Structure-Based Discovery & CADD
I provide end-to-end computational support for drug discovery, transforming target validation into lead optimization. By integrating high-throughput virtual screening with rigorous thermodynamic analysis, I bridge the gap between in silico predictions and experimental synthesis.
Computational Hit-to-Lead Optimization
My approach integrates large-library virtual screening with rigorous thermodynamic integration. I specialize in docking against flexible protein targets, accounting for induced-fit effects and water-mediated interactions to ensure high-affinity binding predictions that align with desired experimental profiles.
Rational Design of New Chemical Entities (NCEs)
I lead the design process using both ligand- and structure-based approaches. This involves directing CADD efforts to ensure the alignment of drug development with the requirements of chemical synthesis, novelty, and ADMET properties. My workflow includes:
- Integrated Drug Design: Incorporating various physiological states of target proteins into the CADD pipeline.
- QSAR & QSTAR Analysis: Conducting quantitative structure-activity relationship modeling, including compartmental system distribution analysis.
- IP Strategy: Conducting comprehensive intellectual property evaluations to ensure that the novel aspects of designed compounds are identified and protected within patent applications.
Predictive Modeling & Pharmacokinetics
I used a combination of Computational Modeling, PBPK (Physiologically Based Pharmacokinetic) modeling, and Molecular Dynamcis Simulatins to evaluate and re-calculate biological activity. This ensures that Clinical Candidates (CCs) are optimized for bioavailability and toxicity before moving into preclinical stages.