Over the past decade, pharmaceutical companies have seen a decline in the number of drug candidates successfully passing through clinical trials, though billions are still spent on drug development. ...Poor aqueous solubility leads to low bio-availability, reducing pharmaceutical effectiveness. The human cost of inefficient drug candidate testing is of great medical concern, with fewer drugs making it to the production line, slowing the development of new treatments. In biochemistry and biophysics, water mediated reactions and interactions within active sites and protein pockets are an active area of research, in which methods for modelling solvated systems are continually pushed to their limits. Here, we discuss a multitude of methods aimed towards solvent modelling and solubility prediction, aiming to inform the reader of the options available, and outlining the various advantages and disadvantages of each approach.
We discuss a multitude of methods aimed towards solvent modelling and solubility prediction, aiming to inform the reader of the options available, and outlining the various advantages and disadvantages of each approach.
Sustainable Development Goal (SDG) indicator 3.b.3 monitors progress in medicines' accessibility for adults and has significant limitations when applying to medicines for children. An adapted ...indicator methodology was developed to fill this gap, but no proof of its robustness exists. We provide this evidence through sensitivity analyses.
Data on availability and prices of child medicines from ten historical datasets were combined to create datasets for analysis: Dataset 1 (medicines selected at random) and Dataset 2 (preference given to available medicines, to better capture affordability of medicines). A base case scenario and univariate sensitivity analyses were performed to test critical components of the methodology, including the new variable of number of units needed for treatment (NUNT), disease burden (DB) weighting, and the National Poverty Line (NPL) limits. Additional analyses were run on a continuously smaller basket of medicines to explore the minimum number of medicines required. Mean facility scores for access were calculated and compared.
The mean facility score for Dataset 1 and Dataset 2 within the base case scenario was 35.5% (range 8.0-58.8%) and 76.3% (range 57.2-90.6%). Different NUNT scenarios led to limited variations in mean facility scores of + 0.1% and -0.2%, or differences of + 4.4% and -2.1% at the more critical NPL of $5.50 (Dataset 1). For Dataset 2, variations to the NUNT generated differences of + 0.0% and -0.6%, at an NPL of $5.50 the differences were + 5.0 and -2.0%. Different approaches for weighting for DB induced considerable fluctuations of 9.0% and 11.2% respectively. Stable outcomes with less than 5% change in mean facility score were observed for a medicine basket down to 12 medicines. For smaller baskets, scores increased more rapidly with a widening range.
This study has confirmed that the proposed adaptations to make SDG indicator 3.b.3 appropriate for children are robust, indicating that they could be an important addition to the official Global Indicator Framework. At least 12 child-appropriate medicines should be surveyed to obtain meaningful outcomes. General concerns that remain about the weighting of medicines for DB and the NPL should be considered at the 2025 planned review of this framework.
Full text
Available for:
CEKLJ, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In this work we make predictions of several important molecular properties of academic and industrial importance to seek answers to two questions:
1) Can we apply efficient machine learning ...techniques, using inexpensive descriptors, to predict melting points to a reasonable level of accuracy?
2) Can values of this level of accuracy be usefully applied to predicting aqueous solubility?
We present predictions of melting points made by several novel machine learning models, previously applied to solubility prediction. Additionally, we make predictions of solubility via the General Solubility Equation (GSE) and monitor the impact of varying the logP prediction model (AlogP and XlogP) on the GSE. We note that the machine learning models presented, using a modest number of 2D descriptors, can make melting point predictions in line with the current state of the art prediction methods (RMSE≥40 °C). We also find that predicted melting points, with an RMSE of tens of degrees Celsius, can be usefully applied to the GSE to yield accurate solubility predictions (log10S RMSE<1) over a small dataset of drug‐like molecules.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Finding out how to scale innovations successfully is high on the agendas of researchers, practitioners and policy makers involved in agricultural development. New approaches and methodologies seek to ...better address related complexities, but none of them include a systematic perspective on the role of capacity in (partnerships for) scaling innovations. We posit that this has left an important topic insufficiently addressed in relation to partnerships for scaling innovations. The need to address this gap became apparent in the context of the CGIAR Roots, Tubers, and Bananas (RTB) Scaling Fund initiative. This paper presents how we explored ways forward in relation to this by combining three methodological approaches: The Five-Capabilities, Scaling Readiness, and the Multi-Level Perspective on socio-technical innovation. This combined approach—dubbed Capacity for Scaling Innovations (C4SI)—was applied in three projects related to scaling innovations for sweet potato, cassava and banana, involving five countries in Africa. It then discusses implications for a partners-in-scaling perspective, the contribution of scaling innovations to sustainable development, the importance of research organisations considering their own capabilities in partnerships for scaling, and the extent to which C4SI was helpful in the three cases—for example, in decision making. The paper concludes that a capacity perspective on the scaling of innovations should be an essential part of a ‘science of scaling’. Finally, it provides recommendations for using the approach or parts of it in research and intervention practice for scaling, pointing in particular to the need for context-specific adaptation.
Full text
Available for:
CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Jamil M, Van Mourik TA, Charnikhova T & Bouwmeester HJ (2012). Effect of diammonium phosphate application on strigolactone production and Striga hermonthica infection in three sorghum cultivars. Weed ...Research.
Summary
Striga hermonthica infection poses a major constraint to sorghum production in sub‐Saharan Africa, and low soil fertility aggravates the S. hermonthica problem. Under mineral nutrient deficiency, the sorghum host secretes large quantities of strigolactones, signalling molecules, into the rhizosphere. These induce S. hermonthica seed germination and subsequent infection of the host roots. In a combination of field and glasshouse experiments, we analysed the effect of microdose applied diammonium hydrogen phosphate (DAP) fertiliser on production of strigolactones, S. hermonthica infection and yield of three different African sorghum genotypes (CGM‐19/1‐1, Lina‐3, DouaG). The sorghum cultivars all produced the strigolactones sorgomol and 5‐deoxystrigol, albeit in different quantity and ratio. Without fertiliser, high S. hermonthica infection and emergence occurred under both glasshouse and field conditions. DAP application reduced secretion of sorgomol and 5‐deoxystrigol and reduced S. hermonthica germination (66–70%), emergence (49–73%) and dry biomass (90–96%) under glasshouse conditions. Under field conditions, DAP microdosing reduced S. hermonthica emergence by 40–84% and increased sorghum grain yield by 47–142%. Thus DAP application reduced secretion of strigolactones into the rhizosphere and S. hermonthica parasitism both under controlled and field conditions. Microdosing of DAP may prove to be an efficient and cost effective option to reduce S. hermonthica damage in sorghum in sub‐Saharan Africa, particularly in combination with other control options, such as intercropping, use of organic fertiliser and hand pulling of S. hermonthica at flowering to achieve integrated S. hermonthica management.
Full text
Available for:
BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
The parasitic weed Striga hermonthica poses a serious threat to cereal production in sub-Saharan Africa. Striga hermonthica seedbanks are long-lived; therefore, long-term effects of control ...strategies on the seedbank only emerge after several years. We developed a spatially explicit, stochastic model to study the effectiveness of control strategies in preventing invasion of S. hermonthica into previously uninfested fields and in reducing established infestations. Spatial expansion of S. hermonthica and decrease in millet yield in a field was slower, on average, when stochasticity of attachment of seedlings to the host was included and compared to the deterministic model. The spatial patterns of emerged S. hermonthica plants 4-7 years after point inoculation (e.g. seeds in a dung patch) in the spatial-stochastic model resembled the distribution typically observed in farmers' fields. Sensitivity analysis showed that only three out of eight life cycle parameters were of minor importance for seedbank dynamics and millet yield. Weeding and intercropping millet with sesame or cowpea reduced the seedbank in the long term, but rotations of millet with trap crops did not. High seedbank replenishment during years of millet monoculture was not sufficiently offset by seedbank depletion in years of trap crop cultivation. Insight from simulations can be employed in a participatory learning context with farmers to have an impact on S. hermonthica control in practice.
Full text
Available for:
BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
The conformational landscapes of the neurotransmitter l-adrenaline (l-epinephrine) and its diastereoisomer pseudo-adrenaline, isolated in the gas phase and un-protonated, have been investigated by ...using a combination of mass-selected ultraviolet and infrared holeburn spectroscopy, following laser desorption of the sample into a pulsed supersonic argon jet, and DFT and ab initio computation (at the B3LYP/6-31+G*, MP2/6-31+G* and MP2/aug-cc-pVDZ levels of theory). Both for adrenaline and its diastereoisomer, pseudo-adrenaline, one dominant molecular conformation, very similar to the one seen in noradrenaline, has been observed. It could be assigned to an extended side-chain structure (AG1a) stabilized by an OH → N intramolecular hydrogen bond. An intramolecular hydrogen bond is also formed between the neighbouring hydroxyl groups on the catechol ring. The presence of further conformers for both diastereoisomers could not be excluded, but overlapping electronic spectra and low ion signals prevented further assignments.
Full text
Available for:
BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
The effects of preconditioning temperature and preconditioning period on the sensitivity of parasitic weed seeds to the synthetic germination stimulant GR24 were studied under laboratory and field ...conditions. The temperature during preconditioning of Orobanche cumana and Striga hermonthica seeds strongly affected the responsiveness of the seeds to the applied germination stimulant. Preconditioning at an optimal temperature (21°C for O. cumana and 30°C for S. hermonthica) rapidly released dormancy and increased the sensitivity to GR24 by several orders of magnitude. After reaching maximum sensitivity, prolonged preconditioning rapidly induced secondary dormancy, i.e. decreased sensitivity of O. cumana and S. hermonthica to GR24. The rapid change in sensitivity of preconditioned seeds to germination stimulants during prolonged preconditioning was particularly visible at low concentrations of GR24. GR24 at higher concentrations (0.1 and 1 mg l1) usually induced high germination of both species, regardless of the preconditioning period. The striking similarities between the response of parasitic weed seeds to GR24, described here, and results in the literature on non-parasitic wild plant seeds are discussed. Our results show that parasitic weed seeds are highly sensitive to the germination stimulant for a short period of time only, and then enter into secondary dormancy relatively quickly. The similar germination pattern of S. hermonthica seeds preconditioned for prolonged periods of time under laboratory and field conditions suggests that the mechanism observed is of ecological significance.
The conformational structures of noradrenaline, isolated in the gas phase, have been explored through a combination of electronic structure computation (at the B3LYP/6-31 + G*, MP2/6-31 + G*, ...MP2/aug-cc-pVDZ and CIS/6-31 + G* levels of theory) and mass selected ultraviolet and infrared ion dip spectroscopy (following laser ablation of the neurotransmitter into a pulsed supersonic argon expansion). Despite the many possible low-lying conformational possibilities predicted by theory, almost the entire population of jet-cooled noradrenaline adopts the global minimum structure, associated with an extended, AG1a, ethanolamine side chain conformation. Intramolecular hydrogen bonds are formed between the neighbouring hydroxyl groups on the catechol ring and between the hydroxyl and amino groups on the side chain.
Full text
Available for:
BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
PDF
