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The International Union for Conservation of Nature (IUCN) Red List is a central tool for extinction risk monitoring and influences global biodiversity policy and action. But, to be effective, it is crucial that it consistently accounts for each driver of extinction. Climate change is rapidly becoming a key extinction driver, but consideration of climate change information remains challenging for the IUCN. Several methods can be used to predict species' future decline, but they often fail to provide estimates of the symptoms of endangerment used by IUCN. We devised a standardized method to measure climate change impact in terms of change in habitat quality to inform criterion A3 on future population reduction. Using terrestrial nonvolant tetrapods as a case study, we measured this impact as the difference between the current and the future species climatic niche, defined based on current and future bioclimatic variables under alternative model algorithms, dispersal scenarios, emission scenarios, and climate models. Our models identified 171 species (13% out of those analyzed) for which their current red‐list category could worsen under criterion A3 if they cannot disperse beyond their current range in the future. Categories for 14 species (1.5%) could worsen if maximum dispersal is possible. Although ours is a simulation exercise and not a formal red‐list assessment, our results suggest that considering climate change impacts may reduce misclassification and strengthen consistency and comprehensiveness of IUCN Red List assessments. [ABSTRACT FROM AUTHOR]

An integrated experimental–computational strategy for the accurate characterization of the conformational landscape of flexible biomolecule building blocks is proposed. This is based on the combination of rotational spectroscopy with quantum-chemical computations guided by artificial intelligence tools. The first step of the strategy is the conformer search and relative stability evaluation performed by means of an evolutionary algorithm. In this step, last generation semiempirical methods are exploited together with hybrid and double-hybrid density functionals. Next, the barriers ruling the interconversion between the low-lying conformers are evaluated in order to unravel the possible fast relaxation paths. The relative stabilities and spectroscopic parameters of the "surviving" conformers are then refined using state-of-the-art composite schemes. The reliability of the computational procedure is further improved by the inclusion of vibrational and thermal effects. The final step of the strategy is the comparison between experiment and theory without any ad hoc adjustment, which allows an unbiased assignment of the spectroscopic features in terms of different conformers and their spectroscopic parameters. The proposed approach has been tested and validated for homocysteine, a highly flexible non-proteinogenic α-amino acid. The synergism of the integrated strategy allowed for the characterization of five conformers stabilized by bifurcated N–H2⋯O=C hydrogen bonds, together with an additional conformer involving a more conventional HN⋯H–O hydrogen bond. The stability order estimated from the experimental intensities as well as the number and type of conformers observed in the gas phase are in full agreement with the theoretical predictions. Analogously, a good match has been found for the spectroscopic parameters. [ABSTRACT FROM AUTHOR]

The fruitful interplay of high-resolution spectroscopy and quantum chemistry has a long history, especially in the field of small, semi-rigid molecules. However, in recent years, the targets of spectroscopic studies are shifting toward flexible molecules, characterized by a large number of closely spaced energy minima, all contributing to the overall spectrum. Here, artificial intelligence comes into play since it is at the basis of powerful unsupervised techniques for the exploration of soft degrees of freedom. Integration of such algorithms with a two-stage QM/QM′ (Quantum Mechanical) exploration/refinement strategy driven by a user-friendly graphical interface is the topic of the present paper. We will address in particular: (i) the performances of different semi-empirical methods for the exploration step and (ii) the comparison between stochastic and meta-heuristic algorithms in achieving a cheap yet complete exploration of the conformational space for medium sized chromophores. As test cases, we choose three amino acids of increasing complexity, whose full conformer enumeration has been reached only very recently. Next, we show that systems in condensed phases can be treated at the same level and with the same efficiency when employing a polarizable continuum description of the solvent. Finally, the challenging issue represented by the vibrational circular dichroism spectra of some rhodium complexes with flexible ligands has been addressed, showing that our fully unsupervised approach leads to remarkable agreement with the experiment. [ABSTRACT FROM AUTHOR]

The increasing interest in the molecular mechanism of the binding of different agonists and antagonists to β 2-adrenergic receptor (β 2AR) inactive and active states has led us to investigate protein–ligand interactions using molecular docking calculations. To perform this study, the 3.2 Å X-ray crystal structure of the active conformation of human β 2AR in the complex with the endogenous agonist adrenaline has been used as a template for investigating the binding of two exogenous catecholamines to this adrenergic receptor. Here, we show the derivation of L-DOPA and Droxidopa OPLS all atom (AA) force field (FF) parameters via quantum mechanical (QM) calculations, molecular dynamics (MD) simulations in aqueous solutions of the two catecholamines and the molecular docking of both ligands into rigid and flexible β 2AR models. We observe that both ligands share with adrenaline similar experimentally observed binding anchor sites, which are constituted by Asp113/Asn312 and Ser203/Ser204/Ser207 side chains. Moreover, both L-DOPA and Droxidopa molecules exhibit binding affinities comparable to that predicted for adrenaline, which is in good agreement with previous experimental and computational results. L-DOPA and Droxidopa OPLS AA FFs have also been tested by performing MD simulations of these ligands docked into β 2AR proteins embedded in lipid membranes. Both hydrogen bonds and hydrophobic interaction networks observed over the 1 μ s MD simulation are comparable with those derived from molecular docking calculations and MD simulations performed with the CHARMM FF. [ABSTRACT FROM AUTHOR]

X-ray absorption spectroscopy (XAS) and quantum mechanics/molecular dynamics (QM/MD) calculations have revealed an unexpected sevenfold coordination of the hydrated Hg(II) complex in aqueous solution. The results are consistent with X-ray absorption near-edge structure experimental data, which has shown preference for a sevenfold instead of a sixfold coordination.

ABSTRACT Studies aimed at estimating species response to climate change generally employ correlative species distribution models (SDMs) coupled with dispersal scenarios. However, dispersal distances are generally lacking or nonrepresentative, so researchers typically estimate dispersal distance from allometric relationships. Yet, these estimates ignore the role of sex bias in dispersal—where one sex disperses more than the other—leading to important prediction errors. We collected sex‐specific dispersal data for 47 mammal species characterised by different levels of sex bias and projected their distribution under future climate scenarios, either considering or disregarding sex‐biased dispersal. Results reveal discrepancies that can be substantial for species with marked sex bias. Given the paucity of sex‐specific dispersal data, climate forecasting efforts should cautiously use a range of dispersal scenarios, favouring partial dispersal scenarios that are likely to encompass true species' range shifting abilities. Further research and data collection are crucial for refining predictions and understanding the ecological drivers of sex bias in dispersal across taxa. [ABSTRACT FROM AUTHOR]