Motivation: Bringing a new drug to the market is expensive and time-consuming. To cut the costs and time, computer-aided drug design (CADD) approaches have been increasingly included in the drug discovery pipeline. However, despite traditional docking tools show a good conformational space sampling ability, they are still unable to produce accurate binding affinity predictions. This work presents a novel scoring function for molecular docking seamlessly integrated into DockingApp, a user-friendly graphical interface for AutoDock Vina. The proposed function is based on a random forest model and a selection of specific features to overcome the existing limits of Vina’s original scoring mechanism. A novel version of DockingApp, named DockingApp RF, has been developed to host the proposed scoring function and to automatize the rescoring procedure of the output of AutoDock Vina, even to nonexpert users. Results: By coupling intermolecular interaction, solvent accessible surface area features and Vina’s energy terms, DockingApp RF’s new scoring function is able to improve the binding affinity prediction of AutoDock Vina. Furthermore, comparison tests carried out on the CASF-2013 and CASF-2016 datasets demonstrate that DockingApp RF’s performance is comparable to other state-of-the-art machine-learning- and deep-learning-based scoring functions. The new scoring function thus represents a significant advancement in terms of the reliability and effectiveness of docking compared to AutoDock Vina’s scoring function. At the same time, the characteristics that made DockingApp appealing to a wide range of users are retained in this new version and have been complemented with additional features.

Iron is an essential transition metal for its involvement in several crucial biological functions, the most notable being oxygen storage and transport. Due to its high reactivity and potential toxicity, intracellular and extracellular iron levels must be tightly regulated. This is achieved through transport systems that mediate cellular uptake and efflux both at the level of the plasma membrane and on the membranes of lysosomes, endosomes and mitochondria. Among these transport systems, the key players are ferroportin, the only known transporter mediating iron efflux from cells; DMT1, ZIP8 and ZIP14, which on the contrary, mediate iron influx into the cytoplasm, acting on the plasma membrane and on the membranes of lysosomes and endosomes; and mitoferrin, involved in iron transport into the mitochondria for heme synthesis and Fe-S cluster assembly. The focus of this review is to provide an updated view of the physiological role of these membrane proteins and of the pathologies that arise from defects of these transport systems.

The ZIP (Zrt and Irt-like proteins) protein family includes transporters responsible for the translocation of zinc and other transition metals, such as iron and cadmium, between the extracellular space (or the lumen of organelles) and the cytoplasm. This protein family is present at all the phylogenetic levels, including bacteria, fungi, plants, insects, and mammals. ZIP proteins are responsible for the homeostasis of metals essential for the cell physiology. The human ZIP family consists of fourteen members (hZIP1-hZIP14), divided into four subfamilies: LIV-1, containing nine hZIPs, the subfamily I, with only one member, the subfamily II, which includes three members and the subfamily gufA, which has only one member. Apart from the extracellular domain, typical of the LIV-1 subfamily, the highly conserved transmembrane domain, containing the binuclear metal center (BMC), and the histidine-rich intracellular loop are the common features characterizing the ZIP family. Here is presented a computational study of the structure and function of human ZIP family members. Multiple sequence alignment and structural models were obtained for the 14 hZIP members. Moreover, a full-length three-dimensional model of the hZIP4-homodimer complex was also produced. Different conformations of the representative hZIP transporters were obtained through a modified version of the AlphaFold2 algorithm. The inward and outward-facing conformations obtained suggest that the hZIP proteins function with an “elevator-type” mechanism.

Butylated hydroxytoluene (BHT) is one of the most commonly used synthetic antioxidants in food, cosmetic, pharmaceutical and petrochemical products. BHT is considered safe for human health; however, its widespread use together with the potential toxicological effects have increased consumers concern about the use of this synthetic food additive. In addition, the estimated daily intake of BHT has been demonstrated to exceed the recommended acceptable threshold. In the present work, using BHT as a case study, the usefulness of computational techniques, such as reverse screening and molecular docking, in identifying protein–ligand interactions of food additives at the bases of their toxicological effects has been probed. The computational methods here employed have been useful for the identification of several potential unknown targets of BHT, suggesting a possible explanation for its toxic effects. In silico analyses can be employed to identify new macromolecular targets of synthetic food additives and to explore their functional mechanisms or side effects. Noteworthy, this could be important for the cases in which there is an evident lack of experimental studies, as is the case for BHT.