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Small Molecules: Hit identification
Small Molecules: Hit-to-Lead optimization
Small Molecules: physicochemical properties
Small Molecules: ADME
Small Molecules: Toxicity
Small Molecules: Selectivity
Antibodies: Humanization and Optimization
Protein Modeling. Discovery
Protein Modeling: HERG binding
Protein Modeling: Albumin binding
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Virtual high throughput screening
Quantum Pharmaceuticals is pleased to offer pharmaceutical, biotech companies and research organizations a fast and accurate virtual screening of compounds for identification of prospective strong inhibitors for a given protein target. The QUANTUM technology capitalizes on a new paradigm in molecular modeling – applying quantum and molecular physics instead of statistical approaches (scoring function- like and QSAR-like methods).
The hit rate of predicted by Quantum inhibitors is about 50%, that is approximately 50% of selected by Quantum inhibitors will show high affinity in vitro!
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Predictive power of QUANTUM. |
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Case study: New Inhibitors of FtsZ - a Tuberculosis Target. |
The key advantages of Quantum technology are summarized 
here and in the table below.
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QUANTUM |
STATISTICAL SCORES |
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Accuracy |
+ (High accuracy independently from the structure of the compound) |
+/- (High accuracy for compounds similar to the training set; low accuracy for structurally distant molecules) |
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Potential to predict new classes of inhibitors |
+ (Uniformly high accuracy all over chemical space enables to identify novel classes of inhibitors) |
- (The predictive power of the methods dramatically falls for compounds structurally distant from the training set) |
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False positives |
Low rate (High selectivity due to detailed potential surface and exact thermodynamics.) |
Higher rate (Low selectivity owing to smooth and rough potential surface.) |
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Other Features |
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Understanding the nature of protein-ligand interactions |
+ (The method calculates free binding energy components allowing to understand which interaction plays leading role in the binding) |
- (The prediction is based on the measure of similarity, thus does not determine the magnitude of free binding energy components) |
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Protein flexibility |
+ (The calculations take into consideration protein flexibility) |
- (The methods consider proteins as rigid structures, that is particularly misleading for highly flexible proteins such as nuclear hormone receptors, kinases, HIV integrase etc.) |
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Need for a training set |
- |
+ |