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3D Compound Libraries for HTS

The 3D shape of a free ligand is a crucial feature for its molecular recognition by the desired biomolecule and its affinity to the binding site [1]. In order to bind strongly to a protein target, the drug ligand should first adopt the suitable conformation and spatial complementarity to fit efficiently into the binding site. If a dramatic change of the molecular shape is necessary, it would require a lot of activation energy, making such a compound unsuitable as a drug. In contrast, if the molecule is already in “bioactive conformation” (suitable shape for binding), it is more likely to bind strongly and be a good drug.

Non-planar screening compounds with diverse and well-developed 3D shapes have become the most attractive ones for HTS in drug discovery projects in the last few years. Higher three-dimensionality (3D) of hit compounds has been shown to correlate with their successful passage of various clinical development stages [2].

Undoubtedly, the use of more complex, more 3D-like sp3-rich screening compounds can significantly add to chemical space that might, in turn, be advantageous in exploring more demanding biological targets.

At present, readily accessible for your selection are the following proprietary collections of 3D-shaped drug-like screening compounds (Fig. 1-3):

Additionally, we offer the 3D-shaped Fragment Library of 15,000 non-flat fragment-like molecules for efficient fragment-based drug discovery (FBDD).

The compound selection can be customized based on your requirements, cherry picking is available.

Please, contact us at orders@lifechemicals.com for any additional information and price quotations.

For a pre plated set based on this Screening Library, please explore our Pre-plated Focused Libraries.

Further exploring our related products will make your search even more rewarding:
 

3D-shaped Diversity Compound Library

The so-called "3D-shapeness" is defined by thresholding principal moments of inertia (PMI), plane of best fit (PBF) parameters, Fsp3, and several other descriptors that are currently the best metrics describing molecular shape. However, none of the indicators is one hundred percent reliable. The Life Chemicals HTS Compound Collection was filtered by means of PMI, the most efficient method of those applied today [3-5], enabling us to obtain more than 244,000 molecules. Then, the selection was narrowed down by chemical diversity to provide over 24,800 3D-enriched small molecules that cover a broad chemical space.

Figure 1. PMI distribution in the 3D-shaped Diversity Compound Library.

Figure 1. PMI distribution in the 3D-shaped Diversity Compound Library.

Figure 2. Physicochemical value distributions of the compounds in the 3D-shaped Diversity Compound Library.

Figure 2. Physicochemical value distributions of the compounds in the 3D-shaped Diversity Compound Library.

Representative screening molecules from the 3D-shaped Diversity Compound Library:

3D-pharmacophore-based Diversity Library

The Life Chemicals HTS Compound Collection was filtered by a number of physicochemical and three-dimensionality parameters selected based on publications (details in Table 1) [2, 6-8]. The obtained subset was further refined by the PAINS filters together with toxicophore and undesired functionalities filters developed in-house. The compound collection was narrowed down by the structural diversity to result in over 8,800 3D-shaped drug-like screening compounds.

Table 1. Physicochemical parameters for 3D-shaped Diversity Compound Library

Physicochemical parameter Range Average Value
MW 250-500 353.74
FSP3 ≥0.35 0.47
  ClogP ≤10 2.04
TPSA ≤140 79.44
H-acceptors ≤10 4.05
H-donors ≤5 1.30
Rotatable Bonds ≤10 4.69
Molecular Flexibility ≥0.35 0.47
Molecular Complexity ≥0.53 0.79
Rings ≥ 1 3.24
npr1 ≥ 0.15 0.21
npr2 ≥ 0.85 0.91
Structure in-house filters all

Figure 3. Physicochemical value distributions of the screening compounds in the 3D-pharmacophore-based Diversity Compound Library.

Figure 3. Physicochemical value distributions of the screening compounds in the 3D-pharmacophore-based Diversity Compound Library.

Representative screening molecules from the 3D-Pharmacophore-based Diversity Library:

References

  1. Kumar A, Zhang KYJ. Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery. Front Chem. 2018;6:315.
  2. Sliwoski G, Kothiwale S, Meiler J, Lowe EW Jr. Computational methods in drug discovery. Pharmacol Rev. 2013;66(1):334-395. doi:10.1124/pr.112.007336
  3. Morrison CN, Prosser KE, Stokes RW, Cordes A, Metzler-Nolte N, Cohen SM. Correction: Expanding medicinal chemistry into 3D space: metallofragments as 3D scaffolds for fragment-based drug discovery. Chem Sci. 2022;13(32):9450-9452. Published 2022 Aug 5. doi:10.1039/d2sc90145e
  4. Asawa Y, Hatsuzawa S, Yoshimori A, et al. Comprehensive exploration of chemical space using trisubstituted carboranes. Sci Rep. 2021;11(1):24101. Published 2021 Dec 16. doi:10.1038/s41598-021-03459-6
  5. Tarbeeva DV, Krylova NV, Iunikhina OV, et al. Biologically active polyphenolic compounds from Lespedeza bicolor. Fitoterapia. 2022;157:105121. doi:10.1016/j.fitote.2021.105121
  6. Firth NC, Brown N, Blagg J. Plane of best fit: a novel method to characterize the three-dimensionality of molecules. J Chem Inf Model. 2012;52(10):2516-2525. doi:10.1021/ci300293f
  7. Meyers J, Carter M, Mok NY, Brown N. On the origins of three-dimensionality in drug-like molecules. Future Med Chem. 2016;8(14):1753-1767. doi:10.4155/fmc-2016-0095
  8. Batool M, Ahmad B, Choi S. A Structure-Based Drug Discovery Paradigm. Int J Mol Sci. 2019;20(11):2783. doi:10.3390/ijms20112783
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