ACS Central Science最新文献

Signal transducer and activator of transcription 3 (STAT3) is an attractive cancer therapeutic target. Unfortunately, targeting STAT3 with small molecules has proven to be very challenging, and for full activation of STAT3, the cooperative phosphorylation of both tyrosine 705 (Tyr705) and serine 727 (Ser727) is needed. Further, a selective inhibitor of STAT3 dual phosphorylation has not been developed. Here, we identified a low nanomolar potency and highly selective small-molecule STAT3 inhibitor that simultaneously inhibits both STAT3 Tyr705 and Ser727 phosphorylation. YY002 potently inhibited STAT3-dependent tumor cell growth in vitro and achieved potent suppression of tumor growth and metastasis in vivo. More importantly, YY002 exhibited favorable pharmacokinetics, an acceptable safety profile, and superior antitumor efficacy compared to BBI608 (STAT3 inhibitor that has advanced into phase III trials). For the mechanism, YY002 is selectively bound to the STAT3 Src Homology 2 (SH2) domain over other STAT members, which strongly suppressed STAT3 nuclear and mitochondrial functions in STAT3-dependent cells. Collectively, this study suggests the potential of small-molecule STAT3 inhibitors as possible anticancer therapeutic agents.

YY002 is the highly selective and potent small molecular inhibitor that simultaneously inhibited STAT3 Tyr705 and Ser727 phosphorylation, demonstrating promising antitumor activity.

Protein aggregation via liquid–liquid phase separation (LLPS) is ubiquitous in nature and is intimately connected to many human diseases. Although it is widely known that the addition of salt has crucial impacts on the LLPS of proteins, full understanding of the salt effects remains an outstanding challenge. Here, we develop a molecular theory that systematically incorporates the self-consistent field theory for charged macromolecules into the solution thermodynamics. The electrostatic interaction, hydrophobicity, ion solvation, and translational entropy are included in a unified framework. Our theory fully captures the long-standing puzzles of the nonmonotonic salt concentration dependence and the specific ion effect. We find that proteins show salting-out at low salt concentrations due to ionic screening. The solubility follows the inverse Hofmeister series. In the high salt concentration regime, protein continues salting-out for small ions but turns to salting-in for larger ions, accompanied by the reversal of the Hofmeister series. We reveal that the solubility at high salt concentrations is determined by the competition between the solvation energy and translational entropy of the ion. Furthermore, we derive an analytical criterion for determining the boundary between the salting-in and salting-out regimes, which is in good agreement with experimental results for various proteins and salt ions.

This work uses a simple theory to capture the long-standing puzzles of the nonmonotonic salt concentration dependence and the specific ion effect in the liquid−liquid phase separation of proteins.

As climate change accelerates, small populations are influencing ecosystems more than they used to.

Streptococcus gordonii is a Gram-positive bacterial species that typically colonizes the human oral cavity, but can also cause local or systemic diseases. Serine-rich repeat (SRR) glycoproteins exposed on the S. gordonii bacterial surface bind to sialylated glycans on human salivary, plasma, and platelet glycoproteins, which may contribute to oral colonization as well as endocardial infections. Despite a conserved overall domain organization of SRR adhesins, the Siglec-like binding regions (SLBRs) are highly variable, affecting the recognition of a wide range of sialoglycans. SLBR-N from the SRR glycoprotein of S. gordonii UB10712 possesses the remarkable ability to recognize complex core 2 O-glycans. We here employed a multidisciplinary approach, including flow cytometry, native mass spectrometry, isothermal titration calorimetry, NMR spectroscopy from both protein and ligand perspectives, and computational methods, to investigate the ligand specificity and binding preferences of SLBR-N when interacting with mono- and disialylated core 2 O-glycans. We determined the means by which SLBR-N preferentially binds branched α2,3-disialylated core 2 O-glycans: a selected conformation of the 3′SLn branch is accommodated into the main binding site, driving the sTa branch to further interact with the protein. At the same time, SLBR-N assumes an open conformation of the CD loop of the glycan-binding pocket, allowing one to accommodate the entire complex core 2 O-glycan. These findings establish the basis for the generation of novel tools for the detection of specific complex O-glycan structures and pave the way for the design and development of potential therapeutics against streptococcal infections.

A multidisciplinary approach combining NMR spectroscopy, native mass spectrometry, flow cytometry, ITC and MD simulation unveiled the binding details of core 2 O-glycans to the Siglec-like adhesin SLBR-N of S. gordonii.

The discovery of the medicinal properties of platinum complexes has fueled the design and synthesis of new anticancer metallodrugs endowed with unique modes of action (MoA). Among the various families of experimental antiproliferative agents, organometallics have emerged as ideal platforms to control the compounds’ reactivity and stability in a physiological environment. This is advantageous to efficiently deliver novel prodrug activation strategies, as well as to design metallodrugs acting only via noncovalent interactions with their pharmacological targets. Noteworthy, another justification for the advance of organometallic compounds for therapy stems from their ability to catalyze bioorthogonal reactions in cancer cells. When not yet ideal as drug leads, such compounds can be used as selective chemical tools that benefit from the advantages of catalytic amplification to either label the target of interest (e.g., proteins) or boost the output of biochemical signals. Examples of metallodrugs for the so-called “catalysis in cells” are considered in this Outlook together with other organometallic drug candidates. The selected case studies are discussed in the frame of more general challenges in the field of medicinal inorganic chemistry.

The unique and exceptional features of metal-based compounds, markedly distinct from classical small-molecule organic drugs, are at the frontiers in the progress of cancer therapy and drug discovery.

Myxobacteria are a prolific source of secondary metabolites with sheer chemical complexity, intriguing biosynthetic enzymology, and diverse biological activities. In this study, we report the discovery, biosynthesis, biomimetic total synthesis, physiological function, structure–activity relationship, and self-resistance mechanism of the 5-methylated pyrazinone coralinone from a myxobacterium Corallococcus exiguus SDU70. A single NRPS/PKS gene corA was genetically and biochemically demonstrated to orchestrate coralinone, wherein the integral PKS part is responsible for installing the 5-methyl group. Intriguingly, coralinone exacerbated cellular aggregation of myxobacteria grown in liquid cultures by enhancing the secretion of extracellular matrix, and the 5-methylation is indispensable for the alleged activity. We provided an evolutionary landscape of the corA-associated biosynthetic gene clusters (BGCs) distributed in the myxobacterial realm, revealing the divergent evolution for the diversity-oriented biosynthesis of 5-alkyated pyrazinones. This phylogenetic contextualization provoked us to identify corB located in the proximity of corA as a self-resistance gene. CorB was experimentally verified to be a protease that hydrolyzes extracellular proteins to antagonize the agglutination-inducing effect of coralinone. Overall, we anticipate these findings will provide new insights into the chemical ecology of myxobacteria and lay foundations for the maximal excavation of these largely underexplored resources.

corA autonomously codes for 5-methylated pyrazinone that promotes secretion of extracellular matrix to induce agglutination of myxobacteria, and corB encoding a protease is the self-resistance gene.

The therapeutic effects of antibodies include neutralization of pathogens, activation of the host complement system, and facilitation of phagocytosis of pathogens. However, antibody alone has never been shown to exhibit bactericidal activity. In this study, we developed a monoclonal antibody that targets the bacterial cell surface component Pseudaminic acid (Pse). This monoclonal antibody, Pse-MAB1, exhibited direct bactericidal activity on Acinetobacter baumannii strains, even in the absence of the host complements or other immune factors, and was able to confer a protective effect against A. baumannii infections in mice. This study provides new insight into the potential of developing monoclonal antibody-based antimicrobial therapy of multidrug resistant bacterial infections, especially those which occurred among immunocompromised patients.

Monoclonal antibody targeting Pse was generated by immunization of mice with synthesized Pse-KLH conjugates. Pse-MAB1 could mediate direct bacterial cell death and promote in vivo protection against A. baumannii infection in mice.

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency─or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its “fitness” for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.

Machine learning can complement enzyme engineering by helping to discover enzymes with desired function and to accelerate the optimization of enzyme fitness.

Peptides have been established as modular catalysts for various transformations. Still, the vast number of potential amino acid building blocks renders the identification of peptides with desired catalytic activity challenging. Here, we develop a machine-learning workflow for the optimization of peptide catalysts. First─in a hypothetical competition─we challenged our workflow to identify peptide catalysts for the conjugate addition reaction of aldehydes to nitroolefins and compared the performance of the predicted structures with those optimized in our laboratory. On the basis of the positive results, we established a universal training set (UTS) containing 161 catalysts to sample an in silico library of ∼30,000 tripeptide members. Finally, we challenged our machine learning strategy to identify a member of the library as a stereoselective catalyst for an annulation reaction that has not been catalyzed by a peptide thus far. We conclude with a comparison of data-driven versus expert-knowledge-guided peptide catalyst optimization.

Statistical learning methods were challenged to identify enantioselective peptide catalysts from a 30,000-member in silico library and compared with expert-knowledge-guided methods.

Interactions between ribosome-bound nascent chains (RNCs) and ribosomal components are critical to elucidate the mechanism of cotranslational protein folding. Nascent protein–ribosome contacts within the ribosomal exit tunnel were previously assessed mostly in the presence of C-terminal stalling sequences, yet little is known about contacts taking place in the absence of these strongly interacting motifs. Further, there is nearly no information about ribosomal proteins (r-proteins) interacting with nascent chains within the outer surface of the ribosome. Here, we combine chemical cross-linking, single-particle cryo-EM, and fluorescence anisotropy decays to determine the structural features of ribosome-bound apomyoglobin (apoMb). Within the ribosomal exit tunnel core, interactions are similar to those identified in previous reports. However, once the RNC enters the tunnel vestibule, it becomes more dynamic and interacts with ribosomal RNA (rRNA) and the L23 r-protein. Remarkably, on the outer surface of the ribosome, RNCs interact mainly with a highly conserved nonpolar patch of the L23 r-protein. RNCs also comprise a compact and dynamic N-terminal region lacking contact with the ribosome. In all, apoMb traverses the ribosome and interacts with it via its C-terminal region, while N-terminal residues sample conformational space and form a compact subdomain before the entire nascent protein sequence departs from the ribosome.

Single-particle cryogenic EM and fluorescence anisotropy decays show that a nascent globin interacts with the L23 ribosomal protein. The interaction site is highly nonpolar, suggesting a chaperone behavior.