deepBBQ: A Deep Learning Approach to the Protein Backbone Reconstruction.

Coarse-grained models have provided researchers with greatly improved computational efficiency in modeling structures and dynamics of biomacromolecules, but, to be practically useful, they need fast and accurate conversion methods back to the all-atom representation. Reconstruction of atomic details may also be required in the case of some experimental methods, like electron microscopy, which may provide Cα-only structures. In this contribution, we present a new method for recovery of all backbone atom positions from just the Cα coordinates.

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.

Automated Protein Secondary Structure Assignment from C 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.

An Unprecedented Number of Cytochrome P450s Are Involved in Secondary Metabolism in 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 species.

Lifestyles Shape the Cytochrome P450 Repertoire of the Bacterial Phylum .

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.

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

Species belonging to the bacterial phyla and 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.

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks.

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met.

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.

In Silico Structural Modeling and Analysis of Interactions of Cytochrome P450 Monooxygenases CYP51s with Substrates and Azoles.

Cytochrome P450 monooxygenase CYP51 (sterol 14α-demethylase) is a well-known target of the azole drug fluconazole for treating cryptococcosis, a life-threatening fungal infection in immune-compromised patients in poor countries. Studies indicate that mutations in CYP51 confer fluconazole resistance on cryptococcal species. Despite the importance of CYP51 in these species, few studies on the structural analysis of CYP51 and its interactions with different azole drugs have been reported.

Ancient Bacterial Class Cytochrome P450 Monooxygenases Can Be Found in Other Bacterial Species.

Cytochrome P450 monooxygenases (CYPs/P450s), heme-thiolate proteins, are well-known players in the generation of chemicals valuable to humans and as a drug target against pathogens. Understanding the evolution of P450s in a bacterial population is gaining momentum. In this study, we report comprehensive analysis of P450s in the ancient group of the bacterial class .

VisuaLife: library for interactive visualization in rich web applications.

Motivation: Visualization is a powerful tool to analyze, understand and present big data. Computational biology, bioinformatics and molecular modeling require dedicated tools, tailored to very complex, highly multidimensional data. Over the recent years, numerous tools have been developed for online presentation, but new challenges like the COVID-19 pandemic require new libraries which will guarantee fast development of online tools for a better understanding of biomedical data/results.

In Silico Analysis of P450s and Their Role in Secondary Metabolism in the Bacterial Class .

The impact of lifestyle on shaping the genome content of an organism is a well-known phenomenon and cytochrome P450 enzymes (CYPs/P450s), heme-thiolate proteins that are ubiquitously present in organisms, are no exception. Recent studies focusing on a few bacterial species such as , , and revealed that the impact of lifestyle affected the P450 repertoire in these species. However, this phenomenon needs to be understood in other bacterial species.

More P450s Are Involved in Secondary Metabolite Biosynthesis in Compared to , , and .

Unraveling the role of cytochrome P450 monooxygenases (CYPs/P450s), heme-thiolate proteins present in living and non-living entities, in secondary metabolite synthesis is gaining momentum. In this direction, in this study, we analyzed the genomes of 203 species for P450s and unraveled their association with secondary metabolism. Our analyses revealed the presence of 5460 P450s, grouped into 253 families and 698 subfamilies.

Macromolecular modeling and design in Rosetta: recent methods and frameworks.

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities.

Practical Considerations for Atomistic Structure Modeling with Cryo-EM Maps.

We describe common approaches to atomistic structure modeling with single particle analysis derived cryo-EM maps. Several strategies for atomistic model building and atomistic model fitting methods are discussed, including selection criteria and implementation procedures. In covering basic concepts and caveats, this short perspective aims to help facilitate active discussion between scientists at different levels with diverse backgrounds.

Better together: Elements of successful scientific software development in a distributed collaborative community.

Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments.

BioShell 3.0: Library for Processing Structural Biology Data.

BioShell is an open-source package for processing biological data, particularly focused on structural applications. The package provides parsers, data structures and algorithms for handling and analyzing macromolecular sequences, structures and sequence profiles. The most frequently used routines are accessible by a set of easy-to-use command line utilities for a Linux environment.

Parallel Implementation of a Sequential Markov Chain in Monte Carlo Simulations of Physical Systems with Pairwise Interactions.

In molecular simulations performed by Markov Chain Monte Carlo (typically employing the Metropolis criterion), each state of a system is obtained by a small random modification of the previous state. Therefore, the process consists of an immense number of small, quick to calculate steps, which are inherently sequential and hence considered to be very hard to parallelise. Here, we present a novel protocol for efficient calculation of multiple sequential steps in parallel.

Mutation goals in the vitamin D receptor predicted by computational methods.

The mechanism through which nuclear receptors respond differentially to structurally distinct agonists is a poorly understood process. We present a computational method that identifies nuclear receptor amino acids that are likely involved in biological responses triggered by ligand binding. The method involves tracing how structural changes spread from the ligand binding pocket to the sites on the receptor surface, which makes it a good tool for studying allosteric effects.

Coarse-Grained Modeling of the Interplay between Secondary Structure Propensities and Protein Fold Assembly.

We recently developed a new coarse-grained model of protein structure and dynamics [ Dawid et al. J. Chem.

SURPASS Low-Resolution Coarse-Grained Protein Modeling.

Coarse-grained modeling of biomolecules has a very important role in molecular biology. In this work we present a novel SURPASS (Single United Residue per Pre-Averaged Secondary Structure fragment) model of proteins that can be an interesting alternative for existing coarse-grained models. The design of the model is unique and strongly supported by the statistical analysis of structural regularities characteristic for protein systems.

In silico analysis of cytochrome P450 monooxygenases in chronic granulomatous infectious fungus Sporothrix schenckii: Special focus on CYP51.

Sporotrichosis is an emerging chronic, granulomatous, subcutaneous, mycotic infection caused by Sporothrix species. Sporotrichosis is treated with the azole drug itraconazole as ketoconazole is ineffective. It is a well-known fact that azole drugs act by inhibiting cytochrome P450 monooxygenases (P450s), heme-thiolate proteins.

Coarse-Grained Protein Models and Their Applications.

The traditional computational modeling of protein structure, dynamics, and interactions remains difficult for many protein systems. It is mostly due to the size of protein conformational spaces and required simulation time scales that are still too large to be studied in atomistic detail. Lowering the level of protein representation from all-atom to coarse-grained opens up new possibilities for studying protein systems.

Improving thermal stability of thermophilic L-threonine aldolase from Thermotoga maritima.

Threonine aldolase (TA) catalyzes a reversible reaction, in which threonine is decomposed into glycine and acetaldehyde. The same enzyme can be used to catalyze aldol reaction between glycine and a variety of aromatic and aliphatic aldehydes, thus creating various alpha-amino-alcohols. Therefore, TA is a very promising enzyme that could be used to prepare biologically active compounds or building blocks for pharmaceutical industry.