Abstract
Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximize the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.
Highlights
Fragment-based drug discovery (FBDD) has been developed in the past twenty years as an approach to derive novel lead compounds for various therapeutic targets [1,2,3,4]
The exact size-diversity relationships for fragment libraries are affected by several factors, including the fragments available for selection, the selection method, and the diversity metric
Using fluorinated fragments as an example, we have shown that similar size-diversity relationships are observed for this subset of available fragments
Summary
Fragment-based drug discovery (FBDD) has been developed in the past twenty years as an approach to derive novel lead compounds for various therapeutic targets [1,2,3,4]. It features the use of fragment-sized compounds that mostly comply with the ‘Rule-of-30 [5] for the identification of hits, which can be subsequently developed into potent lead compounds. More efficient structural optimization of fragment hits [9] With these advantages, FBDD has gained popularity in both academia and industry in recent years [10], and led to the discovery of three. The diversity of a fragment library should be the most
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