8 research outputs found
Making SharePoint<sup>® </sup>Chemically Aware™
Abstract Background The use of SharePoint® collaboration software for content management has become a critical part of today's drug discovery process. SharePoint 2010 software has laid a foundation which enables researchers to collaborate and search on various contents. The amount of data generated during a transition of a single compound from preclinical discovery to commercialization can easily range in terabytes, thus there is a greater demand of a chemically aware search algorithm that supplements SharePoint which enables researchers to query for information in a more intuitive and effective way. Thus by supplementing SharePoint with Chemically Aware™ features provides a great value to the pharmaceutical and biotech companies and makes drug discovery more efficient. Using several tools we have integrated SharePoint with chemical, compound, and reaction databases, thereby improving the traditional search engine capability and enhancing the user experience. Results This paper describes the implementation of a Chemically Aware™ system to supplement SharePoint. A Chemically Aware SharePoint (CASP) allows users to tag documents by drawing a structure and associating it with the related content. It also allows the user to search SharePoint software content and internal/external databases by carrying out substructure, similarity, SMILES, and IUPAC name searches. Building on traditional search, CASP takes SharePoint one step further by providing a intuitive GUI to the researchers to base their search on their knowledge of chemistry than textual search. CASP also provides a way to integrate with other systems, for example a researcher can perform a sub-structure search on pdf documents with embedded molecular entities. Conclusion A Chemically Aware™ system supplementing SharePoint is a step towards making drug discovery process more efficient and also helps researchers to search for information in a more intuitive way. It also helps the researchers to find information which was once difficult to find by allowing one to tag documents with molecular entities and integrating with image recognition software to find information from pdf documents.</p
3D Molecular Descriptors Important for Clinical Success
The pharmacokinetic and safety profiles of clinical drug
candidates
are greatly influenced by their requisite physicochemical properties.
In particular, it has been shown that 2D molecular descriptors such
as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers
correlate with clinical success. Using
the proteomic off-target hit rate of nicotinic ligands, we found that
shape-based 3D descriptors such as the radius of gyration and shadow
indices discriminate off-target promiscuity better than do Fsp3 and
the number of stereo centers. We have deduced the relevant descriptor
values required for a ligand to be nonpromiscuous. Investigating the
MDL Drug Data Report (MDDR) database as compounds move from the preclinical
stage toward the market, we have found that these shape-based 3D descriptors
predict clinical success of compounds at preclinical and phase1 stages
vs compounds withdrawn from the market better than do Fsp3 and LogD.
Further, these computed 3D molecular descriptors correlate well with
experimentally observed solubility, which is among well-known physicochemical
properties that drive clinical success. We also found that about 84%
of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas
withdrawn and discontinued compounds fail to meet the same criteria.
Our studies suggest that spherical compounds (rather than their elongated
counterparts) with a minimal number of aromatic rings may exhibit
a high propensity to advance from clinical trials to market
3D Molecular Descriptors Important for Clinical Success
The pharmacokinetic and safety profiles of clinical drug
candidates
are greatly influenced by their requisite physicochemical properties.
In particular, it has been shown that 2D molecular descriptors such
as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers
correlate with clinical success. Using
the proteomic off-target hit rate of nicotinic ligands, we found that
shape-based 3D descriptors such as the radius of gyration and shadow
indices discriminate off-target promiscuity better than do Fsp3 and
the number of stereo centers. We have deduced the relevant descriptor
values required for a ligand to be nonpromiscuous. Investigating the
MDL Drug Data Report (MDDR) database as compounds move from the preclinical
stage toward the market, we have found that these shape-based 3D descriptors
predict clinical success of compounds at preclinical and phase1 stages
vs compounds withdrawn from the market better than do Fsp3 and LogD.
Further, these computed 3D molecular descriptors correlate well with
experimentally observed solubility, which is among well-known physicochemical
properties that drive clinical success. We also found that about 84%
of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas
withdrawn and discontinued compounds fail to meet the same criteria.
Our studies suggest that spherical compounds (rather than their elongated
counterparts) with a minimal number of aromatic rings may exhibit
a high propensity to advance from clinical trials to market
3D Molecular Descriptors Important for Clinical Success
The pharmacokinetic and safety profiles of clinical drug
candidates
are greatly influenced by their requisite physicochemical properties.
In particular, it has been shown that 2D molecular descriptors such
as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers
correlate with clinical success. Using
the proteomic off-target hit rate of nicotinic ligands, we found that
shape-based 3D descriptors such as the radius of gyration and shadow
indices discriminate off-target promiscuity better than do Fsp3 and
the number of stereo centers. We have deduced the relevant descriptor
values required for a ligand to be nonpromiscuous. Investigating the
MDL Drug Data Report (MDDR) database as compounds move from the preclinical
stage toward the market, we have found that these shape-based 3D descriptors
predict clinical success of compounds at preclinical and phase1 stages
vs compounds withdrawn from the market better than do Fsp3 and LogD.
Further, these computed 3D molecular descriptors correlate well with
experimentally observed solubility, which is among well-known physicochemical
properties that drive clinical success. We also found that about 84%
of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas
withdrawn and discontinued compounds fail to meet the same criteria.
Our studies suggest that spherical compounds (rather than their elongated
counterparts) with a minimal number of aromatic rings may exhibit
a high propensity to advance from clinical trials to market