Drug design of new sigma-1 antagonists against neuropathic pain: A QSAR study using partial least squares and artificial neural networks (2021)
- Authors:
- USP affiliated authors: HONORIO, KÁTHIA MARIA - EACH ; SILVA, ALBÉRICO BORGES FERREIRA DA - IQSC ; CHIARI, LAISE PELLEGRINI ALENCAR - IQSC ; SILVA, ALDINEIA PEREIRA DA - IQSC ; OLIVEIRA, ALINE ALVES - IQSC ; LIPINSKI, CÉLIO FERNANDO - IQSC
- Unidades: EACH; IQSC
- DOI: 10.1016/j.molstruc.2020.129156
- Subjects: QUALIDADE DE VIDA; NEUROLOGIA
- Keywords: MLP-ANN; Neuropathic pain; PLS; QSAR; Sigma-1R
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Molecular Structure
- ISSN: 0022-2860
- Volume/Número/Paginação/Ano: v. 1223, p. 129156, 2021
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
CHIARI, Laise Pellegrini Alencar et al. Drug design of new sigma-1 antagonists against neuropathic pain: A QSAR study using partial least squares and artificial neural networks. Journal of Molecular Structure, v. 1223, p. 129156, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.molstruc.2020.129156. Acesso em: 29 dez. 2025. -
APA
Chiari, L. P. A., Silva, A. P. da, Oliveira, A. A., Lipinski, C. F., Honório, K. M., & Silva, A. B. F. da. (2021). Drug design of new sigma-1 antagonists against neuropathic pain: A QSAR study using partial least squares and artificial neural networks. Journal of Molecular Structure, 1223, 129156. doi:10.1016/j.molstruc.2020.129156 -
NLM
Chiari LPA, Silva AP da, Oliveira AA, Lipinski CF, Honório KM, Silva ABF da. Drug design of new sigma-1 antagonists against neuropathic pain: A QSAR study using partial least squares and artificial neural networks [Internet]. Journal of Molecular Structure. 2021 ; 1223 129156.[citado 2025 dez. 29 ] Available from: https://doi.org/10.1016/j.molstruc.2020.129156 -
Vancouver
Chiari LPA, Silva AP da, Oliveira AA, Lipinski CF, Honório KM, Silva ABF da. Drug design of new sigma-1 antagonists against neuropathic pain: A QSAR study using partial least squares and artificial neural networks [Internet]. Journal of Molecular Structure. 2021 ; 1223 129156.[citado 2025 dez. 29 ] Available from: https://doi.org/10.1016/j.molstruc.2020.129156 - A partial least squares and artifcial neural network study for a series of arylpiperazines as antidepressant agents
- A PLS study on the psychotropic activity for a series of cannabinoid compounds
- Predicting biological activity and design of 5-HT6 antagonists through assessment of ANN-QSAR models in the context of Alzheimer’s disease
- New D2R partial agonist candidates:: an in silico approach from statistical models, molecular docking, and ADME/Tox propertie
- Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery
- Drug design of new 5-HT6R antagonists aided by artificial neural networks
- Elaboração de Modelos Preditivos da Atividade Biológica de uma Série de Compostos Arilpiperazínicos frente ao Receptor 5-HT2a
- Técnicas Computacionais aplicadas a uma série de Antagonistas do Receptor 5-HT6 − Potencial alvo para a Doença de Alzheimer
- Examining the effect of charged lipids on mitochondrial outer membrane dynamics using atomistic simulations
- Drug design of new 5-HT6 antagonists: a QSAR study of arylsulfonamide derivatives
Informações sobre o DOI: 10.1016/j.molstruc.2020.129156 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| P18992.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
