Demonstration and Characterization of two Classes of Cardiac Glycoside Binding Sites to Rat Heart Membrane Preparations Using Quantitative Computer Modeling

Abstract

Cardiac glycoside binding to rat heart membrane preparations was measured by rapid filtration technique. The binding data were analyzed using quantitative computer analysis. The experimental results using [³H]-ouabain as the labeled ligand were consistent with a model in which cardiac glycoside specific binding occurs at two independent classes of sites. The high affinity sites were characterized by a dissociation constants of 40 nM, 50 nM, and 61 nM for ouabain, digoxin and digitoxin, respectively, with a binding capacity of 1.3 pmoles/mg protein. The lower affinity sites for ouabain were characterized by dissociation constants of 2.3 µM, 67 nM and 71 nM for ouabain, digoxin and digitoxin, respectively, with a binding capacity of 3 pmoles/mg protein. Potassium ions inhibit [³H]-ouabain binding in a dose dependent manner with an IC₅₀ of 500 µM. Quantitative computer modelling indicated that potassium inhibits ouabain binding at both binding sites.     

Synthesis of α-oxycarbanilinophosphonates and their anticholinesterase activities: the most potent derivative is bound to the peripheral site of acetylcholinesterase

A novel method has been developed for the synthesis of α-oxycarbanilino phosphonates through a reaction of α-hydroxyphosphonates with isocyanate under microwave irradiation. The synthesized compounds were evaluated for their acetylcholinesterase (AChE) inhibition potency through IC₅₀determination. Molecular modelling studies suggest that the most potent inhibitor (compound 4h, IC₅₀ = 6.36 µM) is bound to the peripheral site of AChE, which suggests that it decreases the catalytic activity not through binding to the active site but through blocking the entrance of the active site gorge. This puts forward the potential of compound 4h and its derivatives to be used in the design of dual inhibitors: inhibition of the catalytic activity of AChE and of amyloid β aggregation.     

Body masses,functional responses and predator–prey stability

The stability of ecological communities depends strongly on quantitative characteristics of population interactions (type‐II vs. type‐III functional responses) and the distribution of body masses across species. Until now, these two aspects have almost exclusively been treated separately leaving a substantial gap in our general understanding of food webs. We analysed a large data set of arthropod feeding rates and found that all functional‐response parameters depend on the body masses of predator and prey. Thus, we propose generalised functional responses which predict gradual shifts from type‐II predation of small predators on equally sized prey to type‐III functional‐responses of large predators on small prey. Models including these generalised functional responses predict population dynamics and persistence only depending on predator and prey body masses, and we show that these predictions are strongly supported by empirical data on forest soil food webs. These results help unravelling systematic relationships between quantitative population interactions and large‐scale community patterns.     

Computationally guided identification of Akt-3, a serine/threonine kinase inhibitors: Insights from homology modelling,structure-based screening,molecular dynamics and quantum mechanical calculations

Abstract

Chemical entities targeting kinase signalling pathways serve as a potential strategy to combat malignancies. Protein Kinase B or Akt is a validated target for various malignancies and Akt3 remains the least explored isoform among all its isoforms. Initially, homology modelling technique was used for generating protein structure and further validation was performed using molecular dynamics simulation and Ramachandran plot. The validated protein structure was then subjected for active site analysis which led to identification of active site residues based on metrics provided by site score. The important residues in binding site were identified as Thr81, Asp271 and Asp289 for binding energetics and inhibition. Subsequently, virtual screening methodologies were used for identification of novel hits for inhibition of Protein Kinase B or Akt3. This led to the identification of two hits, i.e. thiophene derivative and thieno-pyridine derivative which were selected on the basis of their binding affinity and drug likeliness. These identified hits were subjected for molecular dynamics simulations, quantum mechanical and synthetic accessibility studies. The role of crucial residues in binding site stood validated as suggested by molecular dynamics simulations studies.

Communicated by Ramaswamy H. Sarma     

Combining model structure identification and hybrid modelling for photo-production process predictive simulation and optimisation

Integrating physical knowledge and machine learning is a critical aspect of developing industrially focused digital twins for monitoring, optimisation, and design of microalgal and cyanobacterial photo-production processes. However, identifying the correct model structure to quantify the complex biological mechanism poses a severe challenge for the construction of kinetic models, while the lack of data due to the time-consuming experiments greatly impedes applications of most data-driven models. This study proposes the use of an innovative hybrid modelling approach that consists of a simple kinetic model to govern the overall process dynamic trajectory and a data-driven model to estimate mismatch between the kinetic equations and the real process. An advanced automatic model structure identification strategy is adopted to simultaneously identify the most physically probable kinetic model structure and minimum number of data-driven model parameters that can accurately represent multiple data sets over a broad spectrum of process operating conditions. Through this hybrid modelling and automatic structure identification framework, a highly accurate mathematical model was constructed to simulate and optimise an algal lutein production process. Performance of this hybrid model for long-term predictive modelling, optimisation, and online self-calibration is demonstrated and thoroughly discussed, indicating its significant potential for future industrial application.     

Long-term temporal variation in the organization of an ant–plant network

Background and Aims

Functional groups of species interact and coevolve in space and time, forming complex networks of interacting species. A long-term study of temporal variation of an ant–plant network is presented with the aims of: (1) depicting its structural changes over a 20-year period; (2) detailing temporal variation in network topology, as revealed by nestedness and modularity analysis and other parameters (i.e. connectance, niche overlap); and (3) identifying long-term turnover in taxonomic structure (i.e. switches in ant resource use or plant visitor assemblages according to taxa).

Methods

Fieldwork was carried out at La Mancha, Mexico, and ant–plant interactions were observed between 1989 and 1991, between 1998 and 2000, and between May 2010 and 2011. Occurrences of ants on extrafloral nectaries (EFNs) were recorded. The resulting ant–plant networks were constructed from qualitative presence–absence data determined by a species–species matrix defined by the frequency of occurrence of each pairwise ant–plant interaction.

Key Results

Network variation across time was stable and a persistent nested structure may have contributed to the maintenance of resilient and species-rich communities. Modularity was lower than expected, especially in the most recent networks, indicating that the community exhibited high overlap among interacting species (e.g. few species were hubs in the more recent network, being partly responsible for the nested pattern). Structurally, the connections created among modules by super-generalists gave cohesion to subsets of species that otherwise would remain unconnected. This may have allowed an increasing cascade-effect of evolutionary events among modules. Mutualistic ant–plant interactions were structured 20 years ago mainly by the subdominant nectarivorous ant species Camponotus planatus and Crematogaster brevispinosa, which monopolized the best extrafloral nectar resources and out-competed other species with broader feeding habits. Through time, these ants, which are still present, lost their position as network hubs and diminished in their importance in structuring the network; simultaneously, plants gained in importance.

Conclusions

The long-term network analysis reveals a decrease in attended plant species richness, a notable increase in plant species participation from 1990 to 2010 (sustained by less plant taxonomic similarity in the older 1990 network), an increase in the number of ant species and a diminishing dominance of super-generalist ants. The structure of the community has remained highly nested and connected with low modularity, suggesting overall a more participative, homogeneous, cohesive interaction network. Although previous studies have suggested that interactions between ants and EFN-bearing plants are susceptible to seasonality, abiotic factors and perturbation, this cohesive structure appears to be the key for biodiversity and community maintenance.     

The potential for biological control of stoats (Mustela erminea)

Abstract

Accelerating the mortality of stoats (Mustela erminea) using biological agents, or reducing their fertility using chemosterilants or biological agents, are increasingly seen as more sustainable and more humane than trapping and poisoning. Obligate delayed implantation in fertilised female stoats of all ages allows 10–11 months for an applied biological agent or chemosterilant to interfere with gestation. Two chemosterilants (cabergoline and mifepristone) disrupt pregnancy in some species and may be effective on stoats, although they are not species‐specific and are probably more expensive than poisoning. For the longer term, more recent fertility control research has explored potentially more species‐specific options for other species based on inducing an immune response to an animal's own reproductive hormones, gametes, or products from embryos. Conception will be difficult to disrupt in stoats because females are sexually mature and are mated in the nest during a short period before they are weaned. A large research effort will be required to determine which of the immunosterilants being developed could be suitable candidates for stoat control. There are fewer options apparent for using biological agents to increase stoat mortality, although species‐specific strains of canine distemper virus may be effective against stoats.

The greatest impediment to controlling stoat fertility will be effective delivery of sterilants. For the foreseeable future, it will probably be necessary to rely on baits, but they are unlikely to put all target stoats at risk, and will be incapable of delivery over larger scales than at present.

Before undertaking expensive field trials and development of anti‐fertility and biological agents, the effects of putative compensatory changes in demographics that may be associated with changes in stoat density should be modelled to see if the sterilisation and mortality rates that are required to achieve a given level of population control are realistic targets. Also, population control should be defined in terms of accrued benefit for wildlife by establishing the relationships between stoat densities and the viability of prey populations.

Biological control of fertility or mortality may never be suitable as stand‐alone control options for stoats, particularly when some native fauna survive only if stoats are reduced to very low densities. Biological control may have greater potential when integrated with conventional control.