[HTML][HTML] Machine learning-driven QSAR models for predicting the mixture toxicity of nanoparticles
F Zhang, Z Wang, WJGM Peijnenburg… - Environment International, 2023 - Elsevier
Research on theoretical prediction methods for the mixture toxicity of engineered
nanoparticles (ENPs) faces significant challenges. The application of in silico methods …
nanoparticles (ENPs) faces significant challenges. The application of in silico methods …
QSPR analysis of drugs for treatment of schizophrenia using topological indices
Schizophrenia is a chronic psychotic disorder characterized primarily by cognitive deficits.
Drugs and therapies are helpful in managing the symptoms, mostly with long-term …
Drugs and therapies are helpful in managing the symptoms, mostly with long-term …
QSAR, simulation techniques, and ADMET/pharmacokinetics assessment of a set of compounds that target MAO-B as anti-Alzheimer agent
Background Alzheimer's disease (AD), the most common cause of dementia in the elderly, is
a progressive neurodegenerative disorder that gradually affects cognitive function and …
a progressive neurodegenerative disorder that gradually affects cognitive function and …
Unveiling novel inhibitors of dopamine transporter via in silico drug design, molecular docking, and bioavailability predictions as potential antischizophrenic agents
Background The inhibition of dopamine transporter is known to play a significant role in the
treatment of schizophrenia-related and other mental disorders. In a continuing from our …
treatment of schizophrenia-related and other mental disorders. In a continuing from our …
Do AutoML-Based QSAR Models Fulfill OECD Principles for Regulatory Assessment? A 5-HT1A Receptor Case
N Czub, A Pacławski, J Szlęk, A Mendyk - Pharmaceutics, 2022 - mdpi.com
The drug discovery and development process requires a lot of time, financial, and workforce
resources. Any reduction in these burdens might benefit all stakeholders in the healthcare …
resources. Any reduction in these burdens might benefit all stakeholders in the healthcare …
Structure-based design of potential anti-schistosomiasis agent targeting SmHDAC8: an in silico approach utilizing QSAR, MD simulation and ADMET prediction
SC Ja'afaru, A Uzairu, MS Sallau, GI Ndukwe… - Chemistry Africa, 2024 - Springer
Due to the increasing emergences of drug resistance, there is a need to discover new drugs
that can target Schistosoma mansoni histone deacetylase 8 (SmHDAC8) and effectively …
that can target Schistosoma mansoni histone deacetylase 8 (SmHDAC8) and effectively …
Development of novel antipsychotic agents by inhibiting dopamine transporter–in silico approach
V Đorđević, S Pešić, J Živković, GM Nikolić… - New Journal of …, 2022 - pubs.rsc.org
Dopamine transporter inhibition is deemed a promising approach to treating schizophrenia.
This research paper outlines various QSAR models for molecules acting as dopamine …
This research paper outlines various QSAR models for molecules acting as dopamine …
Multivariate QSAR, similarity search and ADMET studies based in a set of methylamine derivatives described as dopamine transporter inhibitors
LHD de Oliveira, JN Cruz, CBR Dos Santos… - Molecular Diversity, 2023 - Springer
The dopamine transporter (DAT), responsible for the regulation of dopaminergic
neurotransmission, is implicated in the etiology of several neuropsychiatric disorders which …
neurotransmission, is implicated in the etiology of several neuropsychiatric disorders which …
Exploring in silico drug design and pharmacokinetics study for identification of potent antidepressant agents
In furtherance to our previous study, in silico drug design and pharmacokinetics study were
employed on some arylpiperazine derivatives as inhibitors of serotonin transporter (SERT) …
employed on some arylpiperazine derivatives as inhibitors of serotonin transporter (SERT) …
[PDF][PDF] Pei nenburg, W.. GM, & Vi er, MG (2023)
F Zhang, Z Wang - Machine learning-dri en QS R … - scholarlypublications …
Research on theoretical prediction methods for the mixture toxicity of engineered
nanoparticles (ENPs) faces significant challenges. The application of in silico methods …
nanoparticles (ENPs) faces significant challenges. The application of in silico methods …