Hit Identification

Hit identification is discovering compounds having the desired activity (10uM IC50) against a fully validated target. These should also be able to reproduce the activity upon retesting. In this critical step of the drug discovery process, the identified small molecules will bind to the target, usually a protein, and modifies its function.

Identifying the right hit is the key in research as it reduces the attrition rate. Depending on the nature of the project, Immunocure’s team applies the most appropriate hit identifying approach to successfully identify a hit series that are validated having the best chance of developing into drug-like compounds.

Immunocure provides a range of customized approaches to deliver high-quality, validated hits to help you succeed with your drug discovery research.

Computational Hit Identification service

Immunocure uses expert computational techniques coupled with AI to identify a hit.

Hit Identifying approaches

To successfully identify high-quality durable hit series, Immunocure chooses the following mentioned hit identifying approaches either individually or in parallel, depending on the nature of your project.

Structure-Based Virtual Screening

Structure-based virtual screening is a computational approach used to identify a hit. In this method:

1. Molecular docking of refined large 3D commercial databases into a given target protein will be performed.
2. Rescoring the hits using Implicit solvation binding energy (MMGBSA).
3. Identifying the hits based on the binding energy, hotspot interaction patterns using ML tools, and manual inspection.
4. The Hits were further checked for solubility, toxic groups, TPSA., target-based properties (For ex., MPO for CNS compounds).
5. *Molecular Dynamic Simulations of diverse hits to understand the stability and interaction patterns (Client request).

Ligand-based Virtual Screening

Screening of the compound databases using known active compounds. Ligand-based methods are the only chosen when no 3D structure of the target protein is available.

Pharmacophore-based Screening

1. Identifying the common features (Pharmacophore) of a set of known active compounds assuming binding to the same pocket of a given target.
2. Screening the databases and finding the hits which are geometrically fitting to the features of the pharmacophore.

Shape-based screening

1. Assuming the receptor recognizes the shape and electrostatic properties of bound molecules.
2. Identify new compounds with shapes and other properties that are similar to the conformations of known active compounds.

Similarity-based Screening

Finding compounds most similar to known actives in 2D topology (binary fingerprints).

Fragment-based Drug Design

1. Docking the fragment libraries as probes in the binding site to scan suitable molecular fragments that bind in specific pockets.
2. Join the molecular fragments with a linker to transform into a new hit.

Best scoring hits will be further evaluated to identify their analogs from various libraries. The analogs will be docked and calculated for binding energy. Thus for each scaffold of the hits, a set of best scoring analogs will be delivered to the clients to test for the potency and rough SAR.

Small molecule databases at Immunocure

1. Compound Libraries are collected from various commercial vendors, refined using various filters, and converted into 3D structures with  Chirality, Tautomers, Protonation states at pH 6.5-8.
2. Minimized to generate low energy conformation and ready to use for structure-based and ligand-based virtual screening.

Filters used to refine databases

1. Molecular Weight: < 550 dt
2. ClogP: < 5
3. HBA: < 10
4. HBD: < 5
5. Rotatable bonds: < 10
6. TPSA: < 150
7. PAINS Filter
8. Toxic functional groups
9. 5 rings
10. >3 fused rings
11. > 2CF3