Balancing Molecular Size, Activity, Permeability, and Other Properties: Drug Candidates in the Context of Their Chemical Structure Optimization

Chemical structure optimization is a vital part of early drug discovery projects. Starting with compounds that show activity on the target of interest, the chemical structures are subsequently optimized toward a development candidate (DC) molecule with the best chances of clinical success. However, the DCs in the context of such optimization programs, as well as detailed characterization of major limiting factors, have not been investigated in detail so far. Here, we report an analysis of the historical DC molecules at Novartis since 2005 in the context of their optimization projects. Mapping the DCs into their respective chemical optimization series, we find that these tend to be synthesized rather early in a substantial number of cases. Further analysis of structural properties, ADMET, and potency-related readouts revealed that DC compounds tend to be generally significantly smaller, more permeable, and have higher ligand efficiency than other compounds sent to <i>in vivo</i> PK studies, which we also show for compounds from the same chemical series. Although this might seem obvious to most practitioners in medicinal chemistry, for all of these properties, we could show that they tend to evolve in an undesired direction during structure optimization. This highlights the difficulty of successfully translating our knowledge to medicinal chemistry optimizations.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2024-08-13
DOI
https://doi.org/10.1021/acs.jcim.4c00898
Citations
3
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.08

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article

Balancing Molecular Size, Activity, Permeability, and Other Properties: Drug Candidates in the Context of Their Chemical Structure Optimization

Nikolas Fechner, Finton Sirockin, Nikolaus Stiefl, Maximilian Beckers
3 citations
Journal of Chemical Information and Modeling
Computational Drug Discovery Methods
1.08
article

Balancing Molecular Size, Activity, Permeability, and Other Properties: Drug Candidates in the Context of Their Chemical Structure Optimization

Nikolas Fechner, Finton Sirockin, Nikolaus Stiefl, Maximilian Beckers
article en
3 citations

Abstract

Chemical structure optimization is a vital part of early drug discovery projects. Starting with compounds that show activity on the target of interest, the chemical structures are subsequently optimized toward a development candidate (DC) molecule with the best chances of clinical success. However, the DCs in the context of such optimization programs, as well as detailed characterization of major limiting factors, have not been investigated in detail so far. Here, we report an analysis of the historical DC molecules at Novartis since 2005 in the context of their optimization projects. Mapping the DCs into their respective chemical optimization series, we find that these tend to be synthesized rather early in a substantial number of cases. Further analysis of structural properties, ADMET, and potency-related readouts revealed that DC compounds tend to be generally significantly smaller, more permeable, and have higher ligand efficiency than other compounds sent to <i>in vivo</i> PK studies, which we also show for compounds from the same chemical series. Although this might seem obvious to most practitioners in medicinal chemistry, for all of these properties, we could show that they tend to evolve in an undesired direction during structure optimization. This highlights the difficulty of successfully translating our knowledge to medicinal chemistry optimizations.

Journal of Chemical Information and ModelingVol. 64(16)
Novartis (Switzerland) (CH)
Novartis
Openalex Percentile: Top 20%
Computational Drug Discovery Methods
1.08
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