In silico insights into the identification of potential novel angiogenic inhibitors against human VEGFR-2: a new SAR-based hierarchical clustering approach

Abstract

In this study, binding efficiency of new pyrrolopyrimidine structural analogs against human vascular endothelial growth factor receptor-2 (VEGFR-2) were elucidated using integrated in silico methods. Optimized high-resolution model of VEGFR-2 was generated and adopted for structure-based virtual screening approaches. Pyrrolopyrimidine inhibitor (CP15) associated compounds were screened from PubChem database and subjected to virtual screening and comparative docking methods against the receptor ligand-binding domain. Accordingly, high efficient compounds were clustered with similarity indices through PubChem structure cluster module using single-linkage algorithm. Moreover, pharmacokinetics including drug metabolism activities of high-binding leads under investigation was portrayed using ADMET and similarity ensemble analysis. Optimal energy orientations of the selected protein model have been shown to be reliable, and highly recommended for screening and docking studies. Docking and clustering strategies were shown that nineteen candidates as most effective binders for VEGFR-2 than CP15, and are grouped as three classes. Lys⁸⁶⁸, Glu⁸⁸⁵, Cys⁹¹⁹, His¹⁰²⁶, Arg¹⁰²⁷, Asp¹⁰⁴⁶, and Gly¹⁰⁴⁸ residues were predicted as novel hotspot residues, and participate in H-bonds, π-cation, π-stacking, halogen bonds, and salt-bridges formation with ligands. These additional bonds are contributing extent stability that holds the receptor structure at flexible state, this make difficult to any further conformational changes for evoking angiogenic signals. The ADMET and similarity ensemble analysis results were strongly indicated that thirteen candidates as best ligands for angiogenesis targets. Altogether, these findings indicate potential angiogenic templates and their binding levels with VEGFR-2; sorted viewpoints could be useful as a promising way to describe potential angiogenesis inhibitors with related molecular targets.     

Implementing a spatial model of Urban Carrying Capacity Load Number (UCCLN) to monitor the environmental loads of urban ecosystems. Case study: Tehran metropolis

The non-linear, unexpected and severe responses of ecosystems to the environmental changes crossing ecological thresholds or environmental limits, necessitate the regular monitoring of the human-induced pressures to the urban ecosystems. The present study aims to introduce a spatial decision support system for sustainable environmental planning and management of urban ecosystems by establishing an Urban Carrying Capacity Load Number model (UCCLN) based on carrying capacity concepts and sustainability principles .This model, by applying 30 temporal and spatial indicators continuously monitors the environmental loads on the urban ecosystems. Environmental load was represented by load number index. It was calculated in each zone of study area (urban districts). Geographical Information System (GIS) was used to establish UCCLN model and Spatial Decision Support System (SDSS). The study area was Tehran metropolis, the capital of Iran. The results showed that none of the 115 urban districts of Tehran had optimal Total Load Number (TLN) ranging from (10 to100); 7 districts (6%) had low-to-medium range of TLN (TLN = 100–200); 11 districts (9.5%) had medium-to-high range (TLN = 200–300); 57 districts (49.5%) had high-to-very high range (TLN = 300–400); 40 districts (34.7%) had the TLN range of very high-to-critical (TLN = 400–500); and none of them had the TLN of 500. Furthermore, the results revealed that Tehran has already overshot its ecological thresholds. Not only most of the 30 indicators of environmental pressure in most of the districts (85%) had high DCC and LN scores, but also most of the 115 districts obtained high DCC, and as a result LN scores. The need for developing more efficient urban planning and management strategies to cope with the increasing environmental loads in the study area is inevitable.     

Do species population parameters and landscape characteristics affect the relationship between local population abundance and surrounding habitat amount?

In landscape ecology, correlational approaches are typically used to analyse links between local population abundance, and the surrounding habitat amount to estimate biologically-relevant landscape size (extent) for managing endangered or pest populations. The direction, strength, and spatial extent of the correlations are then sometimes interpreted in terms of species population parameters. Here we simulated the population dynamics of generalized species across spatially explicit landscapes that included two distinct habitat types. We investigated how characteristics of a landscape (structure), including the variation in habitat quality and spatial aggregation of the habitat, and the precise population-dynamic properties of the simulated species (dispersal and growth rates) affect the correlation between population abundance and amount of surrounding favourable habitat in the landscape. To evaluate these spatial extents of correlation, proportions of favourable habitat were calculated within several circles of increasing diameter centred on sampling patches of favourable habitat where population abundance was recorded.We found that the value of the correlation coefficients between population abundance and amount of surrounding favourable habitat depended on both population dynamic parameters and landscape characteristics. Coefficients of correlation increased with the variation in habitat quality and the aggregation of favourable habitat in the landscape, but decreased with the dispersal distance. The distance at which the correlation was maximized was sensitive to an interaction between the level of aggregation of the habitat and the dispersal distance; whereas the greatest distance at which a significant correlation occurred was more sensitive to the variation in habitat quality. Our results corroborate the view that correlational analyses do provide information on the local population dynamics of a species in a given habitat type and on its dispersal rate parameters. However, even in simplified, model frameworks, direct relationships are often difficult to disentangle and global landscape characteristics should be reported in any studies intended to derive population-dynamic parameters from correlations. Where possible, replicated landscapes should be examined in order to control for the interaction between population dynamics and landscape structure. Finally, we recommend using species-specific, population-dynamic modelling in order to interpret correctly the observed patterns of correlation in the landscape.     

Drove roads: Keystone structures that promote ant diversity in Mediterranean forest landscapes

Drove roads are the traditional corridors used by pastoralists for seasonal movements of livestock (transhumance). They cover a considerable land area in Mediterranean countries and, although they are an obvious source of landscape diversity, their influence on the diversity and composition of animal assemblages has not been documented. Ant communities were studied on four active drove roads, two in forests (submediterranean and conifer) and two in open environments (croplands and rangelands). They were compared with the respective matrix communities and their contribution to local species richness was evaluated. The effects were heavily dependent on the open or closed nature of the matrix. In forest environments, drove roads increased ant species richness at the local scale, acting as clear keystone structures. Their species richness and functional diversity were highest on the fine scale, species composition was different, and a slight edge effect in the matrix was detected. In contrast, drove roads had little or even a negative effect in open environment locations. We conclude that drove roads have a high conservation value for ants in Mediterranean forest environments, in addition to their importance as reservoirs of plant biodiversity and generators of ecological goods and services.     

Estimating density of a forest-dwelling bat: a predictive model for Rafinesque’s big-eared bat

Data on species distribution and abundance are the foundation of population ecology. However, due to difficulties in surveying bats, abundance estimates for tree-roosting microchiropterans are non-existent. Therefore, our objective was to develop methods for estimating colony abundance and density, taking as our model Rafinesque’s big-eared bat Corynorhinus rafinesquii, a species of conservation concern found in cypress-gum swamps of the southeastern United States. We searched 123 transects at eight study sites in the Coastal Plain of Georgia, USA to locate and characterize diurnal summer roosts of C. rafinesquii. We modeled the relationship between the number of bat colonies and landscape-scale habitat variables with zero-inflated negative binomial regression and used Akaike’s information criterion to select the most parsimonious models. We generated a predictive density map to identify areas of high colony density and to estimate overall abundance. Colony density was predicted by the duration of wetland flooding, wetland width, and study site. Application of the regression model to a GIS indicated there were 3,734 colonies containing 6,910 adult bats on the eight study sites. Predicted density ranged from 0.07 colonies/ha and 0.07 adult bats/ha in saturated wetlands to 0.47 colonies/ha and 1.18 adult bats/ha in semi-permanently flooded wetlands. This study is the first to estimate density and abundance of forest-dwelling microchiropterans over a large area. Such data can serve as a baseline for future work on population trends in C. rafinesquii. In addition, our approach could be replicated for other bat species with moderately cryptic roosts.     

Automated analysis of courtship suppression learning and memory in Drosophila melanogaster

Study of the fruit fly, Drosophila melanogaster, has yielded important insights into the underlying molecular mechanisms of learning and memory. Courtship conditioning is a well-established behavioral assay used to study Drosophila learning and memory. Here, we describe the development of software to analyze courtship suppression assay data that correctly identifies normal or abnormal learning and memory traits of individual flies. Development of this automated analysis software will significantly enhance our ability to use this assay in large-scale genetic screens and disease modeling. The software increases the consistency, objectivity, and types of data generated.     

Identification of Pak1 inhibitors using water thermodynamic analysis

Abstract

p21-activated kinases (Paks) play an integral component in various cellular diverse processes. The full activation of Pak is dependent upon several serine residues present in the N-terminal region, a threonine present at the activation loop, and finally the phosphorylation of these residues ensure the complete activation of Pak1. The present study deals with the identification of novel potent candidates of Pak1 using computational methods as anti-cancer compounds. A diverse energy based pharmacophore (e-pharmacophore) was developed using four co-crystal inhibitors of Pak1 having pharmacophore features of 5 (DRDRR), 6 (DRHADR), and 7 (RRARDRP and DRRDADH) hypotheses. These models were used for rigorous screening against e-molecule database. The obtained hits were filtered using ADME/T and molecular docking to identify the high affinity binders. These hits were subjected to hierarchical clustering using dendritic fingerprint inorder to identify structurally diverse molecules. The diverse hits were scored against generated water maps to obtain WM/MM ΔG binding energy. Furthermore, molecular dynamics simulation and density functional theory calculations were performed on the final hits to understand the stability of the complexes. Five structurally diverse novel Pak1 inhibitors (4835785, 32198676, 32407813, 76038049, and 32945545) were obtained from virtual screening, water thermodynamics and WM/MM ΔG binding energy. All hits revealed similar mode of binding pattern with the hinge region residues replacing the unstable water molecules in the binding site. The obtained novel hits could be used as a platform to design potent drugs that could be experimentally tested against cancer patients having increased Pak1 expression.     

Spatial summation of heat induced pain within and between dermatomes

The aim was to study spatial summation within and between ipsi- and contralateral dermatomes at different painful temperatures. For heat stimulation we used a computer controlled thermofoil based thermode. The thermode area could be varied in five discrete steps from 3.14 to 15.70 cm2. When we applied the stimuli within a dermatome, the mean heat pain threshold decreased significantly from 45.6 to 43.5 C as the area was increased from minimum (3.14 cm2) to maximum (15.70 cm2). When the areas were increased involving different dermatomes (both ipsi- or contralateral), we found similar decreases in pain threshold. Spatial summation was also found within and between dermatomes at supra-threshold temperatures (46, 48, 50 C).The study shows that spatial summation of pain is most likely a mechanism acting across segments and is existing from pain threshold to tolerance.