Discovery of Novel Focal Adhesion Kinase Inhibitors Using a Hybrid Protocol of Virtual Screening Approach Based on Multicomplex-Based Pharmacophore and Molecular Docking

Focal adhesion kinase (FAK) is a tyrosine kinase that functions as a key orchestrator of signals leading to invasion and metastasis. In the current study, the multicomplex-based pharmacophore (MCBP)-guided method has been suggested to generate a comprehensive pharmacophore of FAK kinase based on seven crystal structures of FAK-inhibitor complexes. In this investigation, a hybrid protocol of virtual screening methods, comprising of pharmacophore model-based virtual screening (PB-VS) and docking-based virtual screening (DB-VS), is used for retrieving new FAK inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen several chemical databases, including the Specs (202,408 compounds) database. Thirty-five compounds were selected from the final hits and should be shifted to experimental studies. These results may provide important information for further research of novel FAK inhibitors.     

Combined Pharmacophore Modeling,Docking, and 3D QSAR Studies of ABCB1 and ABCC1 Transporter Inhibitors

Quinazolinones, indolo‐ and pyrrolopyrimidines with inhibitory effects toward ABCB1 (P‐gp) and ABCC1 (MRP1) transporters were studied by pharmacophore modeling, docking, and 3D QSAR to describe the binding preferences of the proteins. The pharmacophore overlays between dual and/or highly selective inhibitors point to binding sites of different topology and physiochemical properties for MRP1 and P‐gp. Docking of selective inhibitors into the P‐gp binding cavity by the use of a structural model based on the recently resolved P‐gp structure confirms the P‐gp pharmacophore features identified, and reveals the interactions of some functional groups and atoms in the structures with particular protein residues. The 3D QSAR analysis of the dual‐effect inhibitors allows satisfactory prediction of the selectivity index of the compounds and outlines electrostatics as most important for selectivity. The results from the combined modeling approach complement each other and could improve our understanding of the protein–ligand interactions involved, and could aid in the development of highly selective and potent inhibitors of P‐gp and MRP1.     

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q² = 0.621, r²_pred = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.     

Molecular Dynamics Simulation of Tryptophan Hydroxylase-1: Binding Modes and Free Energy Analysis to Phenylalanine Derivative Inhibitors

Serotonin is a neurotransmitter that modulates many central and peripheral functions. Tryptophan hydroxylase-1 (TPH1) is a key enzyme of serotonin synthesis. In the current study, the interaction mechanism of phenylalanine derivative TPH1 inhibitors was investigated using molecular dynamics (MD) simulations, free energy calculations, free energy decomposition analysis and computational alanine scanning. The predicted binding free energies of these complexes are consistent with the experimental data. The analysis of the individual energy terms indicates that although the van der Waals and electrostatics interaction contributions are important in distinguishing the binding affinities of these inhibitors, the electrostatic contribution plays a more crucial role in that. Moreover, it is observed that different configurations of the naphthalene substituent could form different binding patterns with protein, yet lead to similar inhibitory potency. The combination of different molecular modeling techniques is an efficient way to interpret the interaction mechanism of inhibitors and our work could provide valuable information for the TPH1 inhibitor design in the future.     

Novel Hybrid Virtual Screening Protocol Based on Molecular Docking and Structure-Based Pharmacophore for Discovery of Methionyl-tRNA Synthetase Inhibitors as Antibacterial Agents

Methione tRNA synthetase (MetRS) is an essential enzyme involved in protein biosynthesis in all living organisms and is a potential antibacterial target. In the current study, the structure-based pharmacophore (SBP)-guided method has been suggested to generate a comprehensive pharmacophore of MetRS based on fourteen crystal structures of MetRS-inhibitor complexes. In this investigation, a hybrid protocol of a virtual screening method, comprised of pharmacophore model-based virtual screening (PBVS), rigid and flexible docking-based virtual screenings (DBVS), is used for retrieving new MetRS inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen the Specs (202,408 compounds) database, a structurally diverse chemical database. Fifteen hit compounds were selected from the final hits and shifted to experimental studies. These results may provide important information for further research of novel MetRS inhibitors as antibacterial agents.     

Modelling Atypical Small‐Molecule Mimics of an Important Stem Cell Cytokine,Thrombopoietin

We report the first comprehensive 3D QSAR study of a large, structurally diverse set of compounds that act as atypical thrombopoietin (TPO) mimics by interacting with the transmembrane domain of the TPO receptor, c‐MPL. These agonists of c‐MPL were superimposed according to a pharmacophore hypothesis, resulting in 3D QSAR models of high statistical significance. The pharmacophore‐based superimposition and comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to derive the QSAR models relating structure to the published in vitro bioactivities of the TPO mimics. The CoMFA and CoMSIA models gave high correlation coefficients of the bioactivities with the derived fields, resulting in robust prediction of agonist activity of the superimposed compounds. The models have been interpreted in terms of the requirements for binding to the transmembrane domain of the TPO receptor.     

3D QSAR Studies,Pharmacophore Modeling and Virtual Screening on a Series of Steroidal Aromatase Inhibitors

Aromatase inhibitors are the most important targets in treatment of estrogen-dependent cancers. In order to search for potent steroidal aromatase inhibitors (SAIs) with lower side effects and overcome cellular resistance, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of SAIs to build 3D QSAR models. The reliable and predictive CoMFA and CoMSIA models were obtained with statistical results (CoMFA: q² = 0.636, r²_ncv = 0.988, r²_pred = 0.658; CoMSIA: q² = 0.843, r²_ncv = 0.989, r²_pred = 0.601). This 3D QSAR approach provides significant insights that can be used to develop novel and potent SAIs. In addition, Genetic algorithm with linear assignment of hypermolecular alignment of database (GALAHAD) was used to derive 3D pharmacophore models. The selected pharmacophore model contains two acceptor atoms and four hydrophobic centers, which was used as a 3D query for virtual screening against NCI2000 database. Six hit compounds were obtained and their biological activities were further predicted by the CoMFA and CoMSIA models, which are expected to design potent and novel SAIs.     

The Discovery of Potentially Selective Human Neuronal Nitric Oxide Synthase (nNOS) Inhibitors: A Combination of Pharmacophore Modelling,CoMFA, Virtual Screening and Molecular Docking Studies

Neuronal nitric oxide synthase (nNOS) plays an important role in neurotransmission and smooth muscle relaxation. Selective inhibition of nNOS over its other isozymes is highly desirable for the treatment of neurodegenerative diseases to avoid undesirable effects. In this study, we present a workflow for the identification and prioritization of compounds as potentially selective human nNOS inhibitors. Three-dimensional pharmacophore models were constructed based on a set of known nNOS inhibitors. The pharmacophore models were evaluated by Pareto surface and CoMFA (Comparative Molecular Field Analysis) analyses. The best pharmacophore model, which included 7 pharmacophore features, was used as a search query in the SPECS database (SPECS^®, Delft, The Netherlands). The hit compounds were further filtered by scoring and docking. Ten hits were identified as potential selective nNOS inhibitors.     

Combined pharmacophore modeling, docking, and 3D-QSAR studies of PLK1 inhibitors

Polo-like kinase 1, an important enzyme with diverse biological actions in cell mitosis, is a promising target for developing novel anticancer drugs. A combined molecular docking, structure-based pharmacophore modeling and three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on a set of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as PLK1 inhibitors. The common substructure, molecular docking and pharmacophore-based alignment were used to develop different 3D-QSAR models. The comparative molecular field analysis (CoMFA) and comparative molecule similarity indices analysis (CoMSIA) models gave statistically significant results. These models showed good q(2) and r(2) (pred) values and revealed a good response to test set validation. All of the structural insights obtained from the 3D-QSAR contour maps are consistent with the available crystal structure of PLK1. The contour maps obtained from the 3D-QSAR models in combination with the structure based pharmacophore model help to better interpret the structure-activity relationship. These satisfactory results may aid the design of novel PLK1 inhibitors. This is the first report on 3D-QSAR study of PLK1 inhibitors.     

Design and Synthesis of a Novel PLK1 Inhibitor Scaffold Using a Hybridized 3D-QSAR Model

Polo-like kinase 1 (PLK1) plays an important role in cell cycle progression and proliferation in cancer cells. PLK1 also contributes to anticancer drug resistance and is a valuable target in anticancer therapeutics. To identify additional effective PLK1 inhibitors, we performed QSAR studies of two series of known PLK1 inhibitors and proposed a new structure based on a hybridized 3D-QSAR model. Given the hybridized 3D-QSAR models, we designed and synthesized 4-benzyloxy-1-(2-arylaminopyridin-4-yl)-1H-pyrazole-3-carboxamides, and we inspected its inhibitory activities to identify novel PLK1 inhibitors with decent potency and selectivity.     

5-Hydroxytryptophan (5-HTP): Natural Occurrence,Analysis, Biosynthesis,Biotechnology, Physiology and Toxicology

L-5-hydroxytryptophan (5-HTP) is both a drug and a natural component of some dietary supplements. 5-HTP is produced from tryptophan by tryptophan hydroxylase (TPH), which is present in two isoforms (TPH1 and TPH2). Decarboxylation of 5-HTP yields serotonin (5-hydroxytryptamine, 5-HT) that is further transformed to melatonin (N-acetyl-5-methoxytryptamine). 5-HTP plays a major role both in neurologic and metabolic diseases and its synthesis from tryptophan represents the limiting step in serotonin and melatonin biosynthesis. In this review, after an look at the main natural sources of 5-HTP, the chemical analysis and synthesis, biosynthesis and microbial production of 5-HTP by molecular engineering will be described. The physiological effects of 5-HTP are discussed in both animal studies and human clinical trials. The physiological role of 5-HTP in the treatment of depression, anxiety, panic, sleep disorders, obesity, myoclonus and serotonin syndrome are also discussed. 5-HTP toxicity and the occurrence of toxic impurities present in tryptophan and 5-HTP preparations are also discussed.     

Structure–Activity Relationships of 2‐Sufonylpyrimidines as Quorum‐Sensing Inhibitors to Tackle Biofilm Formation and eDNA Release of Pseudomonas aeruginosa

Drug‐resistant Pseudomonas aeruginosa (PA) strains are on the rise, making treatment with current antibiotics ineffective. Hence, circumventing resistance or restoring the activity of antibiotics by novel approaches is of high demand. Targeting the Pseudomonas quinolone signal quorum sensing (PQS‐QS) system is an intriguing strategy to abolish PA pathogenicity without affecting the viability of the pathogen. Herein we report the structure–activity relationships of 2‐sulfonylpyrimidines, which were previously identified as dual‐target inhibitors of the PQS receptor PqsR and the PQS synthase PqsD. The SAR elucidation was guided by a combined approach using ligand efficiency and ligand lipophilicity efficiency to select the most promising compounds. In addition, the most effective inhibitors were rationally modified by the guidance of QSAR using Hansch analyses. Finally, these inhibitors showed the capacity to decrease biofilm mass and extracellular DNA, which are important determinants for antibiotic resistance.     

A 3D QSAR model of 17beta-HSD1 inhibitors based on a thieno[2,3-d]pyrimidin-4(3H)-one core applying molecular dynamics simulations and ligand-protein docking

The 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) enzyme plays a crucial role in female hormonal regulation by catalysing the NADPH-dependent reduction of the less potent estrone E1 into the biologically active estradiol E2. Because 17beta-HSD1 is a key enzyme in E2 biosynthesis, it has emerged as an attractive drug target for inhibitor development. Herein we report the plausible binding modes and a 3D QSAR model of 17beta-HSD1 inhibitors based on a (di)cycloalkenothieno[2,3-d]pyrimidin-4(3H)-one core. Two generated enzyme complexes with potent inhibitors were subjected to molecular dynamics simulation to mimic the dynamic process of inhibitor binding. A set of 17beta-HSD1 inhibitors based on the thieno[2,3-d]pyrimidin-4(3H)-one core were docked into the resulting active site, and a CoMFA model employing the most extensive training set to date was generated. The model was validated with an external test set. Active site residues involved in inhibitor binding and CoMFA fields for steric and electrostatic interactions were identified. The model will be used to guide structural modifications of 17beta-HSD1 inhibitors based on a thieno[2,3-d]pyrimidin-4(3H)-one core in order to improve the biological activity as well as in the design of novel 17beta-HSD1 inhibitors.