approach against thrombotic diseases.In the present study,a specific strategy is reported to discover 10 novel FXa inhibitors based on ligand-based(pharmacophore)virtual screening and molecular docking analysis from a dataset of specs(containing 220000 molecules).The binding modes analysis provide insights into the contribution of particular structural moieties of the compounds towards their activity against FXa,and 10 novel structural compounds were discovered as potent candidate molecules.This work could be helpful in further design and development of FXa inhibitors.

A Novel Pharmacophore Model Derived from a Class of Capsid Protein Enterovirus 71 Inhibitors

Capsid protein enterovirus 71 （EV71） is one of the major viruses that cause the severe encephalitis and thus result in a high mortality in children less than 5 years of age.In an effort to discover new potent inhibitors against EV71,a novel three-dimensional pharmacophore model was developed on 24 inhibitors with different molecular structures and bioactivities.The best hypothesis （Hypo1） has a high predictive power and consists of four features,namely,one hydrophobic point （HY） and three hydrogen-bond acceptors （HA）.Two key features of the best Hypo1,HY1 and HA3 match well with an important narrow hydrophobic canyon and with the surface of LYS274 in the target EV71 active site,respectively.The more versatile feature,HA1,is firstly found to be very influential on these compounds’ bioactivities,which may interact with the other side of the active site in the EV71 receptor.The application of the model is successful in predicting the activities of 30 known EV71 inhibitors with a correlation coefficient of 0.831.Furthermore,Hypo1 demonstrates a superior screening capability for retrieving inhibitors from the database with a high enrichment factor of 70.This study provides some important clues in search for more potent inhibitors against EV71 infection.

Structural Modification Based on Natural Products Leads to More Drug-like Candidates

Natural products are characterized with diverse structures and biological activities. They show a certain degree of adaptability to human beings. However, they need to be modified to increase their druggability. Several strategies including pharmacophore similarity, physicochemical property optimization, and bioactivity focus may help to make them more drug-like candidates.

In silico investigation of the association of the TRPM8 ion channel with the pungent flavor of Chinese herbs

Objective:Explicating the property and action of traditional Chinese medicine(TCM)in the perspectives of modern science deepens the insight into the property of TCM,and provides the basis for new drug discovery and clinical therapy.In this study,we investigated the relationship between transient receptor potential melastatin 8(TRPM8)and pungent flavor using three-dimensional pharmacophores based on virtual screening methods.Methods:Firstly,an inhouse database was established to identify the related pharmacological action according to the traditional Chinese herbs expressing an action of promoting blood circulation.Then,several therapeutic targets,3-hydroxy-3-methylglutaryl-coenzyme A reductase(HMG-CoAR),cholesteryl ester transfer protein(CETP),Niemann-Pick C1-Like 1(NPC1L1)and platelet-activating factor receptor(PAFR),were selected to screen traditional Chinese herbs,and the common virtual screening hits with various hit scores providing data to reveal the correlation among TRPM8 and therapeutic targets.Results:According to the screening results,TRPM8 agonists were able to identify the effective components of pungent herbs and TRPM8,which shares the common virtual screening hits with the therapeutic targets,was considered to be related to the action of pungent taste.Conclusion:The novel ideas and methods in this study are beneficial to unveil the scientific relationship between a TCM property and its action.

Estimated Binding Energies of Drug-Like and Nondrug-Like Molecules in the Active Site of HIV-1 Integrase, 1BIS.pdb, and Two Mutant Models: Y143R and N155H

Lipinski’s “Rule of Five” was introduced for predicting oral bioavailability to describe drug-like molecules. For the purpose of this research the rules were used to separate potential inhibitors of HIV-1 integrase (1BIS.pdb) into two groups: drug-like and nondrug-like. If one of Lipinski’s “Rule of Five” was not followed the potential inhibitor was classified as nondrug-like. Thirty molecules were identified from the literature, twenty-four drug-like and six nondrug-like, that were docked into the active site of 1BIS.pdb (considered the non-mutated protein) and two mutant models, Y143R and N155H. These are two of the mutations that have led to increased resistance to HIV-1 integrase drugs such as raltegravir and elvitegravir. The computational software, ICM-Pro (Molsoft L.L.C.), was used to determine the estimated binding energy (EBE) of the drug/protein complex. It was found that the nondrug-like molecules generally had a more negative EBE, that is, tighter binding with 1BIS. pdb, though there were several exceptions in the drug-like group. With the protein mutant model Y143R, the majority of drug-like (58%) and nondrug-like molecules (67%) had tighter binding. However, for the mutant model N155H, there was the same percent (46%) of drug-like molecules with tighter binding with the mutant model as with 1BIS.pdb. The drug-like molecules were used when there was a ≥1 kcal/mole difference between 1BIS.pdb and either of the two mutant models to suggest a pharmacophore with structural characteristics for an HIV-1 integrase inhibitor.

Pharmacophore Based Virtual Screening for Identification of Novel CDK₂Inhibitors

CDK2 is one of the most important members of Cyclin-dependent kinases. It is a critical modulator of various oncogenic signaling pathways, and its activity is vital for loss of proliferative control during oncogenesis. This work has focused on developing a pharmacophore model for CDK2 inhibitors by using a dataset of known inhibitors as a pre-filter throughout the virtual screening and docking process. Consequently, the best pharmacophore model was made of one hydrogen bond acceptor, and two aromatic ring features with a high correlation value of 0.906. The validation findings proved out that the selected model can be used as a filter to screen new molecules like Enamine kinase hinge region directed library against CDK2. As a result, 69 hits were subjected to molecular docking studies. Eventually, three compounds (5909, 701 and 8397) scored good interaction energy values and strong molecular interactions. Hence, they were identified as leads for novel CDK2 inhibitors as anticancer drugs.

Discovery of Novel Irreversible HER2 Inhibitors for Breast Cancer Treatment

It has been widely known that human epidermal growth factor receptor 2 (HER2) inhibitors exhibit distinct antitumor responses against HER2-positive breast cancer. To date, Lapatinib (Tykerb®) has been approved by the U.S. Food and Drug Administration (FDA) as a reversible HER2 inhibitor for treating breast cancer. However, HER2 L755S, T798I and T798M mutations confer drug resistance to lapatinib, restricting its efficacy toward HER2-positive breast cancer. Thus, novel therapy toward mutant HER2 is highly desired. Although several irreversible HER2 inhibitors have been developed to overcome these drug resistance problems, most of them were reported to cause severe side effects. In this study, three pharmacophore models based on HER2 L755S, T798I and T798M mutant structures were constructed and then validated through receiver operating characteristic (ROC) curve analysis and Güner-Henry (GH) scoring methods. Subsequently, these well-validated models were utilized as 3D queries to identify novel irreversible HER2 inhibitors from National Cancer Institute (NCI) database. Finally, two potential irreversible HER2 inhibitor candidates, NSC278329 and NSC718305, were identified and validated through molecular docking, molecular dynamics (MD) simulations and ADMET prediction. Furthermore, the analyses of binding modes showed that both NSC278329 and NSC718305 exhibit good binding interactions with HER2 L755S, T798I and T798M mutants. All together, the above results suggest that both NSC278329 and NSC718305 can serve as novel and effective irreversible HER2 inhibitors for treating breast cancers with HER2 L755S, T798I and T798M mutants. In addition, they may act as lead compounds for designing new irreversible HER2 inhibitors by carrying out structural modifications and optimizations in future studies.

<i>In-Silico</i>Identification of Anticancer Compounds;Ligand-Based Pharmacophore Approach against EGFR Involved in Breast Cancer

Objective: Breast cancer is a public health challenge on a global scale that is caused by environmental or genetic factors. Breast cancer is affecting both males and females, but there is still a lack of effective drugs with improved potency and admissibility against breast cancer as many of the breast cancer drugs have severe side effects. Methods: The docking approach has been used to find a new compound for breast cancer with more efficacy and tolerance and with lesser side effects. A ligand-based pharmacophore approach has been generated for 39 anticancer compounds with significance for the development of new drugs. Result: Through docking, the approach found new lead compounds for breast cancer. The proposed pharmacophore model in this study contains two HBAs and one HYD, one hydrophobic domain and two Aromatic rings and the estimated distance range is minimum to maximum of derived pharmacophore features. Conclusion: Based on this research, it is proposed that these two lead compounds may be able to be used against EGFR in breast cancer. New compounds can be identified based on common features in the Pharmacophore model. 3D pharmacophore triangle could be used for further studies because this pharmacophore has better merging and in the future for more studies can suggest the same distance range of pharmacophore features as this pharmacophore.