Dr. Shenkin is a Vice President at Schrödinger and CombiGlide Product Manager. In this column he discusses some of the customer-requested features scheduled to appear in the next release of CombiGlide.

First released as part of the 2006 Schrödinger Suite and substantially enhanced for its forthcoming release as part of the 2007 Suite, CombiGlide uses in-silico combinatorial synthesis and docking to assist researchers in identifying and optimizing lead compounds.

In addition to significant improvements in robustness and speed, CombiGlide 2007 introduces a number of features based on user feedback – chief among new capabilities are core hopping and chemical-feature analysis.

Core hopping. Given a lead compound, there are many common reasons why researchers may wish to identify an alternative core. For example, a more rigid core can lead to stronger binding, while a core with additional functional groups can pick up better receptor interactions. An alternative chemical scaffold can also result in more selective binding, leading to diminished side effects and lower toxicity.

Furthermore, most projects in the discovery stage require one or more back-ups, in case chemical or biological issues should force the current lead molecule to be abandoned. Intellectual-property considerations can also make an alternate scaffold desirable.

CombiGlide scaffold hopping begins with a well-docked template (for example, a lead compound) that contains user-defined splits between the core and side chains. While the traditional use of CombiGlide holds the core constant and varies the side chains, the core hopping algorithm instead screens candidate cores while holding the side chains constant. The algorithm attempts to find new cores that bind well to the receptor and maintain compatibility with the side chains of the lead compound.

CombiGlide 2007 comes equipped with a library of cores for screening. Users can easily augment this library to use cores from proprietary sources, the literature, or even just a set of hypothetical proposals.

A unique feature of CombiGlide's core hopping is its ability to add linker groups where needed to allow for size and shape matching between the template and the candidate cores to be matched.

We are very excited about our initial results from core hopping and are looking forward to user response.

Chemical-feature analysis. CombiGlide users have also expressed a desire to use the program to explore and better define the chemical interaction between a receptor and side chains associated with a given core position. Some chemists regularly perform combinatorial synthesis using side-chain collections designed primarily for determining functional-group preferences rather than for optimizing drug activity. Chemical-feature analysis enables CombiGlide to be used for the same purpose.

Chemical-feature analysis begins with a normal CombiGlide run, using a diverse side-chain collection and a user-supplied core and receptor. Upon completion of the CombiGlide run, the "Chem Features" panel is invoked from the "Analyze Library" stage of the user interface.

Several measures are available. The Site Selectivity plot shows how selective each side-chain position is for chemical features. For example, a position where the strongly binding compounds contain only hydrogen-bond donors will be more selective than a site that allows both donors and hydrophobes. When performing lead optimization, researchers might reasonably suspect that the greatest "bang for the buck" can be obtained by optimizing the most selective position.

CombiGlide 2007 also supplies tools to characterize the nature of the selectivity. For each site, we show how the frequency of occurrence of the various pharmacophore-like features in the strongly binding compounds compares with that in the original side-chain collection.

CombiGlide also displays more detailed plots showing how the combinations of features compare; for example, the user might display a chart making it immediately apparent that site is especially enriched in sidechains containing, say, both hydrophobes and acceptors. These plots, graphs and metrics provide chemical guidance for further chemical variation and optimization.