Future Labs: Bio-computational Resource Center

Bio-computational Resource Center

Given the diversity and complexity of life science related development and commercialization challenges off-the-shelf computational solutions rarely provide the specific functionality you require. In many instances, specific algorithms must be developed and/or adapted to your specific computing challenges.

Our Future Labs team can support your bio-computing needs via two potential modes of engagement:

  • Technology Guidance:  Our team will direct you towards an existing method or technique (if one exists). Your team then integrates the system on your own.

Example: Your team is interested in implementing an algorithm to cluster cell viability profiles. This information will be used as part of an automated screening assay. We will help you understand state-of-the-art techniques and will recommend methods that are best suited to your situation. We will walk you through requisite information and warn you about common pitfalls:

  • Custom Technology Development: Our team will work to support your specific development/commercialization challenge by creating a tailored computational solution.

Example: Your team needs a designed and implemented software tool for the same task as above, a method of automatically clustering and labeling cell viability profiles for use in a screening assay. After conducting a complete project requirements survey, we will construct and deliver a turn-key software solution. We will work to integrate the new tool with your development/commercialization efforts and can provide ongoing support.

Application of best-fit state-of-the-art computational tools can further enable you to:

  • Model complex physical systems
  • Compute the statistical significance of results
  • Rapidly process data and make data more interpretable
  • Predict outcomes to anticipate both positive and negative research results
  • Optimize human and capital resource allocation

Specifically our multidisciplinary team can support your life science centered development efforts towards (among others):

  • High throughput virtual screening: Fast and accurate high-throughput virtual screening of millions of compounds, providing consistently high enrichment against all types of protein targets
  • Similarity based ligand design: Rapid approach toward generating an expanded ‘hit list’ using existing ligand to identify new molecules possessing the same bioactivity as the original hit but occupy a different chemical/patent space
  • Fast and accurate homology modeling of proteins: Fast and accurate method for generating 3-D models for single chain proteins and protein-protein complexes purely from protein and/or DNA sequence information
  • Property prediction for molecules and virtual ADME calculations: Computational based approach toward ligand design to generate leads with optimal predicted ADME properties based on an initial ligand
  • Molecular dynamic simulations: GPU based molecular dynamic simulations of proteins using a number of different standard force fields and solvent molecules as well as “guess path” analysis that would represent starting points for structure based drug discovery
  • Accurate prediction of binding energy and structure based ligand design: Based on existing protein-ligand structure, we offer a number of possibilities including accurate prediction of a ligand mutation on binding affinity as well as structural basis for binding selectivity between related classes of proteins

Our team of scientific and technical professionals can play a valuable role in supporting your ongoing bio-computational needs.