Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease

被引:0
|
作者
Kumar, Vinay [1 ]
Banerjee, Arkaprava [1 ]
Roy, Kunal [1 ]
机构
[1] Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata,700032, India
关键词
Computational chemistry - Learning algorithms - Machine learning - Molecular graphics - Molecular structure - Neurodegenerative diseases - Structural design;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [41] In silico identification of natural product inhibitors for -secretase activating protein, a therapeutic target for Alzheimer's disease
    Gupta, Manoj Kumar
    Vadde, Ramakrishna
    JOURNAL OF CELLULAR BIOCHEMISTRY, 2019, 120 (06) : 10323 - 10336
  • [42] An Improved Multi-Modal based Machine Learning Approach for the Prognosis of Alzheimer?s disease
    Khan, Afreen
    Zubair, Swaleha
    JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2022, 34 (06) : 2688 - 2706
  • [43] Virtual screening and molecular dynamics simulation approach for the identification of potential multi-target directed ligands for the treatment of Alzheimer's disease
    Jangid, Kailash
    Devi, Bharti
    Sahoo, Ashrulochan
    Kumar, Vijay
    Dwivedi, Ashish Ranjan
    Thareja, Suresh
    Kumar, Rajnish
    Kumar, Vinod
    JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 2024, 42 (01): : 509 - 527
  • [44] Novel Pyrrole Derivatives as Multi-Target Agents for the Treatment of Alzheimer's Disease: Microwave-Assisted Synthesis, In Silico Studies and Biological Evaluation
    Mateev, Emilio
    Karatchobanov, Valentin
    Dedja, Marjano
    Diamantakos, Konstantinos
    Mateeva, Alexandrina
    Muhammed, Muhammed Tilahun
    Irfan, Ali
    Kondeva-Burdina, Magdalena
    Valkova, Iva
    Georgieva, Maya
    Zlatkov, Alexander
    PHARMACEUTICALS, 2024, 17 (09)
  • [45] Machine learning-based virtual screening of multi-target anti-obesity compounds from medicinal and edible plants: A combined in silico and in vitro study
    Zhou, Xincheng
    Ni, Jian
    Ge, Weiben
    Wang, Xinyue
    Li, Yubing
    Wang, Hongxin
    Ma, Chaoyang
    FOOD BIOSCIENCE, 2024, 59
  • [46] Exploring the Multi-Target Performance of Mitochondriotropic Antioxidants against the Pivotal Alzheimer's Disease Pathophysiological Hallmarks
    Benfeito, Sofia
    Fernandes, Carlos
    Vilar, Santiago
    Remiao, Fernando
    Uriarte, Eugenio
    Borges, Fernanda
    MOLECULES, 2020, 25 (02):
  • [47] Bioinformatics and Machine Learning-Based Screening of Key Genes in Alzheimer's Disease
    Hou, Meng Ting
    Bao, Juan
    Zheng, Shu Xiong
    Li, Si Tong
    Li, Xi Yu
    INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH, 2024, 21 (01)
  • [48] Pharmacophore-based drug design for the identification of novel butyrylcholinesterase inhibitors against Alzheimer's disease
    Jiang, Yingying
    Gao, Hongwei
    PHYTOMEDICINE, 2019, 54 : 278 - 290
  • [49] A novel cascade machine learning pipeline for Alzheimer's disease identification and prediction
    Zhou, Kun
    Piao, Sirong
    Liu, Xiao
    Luo, Xiao
    Chen, Hongyi
    Xiang, Rui
    Geng, Daoying
    FRONTIERS IN AGING NEUROSCIENCE, 2023, 14
  • [50] Erratum to: Fragment-based in silico modeling of multi-target inhibitors against breast cancer-related proteins
    Alejandro Speck-Planche
    M. Natália D. S. Cordeiro
    Molecular Diversity, 2017, 21 : 525 - 525