Phylum Gemmatimonadota and Its Role in the Environment

Bacteria are an important part of every ecosystem that they inhabit on Earth. Environmental microbiologists usually focus on a few dominant bacterial groups, neglecting less abundant ones, which collectively make up most of the microbial diversity. One of such less-studied phyla is Gemmatimonadota. Currently, the phylum contains only six cultured species. However, data from culture-independent studies indicate that members of Gemmatimonadota are common in diverse habitats. They are abundant in soils, where they seem to be frequently associated with plants and the rhizosphere. Moreover, Gemmatimonadota were found in aquatic environments, such as freshwaters, wastewater treatment plants, biofilms, and sediments. An important discovery was the identification of purple bacterial reaction centers and anoxygenic photosynthesis in this phylum, genes for which were likely acquired via horizontal gene transfer. So far, the capacity for anoxygenic photosynthesis has been described for two cultured species: Gemmatimonas phototrophica and Gemmatimonas groenlandica. Moreover, analyses of metagenome-assembled genomes indicate that it is also common in uncultured lineages of Gemmatimonadota. This review summarizes the current knowledge about this understudied bacterial phylum with an emphasis on its environmental distribution.

Characterizing protein protonation microstates using Monte Carlo sampling

Proteins are polyelectrolytes with acidic or basic amino acids making up ≈25% of the residues. The protonation state of all Asp, Glu, Arg, Lys, His and other protonatable residues, cofactors and ligands define each protonation microstate. As all of these residues will not be fully ionized or neutral, proteins exist in a mixture of microstates. The microstate distribution changes with pH. As the protein environment modifies the proton affinity of each site the distribution may also change in different reaction intermediates or as ligands are bound. Particular protonation microstates may be required for function, while others exist simply because there are many states with similar energy. Here, the protonation microstates generated in Monte Carlo sampling in MCCE are characterized in HEW lysozyme as a function of pH and bacterial photosynthetic reaction centers (RCs) in different reaction intermediates. The lowest energy and highest probability microstates are compared. The ∆G, ∆H and ∆S between the four protonation states of Glu35 and Asp52 in lysozyme are shown to be calculated with reasonable precision. A weighted Pearson correlation analysis identifies coupling between residue protonation states in RCs and how they change when the quinone in the QB site is reduced.

Synthesis, quantum-chemical calculations and virtual screening of the alkaloid cytisine derivatives

The synthesis of some cytisine derivatives was carried out in the work. The article provides the data of quantum-chemical calculation and virtual screening of the alkaloid cytisine derivatives synthesized. At the same time, the reaction centers of the cytisine derivatives molecules were determined. In order to study the reactivity of the derivatives obtained (namely cinnamoylcytisine, lipoylcytisine, and cytisinylisoalantholactone) the quantum-chemical calculations were conducted to determine the energy and charge characteristics of the molecules. The results indicate a sufficient thermodynamic stability of the cinnamoylcytisine and lipoylcytisine molecules. The cytisinylisoalantholactone molecule is not stable according to the results of quantum chemical calculations. The data on the energy values of the frontier molecular orbitals show that, in general, all molecules exhibit electrophilic properties. A bioprediction was implemented using PASS (Prediction of Activity Spectra for Substances) as one of the most efficient and well-known computer program with the aim of detailed study and the probable establishment of the biological activity of the synthesized cytisine derivatives. Based on the results of virtual screening, promising types of alkaloid cytisine derivatives were identified, which are potential sources of original drugs

On the Question of Zwitterionic Intermediates in the [3 + 2] Cycloaddition Reactions between C-arylnitrones and Perfluoro 2-Methylpent-2-ene

The molecular mechanism of the [3 + 2] cycloaddition reaction between C-arylnitrones and perfluoro 2-methylpent-2-ene was explored on the basis of DFT calculations. It was found that despite the polar nature of the intermolecular interactions, as well as the presence of fluorine atoms near the reaction centers, all reactions considered cycloaddition proceed via a one-step mechanism. All attempts for the localization of zwitterionic intermediates on the reaction paths were not successful. Similar results were obtained regardless of the level of theory applied.

De Novo Protein Design of Photochemical Reaction Centers

Natural photosynthetic protein complexes capture sunlight to power the energetic catalysis that supports life on Earth. Yet these natural protein structures carry an evolutionary legacy of complexity and fragility that encumbers protein reengineering efforts and obfuscates the underlying design rules for light-driven charge separation. De novo development of a simplified photosynthetic reaction center protein can clarify practical engineering principles needed to build new enzymes for efficient solar-to-fuel energy conversion. Here we report the rational design, X-ray crystal structure, and electron transfer activity of a multi-cofactor protein that incorporates essential elements of photosynthetic reaction centers. This highly stable, modular artificial protein framework can be reconstituted in vitro with interchangeable redox centers for nanometer-scale photochemical charge separation. Transient absorption spectroscopy demonstrates Photosystem II-like tyrosine and metal cluster oxidation, and we measure charge separation lifetimes exceeding 100 ms, ideal for light-activated catalysis. This de novo-designed reaction center builds upon engineering guidelines established for charge separation in earlier synthetic photochemical triads and modified natural proteins, and it shows how synthetic biology may lead to a new generation of genetically encoded, light-powered catalysts for solar fuel production.

RegioML: Predicting the regioselectivity of electrophilic aromatic substitution reactions using machine learning

We present RegioML, an atom-based machine learning model for predicting the regioselectivities of electrophilic aromatic substitution reactions. The model relies on CM5 atomic charges computed using semiempirical tight binding (GFN1-xTB) combined with the ensemble decision tree variant light gradient boosting machine (LightGBM). The model is trained and tested on 21,201 bromination reactions with 101K reaction centers, which is split into a training, test, and out-of-sample datasets with 58K, 15K, and 27K reaction centers, respectively. The accuracy is 93% for the test set and 90% for the out-of-sample set, while the precision (the percentage of positive predictions that are correct) is 88% and 80%, respectively. The test-set performance is very similar to the graph-based WLN method developed by Struble et al. (React. Chem. Eng. 2020, 5, 896) though the comparison is complicated by the possibility that some of the test and out-of-sample molecules are used to train WLN. RegioML out-performs our physics-based RegioSQM20 method (J. Cheminform. 2021, 13:10) where the precision is only 75%. Even for the out-of-sample dataset, RegioML slightly outperforms RegioSQM20. The good performance of RegioML and WLN is in large part due to the large datasets available for this type of reaction. However, for reactions where there is little experimental data, physics-based approaches like RegioSQM20 can be used to generate synthetic data for model training. We demonstrate this by showing that the performance of RegioSQM20 can be reproduced by a ML-model trained on RegioSQM20-generated data.