AFAL: a web service for profiling amino acids surrounding ligands in proteins.

With advancements in crystallographic technology and the increasing wealth of information populating structural databases, there is an increasing need for prediction tools based on spatial information that will support the characterization of proteins and protein-ligand interactions. Herein, a new web service is presented termed amino acid frequency around ligand (AFAL) for determining amino acids type and frequencies surrounding ligands within proteins deposited in the Protein Data Bank and for assessing the atoms and atom-ligand distances involved in each interaction (availability: http://structuralbio.utalca.cl/AFAL/index.html ). AFAL allows the user to define a wide variety of filtering criteria (protein family, source organism, resolution, sequence redundancy and distance) in order to uncover trends and evolutionary differences in amino acid preferences that define interactions with particular ligands. Results obtained from AFAL provide valuable statistical information about amino acids that may be responsible for establishing particular ligand-protein interactions. The analysis will enable investigators to compare ligand-binding sites of different proteins and to uncover general as well as specific interaction patterns from existing data. Such patterns can be used subsequently to predict ligand binding in proteins that currently have no structural information and to refine the interpretation of existing protein models. The application of AFAL is illustrated by the analysis of proteins interacting with adenosine-5'-triphosphate.

Assessment of satellite-based water requirements for a drip-irrigated apple orchard in Mediterranean agroclimatic conditions.

Accurate assessment of evapotranspiration (ETa) and crop coefficient (Kc) is crucial for optimizing irrigation practices in water-scarce regions. While satellite-based surface energy balance models offer a promising solution, their application to sparse canopies like apple orchards requires specific validation. This study investigated the spatial and temporal dynamics of ETa and Kc in a drip-irrigated 'Pink Lady' apple orchard under Mediterranean conditions over three growing seasons (2012/13, 2013/14, 2014/15). The METRIC model, incorporating calibrated sub-models for leaf area index (LAI), surface roughness (Zom), and soil heat flux (G), was employed to estimate ETa and Kc. These estimates were validated against field-scale Eddy Covariance data. Results indicated that METRIC overpredicted Kc and ETa with errors less than 10 %. These findings highlight the potential of the calibrated METRIC model as a valuable decision-making tool for irrigation management in apple orchards.