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Reversible covalent kinase inhibitors (RCKIs) are a class of novel kinase inhibitors attracting increasing attention because they simultaneously show the selectivity of covalent kinase inhibitors, yet avoid permanent protein-modification-induced adverse effects. Over the last decade, RCKIs have been reported to target different kinases, including atypical kinases. Currently, three RCKIs are undergoing clinical trials to treat specific diseases, for example, Pemphigus, an autoimmune disorder. In this perspective, first, RCKIs are systematically summarized, including characteristics of electrophilic groups, chemical scaffolds, nucleophilic residues, and binding modes. Second, we provide insights into privileged electrophiles, the distribution of nucleophiles and hence effective design strategies for RCKIs. Finally, we provide a brief perspective on future design strategies for RCKIs, including those that target proteins other than kinases.
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Cells have evolved a metabolic control of DNA replication to respond to a wide range of nutritional conditions. Accumulating data suggest that this poorly understood control depends, at least in part, on Central Carbon Metabolism (CCM). In Bacillus subtilis , the glycolytic pyruvate kinase (PykA) is intricately linked to replication. This 585 amino-acid-long enzyme comprises a catalytic (Cat) domain that binds to phosphoenolpyruvate (PEP) and ADP to produce pyruvate and ATP, and a C-terminal domain of unknown function. Interestingly, the C-terminal domain termed PEPut interacts with Cat and is homologous a domain that, in other metabolic enzymes, are phosphorylated at a conserved TSH motif at the expense of PEP and ATP to drive sugar import and catalytic or regulatory activities. To gain insights into the role of PykA in replication, DNA synthesis was analyzed in various Cat and PEPut mutants grown in a medium where the metabolic activity of PykA is dispensable for growth. Measurements of replication parameters ( ori/ter ratio, C period and fork speed) and of the pyruvate kinase activity showed that PykA mutants exhibit replication defects resulting from side chain modifications in the PykA protein rather than from a reduction of its metabolic activity. Interestingly, Cat and PEPut have distinct commitments in replication: while Cat impacts positively and negatively replication fork speed, PEPut stimulates initiation through a process depending on Cat-PEPut interaction and growth conditions. Residues binding to PEP and ADP in Cat, stabilizing the Cat-PEPut interaction and belonging to the TSH motif of PEPut were found important for the commitment of PykA in replication. In vitro , PykA affects the activities of replication enzymes (the polymerase DnaE, helicase DnaC and primase DnaG) essential for initiation and elongation and genetically linked to pykA . Our results thus connect replication initiation and elongation to CCM metabolites (PEP, ATP and ADP), critical Cat and PEPut residues and to multiple links between PykA and the replication enzymes DnaE, DnaC and DnaG. We propose that PykA is endowed with a moonlighting activity that senses the concentration of signaling metabolites and interacts with replication enzymes to convey information on the cellular metabolic state to the replication machinery and adjust replication initiation and elongation to metabolism. This defines a new type of replication regulator proposed to be part of the metabolic control that gates replication in the cell cycle.
We show that weakly reversible mass-action systems can have a continuum of positive steady states, coming from the zeroes of a multivariate polynomial. Moreover, the same is true of systems whose underlying reaction network is reversible and has a single connected component. In our construction, we relate operations on the reaction network to the multivariate polynomial occurring as a common factor in the system of differential equations.
We used machine learning methods to predict NaV1.7 inhibitors and found the model RF-CDK that performed best on the imbalanced dataset. Using the RF-CDK model for screening drugs, we got effective compounds K1. We use the cell patch clamp method to verify K1. However, because the model evaluation method in this article is not comprehensive enough, there is still a lot of research work to be performed, such as comparison with other existing methods. The target protein has multiple active sites and requires our further research. We need more detailed models to consider this biological process and compare it with the current results, which is an error in this article. So we want to withdraw this article.
Patients infected with SARS-CoV-2 show a wide spectrum of clinical manifestations ranging from mild febrile illness and cough up to acute respiratory distress syndrome, multiple organ failure and death. Data from patients with severe clinical manifestations compared to patients with mild symptoms indicate that highly dysregulated exuberant inflammatory responses correlate with severity of disease and lethality. Significantly elevated cytokine levels, i.e. cytokine storm, seem to play a central role in severity and lethality in COVID-19. We have previously shown that excessive cytokine release induced by highly pathogenic avian H5N1 influenza A virus was reduced by application of proteasome inhibitors. In the present study we present experimental data of a central cellular pro-inflammatory signal pathways, NF-kappaB, in the context of published clinical data from COVID-19 patients and develop a hypothesis for a therapeutic approach aiming at the simultaneous inhibition of whole cascades of pro-inflammatory cytokines and chemokines via blocking the nuclear translocation of NF-kappaB by proteasome inhibitors. The simultaneous inhibition of multiple cytokines/chemokines using clinically approved proteasome inhibitors is expected to have a higher therapeutic potential compared to single target approaches to prevent cascade (i.e. triggering, synergistic, and redundant) effects of multiple induced cytokines and may provide an additional therapeutic option to be explored for treatment of critical stage COVID-19 patients.
Our models for detecting the effect of adaptation on population genomic diversity are often predicated on a single newly arisen mutation sweeping rapidly to fixation. However, a population can also adapt to a new situation by multiple mutations of similar phenotypic effect that arise in parallel. These mutations can each quickly reach intermediate frequency, preventing any single one from rapidly sweeping to fixation globally (a soft sweep). Here we study models of parallel mutation in a geographically spread population adapting to a global selection pressure. The slow geographic spread of a selected allele can allow other selected alleles to arise and spread elsewhere in the species range. When these different selected alleles meet, their spread can slow dramatically, and so form a geographic patchwork which could be mistaken for a signal of local adaptation. This random spatial tessellation will dissipate over time due to mixing by migration, leaving a set of partial sweeps within the global population. We show that the spatial tessellation initially formed by mutational types is closely connected to Poisson process models of crystallization, which we extend. We find that the probability of parallel mutation and the spatial scale on which parallel mutation occurs is captured by a single characteristic length that reflects the expected distance a spreading allele travels before it encounters a different spreading allele. This characteristic length depends on the mutation rate, the dispersal parameter, the effective local density of individuals, and to a much lesser extent the strength of selection. We argue that even in widely dispersing species, such parallel geographic sweeps may be surprisingly common. Thus, we predict, as more data becomes available, many more examples of intra-species parallel adaptation will be uncovered.
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