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PROSPECTION OF PROTEIN CANDIDATES FOR DRUG AND VACCINE DEVELOPMENT AGAINST STREPTOCOCCUS PNEUMONIAE INFECTIONS

PROSPECTION OF PROTEIN CANDIDATES FOR DRUG AND VACCINE DEVELOPMENT AGAINST STREPTOCOCCUS PNEUMONIAE INFECTIONS

Igor Oliveira, Sarah Souza and Bernardo Santos

Streptococcus pneumoniae is a Gram-positive bacterium and the etiological agent of many diseases related to the respiratory tract (such as pneumonia), meningitis and middle ear infections. The increase in hospitalization rates resulting from pneumococcal infections and the growing reports on antibiotic-resistant pneumococcal strains lead to the development of new prophylactic and treatment methods. In this work, the subtractive genomics and reverse vaccinology approaches were considered to screen protein targets for the development of drug and vaccine against S. pneumoniae infections. The sequences of 63 complete genomes were retrieved from the NCBI database and processed for the identification of orthologous proteins encoded by all strains using OrthoFinder. The core proteome found to be not homologous to Homo sapiens comprised 287 proteins, of which 112 were predicted to be exported by S. pneumoniae and 160 were classified as cytoplasmic proteins by SurfG. As the exported bacterial proteins most likely interact with the host’s immune system, we used Vaxign to evaluate the affinity of these proteins for the histocompatibility complex (MHC). This analysis revealed 6 immunogenic proteins with great potential use in subunit vaccine development. In addition, we obtained good quality three-dimensional structure models for 33 cytoplasmic proteins using the MHOLline workflow. Among the modeled proteins, 4 drug target candidates were found using the PBIT pipeline. This selection was made according to the involvement of protein in virulence and essentiality in bacteria, and the absence of homology with proteins present in the human intestinal microbiota. These candidates will be considered for molecular docking with a library of 5,000 natural plant compounds using AutoDock Vina. The present work brings up new perspectives to control the emerging and worldwide distributed S. pneumoniae infections in human.

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PREDICTION OF PROTEIN CANDIDATES FOR DRUG AND VACCINE DEVELOPMENT AGAINST PSEUDOMONAS AERUGINOSA INFECTIONS

PREDICTION OF PROTEIN CANDIDATES FOR DRUG AND VACCINE DEVELOPMENT AGAINST PSEUDOMONAS AERUGINOSA INFECTIONS

Sarah Souza, Igor Oliveira and Letícia Carvalho

Pseudomonas aeruginosa is a Gram-negative bacterium widely distributed in the environment. As an opportunistic pathogen, P. aeruginosa is associated with high morbidity and mortality in immunocompromised patients worldwide, especially those already affected by cystic fibrosis. Its extensive resistance to antimicrobials and the lack of an effective vaccine leads to an urgency in searching for new therapeutic options. The present work aimed to use the subtractive genomics and
reverse vaccinology approaches for the screening of protein targets to develop drug and vaccine against P. aeruginosa. The sequences of 174 complete genomes were retrieved from the NCBI database and processed for the identification of orthologous proteins encoded by all strains using OrthoFinder. The core proteome found to be not homologous to the human host comprised 695 proteins, of which 385 were predicted as cytoplasmic proteins and 310 as proteins exported by P. aeruginosa according to SurfG. We were able to obtain good quality three -dimensional structure models for 71 cytoplasmic proteins using the MHOLline workflow. Among the modeled proteins, 5 best drug target candidates were found using the PBIT pipeline. This selection was made according to the
involvement of protein in virulence and essentiality in bacteria, besides the absence of homology with proteins produced by the intestinal microbiota in human. Using Vaxign, 44 candidate antigens were found among the proteins exported by P. aeruginosa, of which 7 presented greater potential for the development of subunit vaccines. Next, the drug target candidates will be used for molecular docking
with a library of 5,000 natural plant compounds using AutoDock Vina. Also, immunoinformatic approaches will be considered to select the best antigen epitopes for the formulation of a chimeric subunit vaccine. This work brings up

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A NEW APPROACH TO RESEARCH THERAPEUTIC TARGETS FOR TRIPLE NEGATIVE BREAST CANCER: INVESTIGATION OF THE ASSOCIATION BETWEEN TUMOR GENOME AMPLIFIED REGIONS AND COMPETING ENDOGENOUS RNAS NETWORKS

A NEW APPROACH TO RESEARCH THERAPEUTIC TARGETS FOR TRIPLE NEGATIVE BREAST CANCER: INVESTIGATION OF THE ASSOCIATION BETWEEN TUMOR GENOME AMPLIFIED REGIONS AND COMPETING ENDOGENOUS RNAS NETWORKS

Igor S. Giner, Leandro E. Garcia, Bruna M. Sugita, Luciane R. Cavalli, Enilze Ribeiro, Jaqueline C. Oliveira and Daniela F. Gradia

Breast cancer (BC) is the second most common type of cancer in women in Brazil. By immunohistochemistry, BC is divided into four subtypes, among which the Triple Negative (TN) is the most aggressive. This subtype has no specific diagnosis or therapy. Thus, the research of therapeutic targets and biomarkers for TN BC is encouraged. It is known that competing endogenous RNAs (ceRNAs) networks are RNA-miRNA-RNA interaction networks that result in gene expression modification. Copy number alterations (CNAs) are gain or loss changes of chromosomal segments. We hypothesize that genome amplified regions in TN tumors may stimulate the formation of ceRNAs networks; this association’s investigation may be an alternative strategy for researching TN BC biomarkers and therapeutic targets. We aimed to identify potential ceRNAs transcribed in TN tumors genome amplified regions and explore this mechanism’s potential in the TN BC carcinogenesis regulation. A previous study realized by the research group identified CNAs in TN (n = 29) and Non-Triple Negative (n = 16) breast tumors using array-CGH. With this data, we performed a computational prediction of ceRNAs networks between transcripts from genome amplified regions in TN tumors and transcripts from the total transcriptome of Basal tumors (a molecular BC subtype, considered correspondent to TN in this study) – using the GDCRNATools package in the R software. We found a possible network of 8 pairs of overexpressed ceRNAs (logFC> 0.58, p-value ≤ 0.01, and positive correlation). Present in this network, TMPO-AS1 is a lncRNA with oncogenic functions already validated. The mir-302 and mir-520 miRNA families, described as tumor suppressors in the literature, are the most frequent in our network. The ceRNAs network around TMPO-AS1 and the most frequent miRNA families present themselves as potential candidates for specific TN BC therapy – showing that our analysis strategy can be an alternative to traditional research methodologies.

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OPTIMIZATION OF SmTGR INHIBITORS USING A FRAGMENT-BASED DRUG DESIGN (FBDD) APPROACH

OPTIMIZATION OF SmTGR INHIBITORS USING A FRAGMENT-BASED DRUG DESIGN (FBDD) APPROACH

Rocío Riveros Maidana, Lauro Ribeiro de Souza Neto, Nicholas Furnham, Raymond J. Owens, José Brandão Neto, Frank von Delft, Ana Carolina Ramos Guimarães and Floriano Paes Silva Junior

Schistosomiasis is a neglected tropical disease caused by Schistosoma spp. Praziquantel (PZQ) is the unique drug used for the treatment of the disease. Despite the success of the treatment, the concern about the emergence of strains less sensitive to PZQ, and the possibility of evolution of drug resistance are growing. Thioredoxin glutathione reductase of Schistosoma mansoni (SmTGR) is a validated drug target that plays a crucial role in the redox homeostasis of the parasite inside the human host. The Fragment-based Drug Design (FBDD) strategy consists of screening low molecular weight compounds against macromolecular targets (usually proteins) of clinical relevance. These small molecular fragments can bind at one or more sites on the target and act as starting points for the development of lead compounds. An FBDD screening campaign was performed obtaining 32 fragments that bind to 8 sites located at the SmTGR surface. From those sites, one secondary site was selected and fragments that bind to that site were optimized using a fragment-growing approach. The optimization was performed using the program AutoGrow 3.0. A total of 42 new ligands were generated from the initial fragments.

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DERIVATED OF DIBENZOYLMETHANE: IN SILICO ANALYSIS FOR DRUG DEVELOPMENT

DERIVATED OF DIBENZOYLMETHANE: IN SILICO ANALYSIS FOR DRUG DEVELOPMENT

Marcela Hauck, Mariá Braga, Jefferson Baêta, Amanda Gonçalves, Anésia Santos and Marisa Dia

In silico analysis is the beginning of many researches and it can predict which way follow it’s possible to evaluate the promisor compounds and the pathways of action. Most drugs for the treatment of cancer have limited efficacy and tumor recurrence rapidly follows. Therefore, the search for new molecules is necessary for the development of more effective clinical therapies. The family of beta-diketones, including dibenzoylmethane, is known by the large bioactivity, such as antitumor, antibacterial, and anti-inflammatory activities. Based on this, the aim of this study was evaluating in silico the derivate of dibenzoylmethane (ABB), one beta-diketone, as pharmacokinects, physicochemical and toxicity by ADMET and bioactivity score methods to a drug development. Using the web platforms Molinspiration Cheminformatics to draw the molecule and generate the SMILES code to run the bioactivity score and the preADMET and pkCSM to check the pharmacokinetics, physicochemical and toxicity, was possible to check all the parameters and use the Lipinski’s rule of five (Ro5) to validated the drug design. According to Ro5 the physicochemical parameters of this molecule was adequous to continue the drug-likeness. The evaluation of inhibitory effects of cytochrome p450 isoforms (CYP), known by monooxygenase family of enzymes, indicates that ABB isn’t an inhibitor of CYP1A2 and CYP2D6, but it inhibits the CYP2C1, CYP2C9 and CYP3A4. Those results show that ABB should be metabolized normally. In complement the test of mutagenicity of ABB showed negative for mutagenicity and carcinogenicity. The risk of hERG I inhibition was negative while for hERG II it was positive, indicating a low cardiotoxicity. In Molinspiration bioactivity score all the points checked were between -5 and 0 that shows a moderate bioactivity. These results showed that the ABB compound has great potencial to provide us with a potent drug in medical clinic and in vivo tests should be performed.

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CCOMPUTO – COLLABORATIVE COMPUTATIONAL TOOLS FOR DUTCH MOLECULAR TUMOR BOARDS

CCOMPUTO – COLLABORATIVE COMPUTATIONAL TOOLS FOR DUTCH MOLECULAR TUMOR BOARDS

Juliana F Vilacha M R Santos, Rick Oerlemanns and Matthew R. Groves

Advances in genomics techniques allowed the analysis of big sets of cancer patients what lead to the identification of mutations, showing a pattern shared by cancer patients. These mutations are often responsible for drive signaling pathways essential for malignant cells’ survival. Within the large number of patients who benefit from these genomics techniques, individuals harboring Non-Small Cell Lung Cancer (NSCLC) are the most favored by, due to the presence of mutations on enzymes such as the Epidermal Growth Factor Receptor, Anaplastic Lymphoma Kinase, Kirsten Rat Sarcoma GTPase or the BRAF serve as a biomarker for treatment regiments with kinase inhibitors.
The success of kinase inhibitors is linked to the presence or absence of a specific subset of mutations widely described in the literature. However, medical times are often challenged with mutation of unknown significance and/or impact on drug binding. Seeking to provide fast identification of mutational impact in the available treatments, Dutch University Medical Centers assembled Molecular Tumor Boards (MTB) where challenging patients flaunting novel mutations can be analyzed under the lights of a personalized medicine approach. Besides involving medical doctors and geneticists, the MTB from the University Medical Center of Groningen (UMCG) also relies on the use of computational biology for rapid assessment of such mutational landscape.
In this work, we present how classical tools from computational biology are applied daily in the context of drug screening in the presence of novel mutations and the impact this approach has on patient survival.

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Virtual screening suggest potential affinity between Corynebacterium ulcerans essential proteins and inedited synthetic derivatives of tetraisoquinoline alkaloids

Virtual screening suggest potential affinity between Corynebacterium ulcerans essential proteins and inedited synthetic derivatives of tetraisoquinoline alkaloids

Luis Felipe de Morais Melo, Gustavo Andrew Mahon Mendes Pereira, Luis Cezar Rodrigues and Edson Luiz Folador

Corynebacterium ulcerans is aerobic, gram-positive bacteria that causes diphtheria, by infecting several hosts have a larger reservoir than the other causative agents. Considered reemergent, isolated cases due C. ulcerans diphtheria have increased even in immunized nations, highlighting the importance to seek new drugs and treatments. In previous work, we applied the interolog mapping method to generate the interactome, identifying the conserved hub proteins for 10 C. ulcerans strains, whose Database of Essential Genes (DEG) validation, COG classification and GO analysis, were confirmed the essentiality of 457 hub proteins, 351 having less than 30% identity against the host, being potential pharmacological targets. Here, we submitted the 351 non-host homologous hub proteins to Phyre2, resulting in 119 viable three-dimensional structure (more than 90% of the amino acids in Ramachandran plot favorable regions). Submitted to fpocket, 145 pockets with drugability score >= 0.5 were identified, which after being subjected to molecular docking in Autodock Vina against a library containing 42 inedited synthetic derivatives of tetraisoquinolinic alkaloid molecules resulted in 6,090 complex, 2,864 getting energy <= -6, considered relevant. The UvrABC system protein B, essential in the DNA repair process, formed the best complex with molecule23 reaching binding energy of -9.9, performing favorable interactions precisely with the protein residues binding to DNA, such as: hydrogen bonds (ARG379, LYS380 and SER166), Van der Waals interactions (ARG146, ASP376, ASP396, GLU122, GLU32, LYS134, MET372 and TYR116), pi-electron interactions (TYR119, TYR119 and TYR169), among others. Additionally, the molecule41 complexed with Bifunctional RNase H/acid phosphatase protein (-9.6); the molecule34 competes for the ADP binding site on Bifunctional protein (-9.5); the molecule20 competes for the uridina-difosfato-n-acetilglicosanima binding site on UDP-N-acetylglucosamine 1-carboxyvinyltransferase protein (-9.4). The results make it possible to understand the molecular binding mechanisms, enabling the rational optimization of molecules, reducing costs associated with synthesis and in-vitro or in-vivo tests.

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Interactome of Corynebacterium ulcerans toxigenic strains reveals hub proteins being potential drug targets

Interactome of Corynebacterium ulcerans toxigenic strains reveals hub proteins being potential drug targets

Gustavo Andrew Mahon Mendes Pereira, Luis Felipe de Morais Melo, Luis Carlos Guimarães, Vasco Ariston de Carvalho Azevedo and Edson Luiz Folador

Corynebacterium ulcerans has toxigenic strains that produce the diphtheria toxin similar to C. diphtheriae. Among the bacteria causing diphtheria, C. ulcerans has a greater mutagenic potential because it has both humans and animals as reservoirs. Being reemergent, there was an increase in cases even in immunized countries, requiring new approaches for new drug targets selection. Applying the interolog mapping method we map interactions with confidence score >= 700 from 5090 STRING database organisms, generating the protein-protein interaction network and identifying 22,347 interactions conserved in 10 toxigenic C. ulcerans strains. Selecting by highest degree interaction, 457 hub proteins were identified, 421 (92.12%) of them have the essentiality validated by homology in the Database of Essential Genes (DEG) and 36 (7.88%) were considered essential after functional and enrichment analysis. The Clusters of Orthologous Groups (COG) analysis highlighted the more representative groups: “Translation, ribosomal structure and biogenesis (J)” (74%), “Amino acid transport and metabolism (E)” (13.96%), “Replication, recombination and repair (L)” (8.21%) and only 5.34% “Function Unknown (S)” composed mostly of hypothetical proteins. The Gene Ontology (GO) enrichment analysis identified the most significant biological processes (p>0.95): “Cell redox homeostasis”, “DNA recombination”, “Cell wall organization”, “SOS response”, among others. Aiming to select targets do not favoring toxicity, we identified 351 (76.8%) non-host homologous hub proteins, some having higher degree interaction are: “Inosine 5-monophosphate dehydrogenase” (195, CulFRC58_1614), “Protein RecA” (182, recA), “DNA-directed RNA polymerase subunit alpha” (165, rpoA), “2-oxoglutarate dehydrogenase E1 component” (156, odhA) and “DNA-directed RNA polymerase subunit beta” (154, rpoB). All non-host homologous hub proteins possess potential for drug targets and are useful to evaluate the affinity of candidate compounds, experimentally or, similarly that our group performed in-silico affinity test against unpublished synthetic derivatives of tetraisoquinoline alkaloids.