Ligand efficiency indices for effective drug discovery: a unifying vector formulation

ABSTRACT

Introduction

The area of ligand efficiency indices (LEIs) in drug discovery has developed significantly since the initial publications nearly 20 years ago. A large number of different LEIs have been defined and applied with certain degrees of success and acceptance in the community. An overall view emphasizing more the common elements than the differences is needed.

Areas covered

In this review, the author accentuates the numerical and algebraic relationships among the different LEIs and proposes the notion of ‘ligand efficiency index’ (LEI) as a vector variable comprising two interrelated components that provide ‘direction’ and ‘distance’ along the drug discovery process. The same concept had been suggested before relating to the graphical representation of the content of Structure-Activity Databases (SAR-Databases).

Expert opinion

The extension of the concept of ligand efficiency from a scalar to a vector will help to unify the different formulations by emphasizing the relationship among the different variables. It should also provide an algebraically robust framework to critically assess the value of LEIs, and to incorporate them routinely in various workflows and protocols. Only cautious and rigorous testing by the community could provide a definitive proof of their possible value as reliable optimization variables in drug discovery.

KEYWORDS:

• Ligand Efficiency Indices (LEIs)
• Multiparameter Optimization in drug discovery
• Graphical representation of the Rule of Five (Ro5)
• Efficiency driven drug discovery
• Alternative variables in drug discovery
• Critical Assessment of Ligand Efficiency Metrics (CALEM)

Acknowledgments

The hospitality of the ChEMBL group at EBI directed by Dr John Overington is greatly appreciated. The guidance and help of Drs George Papadatos and Mark Davies within the group for the installation and implementation of the MyCHEMBL platform and KNIME modules is acknowledged. The collaboration with the group of Optibrium Ltd. and their hospitality and assistance is recognized.

Declaration of interest

C Abad-Zapatero has collaborated with Optibrium Ltd for approximately two months on the Software StarDrop^TM as a platform to validate ligand efficiency indices and for their incorporation into multiparameter optimization protocols. He has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Article highlights

The various definitions of ligand efficiency indices might suggest an impenetrable maze of formulae and expressions for the average medicinal chemist.

• The basic concepts are simple and interconversion factors and algebraic relationships can be easily found among the basic ones.

• The complexity can be reduced even further by introducing the concept of ‘Ligand Efficiency’ as a vector variable that conveys ‘direction’ and ‘distance’ as optimization parameters for the drug discovery process.

• This unifying and extended formulation relates the ‘direction’ of the drug discovery effort to the chemical scaffolds and their physicochemical properties, and the ‘distance’ to the affinity and activity toward their corresponding biological targets.

• The proposed formulation amounts to an algebraic and numerical framework for the ‘Rule of five’ (Ro5) guidelines. The content of the Ro5 provides an overall ‘direction’ to the drug optimization process, given the physicochemical properties of the compounds. The ‘distance’ can now be embedded in the various affinities included in the definition of the LEI vector.

• It is suggested that these concepts should be absorbed by the drug discovery community and implemented in prospective workflows using effective software tools that are already available.

• The community should make an effort to critically assess these concepts and tools to expedite drug discovery satisfying its societal obligations.

This box summarizes key points contained in the article.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

The author is supported indirectly by the University of Illinois at Chicago, Institute of Tuberculosis Research and Center for Biomolecular Sciences.