ArticleDatabase : the journal of biological databases and curation2019
DeepScreening: a deep learning-based screening web server for accelerating drug discovery.
Article in Database : the journal of biological databases and curation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 84 citations in OpenAlex.
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- Identification of Potential Inhibitors Targeting Non-Structural Proteins NS3 and NS5 of Dengue Virus Using Docking and Deep Learning Approaches.Pharmaceuticals (Basel, Switzerland) · 2025Article
- A beginner's approach to deep learning applied to VS and MD techniques.Journal of cheminformatics · 2025Review
- Unveiling the ghost: machine learning's impact on the landscape of virology.The Journal of general virology · 2025Review
- cidalsDB: an AI-empowered platform for anti-pathogen therapeutics research.Journal of cheminformatics · 2024Article
- Computational drug development for membrane protein targets.Nature biotechnology · 2024Review
- Employing Molecular Conformations for Ligand-Based Virtual Screening with Equivariant Graph Neural Network and Deep Multiple Instance Learning.Molecules (Basel, Switzerland) · 2023Article
- AI in drug discovery and its clinical relevance.Heliyon · 2023Review
- Identification of medicinal plant-based phytochemicals as a potential inhibitor for SARS-CoV-2 main protease (MComputers in biology and medicine · 2023Article
- FP-MAP: an extensive library of fingerprint-based molecular activity prediction tools.Frontiers in chemistry · 2023Article
- Review
- DDPD 1.0: a manually curated and standardized database of digital properties of approved drugs for drug-likeness evaluation and drug development.Database : the journal of biological databases and curation · 2022Article
- DenovoProfiling: A webserver forComputational and structural biotechnology journal · 2022Article
- CancerOmicsNet: a multi-omics network-based approach to anti-cancer drug profiling.Oncotarget · 2022Article
- Identification of Zinc-Binding Inhibitors of Matrix Metalloproteinase-9 to Prevent Cancer Through Deep Learning and Molecular Dynamics Simulation Approach.Frontiers in molecular biosciences · 2022Article
- Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents.Molecular diversity · 2021Article
- Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace.Briefings in bioinformatics · 2021Review
- Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products.Frontiers in chemistry · 2021Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep learning contributes significantly to researches in biological sciences and drug discovery. Previous studies suggested that deep learning techniques have shown superior performance to other machine learning algorithms in virtual screening, which is a critical step to accelerate the drug discovery. However, the application of deep learning techniques in drug discovery and chemical biology are hindered due to the data availability, data further processing and lacking of the user-friendly deep learning tools and interface. Therefore, we developed a user-friendly web server with integration of the state of art deep learning algorithm, which utilizes either the public or user-provided dataset to help biologists or chemists perform virtual screening either the chemical probes or drugs for a specific target of interest. With DeepScreening, user could conveniently construct a deep learning model and generate the target-focused de novo libraries. The constructed classification and regression models could be subsequently used for virtual screening against the generated de novo libraries, or diverse chemical libraries in stock. From deep models training to virtual screening, and target focused de novo library generation, all those tasks could be finished with DeepScreening. We believe this deep learning-based web server will benefit to both biologists and chemists for probes or drugs discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.