An integrated deep learning and molecular dynamics pipeline for the discovery of novel CDK8 inhibitors against acute myeloid leukaemia [0.03%]
一种集成深度学习和分子动力学的新型CDK8抑制剂发现管道用于治疗急性髓系白血病
B R Awad,M Sargolzaei,H Nikoofard
B R Awad
Cyclin-dependent kinase 8 (CDK8) has emerged as a promising therapeutic target for acute myeloid leukaemia (AML). We developed an integrated computational pipeline combining neural network-based potency prediction with molecular dynamics (M...
Network toxicology screening of plastic-associated chemicals reveals candidates with structural mimicry to Alzheimer's disease-relevant molecules and predicted neurotoxicity [0.03%]
基于网络毒理学的塑料相关化学品筛查发现具有结构模仿性的与阿尔茨海默病相关的分子及预测神经毒性候选物
W Cai,J Li,C Chen et al.
W Cai et al.
Alzheimer's disease (AD) pathogenesis involves environmental factors, with plastic-associated chemicals emerging as potential neurotoxicants. This study employed a computational toxicology framework to screen plastic-associated chemicals fo...
Mapping toxicity pathways of per- and polyfluoroalkyl substances using interpretable classification-based machine learning models [0.03%]
基于解释性分类算法的机器学习模型构建全氟和多氟化合物毒理学途径映射模型
S Sarkar,S Pore,K Roy
S Sarkar
Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants associated with adverse human health outcomes. However, experimental toxicity data remain unavailable for the vast majority of PFAS, limiting comprehensive...
Structure-based identification of inhibitory compounds targeting M32 metallocarboxypeptidase of Leishmania donovani [0.03%]
基于结构的莱士曼原虫M32金属碳水化合物酶抑制剂筛选体系开发及新先导化合物发现
S Sen,P Jakkula,I A Qureshi
S Sen
Leishmaniasis remains a major public health burden due to limited vaccines, toxic treatments, and drug resistance. The M32 metallocarboxypeptidase of Leishmania donovani (LdMCP1) represents a promising target due to its presence in trypanos...
Multiscale computational evaluation of marine fungal metabolites containing iminohydantoin-like scaffolds as anti-Alzheimer drug candidates [0.03%]
含亚胺杂环骨架海洋真菌代谢物茋类衍生物的抗阿尔茨海默药物候选物的多尺度计算评价研究
A I Foudah,A Ahmad,M A Bakht et al.
A I Foudah et al.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder associated with amyloid-beta accumulation, neuroinflammation, and synaptic dysfunction, making beta-secretase 1 (BACE1) a promising therapeutic target. In the current inve...
Conformational landscapes and binding free energies of multitarget phytochemicals reveal molecular recognition mechanisms in colorectal cancer-associated proteins [0.03%]
构象景观和结合自由能的多靶向植物化学成分揭示结直肠癌相关蛋白分子识别机制
H Deshmukh,S Samanta,J R Kanwar et al.
H Deshmukh et al.
Colorectal cancer (CRC) significantly contributes to global cancer-related morbidity and mortality. As systemic toxicity, poor selectivity, and drug resistance restrict the usefulness of available chemotherapy and radiotherapy, phytochemica...
AI-driven QSAR modelling and virtual screening in the discovery of selective dopamine D2 receptor ligands [0.03%]
基于人工智能的QSAR模型与虚拟筛选在发现选择性多巴胺D2受体配体中的应用
N Maliyakkal,H C Vishwakarma,S Kumar et al.
N Maliyakkal et al.
The dopamine D2 receptor (DRD2) is a key therapeutic target for several neuropsychiatric disorders, driving the need for new ligands with improved safety and efficacy. To find possible DRD2 inhibitors, we developed an integrated in silico w...
Integrating machine learning and pharmacogenomics for biomarker discovery, identification and prioritization of potential drug candidates in ovarian cancer [0.03%]
基于机器学习和药物基因组学的卵巢癌生物标志物发现、潜在药物候选物识别与优先排序
S Yadav,A C Kaushik,G Srivastava et al.
S Yadav et al.
Ovarian cancer remains a major global health concern and leading cause of mortality among women due to late diagnosis, therapeutic resistance, and limited predictive biomarkers for treatment response. There is an urgent need for integrative...
Multi-target QSAR modelling for identification of novel inhibitors of class I HDACs [0.03%]
多靶标QSAR建模以寻找I类HDACs的新型抑制剂
G G Tu
G G Tu
In this study, the multi-target QSAR (mt-QSAR) models were constructed which can predict the inhibitory activity of compounds against various class I HDACs isoforms under different experimental conditions. Models based on mt-QSAR classifica...
QSAR-based evaluation of plant-derived larvicidal agents against Zika vector Aedes aegypti via Monte Carlo optimization and SMILES-based descriptors and molecular docking [0.03%]
基于QSAR的植物源蚊幼虫剂评价研究及对寨卡病毒传播媒介埃及伊蚊的作用机制探究
S Lotfi,F Nooraei,S Ahmadi
S Lotfi
Aedes aegypti is the principal vector responsible for the transmission of several arboviral diseases, including dengue, Zika, chikungunya, and yellow fever, posing a significant threat to global public health. Controlling its population is ...