Lead Optimization with PozeSCAF’s AxDrug Platform
Our integrated pipeline, driven by data-driven and physics-based methods, redefines the lead optimization process. Join us as we delve into the intricacies of our advanced approach to lead optimization.
The Power of AxDrug’s Integrated Pipeline:
PozeSCAF’s AxDrug platform boasts a comprehensive and integrated pipeline that combines data-driven and physics-based methods to generate compounds and optimize key parameters in lead optimization. Our approach goes beyond conventional methods, ensuring a holistic optimization of pharmacokinetics, pharmacodynamic properties, and multiparameter optimization (MPO).
Generative Chemistry for Library enumeration:
AxDrug’s generative chemistry takes center stage in lead optimization by conducting exhaustive enumeration of substituents on the lead compound based on binding pocket interactions. This innovative approach ensures a thorough exploration of the chemical space, leading to enhanced lead compounds.
Predictive Power of ADME Models:
Our platform leverages advanced ADME models to predict crucial pharmacokinetic permeators, including solubility, permeability, bioavailability, p-gp binding, and microsomal stability. This predictive power allows for informed decision-making in the selection and optimization of lead compounds.
Physics-Based Methods and Bio-Models:
PozeSCAF integrates physics-based methods and data-driven bio-models to optimize pharmacodynamic properties. The use of solvation and desolvation energies, coupled with overall binding affinity calculations through highly accurate quantum mechanics-based simulations (QM/MM), provides unparalleled insights into the interactions between ligands and receptors.
Free Energy Simulations for Prioritization:
Prioritizing lead compounds becomes a strategic process with PozeSCAF’s use of free energy simulations (FEP). Compounds are ranked based on the differences in their free energy of binding, ensuring that the most promising candidates move forward in the optimization journey.
Bio-Models: Unraveling Selectivity and Safety:
PozeSCAF’s bio-models, including drug-to-target network models, play a crucial role in assessing selectivity and polypharmacological effects. These models also evaluate structure-related side-effects and adverse drug events, providing a comprehensive safety profile for each lead compound.
Toxicity Predictive Models:
PozeSCAF’s commitment to safety extends to the predictive modeling of toxicity. Our advanced models predict carcinogenicity, mutagenicity, and various organ toxicities, ensuring that lead compounds are not only effective but also safe for further development.
PozeSCAF’s AxDrug platform stands as a beacon of innovation in lead optimization. Our integrated pipeline, powered by generative chemistry, predictive modeling, and advanced simulations, ensures that each lead compound is thoroughly optimized for success. Join us in revolutionizing drug discovery with a commitment to precision, safety, and transformative advancements.