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.

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'/β1', 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.

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 β-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.

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.

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.

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.

Glutantβase: a database for improving the rational design of glucose-tolerant β-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 β-glucosidases are inhibited by high glucose concentrations, which turns it a limiting step for industrial production. Thus, β-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 β-glucosidase structures, called Glutantβase. Our database includes 3842 GH1 β-glucosidase sequences collected from UniProt. We modeled the sequences by comparison and predicted important features in the 3D-structure of each enzyme. Glutantβase 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 β-glucosidases are essential to saccharification in industrial applications. However, thermostable and glucose-tolerant β-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 β-glucosidases. We hope that Glutantβase can help improve second-generation biofuel production. Glutantβase is available at http://bioinfo.dcc.ufmg.br/glutantbase .

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.

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.

The genome anatomy of Corynebacterium pseudotuberculosis VD57 a highly virulent strain causing Caseous lymphadenitis

Corynebacterium pseudotuberculosis strain VD57 (Cp_VD57), a highly virulent, nonmotile, non-sporulating, and a mesophilic bacterium, was isolated from a goat’s granulomatous lesion in the municipality of Juazeiro, Bahia State, Brazil. Here, we describe a set of features of the strain, together with the details of its complete genome sequence and annotation. The genome comprises of a 2.5 Mbp long, single circular genome with 2,101 protein-coding genes, 12 rRNA, 49 tRNA and 47 pseudogenes and a G + C content of 52.85 %. Genetic variation was detected in Cp_VD57 using C. pseudotuberculosis strain 1002 as reference, wherein small genomic insertions and deletions were identified. The comparative analysis of the genome sequence provides means to better understand the host pathogen interactions of this strain and can also help us to understand the molecular and genetic basis of virulence of this bacterium.

CMRegNet-An interspecies reference database for corynebacterial and mycobacterial regulatory networks

Background

Organisms utilize a multitude of mechanisms for responding to changing environmental conditions, maintaining their functional homeostasis and to overcome stress situations. One of the most important mechanisms is transcriptional gene regulation. In-depth study of the transcriptional gene regulatory network can lead to various practical applications, creating a greater understanding of how organisms control their cellular behavior.

Description

In this work, we present a new database, CMRegNet for the gene regulatory networks of Corynebacterium glutamicum ATCC 13032 and Mycobacterium tuberculosis H37Rv. We furthermore transferred the known networks of these model organisms to 18 other non-model but phylogenetically close species (target organisms) of the CMNR group. In comparison to other network transfers, for the first time we utilized two model organisms resulting into a more diverse and complete network of the target organisms.

Conclusion

CMRegNet provides easy access to a total of 3,103 known regulations in C. glutamicum ATCC 13032 and M. tuberculosis H37Rv and to 38,940 evolutionary conserved interactions for 18 non-model species of the CMNR group. This makes CMRegNet to date the most comprehensive database of regulatory interactions of CMNR bacteria. The content of CMRegNet is publicly available online via a web interface found at http://lgcm.icb.ufmg.br/cmregnet.