Predicting Molecular Interactions in silico: I. A Guide to Pharmacophore Identification and its Applications to Drug Design

Abstract

A major goal in contemporary drug design is to develop new ligands with high affinity of binding toward a given protein receptor. Pharmacophore, which is the three-dimensional arrangement of essential features that enable a molecule to exert a particular biological effect, is a very useful model for achieving this goal. If the three-dimensional structure of the receptor is known, pharmacophore is a complementary tool to standard techniques, such as docking. However, frequently the structure of the receptor protein is unknown and only a set of ligands together with their measured binding affinities towards the receptor is available. In such a case, a pharmacophore-based strategy is one of the few applicable tools.Here we present a broad, yet concise guide to pharmacophore identification and review a sample of applications for drug design. In particular, we present the framework of the algorithms, classify their modules and point out their advantages and challenges.

Computational Analysis of Adhesion of Primer Ligands to Dentinal Collagen: Effect of Spacer Groups in Ligand and Amino Acid Residue Sequence Differences in Collagen

“…The presence of -GLY-residue in the triple helix is of importance in the stability of the triple helix motif in collagen structure. CGD is designed with the amino acid residue sequence of (PRO-HYP-GLY) 4 -(PRO-HYP-ALA)-(PRO-HYP-GLY) 5 and was selected because it has been synthesized and crystallographically characterized by Bella et al [12] as an important triple helix motif with a surrounding hydration structure. This structure was extracted from RCSB PDB [13] file 1CGD.…”

“…Bella et al showed that ALA substitution for GLY in the (PRO-HYP-GLY) sequence causes a slight expansion of the triple helix locally at the site of substitution. The residue sequence in QSU is given by (PRO-HYP-GLY) 4 -(GLU-LYS-GLY)-(PRO-HYP-GLY) 5 . The QSU model was synthesized and crystallographically characterized by Kramer et al [14] and is designated as 1QSU in the RCSB PDB.…”

“…Ligands are treated in their respective protonated states. In the HipHop algorithm, a pharmacophore model or hypothesis is generated as a distinct three-dimensional configuration of chemical functions located at centers of tolerance spheres [4,5,16]. A tolerance sphere defines that area in space that should be occupied by a specific type of chemical functionality in the bound ligand structure.…”

“…Such modeling is carried out using *Address correspondence to this author at the Department of Restorative Dentistry, University of Medicine and Dentistry of NJ, Newark, NJ 07103; Tel: --------------; Fax: -----------; E-mail: jvaidyan@umdnj.edu well known molecular modeling software programs such as Dock, AutoDock, Sybyl, Amber and many others programs, as described previously [3]. In the indirect ligand-based method, the common underlying 3-D alignment pattern of the functional features of known bioactive ligands (known as pharmacaphore) is generated from the low energy conformations of ligands [4,5]. In essence, molecules are considered active in a particular target if they carry a number of common features with favorable geometric placements in space to interact favorably with complementary features in a target.…”

Generation of multiple pharmacophore hypotheses using multiobjective optimisation techniques

“…Given a set of active molecules, pharmacophore methods involve analysing the molecules to identify pharmacophoric features (atoms or functional groups that can potentially interact with atoms in the binding site) and then aligning the active conformations of the molecules such that their corresponding pharmacophoric features are overlaid. A recent review on alignment methods is provided by Lemmen and Lengauer [1] and reviews on pharmacophore methods can be found in references [2][3][4].…”