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2. Comparative Study of Docking Tools for Evaluation of Potential Copper Metallodrugs and Their Interaction with TMPRSS2.

Author

Vázquez-Rodríguez, Sergio, Ramírez-Contreras, Diego, Noriega, Lisset, García-García, Amalia, Sánchez-Gaytán, Brenda L., Meléndez, Francisco J., Filgueira de Azevedo Jr., Walter, Castro, María Eugenia, and González-Vergara, Enrique

Subjects
MOLECULAR structure, AMINO acid residues, AMINO acids, VIRUS diseases, COVID-19 treatment
Abstract

COVID-19 has caused over seven million deaths globally due to its high transmission rate. The virus responsible for the disease requires a transmembrane protease serine type II (TMPRSS2-7MEQ) to infiltrate host cells and has been linked to several cancers, particularly prostate cancer. To investigate COVID-19 potential therapies, a series of Casiopeina-like copper complexes containing 1,10-Phenanthroline and amino acids were investigated as TMPRSS2 inhibitors. The molecular structures of twelve Phenanthroline copper complexes were calculated, and their global reactivity indices were analyzed using DFT and conceptual DFT methods. Three molecular docking algorithms were employed to identify the most effective inhibitors by examining their interactions with amino acid residues in the target protein's catalytic activity triad (Asp345, His296, and Ser441). All complexes are docked above the catalytic site, blocking the interaction with substrates. The Phenanthroline complexes showed better interactions than the Bipyridine complexes, likely due to increased hydrophobic contacts. Analogs' cationic nature and amino acids' basic side chains bring them near the active site by interacting with Asp435. The top complexes in this study contain Ornithine, Lysine, and Arginine, making them promising alternatives for researching new drugs for COVID-19 and cancers like prostate cancer. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Machine learning for drug science

Author

de Azevedo Jr. Walter F.

Subjects
Statistics and Probability, Urban Studies, Philosophy, Economics and Econometrics, Visual Arts and Performing Arts, Museology, Architecture, General Engineering, Conservation, Statistics, Probability and Uncertainty, Molecular Biology, Applied Microbiology and Biotechnology, Biotechnology
Published
2023
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10. CRYSTALLOGRAPHIC STUDIES OF FISH HEMOGLOBINS

Author

Plínio DELATORRE, Márcia DELAMANO, Valmir FADEL, Rubens T. HONDA, André Luís S. SMARRA, Fernanda CANDURI, Johnny Rizzieri OLIVIERI, Gustavo Orlando BONILLA-RODRIGUEZ, and Walter Filgueira de AZEVEDO Jr

Subjects
Chemistry, QD1-999
Abstract

The present work reports our succesfull experience concerning crystallization of four fish hemoglobins from three Brazilian species of Teleosts: Liposarcus anisitsi, Brycon cephalus and Piaractus mesopotamicus. The data shown here is part of a systematic functional and structural study of fish hemoglobins with the aim of better understanding the outstanding range of functional and structural properties exhibited by these proteins. We also present a reduced sparse-matrix method for crystallization of fish hemoglobins, which can reduce the amount of hemoglobin initially used in the crystallization experiments.

Published
2018
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11. Salivary glands adenoid cystic carcinoma: a molecular profile update and potential implications.

Author

Jardim da Silva, Fernanda, Carvalho de Azevedo Jr., Juscelino, Lima Ralph, Ana Carolina, Viana Pinheiro, João de Jesus, Morais Freitas, Vanessa, and Queiroz Calcagno, Danielle

Subjects
ADENOID cystic carcinoma, SALIVARY glands, NOTCH signaling pathway, PROTEIN-tyrosine kinase inhibitors, IMMUNOTHERAPY, C-kit protein, DRUG target
Abstract

Adenoid cystic carcinoma (ACC) is an aggressive tumor with a high propensity for distant metastasis and perineural invasion. This tumor is more commonly found in regions of the head and neck, mainly the salivary glands. In general, the primary treatment modality for ACC is surgical resection and, in some cases, postoperative radiotherapy. However, no effective systemic treatment is available for patients with advanced disease. Furthermore, this tumor type is characterized by recurrent molecular alterations, especially rearrangements involving the MYB, MYBL1, and NFIB genes. In addition, they also reported copy number alterations (CNAs) that impact genes. One of them is C-KIT, mutations that affect signaling pathways such as NOTCH, PI3KCA, and PTEN, as well as alterations in chromatin remodeling genes. The identification of new molecular targets enables the development of specific therapies. Despite ongoing investigations into immunotherapy, tyrosine kinase inhibitors, and anti-angiogenics, no systemic therapy is approved by the FDA for ACC. In this review, we report the genetic and cytogenetic findings on head and neck ACC, highlighting possible targets for therapeutic interventions. [ABSTRACT FROM AUTHOR]

Published
2023
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12. Morphological changes in the liver and kidneys of rats subjected to terminal ileum exclusion during obstructive cholestasis

Author

Evandro Luis de Oliveira Costa, Geraldo Magela de Azevedo Jr, and Andy Petroianu

Subjects
Liver Cirrhosis, Cholestasis, Ileum, Liver, Kidney, Histology, Rats, Surgery, RD1-811
Abstract

PURPOSE: To investigate the effects of ileal exclusion on hepatic and renal morphology in extra-hepatic cholestasis. METHODS: Twenty four rats were distributed into three groups. Group 1 (control) underwent laparotomy and laparorrhaphy. The animals in groups 2 and 3 underwent hepatic duct ligature and kept in cholestasis for four weeks. After this period, the rats in groups 2 and 3 underwent internal biliary derivation. In Group 3, the last ten centimeters of the terminal ileum were by passed and excluded. Four weeks later, histological and biochemical analysis were performed in all animals of the three groups. RESULTS: In Group 1, no abnormalities regarding hepatic morphology were observed. All animals from groups 2 and 3 presented hepatic fibrosis. No difference was observed between the two groups. No morphological differences in renal histology could be identified among the three groups. There were differences in AST (p

Published
2014
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20. Mutational analysis of the GAP-related domain of the neurofibromatosis type 1 gene in Brazilian NF1 patients

Author

Alessandra B. Trovó, Eny M. Goloni-Bertollo, Ulises M. Mancini, Paula Rahal, Walter F. de Azevedo Jr., and Eloiza H. Tajara

Subjects
gene NF1, GRD, neurofibromatosis type 1, mutations, polymorphisms, Genetics, QH426-470
Abstract

Neurofibromatosis type 1 (NF1) is a common autosomal dominant disorder caused by mutations in the NF1 gene. In the present study, a total of 55 unrelated NF1 patients were screened for mutations in the GAP-related domain/GRD (exons 20-27a) by single-strand conformation polymorphism (SSCP). Four different mutations were identified and, taken together, they comprise one nonsense substitution (Q1189X), one deletion (3525-3526delAA), one missense substitution (E1356G) and one mutation in the splice acceptor site (c.4111-1G>A). One novel polymorphism (c.4514+11C>G) and other three putative polymorphisms were also found (c.3315-27G>A, V1146I and V1317A). Genotype-phenotype correlations were investigated, but no particular association was detected.

Published
2004
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48. Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2

Author

Bitencourt-Ferreira, Gabriela, Duarte da Silva, Amauri, and Filgueira de Azevedo Jr., Walter

Abstract

Background: The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it possible to develop targeted scoring functions for virtual screening aimed to identify new inhibitors for this enzyme. CDK2 is a protein target for the development of drugs intended to modulate cellcycle progression and control. Such drugs have potential anticancer activities. Objective: Our goal here is to review recent applications of machine learning methods to predict ligand- binding affinity for protein targets. To assess the predictive performance of classical scoring functions and targeted scoring functions, we focused our analysis on CDK2 structures. Methods: We have experimental structural data for hundreds of binary complexes of CDK2 with different ligands, many of them with inhibition constant information. We investigate here computational methods to calculate the binding affinity of CDK2 through classical scoring functions and machine- learning models. Results: Analysis of the predictive performance of classical scoring functions available in docking programs such as Molegro Virtual Docker, AutoDock4, and Autodock Vina indicated that these methods failed to predict binding affinity with significant correlation with experimental data. Targeted scoring functions developed through supervised machine learning techniques showed a significant correlation with experimental data. Conclusion: Here, we described the application of supervised machine learning techniques to generate a scoring function to predict binding affinity. Machine learning models showed superior predictive performance when compared with classical scoring functions. Analysis of the computational models obtained through machine learning could capture essential structural features responsible for binding affinity against CDK2.

Published
2021
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50. Structural bioinformatics study of cyclin-dependent kinases complexed with inhibitors Estudo de bioinformática estrutural de quinases dependentes de ciclinas complexadas com inibidores

Author

F. Canduri, N. J. F. da Silveira, J. C. Camera Jr, and W. F. de Azevedo Jr

Subjects
desenho de drogas, lcsh:Chemistry, lcsh:QD1-999, drug design, CDK, Flavopiridol, bioinformatics, structure, estrutura, bio-informática
Abstract

The present work describes molecular models for the binary complexes CDK9, CDK5 and CDK1 complexed with Flavopiridol and Roscovitine. These structural models indicate that the inhibitors strongly bind to the ATP-binding pocket of CDKs and the structural comparison with the complexes CDK2:Flavopiridol and CDK2:Roscovitine correlates the structural differences with differences in inhibition of these CDKs by the inhibitors. These structures open the possibility of testing new inhibitor families, in addition to new substituents for the already known lead structures such as flavones and adenine derivatives.O presente trabalho descreve modelos moleculares para os complexos binários CDK9, CDK5 e CDK1 complexados com Flavopiridol e Roscovitina. Esses modelos estruturais indicam que os inibidores ligam-se fortemente ao sítio de ligação de ATP das CDKs e comparações estruturais dos complexos CDK2-Flavopiridol e CDK2-Roscovitina relacionam diferenças estruturais com diferenças na inibição dessas CDKs por esses inibidores. Essas estruturas abrem a possibilidade de testar novas famílias de inibidores, em adição aos novos substituintes para as estruturas já conhecidas, tais como flavonas e derivados de adenina.

Published
2003

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