Pharos-3D

Overview
Beyond the Flatlands: Why ULCLs Demand 3D Precision
Pharos-3D: Iptacopan Case Study
Pharmacophore Precision Constraints
A Customer Story
Getting Started
Access and Pricing
References

Overview

Pharos-3D is a novel computational 3D-similarity search method that leverages and combines 3D-shape and pharmacophore models for the efficient virtual screening of ultra-large combinatorial spaces. Pharos-3D screens these spaces to identify candidates that mimic the shape and binding profile of a reference compound, typically a known bioactive conformer.

Small molecules are a cornerstone of modern medicine, comprising the majority of approved therapeutics and showing a consistent rise in new approvals. In drug discovery, computationally assisted hit expansion via scaffold hopping and lead optimization are pivotal strategies for identifying structurally novel lead candidates that mimic shape and function of known active compounds. These approaches are essential for initiating new medicinal chemistry programs, as they provide pathways to secure and expand intellectual property (IP) and resolve liabilities related to ADMET (absorption, distribution, metabolism, excretion, and toxicity).

Beyond the Flatlands: Why ULCLs Demand 3D Precision

1. Overcoming the Limitations of Experimental Screening

The pharmaceutical industry faces a critical demand for continuous access to diverse, safe, and efficacious hits. However, the traditional process of experimental high-throughput screening (HTS) has become a bottleneck due to its prohibitive costs and time-intensive nature. To maintain drug discovery momentum, there is an urgent need to shift from physical screening to computationally efficient methods that can deliver high-quality leads at a fraction of the cost.

2. Transition to Ultra-Large Spaces

The reachability of significant chemical diversity within the immense chemical universe has made ultra-large combinatorial libraries ranging into the billions and trillions of compounds almost a household occurence for modern drug discovery. In 2D or the Flatlands, many current software solutions conquer these spaces efficiently and enable the exploration of 2D substructure and structure similarity within these ultra-large spaces.

3. The Necessity of Advanced 3D Algorithms

The spatial alignment and the interactions of drugs with their respective targets occur in 3D - almost all of the time. To improve the probability of finding viable drug candidates, virtual screening must go beyond the Flatlands. To handle this additional complexity, and in order to truly unlock the potential of the ultra-large combinatorial spaces, virtual screening tools are required to be efficient and exhaustive. Pharos-3D identifies all of those compounds in an ULCS that mimic the shape and interaction profile of an input reference compound, typically a known bioactive conformer.

Pharos-3D: Iptacopan Case Study

As an example result for Pharos-3D, below depicted are the best Pharos-3D alignments from each library with respect to the Pharos-3D Score together with the respective 2D projections of each compound. The Pharos-3D Score represents the shape similarity of the best matching low energy conformer to the query while considering potentially similar protein interactions. The score ranges from 0 to 1, indicating “no alignment” and “perfect alignment with equivalent interaction potential”, respectively.

For the six vendor spaces, we selected all Pharos-3D Scores larger than 0.7, and to retrieve structurally diverse hits from the result set, selected only hits with SkelSpheres Similarity smaller than 0.48. These selection rules yielded a set of 1395 hits, approximately 2.3% of all hits. To illustrate the similarity clustering of this selection, see below a similarity chart color-coded with respect to vendor library.

The SkelSphere Similarity measures 2D structural similarity based on the SkelSphere descriptor, and ranges from 0 to 1, indicating “no 2D structural similarity” and “2D structural identity”, respectively.

Pharmacophore Precision Constraints

Pharos-3D allows users to enforce exact structural requirements through the pharmacophore weighting option. For example, in the case of Adagrasib, a covalent KRAS G12C inhibitor, the fluorinated acrylamide was defined as an exact motif, to be held constant; consequently, the search algorithm will only return compounds that possess this specific structure. This capability streamlines the preselection of essential motifs required in the development of covalent inhibitors, PROTACs, and molecular glues.

To demonstrate this feature, the fluorinated acrylamide of Adagrasib was held constant, while a high pharmacophore weight was applied to the remainder of the (S)-2-(Piperazin-2-yl) acetonitrile scaffold. This configuration ensures that search results strictly adhere to the covalent warhead geometry while prioritizing the core scaffold. A high-scoring hit from the Alipheron collection is displayed below in 3D view video overlay.

Impact for Medicinal and Computational Chemistry Teams

• Medicinal Chemists: This capability enables researchers to strategically ’lock’ validated SAR elements, while exploring novel 3D chemical space. This facilitates scaffold hopping into unexplored chemotypes that maintain essential pharmacophoric features, thereby diversifying the intellectual property portfolio and identifying novel lead series with improved physicochemical profiles.

• Computational Chemists: By reducing noise and enriching the hit list with molecules that align closely with a query’s key chemical characteristics, this method enhances the probability of determining a subset with significant interaction potential with the target. It serves as a critical pre-screening filter before advancing to computationally demanding downstream methodologies.
  
  

A Customer Story

Getting Started

A virtual screen with Pharos-3D is performed via a plugin in DataWarrior by default, and via well-known commercial cheminformatics platforms by request. It is esssetnially the same than executing a Hyperspace search. Make sure, you have installed DataWarrior version v06.04.01 or newer. Then, install the Pharos-3D plugin, either by selecting Alipheron Pharos-3D from the Help->Trusted Plugins menu, or, if you have received a dedicated plugin for your own space, by putting that plugin-jar file into the DataWarrior plugin folder. Then, quit DataWarrior and re-launch it to get a new Alipheron->Pharos-3D Search... menu item. Select this item and the following dialog opens.

After selecting the space to be searched, you need to define your query conformer. A right mouse click in the query field opens a menu letting you paste in or load a molecule from a file or a ligand directly from the PDB database. You may change the protonation state of acidic or basic atoms and assign lower or higher importance to parts of the query conformer. Pressing OK submits your query definition to the server, which immediately starts to work on you request.

Pharos-3D searches are computationally demanding, because they involve the generation of conformers of thousands of partially assembled and also completely enumerated structures. A typical result of a Pharos-3D search contains thousands of molecules with 3-dimensional atom coordinates that match well the query structure. Typically, these molecules are ranked then by another method, e.g. ligand-protein docking, to determine a most promising subset to be ordered for synthesis at the provider of the space. For instance, docking can be performed using DataWarrior directly.

Access and Pricing

For licensing options, contact us at contact@alipheron.com.

References

• Flexophore, a new versatile 3D pharmacophore descriptor that considers molecular flexibility; M von Korff, J Freyss, T Sander; Journal of Chemical Information and Modeling, 2008, 48 (4), 797-810; https://doi.org/10.1021/ci700359j

• PheSA: An Open-Source Tool for Pharmacophore-Enhanced Shape Alignment; J Wahl; Journal of Chemical Information and Modeling, 2024, 64 (15), 5944-5953; https://doi.org/10.1021/acs.jcim.4c00516