22 October 2009

Infarmatik In-3D Library

In what we hope is a new series bringing the latest in Fragment Science up for discussion, we present today to you a discussion of Infarmatik's In-3D Library. We look forward to this discussion, and hopefully, many more.

Fragment based drug discovery has been shown to provide a rapid means for transforming low affinity “hits” to optimized leads. However, most currently available fragment libraries are limited in usefulness, mainly because over 90% of the molecules are planar and thus do not fit well into 3-dimensional receptor protein binding sites. InFarmatik realized [Ed: and others] that “real 3-D” structures offer a better fit within the uneven binding surfaces of protein hot-spots (business sites) than do planar compounds. To address this issue, we have developed a specific series of novel and diverse 3-D fragments, which are not available from any other commercial sources. The structure types of the first release contain 2,3, and 4 member non-aromatic ring systems, with various attachment points, including spiro and 1,2 anellation, 10 electron systems connected to saturated ring systems, saturated bis-heterocyclics and rod shaped compounds. We believe these compounds will exhibit the ability to bind to a wide array of protein targets. In addition, we can offer another 435 structures from existing stock, which conform to Ro3 and are quite “fragment-like”.

Most of the compounds have soft scaffold structures: meaning they were designed to have low reactivity centers to avoid non-specific binding, while preserving the ease of chemically coupling them to each other or to other fragments. The attachment points in the molecules in many cases are useful for regiospecific reactions.

Here are the relevant properties of the 3-D fragment library:
Size: 119 3-D Fragments
Average MW=230 Da
average logP value (calculated) =1.88
confirmed minimum water solubility of at least 0.1% in 2% aqueous DMSO.
Solubility data available for all compounds
Highly diverse, as shown by 3-D Diversity Analysis using ChemAxon supplied tools
Here are the relevant properties of the new standard fragment set
· Size: 435 Fragments
· Average MW=237.8 Da
· Average LogP value (calculated) =2.27

3 comments:

  1. This is an interesting approach, and it makes sense intuitively. Still, it may be a bit of an exaggeration to say that “most currently available fragment libraries are limited in usefulness, mainly because over 90% of the molecules are planar and thus do not fit well into 3-dimensional receptor protein binding sites”. While it is true that most active fragments reported are planar, it is not true that they don’t fit well into proteins: the six most advanced programs we’ve highlighted on this site (NVP-BEP800/VER-82576, DG-051, AT9283, PC190723, Indeglitazar, AT7519) all started with relatively planar fragments, and yet that didn’t keep them from (in most cases) making it all the way to the clinic.

    Moreover, as Brian Shoichet observed (and we discussed on June 14), it may not be a good idea to wander into biologically uncharted chemical space, no matter how structurally intriguing it appears. Infarmatik predicts that their 3-dimensional “compounds will exhibit the ability to bind to a wide array of protein targets”, which may be true. But, recalling the Hann complexity argument, it also seems possible that the fragments’ more chunky shapes will actually prevent them from binding to proteins.

    What do you think? Are 3-dimensional fragments over-represented among your fragment hits? Or underrepresented?

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  2. I don't know if an over-representation of 3D fragments is a good idea BUT I think that most of the binding site bind amino acids. And amino acids are not planar... So, maybe, 3D fragments will bind in a better way.

    The problem for me is that it will not be easy to do chemistry optimization on this 3D fragments.

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  3. There are some planar substrates (for kinases...) for which the obvious solutions would be planar structures.
    Still, we look at some targets now, where some 3D type of structures fit better in silico, especially, when specificity to mutant needed.

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