3D-shaped Fragment Library | Fragment Libraries

A molecular shape, and in particular its 3D variety, is one of the essential prerequisites for a biomolecule to demonstrate its recognition of a specific geometry and affinity to the binding site having such a geometry [1]. Nonetheless, the vast majority of existing drugs have been centered on rather flat sp²-rich aromatic cores [2,3]. Moreover, the same core moiety can often be found in several medicines with different targeted diseases, leading to a low specificity (selectivity) and the rise of side effects [4]. Although most fragment libraries provide a high level of diversity, having been refined to contain the right balance of properties, they all tend to have a limited shape diversity [5,6].

In this context, it has been established that a higher three-dimensionality (3D) of molecules is a desirable feature of drug candidates, and it is one of the decisive factors to affect the successful passage of molecules at various stages of clinical development [7]. Using more complex, more 3D-like sp³-rich fragments would undoubtedly build up the drug-like fragment chemical space that might, in its turn, be advantageous in exploring more demanding biological targets.

Given the above, we have carefully designed a proprietary 3D-shaped Fragment Library of 15,000 non-flat fragment-like molecules for efficient fragment-based drug discovery (FBDD). The selection was focused on physicochemical properties and descriptors that allow evaluation of 3D-dimensionality and structural diversity of the fragment-like screening compounds. This Screening Set covers various molecule shapes: rod-like, disk-like, and spherical, with sufficient diversity shown in a triangle 2D normalized PMI plot (Fig. 1).

Additionally, a new 3D Fragment Subset by the narrowed PMI criteria that contain over 3,800 3D molecules is also offered within this Fragment Screening Library.

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

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

For a pre plated set based on this Screening Library, go over our Pre-plated Fragment Screening Sets.

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Compound selection

First, the Rule of Three with several filtering criteria was applied to the Life Chemicals General Fragment Collection. Principal moments of inertia (PMI) [1,7] calculation was used as an efficient method to calculate and evaluate 3D-dimensionality. Then, appropriate diversity levels of the Library were proved by applying the max Tanimoto diversity coefficient of 85 % (linear fingerprints were used). Finally, undesirable functionalities were eliminated by applying PAINS and our exclusive in-house medicinal chemistry filters. In total, around 15,000 readily available fragments, representing a variety of 3D shaped molecules, were selected for the Screening Library.

The following selection criteria were used to improve the functionality of 3D scaffolds in our Library:

Parameter	Range
MW	100 - 300
Fsp³	> 0.47
TPSA	< 100 Å²
Rotatable bonds	≤ 3.0
H-donors	≤ 3.0
H-acceptors	≤ 4.0
Chiral centers	≥ 1
Functionalization points	2
-CN, -NO2, Br count	≤ 1
S, Cl count	≤ 2
Ring count	1 - 4

The 2D-normalized PMI plot indicates high compound 3D diversity in Life Chemicals 3D Fragments Library.

Figure 1. The 2D-normalized PMI plot indicates high compound 3D diversity in Life Chemicals 3D Fragments Library.

Distribution of Life Chemicals 3D Fragments by Fsp3 values.

Figure 2. Distribution of Life Chemicals 3D Fragments by Fsp3 values.

3D-shaped Fragment Subset by the narrowed PMI criteria

The Rule of Three was applied to the Life Chemicals General Fragment Library. Next, their tautomeric forms were generated for all fragment molecules and principal moments of inertia (PMI) were calculated. All fragments not included in the exclusively 3D range on the graph (point 1: npr1 = 0.6, npr2 = 0.6, point 2: npr1 = 0.2, npr2 = 1.0, point 3: npr1 = 1.0, npr2 = 1.0) were discarded [8]. Finally, duplicates were removed from this 3D Screening Set. to result in over 3,800 non-flat structurally-diverse fragment-like molecules.

Figure 3. The 2D-normalized PMI plot indicates high compound 3D diversity in the 3D-shaped Fragment Subset by the narrowed PMI criteria.

Figure 3. The 2D-normalized PMI plot indicates high compound 3D diversity in the 3D-shaped Fragment Subset by the narrowed PMI criteria.

Representative compounds from the 3D Fragment Library

References

Kumar A, Zhang KYJ. Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery. Front Chem. 2018;6:315.
Morley AD, Pugliese A, Birchall K, et al. Fragment-based hit identification: thinking in 3D. Drug Discov Today. 2013;18(23-24):1221-1227.
Fa S, Yamamoto M, Nishihara H, Sakamoto R, Kamiya K, Nishina Y, Ogoshi T. Carbon-rich materials with three-dimensional ordering at the angstrom level. Chem. Sci., 2020,11, 5866-5873
Brooks WH, Guida WC, Daniel KG. The significance of chirality in drug design and development. Curr Top Med Chem. 2011;11(7):760-770.
Karawajczyk A, Orrling KM, de Vlieger JS, Rijnders T, Tzalis D. The European Lead Factory: A Blueprint for Public-Private Partnerships in Early Drug Discovery. Front Med (Lausanne). 2017;3:75.
Dahlin JL, Walters MA. The essential roles of chemistry in high-throughput screening triage. Future Med Chem. 2014;6(11):1265-1290.
Gregory Sliwoski, Sandeepkumar Kothiwale, Jens Meiler, Edward W. Lowe, Jr. Computational Methods in Drug Discovery. Pharmacol Rev. 2014 Jan; 66(1): 334–395.
Morrison CN, Prosser KE, Stokes RW, Cordes A, Metzler-Nolte N, Cohen SM. Expanding medicinal chemistry into 3D space: metallofragments as 3D scaffolds for fragment-based drug discovery. Chem. Sci., 2020,11, 1216-1225. https://doi.org/10.1039/C9SC05586J