Overview

Virtual screening utilizes computer-based molecular docking software to simulate the interaction between a target and a drug candidate, calculating the magnitude of affinity between the two to predict possible potential drugs. Through virtual screening, drug designers are exempted from the consumption of financial resources, energy, and time brought by traditional experimental screening, which narrows the cycle and investment of drug development. Virtual screening technology has become an important tool in today's drug development.

Our Services

• Structure-Based Virtual Screening

We offer customized solutions for structure-based virtual screening to accurately assess ligand binding to target proteins, thereby helping to identify novel small molecule inhibitors and drug candidates.

• Ligand Virtual Screening

Our advanced ligand virtual screening methodology allows us to efficiently identify structurally diverse compounds with potential therapeutic activity, thereby enhancing the process of new drug identification and lead optimization.

• Fragment-based Virtual Screening

Our fragment-based virtual screening service provides a systematic approach for identifying fragment-sized molecules that can be optimally combined to design effective lead compounds.

• Machine Learning Assisted Virtual Screening

Leveraging the power of machine learning, our service combines predictive modeling and data-driven algorithms to improve the accuracy and efficiency of virtual screening campaigns.

Service Process

Applications

• Identification of potential drug candidates
• Drug repurposing or repositioning
• Medicinal chemistry campaigns
• Structure-based drug design

Advantages

• Ligand-based and structure-based virtual screening
• Super high-performance computer
• 3D pharmacophore model building
• Consideration of water and solvation effects

Screening Process

• Target research
• Model building
• Preparation of small molecule compound library
• Molecular docking/pharmacophore mapping
• Scoring/ranking
• Compound selection

Our Algorithm

Our algorithmic techniques include stochastic algorithms, machine learning-based QSAR techniques, genetic algorithms, and molecular dynamics-based methods. These algorithms can efficiently comb through vast libraries of chemical structures to help identify potential molecules for drug design projects.

Deliverables

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