Jan
18

Post doctoral position on chaperone development for neurological disorders

I would like to highlight an open postdoc position in the lab of a close collaborator Dr. Alexey Pshezhetsky

Open position:

Postdoctoral fellow or Ph.D. student

Supervising researcher and laboratory:

Dr. Alexey Pshezhetsky, laboratory studying lysosomal biology and metabolic disorders, Research Center of CHU Sainte-Justine

Project length:

1 year with renewal opportunity

Start date:

Immediately

Project description:

The successful candidate will participate in the development of the chaperone treatment for the inherited metabolic neurological disorders. He (she) will also participate in pathological and behavioral characterization of gene-targeted mouse models of human diseases.

Ideal candidate:

Applicant should have a strong background and research experience in molecular genetics, biochemistry and cell biology (cell culturing, immunohistochemistry). Experience in handling laboratory animals is an advantage.

Salary: Salary is commensurate with experience.

How to apply:

Applicants must send the following documents to the address listed below:

  • Curriculum vitae
  • Grade transcript
  • Letters of motivation
  • Three reference letters

Dr. Alexey Pshezhetsky

Medical Genetics

CHU Sainte-Justine, Research Centre, Université de Montréal

3175 Cote-Ste-Catherine

Montréal, Québec, Canada

H3T1C5

e-mail: alexei.pchejetski@umontreal.ca

Jan
07

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Dec
20

Small Molecule Bioactivity Databases Book Chapter

Its been a busy year transitioning from spending most of my time with CDD to my start-up Collaborations Pharmaceuticals, Inc etc. Along the way I found time to write a few book chapters. One of these recently published in

High Throughput Screening Methods : Evolution and Refinement

Editors: Joshua A Bittker, Nathan T Ross

Our chapter is on small molecule databases and deals with the explosion in these over the past decade. We are at the point were there is a massive amount of data that can be used for machine learning to predict bioactivity. This has potential utility but the underlying quality of the data may be an issue that should not be forgotten either.
There is definitely a tension between publishing a paper / review and a book chapter. For one its an honor to be invited by the editors, to have your contributions recognized. On the other hand, the accessibility of these books is a challenge unless you have access to a library or significant budget. As both a book editor and contributor there is definitely a conflict here. Sure publishers have to make money to keep the enterprise going, but books and chapters rapidly age and then what? Its unlikely that the editors or contributors ever recoup their time investment in publishing these narrowly focused books. The model is ripe for disruption. Sure, instead of publishing in closed books we could just drop the file in some open publishing repository. There is no money to be made unless you self publish. As long as the contributors get credit, citations etc perhaps thats all that matters to some. Personally I like the physical feel of a real book, to see it on the shelf and to know that some small contribution will last for a while in a library or on some scientists shelf. A bit of permanence in this world were everything moves so fast.

Dec
16

Collaborations Pharmaceuticals, Inc. Announce NIH Award to Develop New Software for Drug Discovery

Today I released the following Collaborations Pharmaceuticals Inc, announcement of our 3rd NIH grant this year. This is an SBIR and will fund software development to provide a tool the company will be able to use in its drug discovery programs but also make commercially available. It will build off our past publications on open source software. A very exciting step for the company which will fund more jobs!

Fuquay Varina – The National Institute of General Medical Sciences (NIGMS) recently awarded $149,999 to Collaborations Pharmaceuticals, Inc. (CPI) to develop software that could make public data more amenable to those scientists who want to use it to build computational models to help their research.

There are massive publically accessible databases that include a broad variety of disease targets and absorption, distribution, metabolism, excretion and toxicology (ADMET) properties that are not in a form that is immediately ready for machine learning model building or accessible for use by small research and development (R&D) organizations that do not have their own in-house cheminformatics teams. This project will compile a comprehensive collection of these datasets (e.g. databases like PubChem, ChEMBL etc) for structure-activity data. This will enable the user to quickly and automatically use machine learning models for various targets and properties that could be of value for drug discovery.

“Being able to use transparent computational models simultaneously for visualizing activity trends for multiple targets (both diseases and ADMET) removes the burden of curation or purchasing and maintaining expensive software, and drastically simplifies the addition of new data. It also represents a new frontier of drug discovery as a world of small, agile distributed R&D organizations has access to valuable public datasets that can inform their research. Such computational models will assist in drug repurposing efforts internally and with our collaborators while likely identifying new compounds for a wide array of drug discovery projects” said Sean Ekins, CEO CPI.

 “We are very grateful to NIGMS for funding so we can illustrate how computational approaches can be used to repurpose drugs already approved for other uses and instead use for neglected and rare diseases” said Dr. Ekins.

About Collaborations Pharmaceuticals, Inc.

Collaborations Pharmaceuticals, Inc. performs research and development on innovative therapeutics for multiple rare and infectious diseases. We partner with leading academics, companies and foundations to identify and translate early preclinical to clinical stage assets. We have considerable experience in preclinical and computational approaches to drug discovery and toxicity prediction. For more information, please visit http://www.collaborationspharma.com/

 

For further information, please contact

Sean Ekins, Ph.D., D.Sc.

CEO and Founder

Collaborations Pharmaceuticals, Inc.

320 N Judd Parkway NE, Suite 217,

Fuquay Varina, NC 27526

collaborationspharma@gmail.com

cell:215-687-1320
office: 919-762-0084

Nov
29

AAPS 2016

A couple of weeks ago I was in Denver for the AAPS2016 meeting. This was the first time I had been at the meeting in quite a number of years and there were some changes. Firstly posters were now electronic and that did not seem a positive change for me. The loss of something to browse was tough. Having only 30 min windows to catch a presenter was also hard to do. I hope they go back to paper posters.

Also the conference center was like a giant cavern and seemed sparsely populated with attendees, apart from in the exhibit room which was pretty busy. The presentations I went to had handfuls of people in them, in generally huge rooms.

I was there to give a couple of presentations – one on drug repurposing in a session with perhaps 50 attendees and the other was on using social media for raising attention for papers and research etc. The latter was more educational presented along with the AAPS and was more interactive. The 20 or so attendees were new to most of the tools I described so I think a few people went away with a better idea of Kudos and Figshare etc.

It was a long way to go to give talks to relatively small audiences however it did help to raise awareness of the company and the postdoc job opening I have currently. Maybe it will be a few more years in between the next AAPS I attend.

 

Nov
14

Leaving the nest – Looking for start-up co-working and incubator space

I have worked from home for the better part of a decade either from my past location in PA or my present location in NC. Thanks to getting a recent grant, I now need to hire a postdoc and that means I can fly the nest (which in my case is my home). But with that comes a whole new array of challenges. This experience may be common to others who have spent long periods working from home who are in the same position (or not), so I thought I would share my experiences.

Working remotely for this long has many advantages – you can dress how you want, work when you want and pretty much do whatever you want – within reason if you are going to remain productive. The cons are just as long – well the main disadvantage is you feel like a prisoner working pretty much 24/7, living at home, especially if you have nothing nearby such as shops etc. Also the lack of interaction with others on a daily basis apart from by email or twitter makes you feel like you are totally isolated.  For the past 5 yrs I have been a literal prisoner, I could have traveled to Mars and back in that time. Instead my only trips have been on business.. OK so you get the picture. So what happens if you have a small company (1-2) people, then what are your options? If you are in a big city you probably have lots of co-working space, or office space – you can rent a room/ cubicle as desired. But what if you want a lab, then your options plummet.

I live in what for many would be a great commuting location. 30min from Raleigh, 30 min from research triangle park, 50-60 min from Chapel Hill or Durham. And yes there are great offices and labs spaces in all these places ..but when it comes to a really small company again you are limited further because its not a spin out from UNC etc. My best bet so far is the incubator at NC State.. over 3 weeks ago I submitted an application (and today a response!) That and the 30 min commute made me want to think what could I do locally as well. I could also put that extra hour lost in commuting to good use. I also have emailed or visited several options locally and visited incubators in other states so I thought why not make a slide deck that might be useful to others undergoing the same hunt. Last week I put my incubator hunting experience up on slideshare. 

This helped to get a bit of attention on twitter and folks told me about other places opening in the future. Today I met with three representatives from my local town and chamber of commerce. Literally this doubled the number of people I have met locally (beyond my optician, coffee shop /bakery, and picture frame shop). I clearly do not get out that much. So I gave them my pitch, what I do, what I would like to build (a biotech, here locally in Fuquay Varina), what I have done so far, how I want to create jobs here etc…I learnt the town would like to create an incubator, there is no time frame but first they need to find a building and measure the level of interest. So this may be my next crazy adventure, not only building a biotech but also a space for other start-ups. In the interim they provided some potential leads on small office space.. its a start. My bet is I will end up at the NC State incubator initially, and from there who knows.

At the weekend, while browsing an old building/ being used as an antiques warehouse in town I realized that it would be perfect for an incubator space- not too far from local amenities, centrally located, not too big, not too small…

To be continued…

 

 

 

 

Nov
10

Antimalarial being tested as possible Ebola virus drug -project started with a tweet

Today we announced a new R21 grant from NCATS NIH awarded to Collaborations Pharmaceuticals, Inc andTexas Biomedical Research Institute. This continues the work published in F1000Research .

What is missing from the press release and papers etc. is the back story. Why are we working on this and how did it start. Essentially it took a couple of years to get to this point, but it all started with tweets with Chris Southan and Megan Coffee discussing Ebola chemistry and screens.  This lead to Peter Madrid and the work he had done previously on identifying a few antimalarials with activity, and then on from there, that provided a dataset for machine learning. When the models pulled up pyronaridine which we had also found for Chagas disease then I knew this was getting interesting. Once we had in vitro data to confirm the prediction we had enough for the paper and then to try to fund in vivo studies. This is were it gets expensive. I have reached out to the company in South Korea that makes pyronaridine for its antimalarial combination but so far no luck..

So in summary- a few tweets, followed by a lot of sweat equity from Peter, Rob, Joel and myself and then a ~$600K grant is obtained after 2 years. It does not always happen this way!

 

Nov
07

Non-classical transpeptidases insights and new antibacterials

Well today’s post has been a few years in gestation and yes I have had to keep it quiet for a long, long time which was extended as our recent paper was embargoed for what seemed like an eternity. It starts back in 2009 when I was using some of the NIAID/SRI whole cell screening data for mycobacterium tuberculosis (here and here). This lead to building machine learning models to predict whole cell activity. One of the side effects of this were tables of fragments that were important or not in compounds used in the model. Little did I know that years later they would be used to design some new molecules and help find new antibiotics.  I guess you could say this is an example of the unintended consequences of research. Over the years, predominantly with my collaborator Joel Freundlich (Rutgers) we have generated more machine learning models for TB (here and here). Then a few years back along with Gyanu Lamichhane at Johns Hopkins University we embarked on an R21 aimed at developing oral carbapenems for drug resistant TB. Joel wanted to make use of the data from the earlier machine learning models to design evolved carbapenems that would have properties that would bias them towards having activity against Mtb. Our new paper published today in Nature Chemical Biology is an extensive study on the mechanism of carbapenems which inhibit L,D-transpeptidases of Mtb as well as ESKAPE pathogens. The new evolved carbapenems made by Joel’s lab and tested by Gyanu’s lab, along with crystal structures, show how these compounds can bind covalently in different orientations in the enzyme binding site . This study also showed that biapenem was more potent against Mtb  and was active in the mouse model (especially when combined with Rifampicin). This work represents an important step towards showing carbapenems are feasible for treating Mtb. It also highlights how some machine learning efforts can ultimately impact design of drugs, albeit not in the manner originally intended, but nonetheless creatively! It represents another collaboration that has been incredibly productive and goes some considerable way to showing what is possible when combining computational and experimental research for Mtb. I am eager to see where this work goes as Gyanu and Joel push this work onwards!

Oct
20

OpenZika – PLOS Neglected Tropical Diseases

After several months our article in PLOS Neglected Tropical Diseases is now out from embargo and published. A big thank you to my co-authors Carolina Horta Andrade and Alexander Perryman who have put a lot of their time into the project. I would also like to thank the reviewers for their constructive comments. We have updated this article considerably since we put out the preprint in figshare back in August. As an added bonus we have made some slides which update the OpenZika story. Please tell others how they could contribute their computer time or Android phone (while charging) – every bit helps. We hope to update at some point with molecules we have tested that have been identified by OpenZika.

Oct
18

Zika Homology models paper makes it to PubMed >6 months after “Publishing” in F1000Research

Who would have thought in February that when we submitted our manuscript on Zika homology models to F1000Research it would finally appear in PubMed over 6 months later. This was no where near as fast as our first article on Zika that took a few months to be approved and then appear in PubMed.

What started out as a challenge to model all the proteins in Zika and put it out into the open – turned into a “publishing” learning experience. Thankfully at least the information and the models were in repositories like figshare and F1000Research and not some other journal that would have kept the information closed until acceptance.

F1000Research had a seemingly impossible time finding reviewers – after we suggested what seemed like every possible person in their database and then kept coming back for more. Why was it so difficult to find reviewers for a manuscript on homology models – regardless of if its Zika or not? This is definitely puzzling.

After a month the cryo-EM and crystal structures started to appear in the PDB and in publications. In the six months this paper was not in the PDB we reckon several others have published one or more Zika homology models and had their papers in PubMed before ours – e.g. this and this …one even cited the F1000Research paper before it was “accepted” or in PubMed.

So my take away here is that – yes we got the information out there ASAP on models for Zika and we shared with the community everything, but F1000Research is not very visible on its own. PubMed is important to amplify manuscripts (alongside Google Scholar etc) – we lost >6 months of visibility even though we tried using Kudos to amplify and had 27 share referalls to date (see metrics in figure – as of today it has 2661 views, 707 downloads – so it appears these data are out of date) Kudos on homology paper. Going forward we will be able to track the effect of being listed in PubMed. If only it could have been there when submitted to F1000Research.

Its likely that other scientists will have missed our work and gone off and done the same or similar. I think this could be prevented by making papers visible in PubMed while under review at Open “journals’ etc. This experience suggests that the open publishing, open review model is not there yet – there are still wrinkles to iron out IMHO.

 

 

 

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