Computational analysis of novel drug opportunities (CANDO)
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We have a developed a unique computational drug discovery platform based on fragment-based docking with dynamics, multitargeting, and drug repurposing to discovery therapeutics with higher efficiency, lowered cost, and increased success rates, compared to current approaches.

We have applied this platform to evaluate how all FDA approved and other human ingestible drugs (such as certain phenethylamines, tryptamines, psychoactives, and dietary supplements) interact with all protein structures (compiled from a nonredundant library of solved protein structures as well as predicted models from various organismal proteomes such as Homo sapiens) to identify and rank relationships between them for all indications (diseases). Interactions between 3733 compounds, 48,278 protein structures encompassing 2030 indications have been determined in the first version (v1) of the platform. The compound-proteome interaction signatures 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 vitro, in vivo, and in the clinic by our collaborators or by contract research organisations (CROs).

The project represents a comprehensive integration of our group's applied research on therapeutic discovery, building upon basic protein and proteome structure, function, interaction, evolution, and design research. Funding sources include the National Institutes Health (specifically a 2010 NIH Director's Pioneer Award), the National Science Foundation, the Kinship Foundation, the University of Washington Technology Gap Innovation Fund, and the Washington Research Foundation.

Indications, collaborations, and current results

We are currently working with almost 30 collaborators throughout the world to find cures for over 20 indications/diseases. See a full list of our indications and collaborators and some results in progress.


We have developed BINDNET, a novel method for predicting likely binding partners for a given ligand within a proteome of interest.


Drug discovery is protein folding with a compound.

This section is in progress. There's a lot of novelty to this project, technically in terms of the methods used, and also in terms of philosophy and paradigms employed (ergo, the reason for the 2010 NIH Director's Pioneer Award). Here are a few of them:




Ultimately the goal is personalisation to improve quality of life, including personalised medicine. When I first came across genetics, my dream was that each person would have their genome sequence and a powerful computing cluster (these days, one can get a personal supercomputer for ~$6000) where they could evaluate the response of their proteins and proteomes (corresponding to their specific genes and genomes) against entities in the environment, such as bioactive chemical compounds, to improve their quality of life, i.e., to treat and/or cure diseases as well develop vaccines. This project is part of that dream and we're going to rigourously evaluate whether it can come to fruition.


Everone has a major responsibility, with some overlap. The rest of our group also helps.


Past contributors





These are some of the key papers that have led up to the development of CANDO v1. See also all our publications related to therapeutic discovery as well as a comprehensive list of all our publications.

Protinfo || Bioverse || Samudrala Computational Biology Research Group ||