Yunierkis Pérez‐Castillo

Universidad de las Américas — NI

Computer Science · Physical Sciences

27h-index2.1kcitations127works4.92yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Computational Drug Discovery Methods(46), Bioinformatics and Genomic Networks(17), Synthesis and biological activity(15), Machine Learning in Bioinformatics(15), Protein Structure and Dynamics(12)

Publications127 total

Computational Investigation of the Potential Antileishmanial Mechanism of the Nitroindazole Derivative VATR131
Pharmaceuticals·2025Open Access
Mapping the Chemical Space of Antiviral Peptides with Half-Space Proximal and Metadata Networks Through Interactive Data Mining
Computers·2025· 1 citedOpen Access
Salicylic Acid Derivatives as Antifungal Agents: Synthesis, In Vitro Evaluation, and Molecular Modeling
Chemistry·2025Open Access
Synthesis and Antimicrobial Evaluation of Chroman-4-One and Homoisoflavonoid Derivatives
Molecules·2025· 1 citedOpen Access
Indazole Derivatives Against Murine Cutaneous Leishmaniasis.
PubMed·2025Open Access
Computational modeling predicts potential effects of the herbal infusion “horchata” against COVID-19
UNC Libraries·2025Open Access
Structural determination of a new non-canonical inhibition complex between porcine trypsin and M271 a potato Kunitz-STI inhibitor
Biochemical and Biophysical Research Communications·2025· 1 cited
Antifungal Evaluation of Benzoxazole and Benzothiazole Derivatives: An In Vitro and In Silico Study
Chemistry & Biodiversity·2025· 3 citedOpen Access
3‐Methyl‐4‐Nitrobenzoate Derivates as Antifungal Drug Candidates: Biological and <i>In Silico</i> Evaluation
Journal of Chemistry·2025Open Access
Peptide hemolytic activity analysis using visual data mining of similarity-based complex networks
npj Systems Biology and Applications·2024· 5 citedOpen Access
3-Alkoxy-1-Benzyl-5-Nitroindazole Derivatives Are Potent Antileishmanial Compounds
International Journal of Molecular Sciences·2024· 4 citedOpen Access
Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses
Scientific Reports·2024· 18 citedOpen Access
Multiquery Similarity Searching Models: An Alternative Approach for Predicting Hemolytic Activity from Peptide Sequence
Chemical Research in Toxicology·2024· 6 citedOpen Access
Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy
Journal of Cheminformatics·2024· 18 citedOpen Access
Rethinking the applicability domain analysis in QSAR models
Journal of Computer-Aided Molecular Design·2024· 14 cited
Exploring the dynamics of the ABCB1 membrane transporter P-glycoprotein in the presence of ATP and active/non-active compounds through molecular dynamics simulations
Toxicology·2024· 7 citedOpen Access
Antifungal activity against Candida albicans of methyl 3,5-dinitrobenzoate loaded nanoemulsion
Brazilian Journal of Microbiology·2023· 5 citedOpen Access
A New Robust Method for Predicting Hemolytic Toxicity from Peptide Se-quence
2023· 3 citedOpen Access
Piplartine Synthetic Analogs: In Silico Analysis and Antiparasitic Study against Trypanosoma cruzi
Applied Sciences·2023· 3 citedOpen Access
Validation of venous thromboembolism predictive model in hematologic malignancies
Annals of Hematology·2023· 5 cited
page 1 of 7Next →

Frequent Co-authors

Eduardo Tejera(24), Alejandro Cabrera‐Andrade(12), Cristian R. Munteanu(12), Damião Pergentino de Sousa(12), Humberto González‐Díaz(11), Andrés López‐Cortés(11), Alejandro Pazos(10), César Paz‐y‐Miño(9), Maykel Cruz‐Monteagudo(7), M. Natália D. S. Cordeiro(7), Fernanda Borges(7), Aminael Sánchez‐Rodríguez(7), Vinicio Armijos‐Jaramillo(5), Stephen J. Barigye(5), Santiago Guerrero(4), José L. Medina‐Franco(3), Carlos da Silva Maia Bezerra Filho(3), Guillermı́n Agüero-Chapin(3), Orazio Nicolotti(2), Eugenio Uriarte(2)