4.5 Article

Fragment databases from screened ligands for drug discovery (FDSL-DD)

Journal

JOURNAL OF MOLECULAR GRAPHICS & MODELLING
Volume 127, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmgm.2023.108669

Keywords

Drug design; Drug discovery; Fragment -based drug design (FBDD); Fragment based design; Structure based design

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Fragment-based drug design is a computer-aided drug discovery method, however, it has limitations in processing time and success rate. In this study, a new method called Fragment Databases from Screened Ligands Drug Design (FDSL-DD) was proposed, which intelligently incorporates fragment characteristics into the drug design process to improve the binding affinity between drugs and protein targets.
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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