Natural Product-like Compound Libraries

Natural products have been used for disease treatment from ancient times and have become an inspiration for modern drug discovery and development. Approximately 40 % of the developed drugs approved by the FDA during the last decades were natural products, their derivatives or synthetic mimetics related to natural products [1].

Remarkable structural diversity and drug-likeness of molecular scaffolds, identified in natural compounds, provide a basis for the design of novel natural product-derived compound libraries within attractive chemicals space for drug discovery and lead optimization [2-3].

Life Chemicals developed its proprietary Natural Product-like Compound Libraries of synthetic compounds similar to natural ones, generated through the following two approaches:

  • 2D fingerprint similarity search against commercial databases of Timetek, Specnet, Analyticalnalyticon, Selleck: 900 in-stock screening compounds
  • Superposition of chemoinformatics and substructure search methods applied to the entire Life Chemicals HTS Compound Collection with the selection of overlapping small molecules [2,4]: 2,000 compounds in stock

These screening compound collections are an extremely useful tool for high throughput screening (HTS) and high content screening (HCS) efforts.

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.

Natural Products-like Compounds Library by Similarity Search

The Library was designed by 2D fingerprint similarity filtering to natural compound scaffolds. The commercial databases of Timetek, Specnet, Analyticon, Selleck were used as the reference sets. A Tanimoto 85 % similarity cut-off was applied to obtain about 900 structurally diverse compounds, available from the Life Chemicals HTS Compound Collection.

Natural Products-like Compounds Library by Chemoinformatics and Substructure Search

The Life Chemicals HTS Compound Collection was analyzed by two different methods - a chemical descriptor calculation (7,300 compounds) and natural-likeness scoring (9,700 compounds). By overlapping both obtained sets, a chemical space of about 2,000 screening compounds with excellent characteristics in both studies was obtained.

Descriptor-based selection method

The selection has been done in two steps:

  1. Substructure search for natural-like scaffolds in the Life Chemicals Stock Collection. About 62,000 were selected from about 380,000 compounds.
  2. Validation of the method and calculation of the parameters listed in Table1 for Drugs (COBRA), Pure Natural Products (PNP, MNP), NPs and Derivatives/Analogs (SNP), and NP-Based Combinatorial Compounds (NatDiv).

values of descriptors which play the most important role in characterization of natural products.

Table 1. Mean values of descriptors which play the most important role in characterization of natural products.


Natural product-likeness calculator

Figure 1 shows the distribution of real natural products by the score.

Natural-likeness scoring was performed according to the workflow shown in Figure 2.

Natural product-likeness scorer. Distribution of real natural products.

Fig. 1. Natural product-likeness scorer. Distribution of real natural products.

Standard cross-platform view of Taverna 2.0 software with a schema of connections between files

Fig. 2. Standard cross-platform view of Taverna 2.0 software with a schema of connections between template files, natural-product likeness calculator and query file the HTS Compound Library

References

  1. D.J. Newman, G.M. Cragg. Natural products as sources of new drugs over the 30 years from 1981 to 2010. J. Nat. Prod., 75 (2012), pp. 311-335
  2. Properties and Architecture of Drugs and Natural Products Revisited. Kristina Grabowski and Gisbert Schneider.
  3. Matthew E Welsch, Scott A Snyder and Brent R Stockwell, Current Opinion in Chemical Biology 2010,141–15
  4. Natural Product-likeness Score and Its Application for Prioritization of Compound Libraries. Peter Ertl, Silvio Roggo, and Ansgar Schuffenhauer. J. Chem. Inf. Model. 2008, 48, 68-74
  5. Scaffold diversity of natural products: inspiration for combinatorial library design. Kristina Grabowski,a Karl-Heinz Baringhausb and Gisbert Schneider