My main interest is the study of the interaction between Natural Products and Humans. My main objective is to make sense and make available the ideas, data and materials collected and created by Humans.
My main research topics are:
- Making sense, creating sense and inferring sense in Natural Products Chemistry and Pharmacognosy through the Center for Natural Products Technologies - CENAPT
- HiFSA, Full-spin analysis of NMR spectra
- Databases on Natural Products (e.g. NAPRALERT), see the section below.
- Liquid-Liquid Chromatography (CCC/CPC/C?C)
- Development of tools to ease research (more about this to come)
I’m also curator with 3 other friends of Natural Products Chemistry Burning News a compilation of recent articles on Natural Products chemistry or Pharmacognosy.
NAPRALERT, acronym of NAtural PRoducts ALERT, is a database created at UIC in 1975 by the late Norman R. Farnsworth. The database aims at being a systematic and curated database of all the research related to Natural Products and Pharmacognosy in general. It includes but is not limited to the coverage of: - Traditional use of plants and Natural Products - Distribution of compounds produced/present in organisms - Distribution of organisms producing/presenting a compound - Biological assays in-vitro and in-vivo of organisms, extracts or purified compounds
The new infrastructure
The database was running until 2015 on an aging IT infrastructure that was both costly and difficult to maintain and enhance. This is why Guido Pauli recently appointed director of NAPRALERT, James Graham, its current editor, and I decided that it would greatly benefit from a complete rewrite.
Starting January 2015 to August 2015, I wrote the new NAPRALERT from scratch using the more Free (as in Free Speech) technologies I was more familiar with:
- Python, as a programming language.
- PostgreSQL, as a database engine.
- GNU/Linux, for everything. For the details, the most critical parts are running Debian GNU/Linux.
- Qemu, for running Virtual Machines.
- NGINX, as a web server.
During that journey, I learned or improved with a lot of other tools and technologies:
- Ansible, for the easy deployment and test. (thanks kuroishi for introducing me to it)
- Packer, for creating new Virtual Machines in a reliable manner. (thanks hef for introducing me to it)
- Docker, for creating easy to toss containers and spinning up instances quickly.
- Django, as a web framework. (thanks Carl and Sheila for showing me the way)
- Django autocomplete-light, as an autocomplete solution that really works.
- Celery, as a task queuing and scheduling system.
- Semantic UI, as a really nice and easy to use web UI interface.
- Gunicorn, as a pre-forker reducing load and allowing way better response times (yes now we can handle 1000 times more than our average user charge…)
- And many other things that would be too long to list.
The service went online on October 2015, and is now happilly serving hundreds of users. There is still a lot to do now that we have a nice and shiny new platform to bring all the nice ideas that we compiled. But I’ll talk more about that later.
What can be done with it
An example of what can be done in term of advanced data analysis has been described in our Open Access paper: Can Invalid Bioactives Undermine Natural Product-Based Drug Discovery?
We used Python, Jupyter Notebooks, Pandas, Bokeh to clean, treat and analyze the behavior of Natural Products chemists such as their most studied compounds and put in evidence that their behavior is following Power laws.
But many other works from academia and in industry have benefited from NAPRALERT, some can be found on Google Scholar.