An arithmetic valuative criterion for proper maps of tame algebraic stacks

The valuative criterion for proper maps of schemes has many applications in arithmetic, e.g. specializing Q(p)-points to F-p-points. For algebraic stacks, the usual valuative criterion for proper maps is ill-suited for these kind of arguments, since it only gives a specialization point defined over an extension of the residue field, e.g. a Q(p)-point will specialize to an F-pn-point for some n. We give a new valuative criterion for proper maps of tame stacks which solves this problem and is well-suited for arithmetic applications. As a consequence, we prove that the Lang-Nishimura theorem holds for tame stacks

An arithmetic valuative criterion for proper maps of tame algebraic stacks

The valuative criterion for proper maps of schemes has many applications in arithmetic, e.g. specializing $\mathbb{Q}_{p}$-points to $\mathbb{F}_{p}$-points. For algebraic stacks, the usual valuative criterion for proper maps is ill-suited for these kind of arguments, since it only gives a specialization point defined over an extension of the residue field, e.g. a $\mathbb{Q}_{p}$-point will specialize to an $\mathbb{F}_{p^{n}}$-point for some $n$. We give a new valuative criterion for proper maps of tame stacks which solves this problem and is well-suited for arithmetic applications. As a consequence, we prove that the Lang-Nishimura theorem holds for tame stacks

Activation Effects of Carnosine- and Histidine-Containing Dipeptides on Human Carbonic Anhydrases: A Comprehensive Study

l-Carnosine (beta-Ala-l-His) and several other histidine-containing peptides, including two N-methylated forms on the imidazole ring (l-anserine and l-balenine), two derivatives modified on the carboxyl function (carcinine and l-carnosinamide), two analogues differing in the length of the N-terminal residue (l-homocarnosine and Gly-l-His) and the N-acetyl derivatives, were investigated as activators of four isoforms of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1). The four human isoforms hCA I, II, VA and IX were activated in the low to high micromolar range, with a rather complex structure activity relationship. A performed computational study allowed us to rationalize these results and to propose a binding mode of these activators within the enzyme active site. Similarly to other CA activators, the here studied peptides could find relevant pharmacological applications such as in the management of CA deficiencies, for therapy memory and enhancing cognition or for artificial tissues engineering

A Comprehensive Mapping of the Druggable Cavities within the SARS-CoV-2 Therapeutically Relevant Proteins by Combining Pocket and Docking Searches as Implemented in Pockets 2.0

(1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) require a detailed characterization of their druggable binding sites, and, more generally, a convenient pocket mapping represents a key step for structure-based in silico studies; (2) Methods: Along with a careful literature search on SARS-CoV-2 protein targets, the study presents a novel strategy for pocket mapping based on the combination of pocket (as performed by the well-known FPocket tool) and docking searches (as performed by PLANTS or AutoDock/Vina engines); such an approach is implemented by the Pockets 2.0 plug-in for the VEGA ZZ suite of programs; (3) Results: The literature analysis allowed the identification of 16 promising binding cavities within the SARS-CoV-2 proteins and the here proposed approach was able to recognize them showing performances clearly better than those reached by the sole pocket detection; and (4) Conclusions: Even though the presented strategy should require more extended validations, this proved successful in precisely characterizing a set of SARS-CoV-2 druggable binding pockets including both orthosteric and allosteric sites, which are clearly amenable for virtual screening campaigns and drug repurposing studies. All results generated by the study and the Pockets 2.0 plug-in are available for download

PRENYLATED CURCUMIN ANALOGUES AS MULTIPOTENT TOOLS TO TACKLE ALZHEIMER'S DISEASE

Alzheimer's disease is likely to be caused by copathogenic factors including aggregation of A\u3b2 peptides into oligomers and fibrils, neuroinflammation and oxidative stress. To date, no effective treatments are available and because of the multifactorial nature of the disease, it emerges the need to act on different and simultaneous fronts. Despite the multiple biological activities ascribed to curcumin as neuroprotector, its poor bioavailability and toxicity limit the success in clinical outcomes. To tackle Alzheimer's disease on these aspects, the curcumin template was suitably modified and a small set of analogues was attained. In particular, derivative 1 turned out to be less toxic than curcumin. As evidenced by capillary electrophoresis and transmission electron microscopy studies, 1 proved to inhibit the formation of large toxic A\u3b2 oligomers, by shifting the equilibrium towards smaller non-toxic assemblies and to limit the formation of insoluble fibrils. These findings were supported by molecular docking and steered molecular dynamics simulations which confirmed the superior capacity of 1 to bind A\u3b2 structures of different complexity. Remarkably, 1 also showed in vitro anti-inflammatory and anti-oxidant properties. In summary, the curcumin-based analogue 1 emerged as multipotent compound worth to be further investigated and exploited in the Alzheimer's disease multi-target context

Itraconazole inhibits nuclear delivery of extracellular vesicle cargo by disrupting the entry of late endosomes into the nucleoplasmic reticulum

Extracellular vesicles (EVs) are mediators of intercellular communication under bothhealthy and pathological conditions, including the induction of pro-metastatic traits,but it is not yet known how and where functional cargoes of EVs are delivered to theirtargets in host cell compartments. We have described that after endocytosis, EVsreach Rab+late endosomes and a fraction of these enter the nucleoplasmic reticu-lum and transport EV biomaterials to the host cell nucleoplasm. Their entry thereinand docking to outer nuclear membrane occur through a tripartite complex formedby the proteins VAP-A, ORP and Rab (VOR complex). Here, we report that theantifungal compound itraconazole (ICZ), but not its main metabolite hydroxy-ICZor ketoconazole, disrupts the binding of Rab to ORP–VAP-A complexes, leadingto inhibition of EV-mediated pro-metastatic morphological changes including cellmigration behaviour of colon cancer cells. With novel, smaller chemical drugs, inhi-bition of the VOR complex was maintained, although the ICZ moieties responsiblefor antifungal activity and interference with intracellular cholesterol distributionwere removed. Knowing that cancer cells hijack their microenvironment and thatEVs derived from them determine the pre-metastatic niche, small-sized inhibitors ofnuclear transfer of EV cargo into host cells could nd cancer therapeutic applications,particularly in combination with direct targeting of cancer cell

MEDIATE - Molecular DockIng at homE: Turning collaborative simulations into therapeutic solutions

IntroductionCollaborative computing has attracted great interest in the possibility of joining the efforts of researchers worldwide. Its relevance has further increased during the pandemic crisis since it allows for the strengthening of scientific collaborations while avoiding physical interactions. Thus, the E4C consortium presents the MEDIATE initiative which invited researchers to contribute via their virtual screening simulations that will be combined with AI-based consensus approaches to provide robust and method-independent predictions. The best compounds will be tested, and the biological results will be shared with the scientific community.Areas coveredIn this paper, the MEDIATE initiative is described. This shares compounds' libraries and protein structures prepared to perform standardized virtual screenings. Preliminary analyses are also reported which provide encouraging results emphasizing the MEDIATE initiative's capacity to identify active compounds.Expert opinionStructure-based virtual screening is well-suited for collaborative projects provided that the participating researchers work on the same input file. Until now, such a strategy was rarely pursued and most initiatives in the field were organized as challenges. The MEDIATE platform is focused on SARS-CoV-2 targets but can be seen as a prototype which can be utilized to perform collaborative virtual screening campaigns in any therapeutic field by sharing the appropriate input files

Review Special FocuS: computational chemiStRy

Chemodiversity & its meaning Chemodiversity begins with the simplest chemical objects, namely atoms. Indeed, there is some electronic diversity in a given atom, since it has a number of electronic states available depending on ionization and occupation of atomic orbitals. However, genuine geometric states emerge at the level of molecules, where conformational states, mainly, and tautomeric states, occasionally, dramatically expand the property space open to molecules compared with atoms Considering the described molecular variability, it comes as no surprise that a detailed analysis of molecular flexibility for both ligand and receptor is now usually taken into account, with a view to enhancing the classical static drug-design methodologies. Modern docking programs routinely account for ligand flexibility as well as receptor flexibility, which can be modelled considering both conformational changes at a macromolecular level and small variations involving one or a few residues. The former is generally due to domain rearrangements and can be accounted for by multiple protein structures obtained experimentally or by in silico techniques, whereas the latter is due to side chain flexibility and can be simulated by exploiting rotamer libraries Chemodiversity and molecular plasticity: recognition processes as explored by property spaces In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure-activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences

MetaClass, a Comprehensive Classification System for Predicting the Occurrence of Metabolic Reactions Based on the MetaQSAR Database

(1) Background: Machine learning algorithms are finding fruitful applications in predicting the ADME profile of new molecules, with a particular focus on metabolism predictions. However, the development of comprehensive metabolism predictors is hampered by the lack of highly accurate metabolic resources. Hence, we recently proposed a manually curated metabolic database (MetaQSAR), the level of accuracy of which is well suited to the development of predictive models. (2) Methods: MetaQSAR was used to extract datasets to predict the metabolic reactions subdivided into major classes, classes and subclasses. The collected datasets comprised a total of 3788 first-generation metabolic reactions. Predictive models were developed by using standard random forest algorithms and sets of physicochemical, stereo-electronic and constitutional descriptors. (3) Results: The developed models showed satisfactory performance, especially for hydrolyses and conjugations, while redox reactions were predicted with greater difficulty, which was reasonable as they depend on many complex features that are not properly encoded by the included descriptors. (4) Conclusions: The generated models allowed a precise comparison of the propensity of each metabolic reaction to be predicted and the factors affecting their predictability were discussed in detail. Overall, the study led to the development of a freely downloadable global predictor, MetaClass, which correctly predicts 80% of the reported reactions, as assessed by an explorative validation analysis on an external dataset, with an overall MCC = 0.44