Ultimate Fragment Library

FBDD allows a reduction of the screening library size and coverage of larger unexplored and underrepresented chemical space. It provides more straightforward starting points for subsequent chemical optimization of initial hits.

The process of fragment synthesis obeys a heuristic rule called the Rule of Three. A state-of-the-art tuning of the Rule of Three parameters helps to generate small-molecule compounds with improved ADME profile for efficient lead identification by FBDD and HTS.

The Life Chemicals Ultimate Fragment Library was designed by applying the ultimately refined picking approach to our HTS Compound Collection: the Rule of Three and the TPSA ≤ 80 Å2 cut-off. It is known that more than 80 % of drugs on the market have an estimated logSw value greater than -4. Thus, solubility filtering was also used to design this Fragment Subset.

Finally, PAINS and in-house developed filtering parameters, such as toxicophore and undesired functionalities, were applied to make up this compound set.

The Life Chemicals Ultimate Fragment Collection comprises nearly 7,500 drug-like fragments. Physicochemical parameters used to create the Ultimate Fragment Library are as follows:

 

Parameter

Range

Average Values

MW

150 - 300

218.35

ClogP

-2 - 3

1.15

TPSA

< 80 Å2

47.03

Rotatable bonds

≤ 3.0

2.14

H-donors

≤ 3.0

1.25

H-acceptors

≤ 3.0

2.36

ClogSw

≥ -3

-1.9

Halogens (except F)

≤ 1

≤ 1

S atoms

≤ 1

≤ 1

Ring count

1 - 3

1 - 3

Fused rings

≤ 2

≤ 2

Benzene count

≤ 1

≤ 1

 Figure 1. Average values for the main physicochemical parameters for the Ultimate Fragment Library compounds

 Ultimate Fragment Library  representative compounds

Figure 2. Representative compounds from Ultimate Fragment Library

 

References

  1. Erlanson, D. A.; McDowell, R. S.; O’Brien, T. Fragment-based drug discovery. J. Med. Chem. 2004, 47, 3463–3482.
  2. Rees, D. C.; Congreve, M.; Murray, C. W.; Carr, R. Fragment-based lead discovery. Nat. Rev. Drug Discovery 2004, 3, 660–672.
  3. Bian Y1,2,3, Xie XS4,5,6,7,8. Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications // AAPS J. 2018 Apr 9;20(3):59. doi: 10.1208/s12248-018-0216-7.
  4. Price AJ1, Howard S1, Cons BD2. Fragment-based drug discovery and its application to challenging drug targets // Essays Biochem. 2017 Nov 8;61(5):475-484. doi: 10.1042/EBC20170029.
  5. Mello JDFRE1, Gomes RA1, Vital-Fujii DG1, Ferreira GM1,2, Trossini GHG1,2. Fragment-based drug discovery as alternative strategy to the drug development for neglected diseases // Chem Biol Drug Des. 2017 Dec;90(6):1067-1078. doi: 10.1111/cbdd.13030.

The Life Chemicals Ultimate Fragment Library was designed by applying the ultimately refined picking approach to our HTS Compound Collectionstock screening compound collection: the Rule of Three and the TPSA ≤ 80 Å2 cut-off. It is known that more than 80 % of drugs on the market have an estimated logSw value greater than -4. Thus, solubility filtering was also used to design this Fragment Subset.