DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks-Reference-Cited by-同舟云学术

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DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks

Published:2021-08-10 Issue: Volume: Page:
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Aggarwal Rishal¹,Gupta Akash¹,Chelur Vineeth¹,Jawahar C. V.¹,Priyakumar U. Deva¹^ORCID

Affiliation:

1. International Institute of Information Technology, Hyderabad 500 032, India

Funder

IHub-Data, IIIT Hyderabad

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.1c00799

Reference58 articles.

1. The Process of Structure-Based Drug Design

2. Exploring the computational methods for protein-ligand binding site prediction

3. Protein-Ligand Blind Docking Using QuickVina-W With Inter-Process Spatio-Temporal Integration

4. Fpocket: An open source platform for ligand pocket detection

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2. Building shape-focused pharmacophore models for effective docking screening;Journal of Cheminformatics;2024-08-09

3. Comparative evaluation of methods for the prediction of protein-ligand binding sites;2024-08-08

4. Protein ligand binding site prediction using graph transformer neural network;PLOS ONE;2024-08-06

5. Machine learning-assisted substrate binding pocket engineering based on structural information;Briefings in Bioinformatics;2024-07-25

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