Pharmacophore-based drug design represents a powerful strategy in drug discovery, capitalizing on the distinctive features of known active molecules to identify or craft novel compounds with the potential to bind to specific target proteins. This approach is instrumental in modulating the activity of target proteins, be they receptors, enzymes, or transporters, implicated in diverse biological processes or diseases. The central goal of pharmacophore-based drug design is to discover compounds capable of influencing the target protein—acting as agonists, antagonists, or modulators.

Methods

Pharmacophore models serve as blueprints, encapsulating essential features required for the interaction between a ligand and a receptor. These models can be derived through two main approaches: structure-based and ligand-based. In the structure-based approach, models are crafted from the three-dimensional structure of the target protein, employing methods such as molecular docking, molecular dynamics, or X-ray crystallography. Conversely, the ligand-based approach involves the alignment and superposition of known active ligands, using methods like similarity search, cluster analysis, or machine learning.

Virtual Screening

Pharmacophore models play a pivotal role in virtual screening, allowing for the in silico screening of extensive compound libraries. This process identifies compounds that align with the pharmacophore features, offering a high likelihood of binding to the target protein. Virtual screening streamlines drug discovery by excluding inactive or undesirable compounds, thereby minimizing both time and costs. Moreover, it aids in understanding how structurally diverse ligands can bind to a common receptor site, revealing shared pharmacophore features influencing binding affinity and specificity.

De Novo Design

Beyond virtual screening, pharmacophore models guide de novo design—suggesting modifications or additions to existing ligands. This innovative process yields novel compounds with enhanced potency and selectivity, addressing limitations of current ligands, such as poor solubility, toxicity, or resistance.

Success Across Therapeutic Areas

Pharmacophore based drug design has been successfully applied in different therapeutic areas, such as infectious diseases, cardiovascular diseases, inflammation, pain, cancer, and neurodegenerative diseases. Some examples of drugs that have been discovered or developed using pharmacophore based drug design are:

•  Saquinavir, ritonavir, and indinavir, which are inhibitors of HIV-1 protease, a key enzyme for the replication of the virus. These drugs were designed using structure-based pharmacophore models derived from the X-ray crystal structure of the enzyme.
• Losartan, valsartan, and candesartan, which are antagonists of the angiotensin II type 1 receptor, a target for the treatment of hypertension and cardiovascular diseases. These drugs were designed using ligand-based pharmacophore models derived from the alignment of known active ligands.
• Ajulemic acid, which is a modulator of the cannabinoid receptor 2, a target for the treatment of inflammation and pain. This drug was designed using ligand-based pharmacophore models derived from the superposition of known active ligands.

In conclusion, pharmacophore-based drug design stands as a cornerstone in the pursuit of novel therapeutic interventions. Its ability to harness molecular insights and guide the creation of compounds with targeted interactions positions it as a vital methodology in the ongoing quest for innovative and effective pharmaceutical solutions.

References

(1) Pharmacophore methods (Chapter 9) – Drug Design. https://www.cambridge.org/core/books/drug-design/pharmacophore-methods/355560AFD7D1999E3838711193EDEABC.

(2) Drug Design by Pharmacophore and Virtual Screening Approach – MDPI. https://www.mdpi.com/1424-8247/15/5/646.

(3) Drug Design – Drug Design Org. https://www.drugdesign.org/chapters/drug-design/.

(4) Advances in Pharmacophore Modeling and Its Role in Drug Designing. https://link.springer.com/chapter/10.1007/978-981-15-6815-2_10.