Ciencia e Ingeniería en Alimentos y Biotecnología

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    Identificación de posibles dianas terapéuticas para la Enfermedad de Parkinson mediante la aplicación de métodos in silico
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Ingeniería Bioquímica, 2024-02) Chimbo Gavilanes, Klever Javier; Galarza Galarza, Cristian Fernando
    In the exploration of possible therapeutic targets to treat Parkinson's disease through computational chemistry, drug design using docking tools is employed. This process is based on the analysis of genes such as LRRK2, where the main objective is to identify the most optimal binding sites in terms of energetic stability, considering them as possible ideal locations for protein action. In this context, virtual screening makes it possible to verify whether the complexes formed between the protein and the ligand represent a potential avenue for the investigation of a disease-specific drug. The analysis of several disease databases, such as MalaCards, Harmonizome, KEGG, OMIM, Unitpro, Disgenet, GeneReviews and Orphanet, has allowed the identification of key genes in Parkinson's disease. These genes are of great importance since, among numerous candidates, those with similarities in molecular processes and common dysfunctions were selected. The grouping and categorization of these genes facilitated the creation of a biological network of interactions using Cytoscape, accompanied by a bibliographic investigation of the metabolic pathways and the relationships between them, thanks to this approach, mutations in the LRRK2 gene were identified to then search for possible druggable sites in this molecule, with the aim of forming protein-ligand complexes. Thus, existing drugs or ligands can be analyzed by screening and evaluation of toxicological properties. In this bioinformatics study of therapeutic targets, I point out that the main ligand Losulazine presents a higher affinity of pharmacological interaction with the LRRK2 gene.
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    Evaluación de posibles dianas terapéuticas para el cáncer de colon aplicando Pipeline Bioinformático como base para el diseño de fármacos asistido por computador
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Biotecnología, 2023-09) Jácome Campos, Mario Fabricio; Galarza Galarza, Cristian Fernando
    Colon cancer is a common type of malignant tumor in the gastrointestinal tract, accounting for about 13 percent of all tumors. Its development is influenced by epigenetic changes, genetic and environmental factors. However, current methods for diagnosing and treating this disease are often expensive, making access to treatment difficult for many patients. To identify the genes that are expressed or inhibited in colon cancer, differential expression analysis was performed using R. These genes were contrasted with databases such as: OMIM, Malacards, Harmonizome, and KEGG. The most relevant genes are grouped according to their biochemical alteration, with this information biological interaction networks are created through Cytoscape to identify proteins that are altered within the disease process. For the identification of the targets, the DrugBank database was used, through DoGSiteScorer the drugable sites were identified, virtual screening is performed through MTiopenScreen to find possible ligands that present high binding affinity. The interaction networks obtained from STITCH allow the identification of the drug that is linked to the metabolic pathways to analyze the protein-ligand interactions. The drug etoposide was identified, and its pharmacokinetic and toxicity properties are assessed by bioinformatics predictions using QSAR VEGA and pkCSM models. The toxicity and hepatotoxicity were found to be negative, suggesting that this could be a viable candidate for the development of drugs targeting the SMAD2 and CASP9 genes.
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    Identificación de posibles dianas terapéuticas en Alzheimer utilizando pipeline bioinformático combinado para aplicarlas al diseño de fármacos asistidos por computadora
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Biotecnología, 2023-09) Barriga Sanchez, Luis Leonardo; Galarza Galarza, Cristian Fernando
    Bioinformatics has a potential biotechnological use because it allows the study of genetically complex diseases using different tools. The aim of this project was to analyze transcriptomic data related to Alzheimer's disease (AD) for the identification of potential therapeutic targets and computer-aided drug design. This was done through the application of a multilevel analysis of biological interaction networks, molecular docking, and evaluation of the pharmacokinetic properties of selected drugs. The analyses indicated a total of 507 and 478 genes with high and low expression, respectively, present in brains with different stages of AD. The results of the protein-protein interaction and miRNA-miRNA network analysis identified only one biomarker, hsa-mir-34a-5p, for the diagnosis of AD and asymptomatic AD in cancer patients. Survival analysis revealed that CDK6 and CD44 are potential therapeutic targets for AD. Additionally, the established pipeline also identified CCND1 as another potential therapeutic target. The drug-gene interaction networks reflected four potential drug candidates for repurposing in the treatment of AD: Estradiol, Trichostatin A, Doxorubicin, and Dorsomorphin. Molecular docking demonstrated that Estradiol and Trichostatin A can inhibit the CCND1 protein, while Dorsomorphin induces inhibition of CDK6, because of their free energy of binding is lower than the reference. The evaluation of pharmacokinetic properties indicated that only Trichostatin A can be used for the treatment of AD in humans.
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    Búsqueda de posibles dianas terapéuticas para el cáncer papilar de tiroides (PTC)
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Ingeniería Bioquímica, 2022-09) Lagua Mainato, Christian Orley; Galarza Galarza, Cristian Fernando
    In the search for possible therapeutic targets through computational chemistry for papillary thyroid cancer (PTC), the design of drugs with docking tools is based on the analysis of the BRAF gene, where the best binding sites are mainly identified. Regarding energy stability, therefore, the virtual screening allowed to verify the drugability of said complexes that were created between protein and ligand, this represents a potential avenue of research for the development of an optimal and specific drug for said disease. The analysis within the databases of diseases such as MalaCards, Harmonizome, KEGG, OMIM, Unitpro, Disgenet, GeneReviews and Orphanet allowed to know the main genes that lead the carcinogenesis process in PTC, certain genes presented common dysfunctions so that it was possible to group and categorize them to then create a biological network of interaction with the help of Cytoscape and subsequently the metabolic pathways of these genes and the relationship between them were investigated bibliographically. In this way, the mutations that this target gene presents and the alterations in its metabolic pathway were identified. Finally, the mutations that the BRAF gene suffers were found to subsequently identify possible drugable sites that can create protein-ligand complexes, so that the existing drugs currently they were analyzed by screening and subsequent analysis of toxicological properties. Therefore, this bioinformatic study allowed to determine that the ligands Entrectinib, Bms-833923, Afacifenacin, Floxacrine, Olaparib, Nolpitantium, Aleplasinin present pharmacological potential for the BRAF gene.
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    Estudios bioinformáticos para la identificación de posibles dianas terapéuticas en la enfermedad de la Diabetes Mellitus tipo 2 (T2DM)
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Ingeniería Bioquímica, 2022-03) Guevara Proaño, Luis David; Galarza Galarza, Cristian Fernando
    The search for therapeutic targets for the disease type 2 diabetes mellitus is based on computer-aided drug development through molecular concentration analysis and virtual screening in disease databases. The identification of the study gene requires analysis in different databases such as MalaCards, OMIM, Harmonizome and KEGG to validate the information on the genes involved in the disease. Thus, the genes with the greatest connections are chosen and grouped according to their genetic dysfunction to create biological networks and validated in the DrugBank database. Subsequently, an analysis of the metabolic pathway taken from KEGG that connect the target genes that maintain the identified mutation is performed and the three-dimensional structures are used to evaluate the domains plus drugs. Molecular coupling and screening simulations are then carried out, considering the compounds with the highest affinity for IRS-1, and finally the toxicity of the drugs is analyzed. QSAR models show that Zosuquidar, Rimacalib, Uk432097, Mosapramine, Devazepide and Setipiprant are the safest ligand compounds in toxicity analyses. The present study is based on the identification of the genes most associated with T2DM and the search for possible therapeutic targets through bioinformatics applied to computer-assisted drug design. The results obtained can be used for subsequent research studies to increase the therapeutic spectrum for T2DM or other metabolic degenerations.
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    Identificación de nuevos inhibidores de la enzima acetohidroxiácido sintasa (AHAS) de Candida albicans mediante cribado virtual de fragmentos
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Ingeniería Bioquímica, 2021-09) Robalino Velasco, Amada Margarita; García Solís, Mario Daniel
    The enzyme acetohydroxyacid synthase (EC 2.2.1.6., AHAS), is considered a new therapeutic target for the control of invasive fungal infections (IFIs) due to its crucial activity in the biosynthesis of essential amino acids (BCAAs) in the fungal agents that cause these diseases. The herbicides of the sulfonylurea and triazolopyrimidine families are some of the most promising compounds for the development of an IFIs treatment by the inhibition of AHAS. These project focuses on the identification of possible new inhibitors of the AHAS enzyme in the yeast, Candida albicans, using virtual fragment screening. The parental structures used for virtual screening are the central fragments of the herbicides Chlorimuron ethyl (CE) and Metosulam (MT), which were selected by a structural analysis of its binding mode to AHAS. This analysis yielded the fragments FRAG1 and FRAG2, based on CE, and FRAGMT, based on MT. Fragment screening was performed on the ACFIS2.0 server, a tool that provided approximately 250. The analysis of calculated Gibbs free energy, the ligand -CaAHAS binding mode and ADME properties allowed the best molecules to be identified. Using this method, it was determined that ligands KIN102, KIN97 KIN20, (generated from FRAG1); PAD271, KIN192, PAD181 (generated from FRAG2), PAD281, PAD165 and PAD180 (generated from FRAGMT) present a higher affinity than CE and MT when binding C. albicans AHAS. Also, these ligands exhibited binding modes analogous to their parental herbicides; therefore, the ligands could act as possible inhibitors of AHAS and potentially become drugs for the treatment of IFIs.
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    Estudios bioinformáticos para la identificación de posibles dianas terapéuticas en la enfermedad de Esclerosis Lateral Amiotrófica (ELA)
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Ingeniería Bioquímica, 2021-09) López Pérez, Iván Gabriel; Galarza Galarza, Cristian Fernando
    The identification of new therapeutic targets for ALS disease is based on computer-aided drug design (CADD) by analyzing genes such as VCP and VABP against the Drugs-lib database, allowing the best site of action of proteins to be analyzed by virtual screening for drugability. Databases such as MalaCards, OMIM, Harmonizome and KEGG are analyzed to visualize the relevant disease genes. Elite genes that correlate with each other are chosen and grouped according to their dysfunction. In addition, biological networks are created and validated with the DrugBank database. Next, the metabolic pathway of the genes that follow the SOD1 gene mutations is analyzed and the most druggable domains are identified. Finally, the toxicological properties of the linked drugs are analyzed. The search for drug-interacting therapeutic targets is the aim of the present study. The results obtained through virtual screening allow the identification of drugs that may have effects on the disease, these are: Saquinavir and Astemizole, which are associated with the VCP and VABP genes, respectively. The drug Astemizole has better QSAR properties. The importance of the present study is the identification of the most relevant genes and the search for therapeutic targets in Amyotrophic Lateral Sclerosis. The information obtained could be used as a starting point for research into new drugs to counteract neurodegeneration.
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    Cribado virtual de inhibidores de la enzima Mpro del virus SARS-CoV-2 empleando librerías de compuestos y homología estructural con proteasas de virus patógenos humanos
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Ingeniería Bioquímica, 2021-01) Sánchez Vaca, Andrés Salomón; García Solís, Mario Daniel
    The present research project was carried out to find and develop ligands with inhibitory activity against the Mpro protease of the SARS CoV-2 virus through a virtual screening of recently developed inhibitors against this and those that have been previously tested in human pathogenic viruses. For which, compound libraries such as Protein Data Bank were used, from which 46 molecules with a high binding affinity to Mpro were chosen from a study of structural homology with the proteases of other viruses that attack humans and Covid Box. library that can be accessed from the following domain: https://www.mmv.org/mmv-open/covid-box from where a total of 79 molecules were taken, the selected ligands were presented as inhibitors of Mpro, at starting from the formation of hydrophobic, polar interactions and pi bonds between carbon - carbon, sulfur - carbon and fluorine - carbon atoms. To select the best molecules, a bioinformatic analysis was carried out in software such as Wincoot, Pymol and GOLD - Protein Ligand Docking Software, the latter for docking or molecular docking tests, studied at a conformational level by the arrangement and overlapping of atoms, level of incidence of intermolecular interactions and the possibility of steric shocks of their functional groups, obtaining as a result that the MMV1580167 molecule from Covid Box presents the best inhibitory activity within the virtual screening, while the designed AS7 ligand presents the highest inhibitory activity in the virtual environment where the investigation was carried out.
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    Cribado virtual de inhibidores de la enzima Mpro del virus SARS-CoV-2 empleando librerías de compuestos y homología estructural con proteasas de virus patógenos de animales
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Ingeniería Bioquímica, 2021-01) Ramos Aristimbay, María Lisette; García Solís, Mario Daniel
    The purpose of this study is to perform virtual screening of SARS-CoV-2 virus Mpro enzyme inhibitors using compound libraries and structural homology with animal pathogenic virus proteases. In response to the present pandemic the world is going through, caused by COVID-19, so it is of paramount importance to search for compounds, which prevent the spread of SARS-CoV-2, with which medicines can be made to curb the contagions of this disease. Since the main protease Mpro is responsible for carrying out the proteolytic processes during the replication of the virus, it has been selected as a target for the search for molecules that inhibit its activity, thus preventing the virus from continuing to multiply. For this, a homology analysis was performed that could identify that this protease is preserved in several species of coronavirus that infect animals, such as those that cause murine hepatitis, swine transmissible gastroenteritis, feline peritonitis, and avian infectious bronchitis. Which allowed us to look for compounds used to treat these diseases, and to create a library with the most effective ligands. This was able to determine the druggable sites of the enzyme and perform a molecular coupling (docking), identifying ten inhibitors that best bind to Mpro, including Ritonavir, with which, through subsequent in vitro studies, COVID-19 drugs could be generated, and tested in other coronaviruses with which homology exists.
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    Cribado virtual de inhibidores de la enzima ARN polimerasa ARN-dependiente (RdRp) del virus SARS-CoV-2, empleando librerías de compuestos y homología estructural con ARN polimerasas virales
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Ingeniería Bioquímica, 2021-01) Espín Sánchez, Daysi de Lourdes; García Solís, Mario Daniel
    In late 2019, an unknown human respiratory disease, later designated as COVID-19, emerged in Wuhan-China, caused by a new coronavirus denominated SARS-CoV-2. The exploration of the SARS-CoV-2 genome and the study of its life cycle have made it possible to identify potential pharmacological targets. One of the most promising is the RNA-dependent RNA polymerase enzyme (RdRp), a key component of the viral replication/transcription mechanism. In this context, the goal of this research was to perform the virtual screening of SARS-CoV-2 RdRp inhibitors, to identify the most appropriate according to the properties of their binding affinity to the enzyme. A homology analysis using protein databases determined that 65 viral polymerases share sequence similarities, secondary structure, or both, with that of SARS-CoV-2, while their multiple sequence alignment showed that the RdRp active site is highly conserved across species. Additionally, using GOLD, molecular docking essays were performed with two target sites identified in the enzyme, one corresponding to the active site and the other to a theoretical allosteric site, in which a total of 285 compounds were tested. Thus, the results show that the compounds R7112, 23E and Lopinavir bind to the active site, while Favipiravir, Triparanol and Anagliptin bind to the allosteric site could be potential inhibitors of RdRp and therefore, candidates for the development of drugs to treat COVID-19.