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Ligand-Based Lead Optimization

Ligand-Based Lead Optimization
Working Without a Target Structure

Even given the recent advancements in protein structure prediction, structure-based drug discovery approaches remain a challenge.
In many cases, the binding mode of a ligand, or sometimes even the target itself, remain unknown, hindering rational drug design efforts.

This is where computational method can be employed to screen for the best options to establish structure-activity relationships (SARs) to advance the campaign.

Exploring the Chemical Space Around a Compound with Analogs

Analogs of a molecules are the most important tools to establish SARs for a compound series. The presence or absence of functional groups and the effects of them on the biological activity of a compound dictate the direction of the next steps to optimize the potency, selectivity and ADME properties.

For this, chemically diverse analogs are synthesized or purchased and tested. Ideally, one works through each position of a molecule, testing a manageable range of functional groups (hydrophilic, lipophilic, bulky, small) to gain an overview of which modifications are tolerated and which impact activity. It can also be beneficial to substitute individual heteroatoms or modify the ring and chain systems within a molecule. Bioisosteres can already be considered at this stage, but it’s also possible to introduce them later to improve ADME properties.

Analogs Come in Different Flavors

As mentioned above, analogs to a compound can come in different forms.
They range from fine-grained modifications, where a single atom is replaced or added to the original molecule, to removal, additions, exchanges, or flipping of functional groups, up to core replacements for similar pharmacophores. Each approach has its own merits and explores the chemical space in a unique way.

The better the access to commercially available analogs, the faster one can gain groundbreaking insights. Here, too, the rule applies: the larger the selection of possible compounds, the better and more relevant the findings among them.
Combinatorial Chemical Spaces and the associated screening technologies bring both aspects together: They represent the largest collections of tangible (and commercially available) compounds and come with efficient methods to retrieve relevant results.
BioSolveIT software for Chemical Space exploration:
  • infiniSee: Chemical Space navigation platform with a graphical user interface.
    infiniSee retrieves relevant chemistry from ultra-large Chemical Spaces containing billions or even trillions of compounds based on their similarity to a query compound. Results are synthetically accessible per design in one or two steps and, in the case of our partners' Chemical Spaces, can be ordered directly to your table.
  • infiniSee xREAL: Exclusive platform to screen Enamine's largest compound catalog featuring trillions of compounds.
    infiniSee xREAL contains all features of infiniSee and supports all three Chemical Space exploration search modes.
Command-line tools for Chemical Space exploration:
  • FTrees: Pharmacophore-based similarity screen. Algorithm behind the Scaffold Hopper Mode.
  • SpaceLight: Retrieves close analogs based on molecular fingerprints. Algorithm behind the Analog Hunter Mode.
  • SpaceMACS: Performs maximum common substructure searches, as well as exact substructure mining. Algorithm behind the Motif Matcher Mode.

Augment Your Search with 3D Methods

Furthermore, ligand-based lead optimization can benefit from 3D methods.
The additional dimension allows for spotting potential new scaffolds that would remain hidden in a two-dimensional approach. In particular, the combination of scaffold hopping (infiniSee's Scaffold Hopper Mode/FTrees) and 3D alignment opens up possibilities to match the shape of the template compound with entirely new structural classes through ring system rearrangement.

BioSolveIT software for 3D LBDD:
  • SeeSAR's Similarity Scanner Mode: Ligand-based virtual screening.
Command-line tools for 3D LBDD:
  • FlexS: 3D compound alignment.

Further readings

Recent Advances in Ligand-Based Drug Design: Relevance and Utility of the Conformationally Sampled Pharmacophore Approach.
Acharya, C.; Coop, A.; E. Polli, J.; D. MacKerell, A.
Current Computer Aided-Drug Design 2011, 7 (1), 10-22.

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