Ligand-based Drug Design

Introduction of Ligand-based Drug Design

One major class of methods integrating both ligand-based and structure-based drug-design methods is based on comparing or modeling protein-ligand interactions across similar protein-ligand systems. The aim is to identify key protein-ligand interactions from available physicochemical data and utilize the obtained interaction data to identify ligands with similar interaction profiles. This class of integrated methods can be further divided into two subcategories. The first subcategory, pseudoreceptor techniques, correlate similarities between ligands with measured biological activity and thereby establish a structural representation of the protein ligand-binding pocket. The other set of techniques is the converse of the first category. These methods analyze protein-ligand interactions from structural data to extract key types of interactions and translate that information into a simplified mathematical representation that can be used by similarity-based methods to screen for active compounds in ligand libraries. Many techniques from this category are based upon fingerprint or pharmacophore models.

Scheme of integrated methods. Fig.1 Scheme of integrated methods. (Wilson, 2011)

Application of Ligand-based Drug Design

Pseudoreceptor methods are primarily expansions of QSAR techniques, mainly 3D-QSAR techniques such as CoMFA, CoMSIA, and GOLPE. These QSAR techniques place physicochemical information onto 3D space surrounding a set of aligned reference compounds that bind into the same binding site of a common macromolecular target. Pseudoreceptor methods expand this mapping by attempting to create models of the target protein binding site around the ligand ensemble. These representative pseudoreceptor models are intended to contain key protein-ligand interactions and to map the appropriate shape and volume of these interactions. The aim of pseudoreceptor modeling is to generate surrogates of the 3D structure of the protein binding site that can be used for structure-based drug-design applications such as virtual screening, rationally modifying, or proposing new small molecules that are complementary to the pseudoreceptor model, and predicting binding affinities of potential ligands. Early pseudoreceptor methods involved the manual folding of peptide chains around the ligand ensemble but these methods have now grown to include a wide variety of automated computational methods. While there are many different ways of generating a pseudoreceptor, researchers divided pseudoreceptor methods into six categories: grid-based, partition-based, peptide-based, (iso)surface-based, atom-based and fragment-based methods.

Different types of pseudoreceptor concepts. Fig 2. Different types of pseudoreceptor concepts. (Wilson, 2011)

The other type of interaction-based methods, mainly protein structure-derived pharmacophore or fingerprint techniques, take an inverse approach to the integration of ligand-based and structure-based design as compared with pseudoreceptor techniques. Where pseudoreceptor methods attempt to analyze the similarity between ligands to derive computational models that mimic protein-ligand interactions, the pharmacophore, and fingerprint techniques analyze the existing structures of one or more protein-ligand complexes to generate a computational representation of important protein-ligand contacts. The generated mathematical representation is subsequently used in similarity searching to find ligands that match the interaction profile. These fingerprint or pharmacophore techniques share the concept of simplifying complex protein-ligand structural data in order to identify a small number of key interactions. These methods are divided into three different categories: pharmacophore-based methods, fingerprint-based direct encoding methods, and fingerprint-based indirect encoding methods.

Ligand-based drug design has shown its great importance in drug discovery methods. With years of accumulation, Creative Biolabs has established a comprehensive technology platform offering a variety of drug discovery-relevant services to global customers. If you are interested in our services or you have any other questions, please feel free to contact us for more information.


  1. Wilson, G. L. and Lill, M. A. Integrating structure-based and ligand-based approaches for computational drug design. Future Med Chem. 2011, 3(6): 735-50.
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