Phosphorylation is an essential process in biological events and is considered critical for biological functions. In tissues, protein phosphorylation mainly occurs on tyrosine (Tyr), serine (Ser) and threonine (Thr) residues. The balance between phosphorylation and dephosphorylation is under the control of two super enzyme families, protein kinases (PKs) and protein phosphatases (PPs), respectively. Although there are many selective and effective drugs targeting phosphokinases, developing drugs targeting phosphatases is challenging. PTP1B, one of the most central protein tyrosine phosphatases (PTPs), is a key player in several human diseases and disorders, such as diabetes, obesity, and hematopoietic malignancies, through modulation of different signaling pathways. However, due to high conservation among PTPs, most PTP1B inhibitors lack specificity, raising the need to develop new strategies targeting this enzyme. In this mini-review, we summarize three classes of PTP1B inhibitors with different mechanisms: (1) targeting multiple aryl-phosphorylation sites including the catalytic site of PTP1B; (2) targeting allosteric sites of PTP1B; (3) targeting specific mRNA sequence of PTP1B. All three types of PTP1B inhibitors present good specificity over other PTPs and are promising for the development of efficient small molecules targeting this enzyme.

IntroductionComputational design has become widely accepted in architecture. However, few approaches use algorithmic and parametric resources supporting urban design in order to develop adaptable masterplans. This logic AbstractThis article focuses on the use of computational tools to provide dynamic assessment and optimized arrangements while planning and discussing interventions in urban areas. The objective is to address the use of algorithmic systems for generating and evaluating urban morphologies guided by Transit-Oriented Development principles. TransitOriented Development is an urban development model that considers geometric and measurable parameters for designing sustainable cities. It advocates compact mixed-use neighborhoods within walking distance to a variety of transportation options and amenities, seeking to result in optimized infrastructure provision and energy-efficient lowcarbon districts. This article presents algorithmic experiments for the optimization of a rapid transit district, through its urban morphology and services' location, providing an accurate Transit-Oriented Development modeling. The main findings of this study highlight that the combination of Transit-Oriented Development and algorithmic-parametric tools has the potential to significantly contribute to a process of responsible planning and, ultimately, to mitigate global warming.

Glycogen phosphorylase (GP) is the key enzyme that regulates glycogen mobilization in cells. GP is a complex allosteric enzyme that comprises a family of three isozymes: muscle GP (mGP), liver GP (lGP), and brain GP (bGP). Although the three isozymes display high similarity and catalyze the same reaction, they differ in their sensitivity to the allosteric activator adenosine monophosphate (AMP). Moreover, inactivating mutations in mGP and lGP have been known to be associated with glycogen storage diseases (McArdle and Hers disease, respectively). The determination, decades ago, of the structure of mGP and lGP have allowed to better understand the allosteric regulation of these two isoforms and the development of specific inhibitors. Despite its important role in brain glycogen metabolism, the structure of the brain GP had remained elusive. Here, we provide an overview of the human brain GP structure and its relationship with the two other members of this key family of the metabolic enzymes. We also summarize how this structure provides valuable information to understand the regulation of bGP and to design specific ligands of potential pharmacological interest.

The novel coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global event that has been challenging governments, health systems, and communities worldwide. Available data from the first months indicated varying patterns of the spread of COVID-19 within American cities, when the spread was faster in high-density and walkable cities such as New York than in low-density and car-oriented cities such as Los Angeles. Subsequent containment efforts, underlying population characteristics, variants, and other factors likely affected the spread significantly. However, this work investigates the hypothesis that urban configuration and associated spatial use patterns directly impact how the disease spreads and infects a population. It follows work that has shown how the spatial configuration of urban spaces impacts the social behavior of people moving through those spaces. It addresses the first 60 days of contagion (before containment measures were widely adopted and had time to affect spread) in 93 urban counties in the United States, considering population size, population density, walkability, here evaluated through walkscore, an indicator that measures the density of amenities, and, therefore, opportunities for population mixing, and the number of confirmed cases and deaths. Our findings indicate correlations between walkability, population density, and COVID-19 spreading patterns but no clear correlation between population size and the number of cases or deaths per 100 k habitants. Although virus spread beyond these initial cases may provide additional data for analysis, this study is an initial step in understanding the relationship between COVID-19 and urban configuration.

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Designing urban areas that provide smaller distances to their amenities is a key factor toward more walkable environments. Moreover, this is a critical aspect of climate-resilient urban planning since it is broadly assumed that areas with greater walkability discourage automobile usage and reduce CO2 emissions. Generative and data-driven design approaches, in turn, increase designers’ ability to explore wider sets of potential solutions. In this sense, identifying designs with an optimized performance out of the vast possibilities that computation can provide is crucial. Shape grammars are a formal method of shape generation that facilitate the elaboration of complex patterns and meaningful designs. This paper hypothesizes that coupling shape grammars with multi-objective optimization can help address trade-offs and decision-making in urban design. It focuses on the pedestrian accessibility and infrastructure cost (as estimated by cumulative street length) trade-off in urban fabrics as a case study to verify the suitability of a grammar-based optimization approach for more dynamic and efficient solution-finding in urban design. Our findings suggest that a grammar-based optimization approach is helpful in addressing urban trade-offs as it could be used to filter the design space and provide optimal alternative fabric layouts with increased pedestrian accessibility and decreased infrastructure cost.

Etoposide is a widely prescribed anticancer drug that is, however, associated with an increased risk of secondary leukemia. Although the molecular basis underlying the development of these leukemias remains poorly understood, increasing evidence implicates the interaction of etoposide metabolites [i.e., etoposide quinone (EQ)] with topoisomerase II enzymes. However, effects of etoposide quinone on other cellular targets could also be at play. We investigated whether T-cell protein tyrosine phosphatase (TCPTP), a protein tyrosine phosphatase that plays a key role in normal and malignant hematopoiesis through regulation of Janus kinase/signal transducer and activator of transcription signaling, could be a target of EQ. We report here that EQ is an irreversible inhibitor of TCPTP phosphatase (IC 50 5 ∼7 mM, second-order rate inhibition constant of ∼810 M 21 ×min 21). No inhibition was observed with the parent drug. The inhibition by EQ was found to be due to the formation of a covalent adduct at the catalytic cysteine residue in the active site of TCPTP. Exposure of human hematopoietic cells (HL60 and Jurkat) to EQ led to inhibition of endogenous TCPTP and concomitant increase in STAT1 tyrosine phosphorylation. Our results suggest that in addition to alteration of topoisomerase II functions, EQ could also contribute to etoposide-dependent leukemogenesis through impairment of key hematopoietic signaling enzymes, such as TCPTP.