Efficient Binding Affinity Estimation for Fragment-Based Compounds Using a Separated Topologies Approach

2026/03/13 by Ana-Maria Caldaruse, Hannah M. Baumann, David L. Mobley · 1 voice
Computer Science · Biochemistry, Genetics and Molecular Biology · #Computational Drug Discovery Methods #Protein Structure and Dynamics #Chemical Synthesis and Analysis

paper · pdf · doi:10.1021/acs.jcim.5c03091

openalex publication_date 2026/03/13 · openalex created_date 2026/03/14 · openalex updated_date 2026/07/12

Abstract

Fragment-based drug discovery (FBDD) is a widely used strategy in early-stage drug development, but accurately predicting the binding affinities of fragments and their elaborated analogs poses unique computational challenges. These difficulties arise from weak binding affinities, diverse chemical scaffolds, and limited structural overlap between fragments and their optimized derivatives. While several free-energy methods exist, few are tailored to the specific requirements of FBDD. In this study, we evaluate the Separated Topologies (SepTop) approach for modeling fragment-based transformations, including fragment merging and linking. Using retrospective data sets from Cyclophilin D and SARS-CoV-2 Macrodomain 1, we demonstrate that SepTop can recover experimental binding affinities with good accuracy across both fragment and lead-like compounds. These results support SepTop's suitability for fragment optimization and highlight its potential to extend the reach of binding free-energy calculations into earlier stages of drug discovery.

Citations

• Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology
• Precise binding free energy calculations for multiple molecules using an optimal measurement network of pairwise differences
• Relationship between the inhibition constant (KI) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an enzymatic reaction
• Improved side‐chain torsion potentials for the Amber ff99SB protein force field

Discussions

• Caldaruse, Baumann & Mobley (2026) Efficient Binding Affinity Estimation for Fragment-Based Compounds Using a Separated Topologies Approach JCIM 7:4202-4214 #FBD #FBDD #CompChem #cheminformatics #MedC [bsky, 4 points, 0 comments]

Related

• FragmentGPT: A Unified GPT Model for Fragment Growing, Linking, and Merging in Molecular Design
• Predicting fragment binding modes using customized Lennard-Jones potentials in short molecular dynamics simulations
• Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology
• A Foundation Chemical Language Model for Comprehensive Fragment-Based Drug Discovery
• Flow-Based Fragment Identification via Binding Site-Specific Latent Representations