A5014262462- Computational Drug Discovery Methods
- Synthesis and biological activity
- Trypanosoma species research and implications
- SARS-CoV-2 and COVID-19 Research
- Influenza Virus Research Studies
- Research on Leishmaniasis Studies
- vaccines and immunoinformatics approaches
- Mosquito-borne diseases and control
- Pharmacogenetics and Drug Metabolism
- Viral Infections and Immunology Research
- Parasites and Host Interactions
- Hepatitis C virus research
- Biomedical Text Mining and Ontologies
- Bioinformatics and Genomic Networks
- Malaria Research and Control
- Microbial Natural Products and Biosynthesis
- Click Chemistry and Applications
- Viral gastroenteritis research and epidemiology
- Tuberculosis Research and Epidemiology
- Protein Degradation and Inhibitors
- Parasite Biology and Host Interactions
- Proteoglycans and glycosaminoglycans research
- Machine Learning in Materials Science
- Natural Language Processing Techniques
- Social Media in Health Education
University of North Carolina at Chapel Hill
2020-2025
University of North Carolina Health Care
2023
Universidade Federal de Goiás
2016-2018
Virtual screening (VS) has emerged in drug discovery as a powerful computational approach to screen large libraries of small molecules for new hits with desired properties that can then be tested experimentally. Similar other approaches, VS intention is not replace vitro or vivo assays, but speed up the process, reduce number candidates experimentally, and rationalize their choice. Moreover, become very popular pharmaceutical companies academic organizations due its time-, cost-, resources-,...
Abstract The main protease (M pro ) of the SARS‐CoV‐2 has been proposed as one major drug targets for COVID‐19. We have identified experimental data on inhibitory activity compounds tested against closely related (96 % sequence identity, 100 active site conservation) M SARS‐CoV. developed QSAR models these inhibitors and employed virtual screening all drugs in DrugBank database. Similarity searching molecular docking were explored parallel, but failed to correctly discriminate between...
Computational models that predict pharmacokinetic properties are critical to deprioritize drug candidates emerge as hits in high-throughput screening campaigns. We collected, curated, and integrated a database of compounds tested 12 major end points comprising over 10,000 unique molecules. then employed these data build validate binary quantitative structure–activity relationship (QSAR) models. All trained achieved correct classification rate above 0.60 positive predictive value 0.50. To...
Schistosomiasis is a debilitating neglected tropical disease, caused by flatworms of Schistosoma genus. The treatment relies on single drug, praziquantel (PZQ), making the discovery new compounds extremely urgent. In this work, we integrated QSAR-based virtual screening (VS) mansoni thioredoxin glutathione reductase (SmTGR) inhibitors and high content (HCS) aiming to discover antischistosomal agents. Initially, binary QSAR models for inhibition SmTGR were developed validated using...
Drug discovery is mostly guided by innovative and knowledge the application of experimental computational approaches. Quantitative structure-activity relationships (QSAR) have a critical task in optimization lead compounds, thereby contributing to development new chemical entities. 3D-QSAR methods use information tridimensional molecular structure ligands can be applied elucidate between 3D interactions their measured biological property, therefore, providing rational approach for potential...
Schistosomiasis is a neglected tropical disease that affects millions of people worldwide. Thioredoxin glutathione reductase Schistosoma mansoni (SmTGR) validated drug target plays crucial role in the redox homeostasis parasite. We report discovery new chemical scaffolds against S. using combi-QSAR approach followed by virtual screening commercial database and confirmation top ranking compounds vitro experimental evaluation with automated imaging schistosomula adult worms. constructed 2D 3D...
The recent severe acute respiratory syndrome coronavirus 2 pandemic has clearly exemplified the need for broad-spectrum antiviral (BSA) medications. However, previous outbreaks show that about one year after an outbreak, interest in research diminishes and work toward effective medication is left unfinished. Martin et al. endeavored to support early stages of focused BSA development by creating Small Molecule Antiviral Compound Collection (SMACC), which publicly available online at...
The COVID-19 pandemic has had enormous health, economic, and social consequences. Vaccines have been successful in reducing rates of infection hospitalization, but there is still a need for acute treatment the disease. We investigate whether compounds that bind human angiotensin-converting enzyme 2 (ACE2) protein can decrease SARS-CoV-2 replication without impacting ACE2's natural enzymatic function. Initial screening diversity library resulted hit active an ACE2-binding assay, which showed...
Malaria is a life-threatening infectious disease caused by parasites of the genus Plasmodium, affecting more than 200 million people worldwide every year and leading to about half deaths. humans have evolved resistance all current antimalarial drugs, urging for discovery new effective compounds. Given that inhibition deoxyuridine triphosphatase Plasmodium falciparum (PfdUTPase) induces wrong insertions in plasmodial DNA consequently parasite death, this enzyme considered an attractive drug...
Drug repurposing has been an interesting and cost-effective approach, especially for neglected diseases, such as Chagas disease.In this work, we studied the activity of antidepressant drug sertraline against Trypanosoma cruzi trypomastigotes intracellular amastigotes Y Tulahuen strains, investigated its action mode using cell biology in silico approaches.Sertraline demonstrated vitro efficacy both T. strains inside different host cells, including cardiomyocytes, with IC50 values between 1 to...
Aim: The shape-based virtual screening was used for the identification of new compounds anti-paracoccidioidomycosis (PCM). Materials & methods: study performed according to following steps: collection and curation a dataset quinolinyl N-oxide chalcones with anti-PCM activity, development validation models, application best model screening, experimental validation. Results Conclusion: Among 31 computational hits, eight showed potent antifungal activity low cytotoxicity mammalian cells....
The outbreak of a novel human coronavirus (SARS-CoV-2) has evolved into global health emergency, infecting hundreds thousands people worldwide. We have identified experimental data on the inhibitory activity compounds tested against closely related (96% sequence identity, 100% active site conservation) protease SARS-CoV and employed this to build QSAR models for dataset. these virtual screening all drugs from DrugBank, including in clinical trials. Molecular docking similarity search...
Treatment regimens, especially in cancer, often include more than one medicine order to achieve durable outcomes. Identifying the optimal combination of treatments has historically been done through clinical trial and error. And for many conditions, such as pancreatic an treatment protocol remained elusive, best available combinations provide only modest benefit. Recent developments have led application both experimental screening approaches silico modeling methods identify synergistic drug...
Abstract Heparan sulfate (HS), a sulfated polysaccharide abundant in the extracellular matrix, plays pivotal roles various physiological and pathological processes by interacting with proteins. Investigating binding selectivity of HS oligosaccharides to target proteins is essential, but exhaustive inclusion all possible microarray experiments impractical. To address this challenge, we present hybrid pipeline that integrates silico techniques design desired protein affinity. Using fibroblast...
Computational models that predict PK properties, such as those related to drug absorption, metabolism, distribution, and excretion, are critical flagging candidates with poor profiles emerge hits in high-throughput screening campaigns. To support the development of reliable computational key we collected, curated, integrated a database compounds tested 13 major endpoints containing over 10,000 unique molecules. We built classification quantitative structure-activity relationship (QSAR) for...
Few Zika virus (ZIKV) outbreaks had been reported since its first detection in 1947, until the recent epidemics occurred South America (2014/2015) and expeditiously became a global public health emergency. This arbovirus reached 0.5-1.3 million cases of ZIKV infection Brazil 2015 rapidly spread new geographic areas such as Americas. Despite mild symptoms fever, major concern is related to severe neurological disorders, especially microcephaly newborns. Advances drug discovery have made...
The outbreak of a novel human coronavirus (SARS-CoV-2) has evolved into global health emergency, infecting hundreds thousands people worldwide. We have identified experimental data on the inhibitory activity compounds tested against closely related (96% sequence identity, 100% active site conservation) protease SARS-CoV and employed this to build QSAR models for dataset. these virtual screening all drugs from DrugBank, including in clinical trials. Molecular docking similarity search...