Comprehensive assessment of nine target prediction web services: which should we choose for target fishing?

Identification of potential targets for known bioactive compounds and novel synthetic analogs is of considerable significance. In silico target fishing (TF) has become an alternative strategy because of the expensive and laborious wet-lab experiments, explosive growth of bioactivity data and rapid development of high-throughput technologies. However, these TF methods are based on different algorithms, molecular representations and training datasets, which may lead to different results when predicting the same query molecules. This can be confusing for practitioners in practical applications. Therefore, this study systematically evaluated nine popular ligand-based TF methods based on target and ligand-target pair statistical strategies, which will help practitioners make choices among multiple TF methods. The evaluation results showed that SwissTargetPrediction was the best method to produce the most reliable predictions while enriching more targets. High-recall similarity ensemble approach (SEA) was able to find real targets for more compounds compared with other TF methods. Therefore, SwissTargetPrediction and SEA can be considered as primary selection methods in future studies. In addition, the results showed that k = 5 was the optimal number of experimental candidate targets. Finally, a novel ensemble TF method based on consensus voting is proposed to improve the prediction performance. The precision of the ensemble TF method outperforms the individual TF method, indicating that the ensemble TF method can more effectively identify real targets within a given top-k threshold. The results of this study can be used as a reference to guide practitioners in selecting the most effective methods in computational drug discovery.

Target fishing reveals PfPYK-1 and PfRab6 as potential targets of an antiplasmodial 4-anilino-2-trichloromethylquinazoline hit compound.

We present investigations about the mechanism of action of a previously reported 4-anilino-2-trichloromethylquinazoline antiplasmodial hit-compound (Hit A), which did not share a common mechanism of action with established commercial antimalarials and presented a stage-specific effect on the erythrocytic cycle of P. falciparum at 8 < t < 16 h. The target of Hit A was searched by immobilising the molecule on a solid support via a linker and performing affinity chromatography on a plasmodial lysate. Several anchoring positions of the linker (6,7 and 3') and PEG-type linkers were assessed, to obtain a linked-hit molecule displaying in vitro antiplasmodial activity similar to that of unmodified Hit A. This allowed us to identify the PfPYK-1 kinase and the PfRab6 GTP-ase as potential targets of Hit A.

Artificial intelligence-driven identification of morin analogues acting as CaV1.2 channel blockers: Synthesis and biological evaluation.

Morin is a vasorelaxant flavonoid, whose activity is ascribable to CaV1.2 channel blockade that, however, is weak as compared to that of clinically used therapeutic agents. A conventional strategy to circumvent this drawback is to synthesize new derivatives differently decorated and, in this context, morin-derivatives able to interact with CaV1.2 channels were found by employing the potential of PLATO in target fishing and reverse screening. Three different derivatives (5a-c) were selected as promising tools, synthesized, and investigated in in vitro functional studies using rat aorta rings and rat tail artery myocytes. 5a-c were found more effective vasorelaxant agents than the naturally occurring parent compound and antagonized both electro- and pharmaco-mechanical coupling in an endothelium-independent manner. 5a, the series' most potent, reduced also Ca2+ mobilization from intracellular store sites. Furthermore, 5a≈5c > 5b inhibited Ba2+ current through CaV1.2 channels. However, compound 5a caused also a concentration-dependent inhibition of KCa1.1 channel currents.

PLATO: A Predictive Drug Discovery Web Platform for Efficient Target Fishing and Bioactivity Profiling of Small Molecules.

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022).

Seafood Paramyosins as Sources of Anti-Angiotensin-Converting-Enzyme and Anti-Dipeptidyl-Peptidase Peptides after Gastrointestinal Digestion: A Cheminformatic Investigation.

Paramyosins, muscle proteins occurring exclusively in invertebrates, are abundant in seafoods. The potential of seafood paramyosins (SP) as sources of anti-angiotensin-converting-enzyme (ACE) and anti-dipeptidyl-peptidase (DPP-IV) peptides is underexplored. This in silico study investigated the release of anti-ACE and anti-DPP-IV peptides from SP after gastrointestinal (GI) digestion. We focused on SP of the common octopus, Humboldt squid, Japanese abalone, Japanese scallop, Mediterranean mussel, Pacific oyster, sea cucumber, and Whiteleg shrimp. SP protein sequences were digested on BIOPEP-UWM, followed by identification of known anti-ACE and anti-DPP-IV peptides liberated. Upon screening for high-GI-absorption, non-allergenicity, and non-toxicity, shortlisted peptides were analyzed via molecular docking and dynamic to elucidate mechanisms of interactions with ACE and DPP-IV. Potential novel anti-ACE and anti-DPP-IV peptides were predicted by SwissTargetPrediction. Physicochemical and pharmacokinetics of peptides were predicted with SwissADME. GI digestion liberated 2853 fragments from SP. This comprised 26 known anti-ACE and 53 anti-DPP-IV peptides exhibiting high-GI-absorption, non-allergenicity, and non-toxicity. SwissTargetPrediction predicted three putative anti-ACE (GIL, DL, AK) and one putative anti-DPP-IV (IAL) peptides. Molecular docking found most of the anti-ACE peptides may be non-competitive inhibitors, whereas all anti-DPP-IV peptides likely competitive inhibitors. Twenty-five nanoseconds molecular dynamics simulation suggests the stability of these screened peptides, including the three predicted anti-ACE and one predicted anti-DPP-IV peptides. Seven dipeptides resembling approved oral-bioavailable peptide drugs in physicochemical and pharmacokinetic properties were revealed: AY, CF, EF, TF, TY, VF, and VY. In conclusion, our study presented in silico evidence for SP being a promising source of bioavailable and safe anti-ACE and anti-DPP-IV peptides following GI digestions.

[Progress of target determination and mechanism of bioactive components of traditional Chinese medicine].

The pharmacodynamic substances of traditional Chinese medicine(TCM) are the basis for the research of TCM and the development of innovative drugs. However, the lack of clarity of targets and molecular mechanisms is the bottleneck problem that restricts the research of pharmacodynamic substances of TCM. Bioactive components are the material basis of the efficacy of TCM, which exert activity by regulating the corresponding targets. Therefore, it is very important to identify the targets of the bioactive components to elucidate the pharmacological mechanism of TCM. Proteins are the most important drug targets, and study of the interaction between the proteins and bioactive components of TCM plays a key role in the development of pharmacological mechanism of TCM. In recent years, the main techniques for detecting the interaction between the bioactive components and proteins include surface plasmon resonance, fluorescence resonance energy transfer, bio-layer interference, molecular docking, proteome chip, target fishing, target mutant, and protein crystallization techniques, etc. This review summarized the biological target detection techniques and their applications in locating the targets of the bioactive components in TCM in the last decade, and this paper will provide useful strategies to elucidate the pharmacological mechanisms of TCM.

Recent Advances in In Silico Target Fishing.

In silico target fishing, whose aim is to identify possible protein targets for a query molecule, is an emerging approach used in drug discovery due its wide variety of applications. This strategy allows the clarification of mechanism of action and biological activities of compounds whose target is still unknown. Moreover, target fishing can be employed for the identification of off targets of drug candidates, thus recognizing and preventing their possible adverse effects. For these reasons, target fishing has increasingly become a key approach for polypharmacology, drug repurposing, and the identification of new drug targets. While experimental target fishing can be lengthy and difficult to implement, due to the plethora of interactions that may occur for a single small-molecule with different protein targets, an in silico approach can be quicker, less expensive, more efficient for specific protein structures, and thus easier to employ. Moreover, the possibility to use it in combination with docking and virtual screening studies, as well as the increasing number of web-based tools that have been recently developed, make target fishing a more appealing method for drug discovery. It is especially worth underlining the increasing implementation of machine learning in this field, both as a main target fishing approach and as a further development of already applied strategies. This review reports on the main in silico target fishing strategies, belonging to both ligand-based and receptor-based approaches, developed and applied in the last years, with a particular attention to the different web tools freely accessible by the scientific community for performing target fishing studies.

Novel pyrazine based anti-tubercular agents: Design, synthesis, biological evaluation and in silico studies.

TB continues to be a leading health threat despite the availability of powerful anti-TB drugs. We report herein the design and synthesis of various hybrid molecules comprising pyrazine scaffold and various formerly identified anti-mycobacterial moieties. Thirty-one compounds were screened in vitro for their activity against Mycobacterium tuberculosis H37Rv strain using MABA assay. The results revealed that six compounds (8a, 8b, 8c, 8d, 14b and 18) displayed significant activity against Mtb with MIC values ≤6.25 µg/ml versus 6.25 µg/ml for pyrazinamide. The most active compounds were then assessed for their in vitro cytotoxicity against PBMC normal cell line using MTT assay and showed SI > 200. Several in silico studies have been carried out for target fishing of the novel compounds such as shape-based similarity, pharmacophore mapping and inverse docking. Based on this multi-step target fishing study, we suggest that pantothenate synthetase could be the possible target responsible for the action of these compounds. The most active compounds were then successfully docked into the active site of pantothenate synthetase enzyme with favorable binding interactions. In addition, in silico prediction of physicochemical, ADMET and drug-like properties were also determined indicating that compounds 8b, 8c and 8d are promising candidates for the development of new anti-TB agents with enhanced activity and better safety profile.

Identification of the Molecular Mechanisms of Peimine in the Treatment of Cough Using Computational Target Fishing.

Peimine (also known as verticine) is the major bioactive and characterized compound of Fritillariae Thunbergii Bulbus, a traditional Chinese medicine that is most frequently used to relieve a cough. Nevertheless, its molecular targets and mechanisms of action for cough are still not clear. In the present study, potential targets of peimine for cough were identified using computational target fishing combined with manual database mining. In addition, protein-protein interaction (PPI), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using, GeneMANIA and Database for Annotation, Visualization and Integrated Discovery (DAVID) databases respectively. Finally, an interaction network of drug-targets-pathways was constructed using Cytoscape. The results identified 23 potential targets of peimine associated with cough, and suggested that MAPK1, AKT1 and PPKCB may be important targets of pemine for the treatment of cough. The functional annotations of protein targets were related to the regulation of immunological and neurological function through specific biological processes and related pathways. A visual representation of the multiple targets and pathways that form a network underlying the systematic actions of peimine was generated. In summary, peimine is predicted to exert its systemic pharmacological effects on cough by targeting a network composed of multiple proteins and pathways.

Antitumor Activity and Mechanism of Robustic Acid from Dalbergia benthami Prain via Computational Target Fishing.

Dalbergia benthami Prain (D.benthami) is an important legume species of the Dalbergia family, due to the use of its trunk and root heart in traditional Chinese medicine (TCM). In the present study, we reported the isolation, characterization and pharmacological activities of robustic acid (RA) from the ethyl acetate extract of D. benthami Prain. The SwissADME prediction showed that the RA satisfied the Lipinski's rule of five (molecule weight (MW): 380.39 g/mol, lipid-water partition coefficient (log P): 3.72, hydrogen bond donors (Hdon): 1, hydrogen bond acceptors (Hacc): 6, rotatable bonds (Rbon): 3. Other chemical and pharmacological properties of this RA were also evaluated, including topological polar surface area (TPSA) = 78.13 Šand solubility (Log S) = -4.8. The probability values of the antineoplastic, anti-free radical activities and topoisomerase I (TopoⅠ) inhibitory activity were found to be 0.784, 0.644 and 0.379, respectively. The molecular docking experiment using the Surflex-Dock showed that the Total Score and C Score of RNA binding with the human DNA-Topo I complex were 7.80 and 4. The MTS assay experiment showed that the inhibitory rates of RA on HL-60, MT4, Hela, HepG2, SK-OV-3 and MCF-7 cells were 37.37%, 97.41%, 81.22%, 34.4%, 32.68% and 51.4%, respectively. In addition, RA exhibited an inhibitory effect on the angiogenesis of zebrafish embryo, a good TopoⅠ inhibitory activity at a 10 mM concentration and in a dose-dependent manner, excellent radical scavenging in the DPPH and ABTS assays, and the free radical scavenging rate was close to the positive control (BHT) at different concentrations (0.5-2.0 mg/mL). Furthermore, 18 potential targets were found for this RA by PharmMapper, including ANXA3, SRC, FGFR2, GSK3B, CSNK2B, YARS, LCK, EPHA2, MAPK14, RORA, CRABP2, PPP1CC, METAP2, MME, TTR, MET and KDR. The GO and KEGG pathway analysis revealed that the "protein tyrosine kinase activity", "rap1 signaling pathway" and "PI3K-Akt signaling pathway" were significantly enriched by the RA target genes. Our results will provide new insights into the pharmaceutical use of this species. More importantly, our data will expand our understanding of the molecular mechanisms of RA functions.

Design and synthesis of biotinylated cardiac glycosides for probing Nur77 protein inducting pathway.

The orphan nuclear receptor Nur77 (also known as TR3 or nerve growth factor-induced clone B NGFI-B) functions as a nuclear transcription factor in the regulation of target gene expression and plays a critical role in the regulation of differentiation, proliferation, apoptosis, and survival of many different cell types. Recent studies demonstrate that Nur77 also involves many important physiological and pathological processes including cancer, inflammation and immunity, cardiovascular diseases, and bone diseases. Our previous studies showed that cardiac glycosides could induce the expression of Nur77 protein and its translocation from the nucleus to the cytoplasm and subsequent targeting to mitochondria, leading to apoptosis of cancer cells. In order to probe the Nur77 protein inducting pathway, we designed and synthesized a series of novel biotinylated cardiac glycosides from ß-Antiarin and α-Antiarin, two typical cardiac glycosides from the plant of Antiaris toxicaria. The induction of Nur77 protein expression of these biotinylated cardiac glycosides and their inhibitory effects on NIH-H460 cancer cell proliferation were evaluated. Results displayed that some biotinylated cardiac glycosides could significantly induce the expression of Nur77 protein comparable with their parent compounds ß-Antiarin and α-Antiarin. Also, their streptavidin binding activities were evaluated. Among them, biotinylated cardiac glycosides P4b and P5a exhibited significant effect on the induction of Nur77 expression along with high binding capacity with streptavidin, suggesting that they can be used as probes for probing Nur77 protein inducting pathway.

Systems pharmacology approach to investigate the molecular mechanisms of herb Rhodiola rosea L. radix.

Rhodiola rosea L. radix (RRL) is one of the most popular medical herb which has been widely used for the treatment of different diseases effectively, including cardiovascular diseases and nerve system diseases. However, due to the multiple compounds in RRL, the underlying molecular mechanisms of RRL are remained unclear. To decipher the action mechanisms of RRL from a systematic perspective, a systems pharmacology approach integrated absorption, distribution, metabolism, and excretion (ADME) system, drug targeting, and network analysis was introduced. First, by the ADME screening system and the target fishing process, 56 potential active compounds and 62 targets were obtained, respectively. In addition, compound-target network demonstrated that most compounds interacted with multiple targets, indicating that RRL may enhance its therapeutic effects probably through hitting on multiple targets in a holistic level. Moreover, target-pathway network and gene ontology analysis showed that multiple targets of RRL were involved in several biological pathways, i.e. Neuroactive ligand-receptor interaction, calcium signaling pathway, adrenergic signaling in cardiomyocytes, and VEGF signaling pathway, which dissecting the therapeutic effects of RRL on various diseases, such as cardiovascular diseases, depression, adaptation diseases, etc. In summary, this work successfully explains the potential active compounds and the multi-scale curative action mechanisms of RRL for treating various diseases; meanwhile, it implies that RRL could be applied as a novel therapeutic agent in arthritic diseases. Most importantly, this work provides an in silico strategy to understand the action mechanisms of herbal medicines from molecular/system levels, which will promote the new drug development of traditional Chinese medicine.

Extensive Reliability Evaluation of Docking-Based Target-Fishing Strategies.

The development of target-fishing approaches, aimed at identifying the possible protein targets of a small molecule, represents a hot topic in medicinal chemistry. A successful target-fishing approach would allow for the elucidation of the mechanism of action of all therapeutically interesting compounds for which the actual target is still unknown. Moreover, target-fishing would be essential for preventing adverse effects of drug candidates, by predicting their potential off-targets, and it would speed up drug repurposing campaigns. However, due to the huge number of possible protein targets that a small-molecule might interact with, experimental target-fishing approaches are out of reach. In silico target-fishing represents a valuable alternative, and examples of receptor-based approaches, exploiting the large number of crystallographic protein structures determined to date, have been reported in the literature. To the best of our knowledge, no proper evaluation of such approaches is, however, reported yet. In the present work, we extensively assessed the reliability of docking-based target-fishing strategies. For this purpose, a set of X-ray structures belonging to different targets was selected, and a dataset of compounds, including 10 experimentally active ligands for each target, was created. A target-fishing benchmark database was then obtained, and used to assess the performance of 13 different docking procedures, in identifying the correct target of the dataset ligands. Moreover, a consensus docking-based target-fishing strategy was developed and evaluated. The analysis highlighted that specific features of the target proteins could affect the reliability of the protocol, which however, proved to represent a valuable tool in the proper applicability domain. Our study represents the first extensive performance assessment of docking-based target-fishing approaches, paving the way for the development of novel efficient receptor-based target fishing strategies.

Molecular Docking: Shifting Paradigms in Drug Discovery.

Molecular docking is an established in silico structure-based method widely used in drug discovery. Docking enables the identification of novel compounds of therapeutic interest, predicting ligand-target interactions at a molecular level, or delineating structure-activity relationships (SAR), without knowing a priori the chemical structure of other target modulators. Although it was originally developed to help understanding the mechanisms of molecular recognition between small and large molecules, uses and applications of docking in drug discovery have heavily changed over the last years. In this review, we describe how molecular docking was firstly applied to assist in drug discovery tasks. Then, we illustrate newer and emergent uses and applications of docking, including prediction of adverse effects, polypharmacology, drug repurposing, and target fishing and profiling, discussing also future applications and further potential of this technique when combined with emergent techniques, such as artificial intelligence.

Substituted N-(Pyrazin-2-yl)benzenesulfonamides; Synthesis, Anti-Infective Evaluation, Cytotoxicity, and In Silico Studies.

We prepared a series of substituted N-(pyrazin-2-yl)benzenesulfonamides as an attempt to investigate the effect of different linkers connecting pyrazine to benzene cores on antimicrobial activity when compared to our previous compounds of amide or retro-amide linker type. Only two compounds, 4-amino-N-(pyrazin-2-yl)benzenesulfonamide (MIC = 6.25 µg/mL, 25 µM) and 4-amino-N-(6-chloropyrazin-2-yl)benzenesulfonamide (MIC = 6.25 µg/mL, 22 µM) exerted good antitubercular activity against M. tuberculosis H37Rv. However, they were excluded from the comparison as they-unlike the other compounds-possessed the pharmacophore for the inhibition of folate pathway, which was proven by docking studies. We performed target fishing, where we identified matrix metalloproteinase-8 as a promising target for our title compounds that is worth future exploration.

[Recent research advances of 1-deoxynojirimycin and its derivatives].

The 1-DNJ named 1-deoxynojirimycinis (2R,3R,4R,5S)-2-(hydroxymethyl) piperidine-3,4,5-triol, which is the nature active components existingin mulberryresources including leaves, stems, roots and silkworm larva, silkworm chrysalis, etc.The 1-deoxynojirimycin is a polyhydroxylated piperidine alkaloid, which was first found in Streptomyces as an antibiotic. Then the Japanese researchers isolated it from the mulberry root. 1-DNJ can inhibit postprandial hyperglycemia by suppressing intestinal alpha glucosidase. Therefore, 1-DNJ is often used to treat treating diabetes and complicating disease and to prevent obesity and weight-related disorders. With the development of the researches, 1-deoxynojirimycin and its derivtiv was discovered to possess anti-hyperglycemic, anti-virus, anti-tumor functions and so on. Therefore,based on our current studythe existing knowledge on source, technique preparation process, pharmacokinetics, bioactivties,and in silico target fishing of 1-DNJ were summarized, so that the researchers may use it to explore future perspective of research on 1-DNJ.

Utilizing random Forest QSAR models with optimized parameters for target identification and its application to target-fishing server.

BACKGROUND: The identification of target molecules is important for understanding the mechanism of "target deconvolution" in phenotypic screening and "polypharmacology" of drugs. Because conventional methods of identifying targets require time and cost, in-silico target identification has been considered an alternative solution. One of the well-known in-silico methods of identifying targets involves structure activity relationships (SARs). SARs have advantages such as low computational cost and high feasibility; however, the data dependency in the SAR approach causes imbalance of active data and ambiguity of inactive data throughout targets. RESULTS: We developed a ligand-based virtual screening model comprising 1121 target SAR models built using a random forest algorithm. The performance of each target model was tested by employing the ROC curve and the mean score using an internal five-fold cross validation. Moreover, recall rates for top-k targets were calculated to assess the performance of target ranking. A benchmark model using an optimized sampling method and parameters was examined via external validation set. The result shows recall rates of 67.6% and 73.9% for top-11 (1% of the total targets) and top-33, respectively. We provide a website for users to search the top-k targets for query ligands available publicly at http://rfqsar.kaist.ac.kr . CONCLUSIONS: The target models that we built can be used for both predicting the activity of ligands toward each target and ranking candidate targets for a query ligand using a unified scoring scheme. The scores are additionally fitted to the probability so that users can estimate how likely a ligand-target interaction is active. The user interface of our web site is user friendly and intuitive, offering useful information and cross references.

Computer-aided discovery of two novel chalcone-like compounds active and selective against Leishmania infantum.

Leishmaniasis are infectious diseases caused by parasites of genus Leishmania that affect affects 12 million people in 98 countries mainly in Africa, Asia, and Latin America. Effective treatments for this disease are urgently needed. In this study, we present a computer-aided approach to investigate a set of 32 recently synthesized chalcone and chalcone-like compounds to act as antileishmanial agents. As a result, nine most promising compounds and three potentially inactive compounds were experimentally evaluated against Leishmania infantum amastigotes and mammalian cells. Four compounds exhibited EC50 in the range of 6.2-10.98µM. In addition, two compounds, LabMol-65 and LabMol-73, exhibited cytotoxicity in macrophages >50µM that resulted in better selectivity compared to standard drug amphotericin B. These two compounds also demonstrated low cytotoxicity and high selectivity towards Vero cells. The results of target fishing followed by homology modeling and docking studies suggest that these chalcone compounds could act in Leishmania because of their interaction with cysteine proteases, such as procathepsin L. Finally, we have provided structural recommendations for designing new antileishmanial chalcones.

Design and synthesis of a novel inhibitor of T. Viride chitinase through an in silico target fishing protocol.

In the last ten years, we identified and developed a new therapeutic class of antifungal agents, the macrocyclic amidinoureas. These compounds are active against several Candida species, including clinical isolates resistant to currently available antifungal drugs. The mode of action of these molecules is still unknown. In this work, we developed an in-silico target fishing procedure to identify a possible target for this class of compounds based on shape similarity, inverse docking procedure and consensus score rank-by-rank. Chitinase enzyme emerged as possible target. To confirm this hypothesis a novel macrocyclic derivative has been produced, specifically designed to increase the inhibition of the chitinase. Biological evaluation highlights a stronger enzymatic inhibition for the new derivative, while its antifungal activity drops probably because of pharmacokinetic issues. Collectively, our data suggest that chitinase represent at least one of the main target of macrocyclic amidinoureas.

Target identification, lead optimization and antitumor evaluation of some new 1,2,4-triazines as c-Met kinase inhibitors.

In silico target fishing approach using PharmMapper server identified c-Met kinase as the selective target for our previously synthesized compound NCI 748494/1. This approach was validated by in vitro kinase assay which showed that NCI 748494/1 possessed promising inhibitory activity against c-Met kinase (IC50=31.70µM). Assessment of ADMET profiling, drug-likeness, drug score as well as docking simulation for the binding pose of that compound in the active site of c-Met kinase domain revealed that NCI 748494/1 could be considered as a promising drug lead. Based on target identification and validation, it was observed that there is structure similarity between NCI 748494/1 and the reported type II c-Met kinase inhibitor BMS-777607. Optimization of our lead NCI 748494/1 furnished newly synthesized 1,2,4-triazine derivatives based on well-established structure-activity relationships, whereas three compounds namely; 4d, 7a and 8c displayed excellent in vitro cytotoxicity against three c-Met addicted cancer cell lines; A549 (lung adenocarcinoma), HT-29 (colon cancer) and MKN-45 (gastric carcinoma); with IC50 values in the range 0.01-1.86µM. In vitro c-Met kinase assay showed 8c to possess the highest c-Met kinase inhibition profile (IC50=4.31µM). Docking of the active compounds in c-Met kinase active site revealed strong binding interactions comparable to the lead NCI 748494/1 and BMS-777607, suggesting that c-Met inhibition is very likely to be the mechanism of the antitumor effect of these derivatives.