<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.

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.

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.

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.

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.

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.

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.

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.

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.

Pharmacophore Model Generation of Thrombin Inhibitors

Thrombin, an important factor of clotting system, take part in a variety of physiological actions, such as blood clotting, anticoagulation, thrombosis and fibrinolysis. Inhibiting thrombin is a pivotal and effective step for the prophylaxis of venous and arterial thrombosis, as well as prevent myocardial infarction for high-risk patients. In this study, a three dimensional pharmacophore model was generated for the molecules which are responsible for vasodilation activities targeting thrombin. Ten compounds with known thrombin-inhibiting activity values were selected as training set to generate the hypothesis using GALAHAD program in SYBYL 7.0 software. The best hypothesis comprises five pharmacophore features: four hydrophobes groups and one positively charged group. It has been further validated towards a test set including known activity compounds obtained from Binding Database, the values of effectively active hit A% and comprehensive evaluation index CAI are respectively 63.33% and 2.34, the pharmacophore was proven to be successful in discriminating active and inactive inhibitors. ?Furthermore, the pharmacophore model was used as a 3D query to screen TCMD (Version 2009) database and 6 hit compounds of higher predicted activity were the reported cardiovascular activities, which may be useful for further study.

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.

The forecast of anticancer targets of cryptotanshinone based on reverse pharmacophore-based screening technology

Anticancer targets of cryptotanshinone were evaluated and rapidly forecasted with PharmMapper, a reverse pharmacophore-based screening platform, as well as drug target databases, including PDTD, DrugBank and TTD. The pathway analyses for the collection of anticancer targets screened were carried out based on the KEGG pathway database, followed by the forecast of potential pharmacological activities and pathways of the effects of cryptotanshinone, and verification of some of the targets screened using whole cell tests. The results showed that a total of eight targets with anticancer potential were screened, including MAP2K1, RARα, RXRα, PDK1, CHK1, AR, Ang-1 R, and Kif11. These targets are mainly related to four aspects of the cancer growth: the cell cycle, angiogenesis, apoptosis, and androgen receptor. The cell tests showed that cryptotanshinone can inhibit the viability of human hepatoma cells SMMC-7721, which is related to the reduction of expression of MAP2K1 mRNA. This method provides a strong clue for the study of the anticancer effects and mechanisms of action of cryptotanshinone in the future.

Pharmacophore-based structure optimization of angiotensin converting enzyme inhibitory peptide

Chemical feature based pharmacophore models were generated for an angiotensin converting enzyme(ACE) inhibitory peptide using the Discovery Studio 2.0 pharmacophore modeling approach. The pharmacophore hypothesis selected has five features(one negative ionizable region,one hydrogen bond donor,one hydrogen bond acceptor and two hydrophobic functional groups). Additionally,ACE inhibitory hexapeptide previously obtained from silkworm pupae protein was optimized to target the ACE based on the selected pharmacophore. The results suggest that tri-peptide(thr-val-phe) may be structural determinant of ACE activity. Docking studies further provided confidence for the validity of the selected pharmacophore model to perform structure optimization of the ACE inhibitory peptide.

AncPhore: A versatile tool for anchor pharmacophore steered drug discovery with applications in discovery of new inhibitors targeting metallo-β-lactamases and indoleamine/tryptophan 2,3-dioxygenases

We herein describe AncPhore,a versatile tool for drug discovery,which is characterized by pharmacophore feature analysis and anchor pharmacophore(i.e.,most important pharmacophore features)steered molecular fitting and virtual screening.Comparative analyses of numerous protein-ligand complexes using AncPhore revealed that anchor pharmacophore features are biologically important,commonly associated with protein conservative characteristics,and have significant contributions to the binding affinity.Performance evaluation of AncPhore showed that it had substantially improved prediction ability on different types of target proteins including metalloenzymes by considering the specific contributions and diversity of anchor pharmacophore features.To demonstrate the practicability of AncPhore,we screened commercially available chemical compounds and discovered a set of structurally diverse inhibitors for clinically relevant metallo-β-lactamases(MBLs);of them,4 and 6 manifested potent inhibitory activity to VIM-2,NDM-1 and IMP-1 MBLs.Crystallographic analyses of VIM-2:4 complex revealed the precise inhibition mode of 4 with VIM-2,highly consistent with the defined anchor pharmacophore features.Besides,we also identified new hit compounds by using AncPhore for indoleamine/tryptophan 2,3-dioxygenases(IDO/TDO),another class of clinically relevant metalloenzymes.This work reveals anchor pharmacophore as a valuable concept for target-centered drug discovery and illustrates the potential of AncPhore to efficiently identify new inhibitors for different types of protein targets.

Pharmacophore Screening on Piperidinecarboxamides Derivatives Based on GALAHAD and CoMFA Models

In order to discover the novel anticonvulsant drugs, pharmacophore screening of the anticonvulsant inhibitors was enforced. Genetic Algorithm with Linear Assignment for Hypermolecular Alignment of Datasets （GALAHAD） and Comparative Molecular Field Analysis （CoMFA） studies were combined to implement our research. Firstly, multiple models were generated using GALAHAG based on high active molecules. Secondly, several of them were validated using the CoMFA study. Finally, a good values of q2 from training set and promising predictive power from test set were obtained based on one model simutaneously. One model had been selected as the most reasonable pharmacophore model. The results of the CoMFA study based on the model 1 suggested that both steric and electrostatic interactions played important roles.

QSAR,docking studies and pharmacophore identification of phenylmethyl phenoxy propyl amino propanoic acid derivatives as leukotriene A_4 hydrolase inhibitors

The enzyme leukotriene A4 (LTA4) plays an important role as precursor of slow reactive substances as LTC4, LTD4, and LTE4. It is an attractive target for molecular modeling and QSAR study. Our effort is mainly focused on exploring the SAR for inhibitors of the LTA4 hydrolase through docking study, pharmacophore modeling and molecular descriptor study. The binding of these small molecules on LTA4 hydrolase enzyme was described by the models developed on 2D molecular descriptors, with good predictive power (39 compounds, 6 descriptors, r2 0.98, SEE 0.167, F-value 268.53, q2 0.90, r2adj 0.97, P-value < 0.0001, SD of residuals 0.15). Docking studies were employed to presume the probable binding conformation of these analogues and exploring the SAR for the compounds. The novel pharmacophore represents the ligand features that are involved in interactions with the target protein, as well as the space around the ligand occupied by the protein. The efforts are aimed to discover the SAR for the inhibitors of LTA4 hydrolase through techniques of QSAR, docking and pharmacophore.

Pharmacophore-based design,synthesis,and biological evaluation of novel 3-((3,4-dichlorophenyl)(4-substituted benzyl)amino)propanamides as cholesteryl ester transfer protein(CETP)inhibitors

Cholesteryl ester transfer protein （CETP） is a plasma glycoprotein that plays an important role in decreasing high-density lipoprotein cholesterol （HDL-C） levels and increasing low-density lipoprotein cholesterol （LDL-C） levels. Inhibition of CETP may be a new therapy for treating atherosclerosis. Herein, we report the development of a ligand-based pharmacophore model and pharmacophore-based virtual screening of the ZINC/big-n-greasy database, leading to the identification of compound H-10 as a potential CETP inhibitor in vitro. Based on H-10, a series of 3-（（3,4-dichlorophenyl）（4-substituted benzyl）amino） propanamides were designed, synthesized, and evaluated against CETP. Compound 41 was found to have the best activity, resulting in 85.0% inhibition of CETP at l0 μmol/L.

The Pharmacophore Hypothesis of Novel Inhibitors for Aurora A Kinase

A three-dimensional pharmacophore model was developed from a series of inhibitors of Aurora A kinase to discover new potent anti-cancer agents using the HypoGen module in the Catalyst software. The pharmacophore model was developed based on the structure of 20 currently available inhibitors, which were carefully selected from the literature. The best hypothesis （Hypo 1） was defined by four features： one hydrogen-bond donor and three hy- drophobic points, with the best correlation coefficient of 0.909, the lowest rms deviation of 1.563, and the highest cost difference of 99.075. The Hypo 1 was then validated by a test set consisting of 24 compounds and by a cross-validation of 95% confidence level through randomizing the data using the CatScramble program, which suggested that a predictive pharmacophore model had been successfully obtained.

Pharmacophore and Docking-based 3D-QSAR Studies on HIV-1 Integrase Inhibitors

Integrase（IN） plays an essential role in the process of HIV-1 replication.IN inhibitors of diketo acid derivatives（DKAs） were analysed by the Comparative Molecular Field Analysis（CoMFA） and Comparative Molecular Similarity Induces Analysis（CoMSIA） methods.A set of 42 compounds were randomly selected as the training set（35） and test set（7）.Firstly,a good pharmacophore（goodness of hit=0.787） was obtained and used to align ligands.Then,predictive models were constructed with the CoMFA and CoMSIA methods based on the pharmacophore alignment.As a result,the CoMS1A method yielded the best model with an r2 of 0.955 and a q2 of 0.665,which can predict the activities of the tested DKAs very well（r2=0.559）.Finally,DKAs were docked into IN,and the predicit modes were superimposed on the contour maps obtained from the best CoMSIA model.The superimposed maps gave a visualized and meaningful insight into the inhibitory behaviors,providing significantly useful information for the rational drug design of anti-IN agents.