Journal article
Fragment databases from screened ligands for drug discovery (FDSL-DD)
Journal of molecular graphics & modelling, v 127, pp 108669-108669
Mar 2024
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Fragment-based drug design (FBDD) is one major drug discovery method employed in computer-aided drug discovery. Due to its inherent limitations, this process experiences long processing times and limited success rates. Here we present a new Fragment Databases from Screened Ligands Drug Design method (FDSL-DD) that intelligently incorporates information about fragment characteristics into a fragment-based design approach to the drug development process. The initial step of the FDSL-DD is the creation of a fragment database from a library of docked, drug-like ligands for a specific target, which deviates from the traditional in silico FBDD strategy, incorporating structure-based design screening techniques to combine the advantages of both approaches. Three different protein targets have been tested in this study to demonstrate the potential of the created fragment library and FDSL-DD. Utilizing the FDSL-DD led to an increase in binding affinity for each protein target. The most substantial increase was exhibited by the ligand designed for TIPE2, with a 3.6 kcalmol-1 difference between the top ligand from the FDSL-DD and top ligand from the high throughput virtual screening (HTVS). Using drug-like ligands in the initial HTVS allows for a greater search of chemical space, with higher efficiency in fragments selection, less grid boxes, and potentially identifying more interactions.
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Details
- Title
- Fragment databases from screened ligands for drug discovery (FDSL-DD)
- Creators
- Jerica Wilson - Drexel UniversityBahrad A Sokhansanj - Drexel UniversityWei Chuen Chong - Drexel UniversityRohan Chandraghatgi - Drexel UniversityGail L Rosen - Drexel UniversityHai-Feng Ji
- Publication Details
- Journal of molecular graphics & modelling, v 127, pp 108669-108669
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; Chemistry
- Web of Science ID
- WOS:001127669300001
- Scopus ID
- 2-s2.0-85181692663
- Other Identifier
- 991021811748504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Biochemical Research Methods
- Biochemistry & Molecular Biology
- Computer Science, Interdisciplinary Applications
- Crystallography
- Mathematical & Computational Biology