|...Research Assistant & Associate for Scientific Informatics
Our molecular mining suit “RAASITM”, (Research Assistant & Associate for Scientific Informatics) will revolutionize research in Bioinformatics/ chemoinformatics/Life Science Informatics. RAASI contains many different modules like:
Biomedical data or Chemical data is stored in unstructured or semi-structured formats. Often a single term is linked to structures, sub-structures, Ids or pathways. Moreover, the biomedical literature is a complex set of information. It makes use of heavy domain specific terminologies. And extraction of useful information while maintaining all the links and relevance is quite a challenge. But LitSpecTM of RAASITM suite can be used to solve such problems. The unstructured cumbersome information can be converted into knowledge by LitSpecTM.
ProtSpecTM of RAASITM suite is one of the most utilitarian applications for building protein – protein, protein- ligand, ligand- ligand network. ProtSpecTM specializes in building a connected network of proteins and ligands thereby enabling the users to get a better view of the related proteins and ligands, which in turn reduces the quantum of work required to find a suitable/ related ligand/protein for in-silico drug designing.
VituoSpecTM of RAASITM suite designs virtual library based on Pharmacophore, Functionophore and customized scaffolds. Virtual library designing helps in creating an array of chemical structures which can be used in ligand-based or target-based in-silico Drug Designing. We use descriptors and fingerprints to create the desired virtual library.
BioSpecTM of RAASITM suite basically predicts the qualitative Biological Activity Spectrum of small molecules. BioSpecTM is designed to assists users to quickly understand the various drug targets, biological processes and therapeutic areas where a structure may be useful. The BioSpecTM Predictions can be applied in various areas like drug target identification, lead discovery and identification, compound selection for vHTS or HTS. Besides, it also assists users in drug repositioning, buying chemical libraries, exploring in-house corporate molecular libraries.
Every drug has a therapeutic index, and no drug can be said to be free of toxicity. So it is essential to know whether a drug molecule is likely to prove toxic in the given therapeutic range. Even if a molecule is toxic, it may not be reasonable to throw it out of the pipeline initially, as the positioning of the drug may well decide if the toxic effect can be disregarded. Hence toxicity prediction is a very critical step in the drug development life cycle.
We introduce ToxSpecTM, as a module in our RAASITM suite, adapted for Toxicity and Side Effect alert based on 2D molecular structure. We advocate usage of ToxSpec as a tool to flag potential problems and not as something to help discard promising drug candidates. The situation is complicated by the fact that the toxicity that is present or absent in animal models may not always show up in human beings. Many a times, it is the metabolites and not the dosed molecules that are toxic. Hence, any toxicity prediction approach should flag the mechanistic reasons behind a prediction and not merely give a Boolean answer.
The "ADME" acronym is commonly used in the pharmaceutical industry to indicate all the phenomena associated with Absorption, Distribution, Metabolism, Elimination. Silent feature of ADMESpecTM of RAASITM suite
- High accuracy
- High Speed
- Easy to use
- Batch processing
ADME incoming modules:
- Blood-brain Barrier(BBB),
- Blood-to-plasma concentration ratio
Automatic generation of chemically meaningful precursors and their reasonable validation is a main challenge for industry experts. RexnSpecTM of RAASITM suite works on Retrosynthesis technique based on functional group strategy. RexnSpecTM plan a synthesis backwards, by starting at the product, the "target" and taking it back a step at a time to simple, available starting materials or precursors. RexnSpecTM provides vendor list for starting material or precursor of target molecule. RexnSpecTM also predicts target molecules biological reaction pathways information.
Three-dimensional molecular structure is one of the foundations of structure-based drug design. Often, data are available for the shape of a protein and a drug separately, but not for the two together. Docking is the process by which two molecules fit together in 3D space. But docking can eat up a lot of preious time if we have a large library of lead molecules. To speed up the docking process RASA has introduced DockSpeckTM , which is basically a pre-docking application. It allows the user to test whether the molecule is dock-able or not and if its dock-able then how well does it dock. This pre-docking analysis will help the user to save time and perform docking only with the molecules which fit well.