A database overview of metal-coordination distances in metalloproteins

Metalloproteins are ubiquitous in all living organisms and take part in a very wide range of biological processes. For this reason, their experimental characterization is crucial to obtain improved knowledge of their structure and biological functions. The three-dimensional structure represents highly relevant information since it provides insight into the interaction between the metal ion(s) and the protein fold. Such interactions determine the chemical reactivity of the bound metal. The available PDB structures can contain errors due to experimental factors such as poor resolution and radiation damage. A lack of use of distance restraints during the refinement and validation process also impacts the structure quality. Here, the aim was to obtain a thorough overview of the distribution of the distances between metal ions and their donor atoms through the statistical analysis of a data set based on more than 115 000 metal-binding sites in proteins. This analysis not only produced reference data that can be used by experimentalists to support the structure-determination process, for example as refinement restraints, but also resulted in an improved insight into how protein coordination occurs for different metals and the nature of their binding interactions. In particular, the features of carboxylate coordination were inspected, which is the only type of interaction that is commonly present for nearly all metals.

Classifying metal-binding sites with neural networks

To advance our ability to predict impacts of the protein scaffold on catalysis, robust classification schemes to define features of proteins that will influence reactivity are needed. One of these features is a protein's metal-binding ability, as metals are critical to catalytic conversion by metalloenzymes. As a step toward realizing this goal, we used convolutional neural networks (CNNs) to enable the classification of a metal cofactor binding pocket within a protein scaffold. CNNs enable images to be classified based on multiple levels of detail in the image, from edges and corners to entire objects, and can provide rapid classification. First, six CNN models were fine-tuned to classify the 20 standard amino acids to choose a performant model for amino acid classification. This model was then trained in two parallel efforts: to classify a 2D image of the environment within a given radius of the central metal binding site, either an Fe ion or a [2Fe-2S] cofactor, with the metal visible (effort 1) or the metal hidden (effort 2). We further used two sub-classifications of the [2Fe-2S] cofactor: (1) a standard [2Fe-2S] cofactor and (2) a Rieske [2Fe-2S] cofactor. The accuracy for the model correctly identifying all three defined features was >95%, despite our perception of the increased challenge of the metalloenzyme identification. This demonstrates that machine learning methodology to classify and distinguish similar metal-binding sites, even in the absence of a visible cofactor, is indeed possible and offers an additional tool for metal-binding site identification in proteins.

[Substitutability of metal-binding sites in an alcohol dehydrogenase]

Covalently anchoring of a ligand/metal via polar amino acid side chain(s) is often observed in metalloenzyme, while the substitutability of metal-binding sites remains elusive. In this study, we utilized a zinc-dependent alcohol dehydrogenase from Thermoanaerobacter brockii (TbSADH) as a model enzyme, analyzed the sequence conservation of the three residues Cys37, His59, and Asp150 that bind the zinc ion, and constructed the mutant library. After experimental validation, three out of 224 clones, which showed comparative conversion and ee values as the wild-type enzyme in the asymmetric reduction of the model substrate tetrahydrofuran-3-one, were screened out. The results reveal that the metal-binding sites in TbSADH are substitutable without tradeoff in activity and stereoselectivity, which lay a foundation for designing ADH-catalyzed new reactions via metal ion replacement.

Ceruloplasmin revisited: structural and functional roles of various metal cation-binding sites

The three-dimensional molecular structure of human serum ceruloplasmin has been reinvestigated using X-ray synchrotron data collected at 100 K from a crystal frozen to liquid-nitrogen temperature. The resulting model, with an increase in resolution from 3.1 to 2.8 A, gives an overall improvement of the molecular structure, in particular the side chains. In addition, it enables the clear definition of previously unidentified Ca2+-binding and Na+-binding sites. The Ca2+ cation is located in domain 1 in a configuration very similar to that found in the activated bovine factor Va. The Na+ sites appear to play a structural role in providing rigidity to the three protuberances on the top surface of the molecule. These features probably help to steer substrates towards the mononuclear copper sites prior to their oxidation and to restrict the size of the approaching substrate. The trinuclear copper centre appears to differ from the room-temperature structure in that a dioxygen moiety is bound in a similar way to that found in the endospore coat protein CotA from Bacillus subtilis.

The presence and possible role of zinc in RNA polymerase obtained from Escherichia coli

Highly purified preparations of the DNA-dependent RNA polymerase obtained from Escherichia coli contain about 2 g-atoms of tightly bound zinc per mol (molecular weight 370,000) of enzyme. When the purified enzyme is fractionated on Sephadex G-150 or G-200, correlation is observed between the zinc and enzymic activity. Although some of the preparations examined also contain iron, copper, and magnesium, the content of these metal ions show no consistent correlation with RNA polymerase activity. Initiation of RNA synthesis is specifically inhibited by 1,10-phenanthroline. Less-effective inhibition is observed for other chelating agents or for a nonchelating phenanthroline analog. The analog also exhibits a pattern of inhibition differing from that characteristic of 1,10-phenanthroline. Binding of purine nucleoside triphosphates at the lower-affinity (K(d) = 0.15 mM) site may also be prevented by the addition of 1,10-phenanthroline. One or both of the bound zinc atoms may, therefore, participate in the initiation of RNA synthesis.