Identification of active compounds as novel dipeptidyl peptidase-4 inhibitors through machine learning and structure-based molecular docking simulations-Reference-Cited by-同舟云学术

Identification of active compounds as novel dipeptidyl peptidase-4 inhibitors through machine learning and structure-based molecular docking simulations

Published:2023-12-15 Issue: Volume: Page:1-10
ISSN:0739-1102
Container-title:Journal of Biomolecular Structure and Dynamics
language:en
Short-container-title:Journal of Biomolecular Structure and Dynamics

Author:

Ali Shahid¹²,Shaikh Sibhghatulla¹²,Ahmad Khurshid¹²^ORCID,Choi Inho¹²

Affiliation:

1. Department of Medical Biotechnology, Yeungnam University, Gyeongsan, South Korea

2. Research Institute of Cell Culture, Yeungnam University, Gyeongsan, South Korea

Funder

National Research Foundation of Korea

Publisher

Informa UK Limited

Subject

Molecular Biology,General Medicine,Structural Biology

Link

https://www.tandfonline.com/doi/pdf/10.1080/07391102.2023.2292299

Reference58 articles.

1. Machine learning for neuroimaging with scikit-learn

2. Computational Identification of Dithymoquinone as a Potential Inhibitor of Myostatin and Regulator of Muscle Mass

3. Mss51 protein inhibition serves as a novel target for type 2 diabetes: a molecular docking and simulation study

4. Identification and Evaluation of Traditional Chinese Medicine Natural Compounds as Potential Myostatin Inhibitors: An In Silico Approach

5. Identification and Evaluation of Inhibitors of Lipase from Malassezia restricta using Virtual High-Throughput Screening and Molecular Dynamics Studies

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