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CANDO specifications


Unique identifier OMICS_31917
Alternative name Computational Analysis of Novel Drug Opportunities
Restrictions to use None
Community driven No
Data access Browse
User data submission Not allowed
Maintained Yes

Publications for Computational Analysis of Novel Drug Opportunities

CANDO citations


Structure and conformational dynamics of scaffolded DNA origami nanoparticles

Nucleic Acids Res
PMCID: 5499760
PMID: 28482032
DOI: 10.1093/nar/gkx378

[…] f highly structured DNA assemblies programmed using the principle of scaffolded DNA origami remain challenging to predict using these models.As an alternative, here we apply our FE modeling framework CanDo to solve for the ground-state equilibrium structure and mechanical properties of structured DNA nanoparticles. Compared with the aforementioned computational tools, our FE model treats DNA duple […]


Combating Ebola with Repurposed Therapeutics Using the CANDO Platform

PMCID: 5958544
PMID: 27898018
DOI: 10.3390/molecules21121537

[…] (unpublished). This is further supported by our successful initial shotgun multitarget drug repurposing studies that used a different docking with dynamics protocol from what is currently used by the CANDO platform, namely Autodock for docking and NAMD for dynamics simulation [,].The proteomic signature similarity of drugs is then used to rank putative drug candidates for all indications in a shot […]


Lattice free prediction of three dimensional structure of programmed DNA assemblies

Nat Commun
PMCID: 4268701
PMID: 25470497
DOI: 10.1038/ncomms6578

[…] ight nucleic acid assemblies in a computationally efficient manner, within the limits imposed by the preceding assumptions.Integration of this procedure into our online structure-prediction framework CanDo will provide a broadly accessible 3D structure-prediction framework that can be refined and extended in the future using high-resolution structural feedback, which can include the detailed explo […]


Data access for the 1,000 Plants (1KP) project

PMCID: 4306014
PMID: 25625010
DOI: 10.1186/2047-217X-3-17

[…] nships at the iPlant site, functional relationships between proteins and their associated metabolites are available from the Computational Biology Group at the University of Washington, developers of CANDO []. Sequence similarity-based methods are used to map 1KP proteins to curated repositories of protein-protein interactions (i.e., BioGRID []) and biochemical pathways (i.e., Kyoto Encylopedia of […]

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CANDO institution(s)
Department of Biomedical Informatics, University at Buffalo, Buffalo, NY, USA
CANDO funding source(s)
Supported by a National Institutes of Health Director’s Pioneer Award (1DP1OD006779-01).

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