ArticleJournal of chemical information and modeling2019
ezCADD: A Rapid 2D/3D Visualization-Enabled Web Modeling Environment for Democratizing Computer-Aided Drug Design.
Article in Journal of chemical information and modeling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
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- DFT Study of Regio- and Stereoselective 13DC Reaction between Diazopropane and Substituted Chalcone Derivatives: Molecular Docking of Novel Pyrazole Derivatives as Anti-Alzheimer's Agents.Molecules (Basel, Switzerland) · 2023Article
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- SARS-COV-2 Coronavirus Papain-like Protease PLpro as an Antiviral Target for Inhibitors of Active Site and Protein-Protein Interactions.Biophysics · 2022Article
- Unraveling the Compositional and Molecular Features Involved in Lysozyme-Benzothiazole Derivative Interactions.Molecules (Basel, Switzerland) · 2021Article
- Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace.Briefings in bioinformatics · 2021Review
- Targeting Beta-Blocker Drug-Drug Interactions with Fibrinogen Blood Plasma Protein: A Computational and Experimental Study.Molecules (Basel, Switzerland) · 2020Article
- First-in-class humanized FSH blocking antibody targets bone and fat.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
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Authors and funding
6 authors.
Funding
Abstract
As abundant and user-friendly as computer-aided drug design (CADD) software may seem, there is still a large underserved population of biomedical researchers around the world, particularly those with no computational training and limited research funding. To address this important need and help scientists overcome barriers that impede them from leveraging CADD in their drug discovery work, we have developed ezCADD, a web-based CADD modeling environment that manifests four simple design concepts: easy, quick, user-friendly, and 2D/3D visualization-enabled. In this paper, we describe the features of three fundamental applications that have been implemented in ezCADD: small-molecule docking, protein-protein docking, and binding pocket detection, and their applications in drug design against a pathogenic microbial enzyme as an example. To assess user experience and the effectiveness of our implementation, we introduced ezCADD to first-year pharmacy students as an active learning exercise in the Principles of Drug Action course. The web service robustly handled 95 simultaneous molecular docking jobs. Our survey data showed that among the 95 participating students, 97% completed the molecular docking experiment on their own at least partially without extensive training; 88% considered ezCADD easy and user-friendly; 99-100% agreed that ezCADD enhanced the understanding of drug-receptor structures and recognition; and the student experience in molecular modeling and visualization was significantly improved from zero to a higher level. The student feedback represents the baseline data of user experience from noncomputational researchers. It is demonstrated that in addition to supporting drug discovery research, ezCADD is also an effective tool for promoting science, technology, engineering, and mathematics (STEM) education. More advanced CADD applications are being developed and added to ezCADD, available at http://dxulab.org/software .
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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.