An Approach for Engineering Peptides for Competitive Inhibition of the SARS-COV-2 Spike Protein.

SARS-CoV-2 is the virus responsible for a respiratory disease called COVID-19 that devastated global public health. Since 2020, there has been an intense effort by the scientific community to develop safe and effective prophylactic and therapeutic agents against this disease. In this context, peptides have emerged as an alternative for inhibiting the causative agent. However, designing peptides that bind efficiently is still an open challenge. Here, we show an algorithm for peptide engineering. Our strategy consists of starting with a peptide whose structure is similar to the interaction region of the human ACE2 protein with the SPIKE protein, which is important for SARS-COV-2 infection. Our methodology is based on a genetic algorithm performing systematic steps of random mutation, protein-peptide docking (using the PyRosetta library) and selecting the best-optimized peptides based on the contacts made at the peptide-protein interface. We performed three case studies to evaluate the tool parameters and compared our results with proposals presented in the literature. Additionally, we performed molecular dynamics (MD) simulations (three systems, 200 ns each) to probe whether our suggested peptides could interact with the spike protein. Our results suggest that our methodology could be a good strategy for designing peptides.

Thermostabilizing mechanisms of canonical single amino acid substitutions at a GH1 ß-glucosidase probed by multiple MD and computational approaches.

ß-glucosidases play a pivotal role in second-generation biofuel (2G-biofuel) production. For this application, thermostable enzymes are essential due to the denaturing conditions on the bioreactors. Random amino acid substitutions have originated new thermostable ß-glucosidases, but without a clear understanding of their molecular mechanisms. Here, we probe by different molecular dynamics simulation approaches with distinct force fields and submitting the results to various computational analyses, the molecular bases of the thermostabilization of the Paenibacillus polymyxa GH1 ß-glucosidase by two-point mutations E96K (TR1) and M416I (TR2). Equilibrium molecular dynamic simulations (eMD) at different temperatures, principal component analysis (PCA), virtual docking, metadynamics (MetaDy), accelerated molecular dynamics (aMD), Poisson-Boltzmann surface analysis, grid inhomogeneous solvation theory and colony method estimation of conformational entropy allow to converge to the idea that the stabilization carried by both substitutions depend on different contributions of three classic mechanisms: (i) electrostatic surface stabilization; (ii) efficient isolation of the hydrophobic core from the solvent, with energetic advantages at the solvation cap; (iii) higher distribution of the protein dynamics at the mobile active site loops than at the protein core, with functional and entropic advantages. Mechanisms i and ii predominate for TR1, while in TR2, mechanism iii is dominant. Loop A integrity and loops A, C, D, and E dynamics play critical roles in such mechanisms. Comparison of the dynamic and topological changes observed between the thermostable mutants and the wildtype protein with amino acid co-evolutive networks and thermostabilizing hotspots from the literature allow inferring that the mechanisms here recovered can be related to the thermostability obtained by different substitutions along the whole family GH1. We hope the results and insights discussed here can be helpful for future rational approaches to the engineering of optimized ß-glucosidases for 2G-biofuel production for industry, biotechnology, and science.

E-Volve: understanding the impact of mutations in SARS-CoV-2 variants spike protein on antibodies and ACE2 affinity through patterns of chemical interactions at protein interfaces.

Background: The SARS-CoV-2 pandemic reverberated, posing health and social hygiene obstacles throughout the globe. Mutant lineages of the virus have concerned scientists because of convergent amino acid alterations, mainly on the viral spike protein. Studies have shown that mutants have diminished activity of neutralizing antibodies and enhanced affinity with its human cell receptor, the ACE2 protein. Methods: Hence, for real-time measuring of the impacts caused by variant strains in such complexes, we implemented E-Volve, a tool designed to model a structure with a list of mutations requested by users and return analyses of the variant protein. As a proof of concept, we scrutinized the spike-antibody and spike-ACE2 complexes formed in the variants of concern, B.1.1.7 (Alpha), B.1.351 (Beta), and P.1 (Gamma), by using contact maps depicting the interactions made amid them, along with heat maps to quantify these major interactions. Results: The results found in this study depict the highly frequent interface changes made by the entire set of mutations, mainly conducted by N501Y and E484K. In the spike-Antibody complex, we have noticed alterations concerning electrostatic surface complementarity, breaching essential sites in the P17 and BD-368-2 antibodies. Alongside, the spike-ACE2 complex has presented new hydrophobic bonds. Discussion: Molecular dynamics simulations followed by Poisson-Boltzmann calculations corroborate the higher complementarity to the receptor and lower to the antibodies for the K417T/E484K/N501Y (Gamma) mutant compared to the wild-type strain, as pointed by E-Volve, as well as an intensification of this effect by changes at the protein conformational equilibrium in solution. A local disorder of the loop α1'/ß1', as well its possible effects on the affinity to the BD-368-2 antibody were also incorporated to the final conclusions after this analysis. Moreover, E-Volve can depict the main alterations in important biological structures, as shown in the SARS-CoV-2 complexes, marking a major step in the real-time tracking of the virus mutant lineages. E-Volve is available at http://bioinfo.dcc.ufmg.br/evolve.

Molecular and genetic characterization of a large Brazilian cohort presenting hearing loss.

Hearing loss is one of the most common sensory defects, affecting 5.5% of the worldwide population and significantly impacting health and social life. It is mainly attributed to genetic causes, but their relative contribution reflects the geographical region's socio-economic development. Extreme genetic heterogeneity with hundreds of deafness genes involved poses challenges for molecular diagnosis. Here we report the investigation of 542 hearing-impaired subjects from all Brazilian regions to search for genetic causes. Biallelic GJB2/GJB6 causative variants were identified in 12.9% (the lowest frequency was found in the Northern region, 7.7%), 0.4% carried GJB2 dominant variants, and 0.6% had the m.1555A > G variant (one aminoglycoside-related). In addition, other genetic screenings, employed in selected probands according to clinical presentation and presumptive inheritance patterns, identified causative variants in 2.4%. Ear malformations and auditory neuropathy were diagnosed in 10.8% and 3.5% of probands, respectively. In 3.8% of prelingual/perilingual cases, Waardenburg syndrome was clinically diagnosed, and in 71.4%, these diagnoses were confirmed with pathogenic variants revealed; seven out of them were novel, including one CNV. All these genetic screening strategies revealed causative variants in 16.2% of the cases. Based on causative variants in the molecular diagnosis and genealogy analyses, a probable genetic etiology was found in ~ 50% of the cases. The present study highlights the relevance of GJB2/GJB6 as a cause of hearing loss in all Brazilian regions and the importance of screening unselected samples for estimating frequencies. Moreover, when a comprehensive screening is not available, molecular diagnosis can be enhanced by selecting probands for specific screenings.

Propedia: a database for protein-peptide identification based on a hybrid clustering algorithm.

BACKGROUND: Protein-peptide interactions play a fundamental role in a wide variety of biological processes, such as cell signaling, regulatory networks, immune responses, and enzyme inhibition. Peptides are characterized by low toxicity and small interface areas; therefore, they are good targets for therapeutic strategies, rational drug planning and protein inhibition. Approximately 10% of the ethical pharmaceutical market is protein/peptide-based. Furthermore, it is estimated that 40% of protein interactions are mediated by peptides. Despite the fast increase in the volume of biological data, particularly on sequences and structures, there remains a lack of broad and comprehensive protein-peptide databases and tools that allow the retrieval, characterization and understanding of protein-peptide recognition and consequently support peptide design. RESULTS: We introduce Propedia, a comprehensive and up-to-date database with a web interface that permits clustering, searching and visualizing of protein-peptide complexes according to varied criteria. Propedia comprises over 19,000 high-resolution structures from the Protein Data Bank including structural and sequence information from protein-peptide complexes. The main advantage of Propedia over other peptide databases is that it allows a more comprehensive analysis of similarity and redundancy. It was constructed based on a hybrid clustering algorithm that compares and groups peptides by sequences, interface structures and binding sites. Propedia is available through a graphical, user-friendly and functional interface where users can retrieve, and analyze complexes and download each search data set. We performed case studies and verified that the utility of Propedia scores to rank promissing interacting peptides. In a study involving predicting peptides to inhibit SARS-CoV-2 main protease, we showed that Propedia scores related to similarity between different peptide complexes with SARS-CoV-2 main protease are in agreement with molecular dynamics free energy calculation. CONCLUSIONS: Propedia is a database and tool to support structure-based rational design of peptides for special purposes. Protein-peptide interactions can be useful to predict, classifying and scoring complexes or for designing new molecules as well. Propedia is up-to-date as a ready-to-use webserver with a friendly and resourceful interface and is available at: https://bioinfo.dcc.ufmg.br/propedia.

From In-Person to the Online World: Insights Into Organizing Events in Bioinformatics.

Bioinformatics is a fast-evolving research field, requiring effective educational initiatives to bring computational knowledge to Life Sciences. Since 2017, an organizing committee composed of graduate students and postdoctoral researchers from the Universidade Federal de Minas Gerais (Brazil) promotes a week-long event named Summer Course in Bioinformatics (CVBioinfo). This event aims to diffuse bioinformatic principles, news, and methods mainly focused on audiences of undergraduate students. Furthermore, as the advent of the COVID-19 global pandemic has precluded in-person events, we offered the event in online mode, using free video transmission platforms. Herein, we present and discuss the insights obtained from promoting the Online Workshop in Bioinformatics (WOB) organized in November 2020, comparing it to our experience in previous in-person editions of the same event.

VTR: A Web Tool for Identifying Analogous Contacts on Protein Structures and Their Complexes.

Evolutionarily related proteins can present similar structures but very dissimilar sequences. Hence, understanding the role of the inter-residues contacts for the protein structure has been the target of many studies. Contacts comprise non-covalent interactions, which are essential to stabilize macromolecular structures such as proteins. Here we show VTR, a new method for the detection of analogous contacts in protein pairs. The VTR web tool performs structural alignment between proteins and detects interactions that occur in similar regions. To evaluate our tool, we proposed three case studies: we 1) compared vertebrate myoglobin and truncated invertebrate hemoglobin; 2) analyzed interactions between the spike protein RBD of SARS-CoV-2 and the cell receptor ACE2; and 3) compared a glucose-tolerant and a non-tolerant ß-glucosidase enzyme used for biofuel production. The case studies demonstrate the potential of VTR for the understanding of functional similarities between distantly sequence-related proteins, as well as the exploration of important drug targets and rational design of enzymes for industrial applications. We envision VTR as a promising tool for understanding differences and similarities between homologous proteins with similar 3D structures but different sequences. VTR is available at http://bioinfo.dcc.ufmg.br/vtr.

Conformational flexibility correlates with glucose tolerance for point mutations in ß-glucosidases - a computational study.

ß-glucosidases (EC 3.2.1.21) have been described as essential to second-generation biofuel production. They act in the last step of the lignocellulosic saccharification, cleaving the ß - 1,4 glycosidic bonds in cellobiose to produce two molecules of glucose. However, ß-glucosidases have been described as strongly inhibited by glucose, causing an increment of cellobiose concentration. Also, cellobiose is an inhibitor of other enzymes used in this process, such as exoglucanases and endoglucanases. Hence, the engineering of thermostable and glucose-tolerant ß-glucosidases has been targeted by many studies. In this study, we performed high sampling accelerated molecular dynamics for a wild glucose-tolerant GH1 ß-glucosidase (Bgl1A), a wild non-tolerant (Bgl1B), and a set of glucose-tolerant Bgl1B's mutants: V302F, N301Q/V302F, F172I, V227M, G246S, T299S, and H228T. Our results suggest that point mutations promissory to induce glucose tolerance trend to enhance the mobility of the flexible loops around the active site. Mutations affected B and C loops regions, and an αß-hairpin motif between them. Conformational clusters and free energy landscape profiles suggest that the mobility acquired by mutants allows a higher closure of the substrate channel. This closure is compatible with a higher impedance for glucose entrance and stimulus of its withdrawal. Based on mutants' structural analyses, we inferred that both the direct stereochemical effect on the glucose path and the changes in the mobility affect glucose tolerance. We hope these results be useful for the rational design of glucose-tolerant and industrially promising enzymes.Communicated by Ramaswamy H. Sarma.

Glutantßase: a database for improving the rational design of glucose-tolerant ß-glucosidases.

Β-glucosidases are key enzymes used in second-generation biofuel production. They act in the last step of the lignocellulose saccharification, converting cellobiose in glucose. However, most of the ß-glucosidases are inhibited by high glucose concentrations, which turns it a limiting step for industrial production. Thus, ß-glucosidases have been targeted by several studies aiming to understand the mechanism of glucose tolerance, pH and thermal resistance for constructing more efficient enzymes. In this paper, we present a database of ß-glucosidase structures, called Glutantßase. Our database includes 3842 GH1 ß-glucosidase sequences collected from UniProt. We modeled the sequences by comparison and predicted important features in the 3D-structure of each enzyme. Glutantßase provides information about catalytic and conserved amino acids, residues of the coevolution network, protein secondary structure, and residues located in the channel that guides to the active site. We also analyzed the impact of beneficial mutations reported in the literature, predicted in analogous positions, for similar enzymes. We suggested these mutations based on six previously described mutants that showed high catalytic activity, glucose tolerance, or thermostability (A404V, E96K, H184F, H228T, L441F, and V174C). Then, we used molecular docking to verify the impact of the suggested mutations in the affinity of protein and ligands (substrate and product). Our results suggest that only mutations based on the H228T mutant can reduce the affinity for glucose (product) and increase affinity for cellobiose (substrate), which indicates an increment in the resistance to product inhibition and agrees with computational and experimental results previously reported in the literature. More resistant ß-glucosidases are essential to saccharification in industrial applications. However, thermostable and glucose-tolerant ß-glucosidases are rare, and their glucose tolerance mechanisms appear to be related to multiple and complex factors. We gather here, a set of information, and made predictions aiming to provide a tool for supporting the rational design of more efficient ß-glucosidases. We hope that Glutantßase can help improve second-generation biofuel production. Glutantßase is available at http://bioinfo.dcc.ufmg.br/glutantbase .

Proteus: An algorithm for proposing stabilizing mutation pairs based on interactions observed in known protein 3D structures.

BACKGROUND: Protein engineering has many applications for industry, such as the development of new drugs, vaccines, treatment therapies, food, and biofuel production. A common way to engineer a protein is to perform mutations in functionally essential residues to optimize their function. However, the discovery of beneficial mutations for proteins is a complex task, with a time-consuming and high cost for experimental validation. Hence, computational approaches have been used to propose new insights for experiments narrowing the search space and reducing the costs. RESULTS: In this study, we developed Proteus (an acronym for Protein Engineering Supporter), a new algorithm for proposing mutation pairs in a target 3D structure. These suggestions are based on contacts observed in other known structures from Protein Data Bank (PDB). Proteus' basic assumption is that if a non-interacting pair of amino acid residues in the target structure is exchanged to an interacting pair, this could enhance protein stability. This trade is only allowed if the main-chain conformation of the residues involved in the contact is conserved. Furthermore, no steric impediment is expected between the proposed mutations and the surrounding protein atoms. To evaluate Proteus, we performed two case studies with proteins of industrial interests. In the first case study, we evaluated if the mutations suggested by Proteus for four protein structures enhance the number of inter-residue contacts. Our results suggest that most mutations proposed by Proteus increase the number of interactions into the protein. In the second case study, we used Proteus to suggest mutations for a lysozyme protein. Then, we compared Proteus' outcomes to mutations with available experimental evidence reported in the ProTherm database. Four mutations, in which our results agree with the experimental data, were found. This could be initial evidence that changes in the side-chain of some residues do not cause disturbances that harm protein structure stability. CONCLUSION: We believe that Proteus could be used combined with other methods to give new insights into the rational development of engineered proteins. Proteus user-friendly web-based tool is available at < http://proteus.dcc.ufmg.br >.

Molecular Dynamics Gives New Insights into the Glucose Tolerance and Inhibition Mechanisms on ß-Glucosidases.

ß-Glucosidases are enzymes with high importance for many industrial processes, catalyzing the last and limiting step of the conversion of lignocellulosic material into fermentable sugars for biofuel production. However, ß-glucosidases are inhibited by high concentrations of the product (glucose), which limits the biofuel production on an industrial scale. For this reason, the structural mechanisms of tolerance to product inhibition have been the target of several studies. In this study, we performed in silico experiments, such as molecular dynamics (MD) simulations, free energy landscape (FEL) estimate, Poisson-Boltzmann surface area (PBSA), and grid inhomogeneous solvation theory (GIST) seeking a better understanding of the glucose tolerance and inhibition mechanisms of a representative GH1 ß-glucosidase and a GH3 one. Our results suggest that the hydrophobic residues Y180, W350, and F349, as well the polar one D238 act in a mechanism for glucose releasing, herein called "slingshot mechanism", dependent also on an allosteric channel (AC). In addition, water activity modulation and the protein loop motions suggest that GH1 ß-Glucosidases present an active site more adapted to glucose withdrawal than GH3, in consonance with the GH1s lower product inhibition. The results presented here provide directions on the understanding of the molecular mechanisms governing inhibition and tolerance to the product in ß-glucosidases and can be useful for the rational design of optimized enzymes for industrial interests.

Introducing Programming Skills for Life Science Students.

The advent of the high-throughput next-generation sequencing produced a large number of biological data. Knowledge discovery from the huge amount of available biological data requires researchers to develop solid skills in biology and computer science. As the majority of the Bioinformatics professionals are either computer science or life sciences graduates, to teach biology skills to computer science students and computational skills to life science students has become usual. In this article, we reported the experience of teaching programming for life science students. Our strategy is composed by explaining basic concepts of algorithms, abstraction of biological problems, and script programming using Python language. Based on the student's answers to an assessment questionnaire, we conclude that the course achieved positive results. They reported an improvement in their skills in programming and bioinformatics. Furthermore, the students approved the didactic adopted in the classes and evaluation methods (programming exercises and final presentation). This article is useful for other professors who want to implement an initial bioinformatics training for undergraduate or graduate students in life sciences. We believe that the strategies here demonstrated could be reproduced, which could help in the formation of a new generation of bioinformaticians with hybrid abilities in computation and biology. © 2019 International Union of Biochemistry and Molecular Biology, 47(3):288-295, 2019.

A Computational Method to Propose Mutations in Enzymes Based on Structural Signature Variation (SSV).

With the use of genetic engineering, modified and sometimes more efficient enzymes can be created for different purposes, including industrial applications. However, building modified enzymes depends on several in vitro experiments, which may result in the process being expensive and time-consuming. Therefore, computational approaches could reduce costs and accelerate the discovery of new technological products. In this study, we present a method, called structural signature variation (SSV), to propose mutations for improving enzymes' activity. SSV uses the structural signature variation between target enzymes and template enzymes (obtained from the literature) to determine if randomly suggested mutations may provide some benefit for an enzyme, such as improvement of catalytic activity, half-life, and thermostability, or resistance to inhibition. To evaluate SSV, we carried out a case study that suggested mutations in ß-glucosidases: Essential enzymes used in biofuel production that suffer inhibition by their product. We collected 27 mutations described in the literature, and manually classified them as beneficial or not. SSV was able to classify the mutations with values of 0.89 and 0.92 for precision and specificity, respectively. Then, we used SSV to propose mutations for Bgl1B, a low-performance ß-glucosidase. We detected 15 mutations that could be beneficial. Three of these mutations (H228C, H228T, and H228V) have been related in the literature to the mechanism of glucose tolerance and stimulation in GH1 ß-glucosidase. Hence, SSV was capable of detecting promising mutations, already validated by in vitro experiments, that improved the inhibition resistance of a ß-glucosidase and, consequently, its catalytic activity. SSV might be useful for the engineering of enzymes used in biofuel production or other industrial applications.

Transcriptome analysis of Corynebacterium pseudotuberculosis biovar Equi in two conditions of the environmental stress.

Corynebacterium pseudotuberculosis has been widely studied in an effort to understand its biological evolution. Transcriptomics has revealed possible candidates for virulence and pathogenicity factors of strain 1002 (biovar Ovis). Because C. pseudotuberculosis is classified into two biovars, Ovis and Equi, it was interesting to assess the transcriptional profile of biovar Equi strain 258, the causative agent of ulcerative lymphangitis. The genome of this strain was re-sequenced; the reassembly was completed using optical mapping technology, and the sequence was subsequently re-annotated. Two growth conditions that occur during the host infection process were simulated for the transcriptome: the osmotic and acid medium. Genes that may be associated with the microorganism's resilience under unfavorable conditions were identified through RNAseq, including genes present in pathogenicity islands. The RT-qPCR was performed to confirm the results in biological triplicate for each condition for some genes. The results extend our knowledge of the factors associated with the spread and persistence of C. pseudotuberculosis during the infection process and suggest possible avenues for studies related to the development of vaccines, diagnosis, and therapies that might help minimize damage to agribusinesses.

Draft Genome Sequence of a Virulent Strain of Pasteurella Multocida Isolated From Alpaca.

Pasteurella multocida is one of the most frequently isolated bacteria in acute pneumonia cases, being responsible for high mortality rates in Peruvian young alpacas, with consequent social and economic costs. Here we report the genome sequence of P. multocida strain UNMSM, isolated from the lung of an alpaca diagnosed with pneumonia, in Peru. The genome consists of 2,439,814 base pairs assembled into 82 contigs and 2,252 protein encoding genes, revealing the presence of known virulence-associated genes (ompH, ompA, tonB, tbpA, nanA, nanB, nanH, sodA, sodC, plpB and toxA). Further analysis could provide insights about bacterial pathogenesis and control strategies of this disease in Peruvian alpacas.

Complete Genome Sequence of the Attenuated Corynebacterium pseudotuberculosis Strain T1.

We present here the genome sequence of the attenuated Corynebacterium pseudotuberculosis strain T1. The sequencing was performed with an Ion Torrent Personal Genome Machine platform. The genome is a circular chromosome of 2,337,201 bp, with a G+C content of 52.85% and a total of 2,125 coding sequences (CDSs), 12 rRNAs, 49 tRNAs, and 24 pseudogenes.

Whole-Genome Sequence of Corynebacterium auriscanis Strain CIP 106629 Isolated from a Dog with Bilateral Otitis from the United Kingdom.

In this work, we describe a set of features of Corynebacterium auriscanis CIP 106629 and details of the draft genome sequence and annotation. The genome comprises a 2.5-Mbp-long single circular genome with 1,797 protein-coding genes, 5 rRNA, 50 tRNA, and 403 pseudogenes, with a G+C content of 58.50%.

Draft Genome Sequence of Toxigenic Corynebacterium ulcerans Strain 03-8664 Isolated from a Human Throat.

Corynebacterium ulcerans is an emergent pathogen infecting wild and domesticated animals worldwide that may serve as reservoirs for zoonotic infections. In this study, we present the draft genome of C. ulcerans strain 03-8664. The draft genome has 2,428,683 bp, 2,262 coding sequences, and 12 rRNA genes.