Ligand-based Pharmacophore Modeling

Ligand-based pharmacophore modeling has become a key computational strategy for facilitating drug discovery in the absence of a macromolecular target structure. Creative Biolabs is dedicated to establishing the most advanced in silico platform and providing one-stop pharmacophore modeling services to give comprehensive technical support for your projects.

Introduction to Ligand-based Pharmacophore Modeling

Ligand-based pharmacophore modeling is usually carried out by extracting common chemical features from 3D structures of a set of known ligands representative of essential interactions between the ligands and a specific macromolecular target. In general, pharmacophore generation from multiple ligands (usually called training set compounds) involves two main steps: creating the conformational space for each ligand in the training set to represent conformational flexibility of ligands, and aligning the multiple ligands in the training set and determining the essential common chemical features to construct pharmacophore models. Handling conformational flexibility of ligands and conducting molecular alignment represent the key techniques and also are the main difficulties in ligand-based pharmacophore modeling.

Two strategies have been used to deal with the problem of ligand flexibility:

The first is the pre-enumerating method, in which multiple conformations for each molecule are precomputed and saved in a database.
The second is the on-the-fly method, in which the conformation analysis is carried out in the pharmacophore modeling process.

The molecular alignment methods can be classified into two categories in terms of their fundamental nature: point-based and property-based approaches.

In point-based algorithms, pairs of atoms, fragments or chemical feature points are usually superimposed using a least-squares fitting.
The property-based algorithms make use of molecular field descriptors, usually represented by sets of Gaussian functions, to generate alignments. The alignment optimization is carried out with some variant of similarity measure of the intermolecular overlap of the Gaussians as the objective function.

Fig.1 Ligand-based pharmacophore modeling and screening.

Services

Pharmacophore models represent the spatial arrangement of ligand’s chemical features, such as hydrogen bond donors and acceptors, that are necessary for binding to its target protein. Ligand-based pharmacophores are important when no structural information about the target protein or the ligand’s active conformation is available. A set of structurally and functionally diverse ligands with known biological activities is used to build a pharmacophore model. Ligand-based pharmacophore modeling is very popular and has been implemented in the main commercially available molecular modeling packages such as Discovery Studio, MOE, Sybyl, or Phase. We can offer a variety of ligand-based pharmacophore modeling services to meet specific customers’ requirements.

Creative Biolabs has focused on the development of computational protein design for years, and we whole-heartedly cooperate with you to accomplish our shared goals. Our team provides you with outstanding support and meets your specific needs with a professional technology platform. If you are interested in our services, please contact us for more details.

All listed services and products are For Research Use Only. Do Not use in any diagnostic or therapeutic applications.

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