Drug discovery is iterative by nature — an endless loop of hypotheses, experiments, and corrections. This blog sits in the middle of that loop, focusing on the computational side: docking poses, pharmacophore models, MD trajectories, similarity metrics, and machine learning pipelines that try (and often fail) to predict biology from data.
Ligand in the Loop is a personal, anonymous space to share thoughts, methods, tools, and reflections that arise during real research projects in molecular modeling and cheminformatics. I’ll post short essays, technical notes, critiques of published papers, code snippets, and commentary on methods I use or avoid — often with more candor than peer review allows.
The intended audience includes:
- Computational chemists and molecular modelers
- Medicinal chemists curious about in silico tools
- Data scientists working at the chemistry-biology interface
- PhD students and postdocs navigating the black box of virtual screening
There won’t be fixed formats or schedules — just ideas worth documenting. If any of these resonate with your own work, you’re in the loop too.
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