Integration of ligand and structure based approaches for identification of novel MbtI inhibitors in Mycobacterium tuberculosis and molecular dynamics simulation studies

Mycobacterium tuberculosis is an obligate pathogen of mammals and is responsible for more than two million deaths annually. The ability to acquire iron from the extracellular environment is a key determinant of pathogenicity in mycobacteria. M. tuberculosis acquires iron exclusively through the siderophores. Several lines of evidence suggest that siderophores have a critical role in bacterial growth and virulence. Hence, in the present study, we have used a combined ligand and structure-based drug design approach for identification of novel inhibitors against salicylate synthase MbtI, a unique and essential enzyme for the biosynthesis of siderophores in M. tuberculosis. We have generated the ligand based and structure based pharmacophores and validated exhaustively. From the validation results it was found that GH (Goodness of Hit) scores for the selected ligand based and structure based pharmacophore models were 0.89 and 0.97, respectively, which indicate that the quality of the pharmacophore models are acceptable as GH value is >0.7. The validated pharmacophores were used for screening the ZINC database. A total of 73 hits, obtained through various insilico screening techniques, were further enriched to 17 hits using docking studies. Molecular dynamics simulations were carried out to compare the binding mode and stability of complexes of MbtI bound with substrate, known inhibitors, and three top ranked hits. The results obtained in this study gave assurance about the identified hits as prospective inhibitors of MbtI.     

Identification of Mycobacterium tuberculosis enoyl-acyl carrier protein reductase inhibitors: A combined in-silico and in-vitro analysis

Mycobacterium tuberculosis (Mtb), had developed evolutionary changes in its genome to adapt for survival and thereby generated multi-drug resistant strains. However, novel drug targets that remained unchanged for their biochemical role has impressed the research community to target such proteins. The comprehensive analysis of multiple protein targets has influenced us to make a consensus structural rule exploited by pharmacophore and other allied techniques from a large repository of protein structures. In this pursuit, we made a retrospective analysis of pharmacophores mapped from the tuberculosis structural proteome and identified unique patterns that can be employed for the novel molecules design. The current work on NADH–dependent enoyl–acyl carrier protein reductase (InhA) has yielded top scored pharmacophore models which were searched over SPECS natural product database to prioritize the molecules that can be targeted against Mtb. With efforts on rigorous validation and expertise, we have identified such pharmacophoric patterns from natural compounds that can be used as initial hits. Subsequently, these hits were subjected to in-vitro antitubercular evaluation to ensure the inhibitory activity against the mycobacterium culture growth (MtbH37Rv). Furthermore, docking simulations were carried out to provide an insight on the possible modes of interaction between the experimentally explored compounds and InhA.     

Identification of novel inhibitors against Mycobacterium tuberculosis l-alanine dehydrogenase (MTB-AlaDH) through structure-based virtual screening

Mycobacterium tuberculosis (MTB) the etiological agent of tuberculosis (TB) survives in the human host for decades evading the immune system in a latent or persistent state. The Rv2780 (ald) gene that codes for l-alanine dehydrogenase (l-AlaDH) enzyme catalyzes reversible oxidative deamination of l-alanine to pyruvate and is overexpressed under hypoxic and nutrient starvation conditions in MTB. At present, as there is no suitable drug available to treat dormant tuberculosis; it is essential to identify drug candidates that could potentially treat dormant TB. Availability of crystal structure of MTB l-AlaDH bound with co-factor NAD⁺ facilitated us to employ structure-based virtual screening approach to obtain new hits from a commercial library of Asinex database using energy-optimized pharmacophore modeling. The resulting pharmacophore consisted of three hydrogen bond donor sites (D) and two hydrogen bond acceptor sites (A). The database compounds with a fitness score more than 1.0 were further subjected to Glide high-throughput virtual screening and docking. Thus, we report the identification of best five hits based on structure-based design and their in vitro enzymatic inhibition studies revealed IC₅₀ values in the range of 35–80 μM.     

Identification and in vitro evaluation of new leads as selective and competitive glycogen synthase kinase-3β inhibitors through ligand and structure based drug design

Glycogen synthase kinase-3β elicits multi-functional effects on intracellular signaling pathways, thereby making the kinase a therapeutic target in multiple pathologies. Hence, it is important to selectively inhibit GSK-3β over structurally and biologically similar targets, such as CDK5. The current study was designed to identify and evaluate novel ATP-competitive GSK-3β inhibitors. The study was designed to identify new leads by ligand based drug design, structure based drug design and in vitro evaluation. The best validated pharmacophore model (AADRRR) identified using LBDD was derived from a dataset of 135 molecules. There were 357 primary hits within the SPECS database using this pharmacophore model. A SBDD approach to the GSK-3β and CDK5 proteins was applied to all primary hits, and 5 selective inhibitors were identified for GSK-3β. GSK-3β and CDK5 in vitro kinase inhibition assays were performed with these molecules to confirm their selectivity for GSK-3β. The molecules showed IC₅₀ values ranging from 0.825 μM to 1.116 μM and were 23- to 57-fold selective for GSK-3β. Of all the molecules, molecule 3 had the lowest IC₅₀ value of 0.825 μM. Our research identified molecules possessing benzothiophene, isoquinoline, thiazolidinedione imidazo-isoquinoline and quinazolinone scaffolds. Potency of these molecules may be due to H-bond interaction with backbone residues of Val135, Asp133 and side chain interaction with Tyr134. Selectivity over CDK5 may be due to side chain interactions with Asp200, backbone of Val61, ionic interaction with Lys60 and π-cationic interaction with Arg141. These selective molecules were also exhibited small atom hydrophobicity and H-bond interaction with water molecule.     

A mechanistic approach to explore novel HDAC1 inhibitor using pharmacophore modeling, 3D- QSAR analysis,molecular docking,density functional and molecular dynamics simulation study

Deregulated epigenetic activity of Histone deacetylase 1 (HDAC1) in tumor development and carcinogenesis pronounces it as promising therapeutic target for cancer treatment. HDAC1 has recently captured the attention of researchers owing to its decisive role in multiple types of cancer. In the present study a multistep framework combining ligand based 3D-QSAR, molecular docking and Molecular Dynamics (MD) simulation studies were performed to explore potential compound with good HDAC1 binding affinity. Four different pharmacophore hypotheses Hypo1 (AADR), Hypo2 (AAAH), Hypo3 (AAAR) and Hypo4 (ADDR) were obtained. The hypothesis Hypo1 (AADR) with two hydrogen bond acceptors (A), one hydrogen bond donor (D) and one aromatics ring (R) was selected to build 3D-QSAR model on the basis of statistical parameter. The pharmacophore hypothesis produced a statistically significant QSAR model, with co-efficient of correlation r² = 0.82 and cross validation correlation co-efficient q² = 0.70. External validation result displays high predictive power with r² (o) value of 0.88 and r² (m) value of 0.58 to carry out further in silico studies. Virtual screening result shows ZINC70450932 as the most promising lead where HDAC1 interacts with residues Asp99, His178, Tyr204, Phe205 and Leu271 forming seven hydrogen bonds. A high docking score (−11.17 kcal/mol) and lower docking energy −37.84 kcal/mol) displays the binding efficiency of the ligand. Binding free energy calculation was done using MM/GBSA to access affinity of ligands towards protein. Density Functional Theory was employed to explore electronic features of the ligands describing intramolcular charge transfer reaction. Molecular dynamics simulation studies at 50 ns display metal ion (Zn)-ligand interaction which is vital to inhibit the enzymatic activity of the protein.     

Molecular dynamics simulations of mutated Mycobacterium tuberculosis l-alanine dehydrogenase to illuminate the role of key residues

l-Alanine dehydrogenase from Mycobacterium tuberculosis (l-MtAlaDH) catalyzes the NADH-dependent interconversion of l-alanine and pyruvate, and it is considered to be a potential target for the treatment of tuberculosis. The experiment has verified that amino acid replacement of the conserved active-site residues which have strong stability and no great changes in biological evolutionary process, such as His96 and Asp270, could lead to inactive mutants [Ågren et al., J. Mol. Biol. 377 (2008) 1161–1173]. However, the role of these conserved residues in catalytic reaction still remains unclear. Based on the crystal structures, a series of mutant structures were constructed to investigate the role of the conserved residues in enzymatic reaction by using molecular dynamics simulations. The results show that whatever the conserved residues were mutated, the protein can still convert its conformation from open state to closed state as long as NADH is present in active site. Asp270 maintains the stability of nicotinamide ring and ribose of NADH through hydrogen bond interactions, and His96 is helpful to convert the protein conformation by interactions with Gln271, whereas, they would lead to the structural rearrangement in active site and lose the catalytic activity when they were mutated. Additionally, we deduce that Met301 plays a major role in catalytic reaction due to fixing the nicotinamide ring of NADH to prevent its rotation, and we propose that Met301 would be mutated to the hydrophobic residue with large steric hindrance in side chain to test the activity of the protein in future experiment.     

Discovery of high affinity ligands for β2-adrenergic receptor through pharmacophore-based high-throughput virtual screening and docking

Novel high affinity compounds for human β₂-adrenergic receptor (β₂-AR) were searched among the clean drug-like subset of ZINC database consisting of 9,928,465 molecules that satisfy the Lipinski's rule of five. The screening protocol consisted of a high-throughput pharmacophore screening followed by an extensive amount of docking and rescoring. The pharmacophore model was composed of key features shared by all five inactive states of β₂-AR in complex with inverse agonists and antagonists. To test the discriminatory power of the pharmacophore model, a small-scale screening was initially performed on a database consisting of 117 compounds of which 53 antagonists were taken as active inhibitors and 64 agonists as inactive inhibitors. Accordingly, 7.3% of the ZINC database subset (729,413 compounds) satisfied the pharmacophore requirements, along with 44 antagonists and 17 agonists. Afterwards, all these hit compounds were docked to the inactive apo form of the receptor using various docking and scoring protocols. Following each docking experiment, the best pose was further evaluated based on the existence of key residues for antagonist binding in its vicinity. After final evaluations based on the human intestinal absorption (HIA) and the blood brain barrier (BBB) penetration properties, 62 hit compounds have been clustered based on their structural similarity and as a result four scaffolds were revealed. Two of these scaffolds were also observed in three high affinity compounds with experimentally known K_i values. Moreover, novel chemical compounds with distinct structures have been determined as potential β₂-AR drug candidates.     

Identification of p38α MAP kinase inhibitors by pharmacophore based virtual screening

The p38α mitogen-activated protein (MAP) kinase plays a vital role in treating many inflammatory diseases. In the present study, a combined ligand and structure based pharmacophore model was developed to identify potential DFG-in selective p38 MAP kinase inhibitors. Conformations of co-crystallised inhibitors were used in the development and validation of ligand and structure based pharmacophore modeling approached. The validated pharmacophore was utilized in database screening to identify potential hits. After Lipinski's rule of five filter and molecular docking analysis, nineteen hits were purchased and selected for in vitro analysis. The virtual hits exhibited promising activity against tumor necrosis factor-α (TNF-α) with 23–98% inhibition at 10 μM concentration. Out of these seven compounds has shown potent inhibitory activity against p38 MAP kinase with IC₅₀ values ranging from 12.97 to 223.5 nM. In addition, the toxicity study against HepG2 cells was also carried out to confirm the safety profile of identified virtual hits.     

In silico screening and study of novel ERK2 inhibitors using 3D QSAR,docking and molecular dynamics

ERK2 is a dual specificity protein kinase, part of the Ras/Raf/MEK/ERK signal transduction cascade. It forms an interesting target for inhibition based on its relationship with cell proliferation and oncogenesis. A 3D QSAR pharmacophore model (Hypo1) with high correlation (r = 0.938) was developed for ERK2 ATP site on the basis of experimentally known inhibitors. The model included three hydrogen bonds, and one hydrophobic site. Assessment of Hypo1 through Fisher randomization, cost analysis, leave one out method and decoy test suggested that the model can reliably detect ERK2 inhibitors. Hypo1 has been used for virtual screening of potential inhibitors from ZINC, Drug Bank, NCI, Maybridge and Chembank databases. Using Hypo1 as a query, databases have been interrogated for compounds who meet the pharmacophore features. The resulting hit compounds were subject to docking and analysis. Docking and molecular dynamics analysis showed that in order to achieve a higher potency compounds have to interact with catalytic site, glycine rich loop, Hinge region, Gatekeeper region and ATP site entrance residues. We also identified catalytic site and Glycine rich loop as important regions to bind by molecules for better potency and selectivity.     

Molecular modeling study on the effect of residues distant from the nucleotide-binding portion on RNA binding in Staphylococcus aureus Hfq

Hfq is an abundant RNA-binding bacterial protein that was first identified in E. coli as a required host factor for phage Qβ RNA replication. The pleiotrophic phenotype resulting from the deletion of Hfq predicates the importance of this protein. Two RNA-binding sites have been characterized: the proximal site which binds sRNA and mRNA and the distal site which binds poly(A) tails. Previous studies mainly focused on the key residues in the proximal site of the protein. A recent mutation study in E. coli Hfq showed that a distal residue Val43 is important for the protein function. Interestingly, when we analyzed the sequence and structure of Staphylococcus aureus Hfq using the CONSEQ server, the results elicited that more functional residues were located far from the nucleotide-binding portion (NBP). From the analysis seven individual residues Asp9, Leu12, Glu13, Lys16, Gln31, Gly34 and Asp40 were selected to investigate the conformational changes in Hfq–RNA complex due to point mutation effect of those residues using molecular dynamics simulations. Results showed a significant effect on Asn28 which is an already known highly conserved functionally important residue. Mutants D9A, E13A and K16A depicted effects on base stacking along with increase in RNA pore diameter, which is required for the threading of RNA through the pore for the post-translational modification. Further, the result of protein stability analysis by the CUPSAT server showed destabilizing effect in the most mutants. From this study we characterized a series of important residues located far from the NBP and provide some clues that those residues may affect sRNA binding in Hfq.     

Pharmacophore modeling,virtual screening,docking and in silico ADMET analysis of protein kinase B (PKB β) inhibitors

Protein kinase B (PKB) is a key mediator of proliferation and survival pathways that are critical for cancer growth. Therefore, inhibitors of PKB are useful agents for the treatment of cancer. Herein, we describe pharmacophore-based virtual screening combined with docking study as a rational strategy for identification of novel hits or leads. Pharmacophore models of PKB β inhibitors were established using the DISCOtech and refined with GASP from compounds with IC₅₀ values ranging from 2.2 to 246 nM. The best pharmacophore model consists of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD) site and two hydrophobic (HY) features. The pharmacophore models were validated through receiver operating characteristic (ROC) and Güner-Henry (GH) scoring methods indicated that the model-3 was statistically valuable and reliable in identifying PKB β inhibitors. Pharmacophore model as a 3D search query was searched against NCI database. Several compounds with different structures (scaffolds) were retrieved as hits. Molecules with a Q_fit value of more than 95 and three other known inhibitors were docked in the active site of PKB to further explore the binding mode of these compounds. Finally in silico pharmacokinetic and toxicities were predicted for active hit molecules. The hits reported here showed good potential to be PKB β inhibitors.     

Isolation and in silico evaluation of antidiabetic molecules of Cynodon dactylon (L.)

Cynodon dactylon is a potential source of metabolites such as flavanoids, alkaloids, glycosides and β-sitosterol and has been traditionally employed to treat urinary tract and other microbial infections and dysentery. The present work attempts to evaluate the activity of C. dactylon extracts for glycemic control. Aqueous extracts of C. dactylon analyzed by HPLC–ESI MS have identified the presence of apigenin, luteolin, 6-C-pentosyl-8-C-hexosyl apigenin and 6-C-hexosyl-8-C-pentosyl luteolin. Evaluation of hypoglycemic activity through an extensive in silico docking approach with PPARγ (Peroxisome Proliferator-Activated Receptor), GLUT-4 (glucose transporter-4) and SGLT2 (sodium glucose co-transporter-2) revealed that luteolin, apigenin, 6-C-pentosyl-8-C-hexosyl apigenin, 6-C-hexosyl-8-C-pentosyl luteolin interact with SGLT2. Interactions of these molecules with Gln 295 and Asp 294 residues of SGLT2 have been shown to compare well with that of the phase III drug, dapagliflozin. These residues have been proven to be responsible for sugar sensing and transport. This work establishes C. dactylon extract as a potential SGLT2 inhibitor for diabetic neuropathy thus enabling a possibility of this plant extract as a new alternative to existing diabetic approaches.     

Unravelling the structural interactions between PKR kinase domain and its small molecule inhibitors using computational approaches

The RNA-dependent protein kinase (PKR), an eIF2α kinase plays an important role in anti-viral response, apoptosis and cell survival. It is also implicated to play a role in several cancers, metabolic and neurodegenerative disorders. A few ATP competitive inhibitors of the PKR have been reported in the literature with promising results in vitro and in vivo. The aim of this study was to unravel the structural interactions between these inhibitors and the PKR kinase domain using molecular simulations and docking. Our study reveals that the reported inhibitors bind in the adenine pocket and form hydrogen bonds with the hinge region and vdW interactions with non-polar residues in the binding site. The most potent inhibitor has several favorable interactions with the binding site and induces the P-loop to fold inward, creating a significant hydrophobic enclosure for itself. The computed binding free energies of these inhibitors are in accord with experimental data (IC₅₀). Strategies to design potent and selective PKR inhibitors are discussed to overcome the reported promiscuity.     

A structural insight into the inhibitory mechanism of an orally active PI3K/mTOR dual inhibitor,PKI-179 using computational approaches

The PI3K/AKT/mTOR signaling pathway has been identified as an important target for cancer therapy. Attempts are increasingly made to design the inhibitors against the key proteins of this pathway for anti-cancer therapy. The PI3K/mTOR dual inhibitors have proved more effective than the inhibitors against only single protein targets. Recently discovered PKI-179, an orally effective compound, is one such dual inhibitor targeting both PI3K and mTOR. This anti-cancer compound is efficacious both in vitro and in vivo. However, the binding mechanisms and the molecular interactions of PKI-179 with PI3K and mTOR are not yet available. The current study investigated the exact binding mode and the molecular interactions of PKI-179 with PI3Kγ and mTOR using molecular docking and (un)binding simulation analyses. The study identified PKI-179 interacting residues of both the proteins and their importance in binding was ranked by the loss in accessible surface area, number of molecular interactions of the residue, and consistent appearance of the residue in (un)binding simulation analysis. The key residues involved in binding of PKI-179 were Ala-805 in PI3Kγ and Ile-2163 in mTOR as they have lost maximum accessible surface area due to binding. In addition, the residues which played a role in binding of the drug but were away from the catalytic site were also identified using (un)binding simulation analyses. Finally, comparison of the interacting residues in the respective catalytic sites was done for the difference in the binding of the drug to the two proteins. Thus, the pairs of the residues falling at the similar location with respect to the docked drug were identified. The striking similarity in the interacting residues of the catalytic site explains the concomitant inhibition of both proteins by a number of inhibitors. In conclusion, the docking and (un)binding simulation analyses of dual inhibitor PKI-179 with PI3K and mTOR will provide a suitable multi-target model for studying drug–protein interactions and thus help in designing the novel drugs with higher potency.     

Binding mode analyses and pharmacophore model development for sulfonamide chalcone derivatives,a new class of α-glucosidase inhibitors

Sulfonamide chalcone derivatives are a new class of non-saccharide compounds that effectively inhibit glucosidases which are the major targets in the treatment of Type 2 diabetes and HIV infection. Our aim is to explore their binding mode of interaction at the active site by comparing with the sugar derivatives and to develop a pharmacophore model which would represent the critical features responsible for α-glucosidase inhibitory activity. The homology modeled structure of Saccharomyces cerevisiae α-glucosidase was built and used for molecular docking of non-sugar/sugar derivatives. The validated docking results projected the crucial role of NH group in the binding of sugar/non-sugar derivatives to the active site. Ligplot analyses revealed that Tyr71, and Phe177 form hydrophobic interactions with sugar/non-sugar derivatives by holding the terminal glycosidic ring mimics. Molecular dynamic (MD) simulation studies were performed for protein alone and with chalcone derivative to prove its binding mechanism as shown by docking/Ligplot results. It would also help to substantiate the homology modeled structure stability. With the knowledge of the crucial interactions between ligand and protein from docking and MD simulation studies, features for pharmacophore model development were chosen. The CATALYST/HipHop was used to generate a five featured pharmacophore model with a training set of five non-sugar derivatives. As validation, all the crucial features of the model were perfectly mapped onto the 3D structures of the sugar derivatives as well as the newly tested non-sugar derivatives. Thus, it can be useful in virtual screening for finding new non-sugar derivatives as α-glucosidase inhibitors.     

In silico identification of novel inhibitors against Plasmodium falciparum dihydroorate dehydrogenase

Plasmodium falciparum causes the most fatal form of malaria and accounts for over 1 million deaths annually, yet currently used drug therapies are compromised by resistance. The malaria parasite cannot salvage pyrimidines and relies on de novo biosynthesis for survival. The enzyme dihydrooratate dehydrogenase (DHODH), a mitochondrial flavoenzyme, catalyzes the rate-limiting step of this pathway and is therefore an attractive anti-malarial chemotherapeutic target. In an effort to design new and potential anti-malarials, structure-based pharmacophore mapping, molecular docking, binding energy calculations and binding affinity predictions were employed in a virtual screening strategy to design new and potent P. falciparum dihydrooratate dehydrogenase (PfDHODH) inhibitors. A structure-based pharmacophore model was generated which consist of important interactions as observed in co-crystal of PfDHODH enzyme. The developed model was used to retrieve molecules from ChemBridge database, a freely available commercial database. A total of 87 molecules mapped on the modeled pharmacophore from the database. The retrieved hits were further screened by docking simulation, binding energy calculations and biding affinity predictions using genetic optimization for ligand docking (GOLD) and MOE. Based on these results, finally 26 chemo-types molecules were predicted as new, potential and structurally diverse PfDHODH inhibitors.     

Multi-step virtual screening to develop selective DYRK1A inhibitors

Developing selective inhibitors for a particular kinase remains a major challenge in kinase-targeted drug discovery. Here we performed a multi-step virtual screening for dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) inhibitors by focusing on the selectivity for DYRK1A over cyclin-dependent kinase 5 (CDK5). To examine the key factors contributing to the selectivity, we constructed logistic regression models to discriminate between actives and inactives for DYRK1A and CDK5, respectively, using residue-based binding free energies. The residue-based parameters were calculated by molecular mechanics-generalized Born surface area (MM-GBSA) decomposition methods for kinase–ligand complexes modeled by computer ligand docking. Based on the findings from the logistic regression models, we built a three-dimensional (3D) pharmacophore model and chose filter criteria for the multi-step virtual screening. The virtual hit compounds obtained from the screening were assessed for their inhibitory activities against DYRK1A and CDK5 by in vitro assay. Our screening identified two novel selective DYRK1A inhibitors with IC₅₀ values of several μM for DYRK1A and >100 μM for CDK5, which can be further optimized to develop more potent selective DYRK1A inhibitors.     

Identification of novel PAD4 inhibitors based on a pharmacophore model derived from transition state coordinates

1.4 Protein arginine deiminases 4 (PAD4) is an attractive target for the development of novel and selective inhibitors of Rheumatoid Arthritis (RA). F-amidine is known as mechanism-based inhibitor targeting PAD4 and used as inactivators by covalently modifying the active site Cys645. To identify novel structural inhibitors of PAD4, we investigated the flexibility of protein on basis of the transition state geometry of PAD4 inhibited by F-amidine from our previous QM/MM calculation. And a pharmacophore model was generated containing four features (ADHH) using five representative structures from molecular dynamic (MD) simulation on basis of the transition state geometry of PAD4 inhibited by F-amidine. We performed virtual screening using the pharmacophore model and molecular docking methods, resulting in the discovery of two molecules with K_D (dissociation equilibrium constant) values of 112 μM and 218 μΜ against PAD4 through Surface Plasmon Resonance (SPR) experiments. These two molecules could potentially serve as PAD4 inhibitors.     

Computational investigation of interactions between human H2 receptor and its agonists

Type 2 histamine receptor (H(2)R) is widely distributed in the body. Its main function is modulating the secretion of gastric acid. Most gastric acid-related diseases are closely associated with it. In this study, a combination of pharmacophore modeling, homology modeling, molecular docking and molecular dynamics methods were performed on human H(2)R and its agonists to investigate interaction details between them. At first, a pharmacophore model of H(2)R agonists was developed, which was then validated by QSAR and database searching. Afterwards, a model of the H(2)R was built utilizing homology modeling method. Then, a reference agonist was docked into the receptor model by induced fit docking. The 'induced' model can dramatically improve the recovery ratio from 46.8% to 69.5% among top 10% of the ranked database in the simulated virtual screening. The pharmocophore model and the receptor model matched very well each other, which provided valuable information for future studies. Asp98, Asp186 and Tyr190 played key roles in the binding of H(2)R agonists, and direct interactions were observed between the three residues and agonists. Residue Tyr250 could also form a hydrogen bond with H(2)R agonists. These findings would be very useful for the discovery of novel and potent H(2)R agonists.     

Sub-microliter scale in-gel loop-mediated isothermal amplification (LAMP) for detection of Mycobacterium tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a common human disease that is prevalent in resource-deprived areas of the world. Current detection techniques for TB require expensive conventional instruments in a laboratory setting, preventing accessible and low cost diagnosis of the disease. Using a loop-mediated isothermal amplification (LAMP) assay, we have amplified and detected TB in a 6 × 8 semisolid polyacrylamide gel post array using an inexpensive prototype instrument. Each post contains 670 nL of volume, minimizing the need for large quantities of reagents. Amplified DNA is detected via fluorescence of the dye LCGreen Plus+, which is polymerized into the gel along with other reagents. The prototype device contains a Peltier element for heating, a diode laser as an excitation source, and a CCD camera for detecting fluorescence in real-time. About 12 Mycobacterium tuberculosis genomes per gel post can be detected within 75 min of amplification. This sensitivity is similar to that obtained by conventional methods using a commercial thermocycler. We achieved comparable LAMP amplification when the template is added externally or when the template is polymerized in the gel. This rapid isothermal amplification technology, with its simple thermal requirements, has the potential to be integrated into micro-devices and serves as a model for implementing future low-cost point of care diagnostics.