The Crystal Structure of the C-Terminal Domain of the Salmonella enterica PduO Protein: An Old Fold with a New Heme-Binding Mode

A method for the efficient adenosylation of corrinoids

Adenosylcobamides (AdoCbas) are coenzymes required by organisms from all domains of life to perform challenging chemical reactions. AdoCbas are characterized by a cobalt-containing tetrapyrrole ring, where an adenosyl group is covalently attached to the cobalt ion via a unique Co-C organometallic bond. During catalysis, this bond is homolytically cleaved by AdoCba-dependent enzymes to form an adenosyl radical that is critical for intra-molecular rearrangements. The formation of the Co-C bond is catalyzed by a family of enzymes known as ATP:Co(I)rrinoid adenosyltransferases (ACATs). ACATs adenosylate Cbas in two steps: (I) they generate a planar, Co(II) four-coordinate Cba to facilitate the reduction of Co(II) to Co(I), and (II) they transfer the adenosyl group from ATP to the Co(I) ion. To synthesize adenosylated corrinoids in vitro, it is imperative that anoxic conditions are maintained to avoid oxidation of Co(II) or Co(I) ions. Here we describe a method for the enzymatic synthesis and quantification of specific AdoCbas.

EfgA is a conserved formaldehyde sensor that leads to bacterial growth arrest in response to elevated formaldehyde

Normal cellular processes give rise to toxic metabolites that cells must mitigate. Formaldehyde is a universal stressor and potent metabolic toxin that is generated in organisms from bacteria to humans. Methylotrophic bacteria such as Methylorubrum extorquens face an acute challenge due to their production of formaldehyde as an obligate central intermediate of single-carbon metabolism. Mechanisms to sense and respond to formaldehyde were speculated to exist in methylotrophs for decades but had never been discovered. Here, we identify a member of the DUF336 domain family, named efgA for enhanced formaldehyde growth, that plays an important role in endogenous formaldehyde stress response in M. extorquens PA1 and is found almost exclusively in methylotrophic taxa. Our experimental analyses reveal that EfgA is a formaldehyde sensor that rapidly arrests growth in response to elevated levels of formaldehyde. Heterologous expression of EfgA in Escherichia coli increases formaldehyde resistance, indicating that its interaction partners are widespread and conserved. EfgA represents the first example of a formaldehyde stress response system that does not involve enzymatic detoxification. Thus, EfgA comprises a unique stress response mechanism in bacteria, whereby a single protein directly senses elevated levels of a toxic intracellular metabolite and safeguards cells from potential damage.

DeepDrug3D: Classification of ligand-binding pockets in proteins with a convolutional neural network

Comprehensive characterization of ligand-binding sites is invaluable to infer molecular functions of hypothetical proteins, trace evolutionary relationships between proteins, engineer enzymes to achieve a desired substrate specificity, and develop drugs with improved selectivity profiles. These research efforts pose significant challenges owing to the fact that similar pockets are commonly observed across different folds, leading to the high degree of promiscuity of ligand-protein interactions at the system-level. On that account, novel algorithms to accurately classify binding sites are needed. Deep learning is attracting a significant attention due to its successful applications in a wide range of disciplines. In this communication, we present DeepDrug3D, a new approach to characterize and classify binding pockets in proteins with deep learning. It employs a state-of-the-art convolutional neural network in which biomolecular structures are represented as voxels assigned interaction energy-based attributes. The current implementation of DeepDrug3D, trained to detect and classify nucleotide- and heme-binding sites, not only achieves a high accuracy of 95%, but also has the ability to generalize to unseen data as demonstrated for steroid-binding proteins and peptidase enzymes. Interestingly, the analysis of strongly discriminative regions of binding pockets reveals that this high classification accuracy arises from learning the patterns of specific molecular interactions, such as hydrogen bonds, aromatic and hydrophobic contacts. DeepDrug3D is available as an open-source program at https://github.com/pulimeng/DeepDrug3D with the accompanying TOUGH-C1 benchmarking dataset accessible from https://osf.io/enz69/.

A New Class of EutT ATP:Co(I)rrinoid Adenosyltransferases Found in Listeria monocytogenes and Other Firmicutes Does Not Require a Metal Ion for Activity

ATP:Co(I)rrinoid adenosyltransferases (ACATs) are involved in de novo adenosylcobamide (AdoCba) biosynthesis and in salvaging complete and incomplete corrinoids from the environment. The ACAT enzyme family is comprised of three classes of structurally and evolutionarily distinct proteins (i.e., CobA, PduO, and EutT). The structure of EutT is unknown, and an understanding of its mechanism is incomplete. The Salmonella enterica EutT ( SeEutT) enzyme is the best-characterized member of its class and is known to be a ferroprotein. Here, we report the identification and initial biochemical characterization of an enzyme representative of a new class of EutTs that does not require a metal ion for activity. In vivo and in vitro evidence shows that the metal-free EutT homologue from Listeria monocytogenes ( LmEutT) has ACAT activity and that, unlike other ACATs, the biologically active form of LmEutT is a tetramer. In vitro studies revealed that LmEutT was more efficient than SeEutT and displayed positive cooperativity. LmEutT adenosylated cobalamin, but not cobinamide, showed specificity for ATP and 2'-deoxyATP and released a triphosphate byproduct. Bioinformatics analyses suggest that metal-free EutT ACATs are also present in other Firmicutes.