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Coarse-grained potential for hydrogen bond interactions

Understanding protein structure and dynamics is crucial for investigating numerous biological processes. This however requires proper description of molecular interactions, most notably hydrogen bonds, which are the driving force behind the folding of protein sequences into working molecules. Due to the multi-body character of this interaction, proper mathematical formulation has been a matter of long debate in the literature. This description becomes even more complex in reduced protein models. In this contribution, we propose a novel hydrogen bond energy function definition that is based only on Cα positions and used for coarse-grained simulations. We show that this new method has the capability to recognize hydrogen bonds with over 80% accuracy and can successfully identify β-sheet in β-amyloid peptide simulations.

Automated Protein Secondary Structure Assignment from Cα Positions Using Neural Networks

The assignment of secondary structure elements in protein conformations is necessary to interpret a protein model that has been established by computational methods. The process essentially involves labeling the amino acid residues with H (Helix), E (Strand), or C (Coil, also known as Loop). When particular atoms are absent from an input protein structure, the procedure becomes more complicated, especially when only the alpha carbon locations are known. Various techniques have been tested and applied to this problem during the last forty years. The application of machine learning techniques is the most recent trend. This contribution presents the HECA classifier, which uses neural networks to assign protein secondary structure types. The technique exclusively employs Cα coordinates. The Keras (TensorFlow) library was used to implement and train the neural network model. The BioShell toolkit was used to calculate the neural network input features from raw coordinates. The study’s findings show that neural network-based methods may be successfully used to take on structure assignment challenges when only Cα trace is available. Thanks to the careful selection of input features, our approach’s accuracy (above 97%) exceeded that of the existing methods.

Lifestyles Shape the Cytochrome P450 Repertoire of the Bacterial Phylum Proteobacteria

For the last six decades, cytochrome P450 monooxygenases (CYPs/P450s), heme thiolate proteins, have been under the spotlight due to their regio- and stereo-selective oxidation activities, which has led to the exploration of their applications in almost all known areas of biology. The availability of many genome sequences allows us to understand the evolution of P450s in different organisms, especially in the Bacteria domain. The phenomenon that “P450s play a key role in organisms’ adaptation vis a vis lifestyle of organisms impacts P450 content in their genome” was proposed based on studies on a handful of individual bacterial groups. To have conclusive evidence, one must analyze P450s and their role in secondary metabolism in species with diverse lifestyles but that belong to the same category. We selected species of the phylum Proteobacteria classes, Alpha, Beta, Gamma, Delta, and Epsilon, to address this research gap due to their diverse lifestyle and ancient nature. The study identified that the lifestyle of alpha-, beta-, gamma-, delta-, and epsilon-proteobacterial species profoundly affected P450 profiles in their genomes. The study determined that irrespective of the species associated with different proteobacterial classes, pathogenic species or species adapted to a simple lifestyle lost or had few P450s in their genomes. On the contrary, species with saprophytic or complex lifestyles had many P450s and secondary metabolite biosynthetic gene clusters. The study findings prove that the phenomenon mentioned above is factual, and there is no link between the number and diversity of P450s and the age of the bacteria.

Contrasting Health Effects of Bacteroidetes and Firmicutes Lies in Their Genomes: Analysis of P450s, Ferredoxins, and Secondary Metabolite Clusters

Species belonging to the bacterial phyla Bacteroidetes and Firmicutes represent over 90% of the gastrointestinal microbiota. Changes in the ratio of these two bacterial groups were found to have contrasting health effects, including obesity and inflammatory diseases. Despite the availability of many bacterial genomes, comparative genomic studies on the gene pools of these two bacterial groups concerning cytochrome P450 monooxygenases (P450s), ferredoxins, and secondary metabolite biosynthetic gene clusters (smBGCs) are not reported. This study is aimed to address this research gap. The study revealed the presence of diverse sets of P450s, ferredoxins, and smBGCs in their genomes. Bacteroidetes species have the highest number of P450 families, ferredoxin cluster-types, and smBGCs compared to Firmicutes species. Only four P450 families, three ferredoxin cluster types, and five smBGCs are commonly shared between these two bacterial groups. Considering the above facts, we propose that the contrasting effects of these two bacterial groups on the host are partly due to the distinct nature of secondary metabolites produced by these organisms. Thus, the cause of the contrasting health effects of these two bacterial groups lies in their gene pools.

An Unprecedented Number of Cytochrome P450s Are Involved in Secondary Metabolism in Salinispora Species

Cytochrome P450 monooxygenases (CYPs/P450s) are heme thiolate proteins present in species across the biological kingdoms. By virtue of their broad substrate promiscuity and regio- and stereo-selectivity, these enzymes enhance or attribute diversity to secondary metabolites. Actinomycetes species are well-known producers of secondary metabolites, especially Salinispora species. Despite the importance of P450s, a comprehensive comparative analysis of P450s and their role in secondary metabolism in Salinispora species is not reported. We therefore analyzed P450s in 126 strains from three different species Salinispora arenicola, S. pacifica, and S. tropica. The study revealed the presence of 2643 P450s that can be grouped into 45 families and 103 subfamilies. CYP107 and CYP125 families are conserved, and CYP105 and CYP107 families are bloomed (a P450 family with many members) across Salinispora species. Analysis of P450s that are part of secondary metabolite biosynthetic gene clusters (smBGCs) revealed Salinispora species have an unprecedented number of P450s (1236 P450s-47%) part of smBGCs compared to other bacterial species belonging to the genera Streptomyces (23%) and Mycobacterium (11%), phyla Cyanobacteria (8%) and Firmicutes (18%) and the classes Alphaproteobacteria (2%) and Gammaproteobacteria (18%). A peculiar characteristic of up to six P450s in smBGCs was observed in Salinispora species. Future characterization Salinispora species P450s and their smBGCs have the potential for discovering novel secondary metabolites.

Diversification of Ferredoxins across Living Organisms

Ferredoxins, iron-sulfur (Fe-S) cluster proteins, play a key role in oxidoreduction reactions. To date, evolutionary analysis of these proteins across the domains of life have been confined to observing the abundance of Fe-S cluster types (2Fe-2S, 3Fe-4S, 4Fe-4S, 7Fe-8S (3Fe-4s and 4Fe-4S) and 2[4Fe-4S]) and the diversity of ferredoxins within these cluster types was not studied. To address this research gap, here we propose a subtype classification and nomenclature for ferredoxins based on the characteristic spacing between the cysteine amino acids of the Fe-S binding motif as a subtype signature to assess the diversity of ferredoxins across the living organisms. To test this hypothesis, comparative analysis of ferredoxins between bacterial groups, Alphaproteobacteria and Firmicutes and ferredoxins collected from species of different domains of life that are reported in the literature has been carried out. Ferredoxins were found to be highly diverse within their types. Large numbers of alphaproteobacterial species ferredoxin subtypes were found in Firmicutes species and the same ferredoxin subtypes across the species of Bacteria, Archaea, and Eukarya, suggesting shared common ancestral origin of ferredoxins between Archaea and Bacteria and lateral gene transfer of ferredoxins from prokaryotes (Archaea/Bacteria) to eukaryotes. This study opened new vistas for further analysis of diversity of ferredoxins in living organisms.