Computer-Assisted Molecular Design Resources
  • Structural/functional analysis for disease related biological process
  • Computer-aided therapeutic discovery and development
  • Provide the High-Throughput Screening Core with data analysis and data management assistance.
  • Provide consultation, interpretation, and visualization of analysis results
  • Develop novel tools for analysis
  • Create laboratory information management systems (LIMS) for sample and experiment inventory as well as automated data pre-processing pipelines
  • Provide software (such as PyMol, NAMD, etc.) to assist users with their own analysis
The following types of drug-discovery initiatives are currently supported:
 
  1. Biomarker Analysis: An in depth understanding and analysis of the biological functions and 3D structural relationships of therapeutic targets (protein, small RNA, organic compounds) are essential for understanding the molecular mechanisms and binding modes of these tertiary complex interactions. Virtual screening can be performed on the 3D structure and binding sites based on the X-ray structure and/or predicted homology model.  Ligand-based virtual screening can be performed by 2D and/or 3D tools (developed in house) as well as the compounds library database to find analogues among more than 15 million drug-like compounds.
     
  2. Chemical Library Preparation: The drug candidates are screened from a collection of chemical libraries that the BIC core has collected.  Millions of compounds from various commercial and public libraries have been integrated.  The BIC core also filters HTS results based on HTS and ADMET requirements to help reduce the redundancy, as well as false positive and false negative hits.
     
  3. Lead Identification: Structure-based or ligand-based virtual screening is conducted, as well as 2D/3D structure similarity compound searches among several million candidates from the NCI DTP, UCSF ZINC, NCBI Pubmed and COH HTS compound libraries.
     
  4. Lead Optimization: The lead compounds are further optimized by computational chemistry methods such as Molecular Dynamic Simulation and QSAR analysis.
     
  5. Pre-clinical Trial: The drug candidates obtained from the virtual screenings are readied by the investigator for pre-clinical trials.  The experimental results are then fed back through the drug-design process for drug refinement.