CIISB Research Highlights Archive

Catalytic metal clusters play critical roles in important enzymatic pathways such as carbon fixation and energy conservation. However, how ligand binding to the active-site metal regulates conformational changes critical for enzyme function is often not well understood. One carbon fixation pathway that relies heavily on metalloenzymes is the reductive acetyl-coenzyme A (acetyl-CoA) pathway. In this study, we investigated the catalysis of the last step of the reductive acetyl-CoA pathway by the CO-dehydrogenase (CODH)-acetyl-CoA synthase (ACS) complex from Carboxydothermushydrogenoformans, focusing on how ligand binding to the nickel atom in the active site affects the conformational equilibrium of the enzyme. We captured six intermediate states of the enzyme by cryo-electron microscopy, with resolutions of 2.5-1.9A, and visualized reaction products bound to cluster A (an Ni,Ni-[4Fe4S] cluster) and identified several previously uncharacterized conformational states of CODH-ACS. The structures demonstrate how substrate binding controls conformational changes in the ACS subunit to prepare for the next catalytic step. 

The rational design and selective self-assembly of flexible and unsymmetric ligands into large coordination complexes is an eminent challenge in supramolecular coordination chemistry. Here, we present the coordination-driven self-assembly of natural ursodeoxycholic-bile-acid-derived unsymmetric tris-pyridyl ligand (L) resulting in the selective and switchable formation of chiral stellated Pd6L8 and Pd12L16 cages. The selectivity of the cage originates in the adaptivity and flexibility of the arms of the ligand bearing pyridyl moieties. The interspecific transformations can be controlled by changes in the reaction conditions. The orientational self-sorting of L into a single constitutional isomer of each cage, i.e., homochiral quadruple and octuple right-handed helical species, was confirmed by a combination of molecular modelling and circular dichroism. The cages, derived from natural amphiphilic transport molecules, mediate the higher cellular uptake and increase the anticancer activity of bioactive palladium cations as determinedin studies using in vitro 3D spheroids of the human hepatic cells HepG2. 

Microtubules (MTs) undergo diverse posttranslational modifications that regulate their structural and functional properties. Among these, polyglutamylation-a dominant and conserved modification targeting unstructured tubulin C-terminal tails-plays a pivotal role in defining the tubulin code. Here, we describe a mechanism by which tubulin tyrosine ligase-like 11 (TTLL11) expands and diversifies the code. Cryo-electron microscopy revealed a unique bipartite MT recognition strategy wherein TTLL11 binding and catalytic domains engage adjacent MT protofilaments. Biochemical and cellular assays identifiedpreviously uncharacterized polyglutamylation patterns, showing that TTLL11 directly extends the primary polypeptide chains of alpha- and beta-tubulin in vitro, challenging the prevailing paradigms emphasizing lateral branching. Moreover, cell-based and in vivo data suggest a cross-talk between polyglutamylation and the detyrosination/tyrosination cycle likely linked to the TTLL11-mediated elongation of the primary alpha-tubulin chain. These findings unveil an unrecognized layer of complexity within the tubulin code and offer mechanistic insights into the molecular basis of functional specialization of MT cytoskeleton.

Untargeted high-resolution mass spectrometry is a key tool in clinical metabolomics, natural product discovery and exposomics, with compound identification remaining the major bottleneck. Currently, the standard workflow applies spectral library matching against tandem mass spectrometry (MS2) fragmentation data. Multi-stage fragmentation (MSn) yields more profound insights into substructures, enabling validation of fragmentation pathways; however, the community lacks open MSn reference data of diverse natural products and other chemicals. Here we describe MS(n)Lib, a machine learning-ready open resource of >2 million spectra in MSn trees of 30,008 unique small molecules, built with a high-throughput data acquisition and processing pipeline in the open-source software mzmine.