Shape-based virtual screening,docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand–enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6?Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.     

Synthesis, in vitro and in silico evaluation of l-tyrosine containing PPARalpha/gamma dual agonists

A novel series of l-tyrosine derivatives have been reported with potential PPARalpha/gamma dual agonistic activity. In vitro cell based PPARalpha/gamma transactivation studies have shown compound 4a and compound 4f to be the most potent PPARgamma and PPARalpha activators, respectively. Molecular docking studies performed on these series of compounds have complemented the experimental results and have led to interesting inferences.     

A microsatellite-based consensus linkage map for species of Eucalyptus and a novel set of 230 microsatellite markers for the genus

Background  

Eucalypts are the most widely planted hardwood trees in the world occupying globally more than 18 million hectares as an important source of carbon neutral renewable energy and raw material for pulp, paper and solid wood. Quantitative Trait Loci (QTLs) in Eucalyptus have been localized on pedigree-specific RAPD or AFLP maps seriously limiting the value of such QTL mapping efforts for molecular breeding. The availability of a genus-wide genetic map with transferable microsatellite markers has become a must for the effective advancement of genomic undertakings. This report describes the development of a novel set of 230 EMBRA microsatellites, the construction of the first comprehensive microsatellite-based consensus linkage map for Eucalyptus and the consolidation of existing linkage information for other microsatellites and candidate genes mapped in other species of the genus.     

Design of Benzene-1,2-diamines as selective inducible nitric oxide synthase inhibitors: a combined de novo design and docking analysis

Selective inhibition of inducible nitric oxide synthases (iNOS) has been a challenging problem for researchers pursuing work in finding methods to treat inflammatory disorders, shock, etc. Though many inhibitors have been studied to date, all are associated with selectivity or potency problems. Additionally, most of the reported compounds have several similarities and fewer number of novel structures are being tried. There is an increasing need to design novel molecules for this target. In this work, de novo design using LUDI, combined with docking analysis using FlexX has been employed in an attempt to identify novel scaffolds. Benzene-1,2-diamines were identified which could mimic the interactions of the substrate analogs and other inhibitors. Comparative docking scores in each of the isoforms of nitric oxide synthase were employed to recognize hits for iNOS selectivity. Figure Figure shows the docked poses of the ligand M226 along with that of the reference GW274150. (FlexX analysis)     

Mutational and Structural Analysis of Conserved Residues in Ribose-5-Phosphate Isomerase B from Leishmania donovani: Role in Substrate Recognition and Conformational Stability

Ribose-5-phosphate isomerase B from Leishmania donovani (LdRpiB) is one of the potential drug targets against visceral leishmaniasis. In the present study, we have targeted several conserved amino acids for mutational analysis (i.e. Cys69, His11, His102, His138, Asp45, Tyr46, Pro47 and Glu149) to gain crucial insights into their role in substrate binding, catalysis and conformational stability of the enzyme. All the eight LdRpiB variants were cloned, sequenced, expressed and purified. C69S, H102N, D45N and E149A mutants exhibited complete loss of enzyme activity indicating that they are indispensable for the enzyme activity. Kinetic parameters were altered in case of H138N, H11N and P47A variants; however Y46F exhibited similar kinetic behaviour as wild type. All the mutants except H138N exhibited altered protein structure as determined by CD and fluorescence spectral analysis. This data was supported by the atomic level details of the conformational changes and substrate binding using molecular dynamic simulations. LdRpiB also exhibited activity with D-form of various aldose substrates in the order of D-ribose > D-talose > D-allose > D-arabinose. Our study provides insights for better understanding of substrate enzyme interactions which can rationalize the process of drug design against parasite RpiB.     

Pharmacoinformatics analysis to identify inhibitors of Mtb-ASADH

Aspartate-semialdehyde dehydrogenase (ASADH; EC 1.2.1.11) is a key enzyme in the biosynthesis of essential amino acids in prokaryotes and fungi, inhibition of ASADH leads to the development of novel antitubercular agents. In the present work, a combined structure and ligand-based pharmacophore modeling, molecular docking, and molecular dynamics (MD) approaches were employed to identify potent inhibitors of mycobacterium tuberculosis (Mtb)-ASADH. The structure-based pharmacophore hypothesis consists of three hydrogen bond acceptor (HBA), two negatively ionizable, and one positively ionizable center, while ligand-based pharmacophore consists of additional one HBA and one hydrogen bond donor features. The validated pharmacophore models were used to screen the chemical databases (ZINC and NCI). The screened hits were subjected to ADME and toxicity filters, and subsequently to the molecular docking analysis. Best-docked 25 compounds carry the characteristics of highly electronegative functional groups (–COOH and –NO₂) on both sides and exhibited the H-bonding interactions with highly conserved residues Arg99, Arg249, and His256. For further validation of docking results, MD simulation studies were carried out on two representative compounds NSC51108 and ZINC04203124. Both the compounds remain bound to the key active residues of Mtb-ASADH during the MD simulations. These identified hits can be further used for lead optimization and in the design more potent inhibitors against Mtb-ASADH.     

3D-QSAR studies of substituted 1-(3, 3-diphenylpropyl)-piperidinyl amides and ureas as CCR5 receptor antagonists

3D-QSAR studies on the derivatives of 1-(3,3-diphenylpropyl)-piperidinyl amide and urea as CCR5 receptor antagonists were performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods to rationalize the structural requirements responsible for the inhibitory activity of these compounds. The global minimum energy conformer of the template molecule, the most active and pharmacokinetically stable molecule of the series, was obtained by systematic search and used to build structures of the molecules in the dataset. The best predictions for the CCR5-receptor were obtained with the CoMFA standard model (q ² = 0.787, r ² = 0.962) and CoMSIA model combined steric, electrostatic and hydrophobic fields (q ² = 0.809, r ² = 0.951). The predictive ability of CoMFA and CoMSIA were determined using a test set of 12 compounds giving predictive correlation coefficients of 0.855 and 0.83, respectively, indicating good predictive power. Further, the robustness of the model was verified by bootstrapping analysis. The contour maps produced by the CoMFA and CoMSIA models were used to identify the structural features relevant to the biological activity in this series. Based on the CoMFA and CoMSIA analysis, we have identified some key features in the series that are responsible for CCR5 antagonistic activity which may be used to design more potent 1-(3,3-diphenylpropyl)-piperidinyl derivatives and predict their activity prior to synthesis. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Quantification of angiogenesis in estrogen receptor-positive and negative breast carcinoma

Background

The objective of this study was to evaluate angiogenesis according to CD34 antigen expression in estrogen receptor (ER)-positive and negative breast carcinomas.

Methods

This study comprised 64 cases of infiltrating ductal carcinoma in postmenopausal women divided into two groups: Group A: ER-positive, n = 35; and Group B: ER-negative, n = 29. The anti-CD34 monoclonal antibody was used as a marker for endothelial cells. Microvessel count was carried out in 10 fields per slide using a 40× objective lens (magnification 400×). Statistical analysis of the data was performed using Student's t-test (p < 0.05).

Results

The mean number of vessels stained with the anti-CD34 antibody in the estrogen receptor-positive and negative tumors was 23.51 ± 1.15 and 40.24 ± 0.42, respectively. The number of microvessels was significantly greater in the estrogen receptor-negative tumors (p < 0.001).

Conclusion

ER-negative tumors have significantly greater CD34 antigen expression compared to ER-positive tumors.