CANDO collaborator form
Computational analysis of novel drug opportunities (CANDO) collaboration form Discover new cures and treatments with us!


We have a developed a unique computational multitarget fragment-based docking with dynamics protocol to implement a comprehensive and efficient drug discovery pipeline with higher efficiency, lowered cost, and increased success rates compared to current approaches. We are applying this pipeline to evaluate how all FDA approved drugs, phenethylamines, tryptamines and other physchoactive drugs bind to all known protein structures in Homo sapiens and several pathogenic species. The binding studies are combined with pharmacalogical, physiological, and cheminformatics data to predict new therapeutics through repurposing drugs already approved for other indications. The top predictions are verified in the laboratory and clinic by our collaborators.

We are always on the look out for new collaborators, particularily those trying to cure underserved indications/diseases! If you think our computational pipeline could help you identify new therapeutics for your indications/diseases of interest, then we would like to hear from you. Please take a moment to fill out the form below. We will read your information carefully and contact you within the next few days. Other than adding your name and indication to our collaborator list we will not share any other information you provide us without your consent. If you are a current collaborator and are updating your information, please submit your email and password first on the collaborator update line to retrieve the information we currently have.

Caveats: Please keep in mind that if there are any "obvious" choices for small molecule therapeutics (like retrovirals for viruses), they most likely will light up in our screens and may be the only hits we can predict. Also, if the indication/disease already has a decent treatment, then it's likely that we might have to go through a lot of nonhuman studies before we can try out our predictions in humans. So our approach is best suited for underserved diseases with poor or no (obvious) treatments. However, in any case where there's a demand for new drugs, we can always go through the more traditional processes. Our approach works best in cases where we can exploit multitargeting, i.e. where we have multiple targets for an indication already known.


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Name:
Principal Investigator (if you are not the PI):
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Indications.

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Indication name:

Pathogens.

Current therapeutic status: good poor untreatable neglected

Known therapeutics.

Compounds of interest, or potential therapeutics.

Known protein targets (submit FASTA format sequences or PDB names in the text box below, or upload an appropriate file).


Putative protein targets (submit FASTA format sequences or PDB names in the text box below or upload an appropriate file).


Any research on small molecule inhibitors/drugs and challenges you know about thus far.

Pertinent references/reading material.

Areas of collaboration (i.e. your expertise).
in vitro binding.
in vitro protein assays.
in vivo animal assays.
clinical studies (access to patient cohort for evaluating putative drugs).

What are your expectations/needs with respect to the timing of our predictions?

What is your funding situation for this project? Would you be interested in pursuing additional funding with us? Please explain.

What are your ultimate (career or other) goals with regards to this project? If our collaboration results in the prediction of one or several readily available drug(s) for this indication, what would be the best/most challenging/rigorous next step in terms of small molecule therapeutic discovery, assuming money is not an objection?

With regards to the previous answer above if costs are on the very low side, the CANDO project may be able to help. If costs are high, what are the ideas/means for obtaining them (i.e. apply for more grants, VC funding, etc.)?

Other comments about this collaboration.


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