Structural optimization

The MCE 1K Drug Fragment Library consists of 1,000 drug fragments. These drug fragments are derived from 2,946 FDA-approved drug molecules, and fragments from one drug can appear in other drugs, so these fragments are somewhat correlated with good PK/PD properties. Fragment-based screening can reserve enough chemical space for subsequent structural optimization. This compound library is an essential tool for drug screening based on FBDD (Fragment-Based Drug Discovery).

Fragment-based drug development (FBDD) is a strategy for drug discovery that can be applied both academically and commercially to enhance the identification of some non-drug targets. Fragment-based drug development has identified low molecular weight molecules (<300 Da) capable of binding to related macromolecules. These fragments can cover a wide chemical space and are easy to optimize later. Currently, several fragment-based drugs have entered clinical trials, of which two drugs, Vemurafenib and Venetoclax, have been approved for marketing.

Based on Tanimoto coefficient, MCE uses similarity algorithm to carefully select 2,323 high-structurally diverse 'RO3' compliant fragment molecules from large-scale fragment molecules, which can be applied to fragment based drug development.

The incidence and significance of central nervous system diseases are increasing at an alarming rate all over the world. Although substantial research efforts have been applied to develop new CNS-active drugs, only a few CNS disorders are addressed satisfactorily, while the remaining ones pose significant clinical challenges. Blood-brain barrier (BBB) permeability is one of the most important limiting factors in the design and development of novel CNS-targeted pharmaceuticals for the treatment of neurological disorders.

Carefully selected from the HTS Compound Collection to meet the parameters optimized for high BBB-permeability, our CNS Focused Screening Library comprising over 30,300 structurally-diverse and potentially CNS-active screening compounds. This original Screening Compound Library is aimed at supporting CNS drug design projects and HTS efforts in search for novel neurotherapeutics.

Fragment-based drug discovery (FBDD) is well suited for discovering both drug leads and chemical probes of protein function. 3-dimensionality (3D) diversity is pivotal because the molecular shape is one of the most important factors in molecular recognition by a biomolecule. There is a developing appreciation that 3D fragments could offer opportunities that are not provided by 2D fragments.

MCE 3D Diverse Fragment Library consists of 5,400 non-flat fragment-like molecules (average Fsp3 value 0.58). More than 4,700 fragment compounds contain at least one chiral center in the structure. The key concepts that underlie the library design were 3D shape, structural diversity, reactive functionality and fragment-like. This 3D Diverse Fragment Library brings higher fragment hit optimization and increases the likelihood to find innovative hits in FBDD.