Research Overview

My research integrates computational molecular design with experimental organic synthesis to develop and optimize small-molecule modulators of cytoskeletal regulatory proteins. By combining structure-based modeling, molecular docking, molecular dynamics simulations, and rational synthetic strategies, I aim to accelerate drug discovery through mechanistic insight and iterative structure–activity refinement.

My work is centered on bridging in-silico prediction with laboratory validation to create a closed-loop design–synthesis–evaluation workflow that reduces empirical trial-and-error and enhances the efficiency of lead optimization.

Rational Design of Arp2/3 Complex Inhibitors

The Arp2/3 complex plays a central role in actin nucleation and cytoskeletal dynamics, regulating processes such as cell motility, invasion, and pathogen-driven cytoskeletal remodeling. Dysregulation of actin polymerization pathways is implicated in infectious disease, cancer metastasis, and cellular motility disorders.

Building upon the CK-666 scaffold, I design and synthesize novel analogs aimed at improving binding affinity, selectivity, and mechanistic modulation of the Arp2/3 complex. My approach focuses on:

  • Strategic scaffold modification guided by structure-based analysis
  • Optimization of substituent patterns to enhance key hydrogen bonding and hydrophobic interactions
  • Fine-tuning steric and electronic properties to improve target engagement
  • Exploration of conformationally constrained analogs to improve binding stability

Computational modeling identifies key residues within the binding pocket and predicts favorable interaction geometries, which then inform synthetic prioritization. This rational workflow ensures that synthetic efforts are guided by structural and energetic insight rather than empirical screening alone.

Computational Drug Discovery Workflow

A central pillar of my research is the development and application of integrated computational pipelines for small-molecule discovery. My workflow includes:

Structure-Based Molecular Docking

I employ molecular docking to evaluate binding modes, interaction networks, and predicted affinity across rationally designed compound libraries. Binding pose validation is performed through interaction analysis and comparison with known inhibitor geometries.

Molecular Dynamics Simulations

Docking predictions are further validated through molecular dynamics simulations to assess:

  • Stability of ligand–protein complexes
  • Conformational flexibility
  • Binding pocket adaptability
  • Long-timescale interaction persistence

These simulations provide mechanistic insight into dynamic behavior beyond static docking poses.

Energetic and Interaction Analysis

I analyze hydrogen bonding persistence, hydrophobic contacts, π–π stacking interactions, and binding free energy trends to prioritize analogs for synthesis.

This computational framework enables predictive compound ranking, minimizing synthetic redundancy and focusing laboratory efforts on the most promising candidates.

Organic Synthesis and Analog Development

Complementing computational modeling, my research includes hands-on development of synthetic routes to small-molecule analogs. I focus on:

  • Rational modification of heterocyclic scaffolds
  • Optimization of substitution patterns informed by computational predictions
  • Development of efficient and scalable reaction conditions
  • Structure–activity relationship (SAR) mapping

Each synthetic analog is designed with a specific structural hypothesis in mind—whether targeting improved binding orientation, enhanced electronic complementarity, or increased rigidity to reduce entropic penalties upon binding.

The integration of computational prediction with experimental synthesis forms a feedback loop:

Design → Model → Synthesize → Evaluate → Refine

This iterative approach accelerates lead optimization and improves mechanistic understanding of molecular recognition.

Integration of Computational and Experimental Approaches

My research philosophy is grounded in the belief that modern drug discovery must seamlessly integrate computational precision with synthetic feasibility. Rather than treating modeling and synthesis as independent domains, I develop workflows in which:

  • In-silico screening guides synthetic prioritization
  • Experimental observations refine computational models
  • Mechanistic insights inform next-generation analog design

This integrated strategy reduces synthetic waste, improves efficiency, and enhances the likelihood of identifying biologically active compounds with optimized properties.

Future Directions

Moving forward, my research aims to:

  • Expand rational inhibitor design beyond single scaffolds to diverse heterocyclic frameworks
  • Incorporate enhanced free-energy estimation techniques for improved predictive accuracy
  • Explore dynamic allosteric modulation of cytoskeletal regulatory proteins
  • Integrate high-throughput computational screening with focused synthetic libraries

Ultimately, my goal is to develop a robust, transferable platform for rational small-molecule design that bridges computation and chemistry to address biologically relevant targets.

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