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Cambridge MedChem Consulting

artificial intelligence

Upcoming Conferences

I just thought I'd mention a couple of meetings I'm helping to organise.

2nd RSC-BMCS / RSC-CICAG Artificial Intelligence in Chemistry

Artificial Intelligence is presently experiencing a renaissance in development of new methods and practical applications to ongoing challenges in Chemistry. Following the success of the inaugural “Artificial Intelligence in Chemistry” meeting in 2018 a second meeting has been organised at Fitzwilliam College, Cambridge (2nd to 3rd September 2019). The lineup is now finalised and looks like a great selection of speakers. There is still time to submit posters (closing date 5th July).

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Registration is open and there are discounts for RSC members.

The Twitter hashtag - #AIChem19 is already being actively used.

20th SCI/RSC Medicinal Chemistry Symposium

This is Europe’s premier biennial Medicinal Chemistry event, focussing on first disclosures and new strategies in Medicinal Chemistry. It takes place a Churchill College, Cambridge UK, 8 September - 11 September 2019. There is a fantastic lineup of speakers and looks to be one of the highlights of the MedChem calendar. Early career scientists can also take part in a Medicinal chemistry workshop on the Sunday afternoon, a great way for people to learn medicinal chemistry and meet other scientists in a fun and informal setting.

You can register here both RSC and SCI members get a reduced rate, and despite the slightly confusing page on the SCI website you don't have to be a member to attend, just select "Event Member FREE from the dropdown menu and you can register for the event without membership.

Screenshot 2019-06-05 at 20.25.03

Twenty Years of the Rule of Five

It has been over twenty years since Lipinski published his work determining the properties of drug molecules associated with good solubility and permeability. Since then, there have been a number of additions and expansions to these “rules”. There has also been keen interest in the application of these guidelines in the drug discovery process and how these apply to new emerging chemical structures such as macrocycles.

This meeting aims to have a look at the impact the Ro5 has had on drug discovery and as well as looking to the future and how we use these rules in the changing drug compound landscape as drug discovery moves into novel areas of chemistry.

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There is a very exciting group of speakers and the timetable has been designed to allow a panel discussion after each session. Given the topic and the speakers I'm sure these will be entertaining sessions.

You can register here and there are discounts for RSC members

Twitter hashtag - #RuleofFive2019

2nd RSC-BMCS / RSC-CICAG Artificial Intelligence in Chemistry

The lineup for the 2nd RSC-BMCS / RSC-CICAG Artificial Intelligence in Chemistry Monday-Tuesday, 2nd to 3rd September 2019 Fitzwilliam College, Cambridge, UK has been updated.

AI-webpage-image

Twitter #AIChem19

Artificial Intelligence is presently experiencing a renaissance in development of new methods and practical applications to ongoing challenges in Chemistry. Following the success of the inaugural “Artificial Intelligence in Chemistry” meeting in 2018, we are pleased to announce that the Biological & Medicinal Chemistry Sector (BMCS) and Chemical Information & Computer Applications Group (CICAG) of the Royal Society of Chemistry are once again organising a conference to present the current efforts in applying these new methods. The meeting will be held over two days and will combine aspects of artificial intelligence and deep machine learning methods to applications in chemistry.

Speakers

Deep learning applied to ligand-based de novo design: a real-life lead optimization case study, Quentin Perron, IKTOS, USA
A Turing test for molecular generators, Jacob Bush, GlaxoSmithKline, UK
Presentation title to be confirmed, Keynote: Regina Barzilay, Massachusetts Institute of Technology, USA
Artificial intelligence for predicting molecular Electrostatic Potentials (ESPs): a step towards developing ESP-guided knowledge-based scoring functions, Prakash Rathi, Astex Pharmaceuticals, UK
Molecular transformer for chemical reaction prediction and uncertainty estimation, Alpha Lee, University of Cambridge, UK
Drug discovery disrupted - quantum physics meets machine learning, Noor Shaker, GTN, UK
Presentation title to be confirmed, Christian Tyrchan, AstraZeneca,
Presentation title to be confirmed, Anthony Nicholls, OpenEye Scientific Software, USA
Deep generative models for 3D compound design from fragment screens, Fergus Imrie, University of Oxford, UK
DeeplyTough: learning to structurally compare protein binding sites, Joshua Meyers, BenevolentAI, UK
Presentation title to be confirmed, Maciej Haranczyk, IMDEA, Spain
Deep learning for drug discovery, Keynote:  David Koes, University of Pittsburgh, USA
Presentation title to be confirmed, Olexandr Isayev, University of North Carolina at Chapel Hill, USA
Dreaming functional molecules with generative ML models, Christoph Kreisbeck, Kebotix, USA
Presentation title to be confirmed, Keynote:  Adrian Roitberg, University of Florida, USA

Applications for poster presentations are welcomed, the closing date for submission is 5th July. A number of RSC-BMCS and RSC-CICAG student bursaries are available up to a value of £250, to support registration, travel and accommodation costs for PhD and post-doctoral applicants studying at European academic institutions. The closing date for bursary applications is 15th July.

Full details are on the conference website





Atomwise AIMS awards

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I suspect many will have noticed the recent announcement of the Early Results in Drug Discovery Partnership with AI Biotech Company. These are the first results of the Atomwise AIMS awards:

The researchers have been using Atomwise’s AI-powered in silico screening technology to develop therapeutic treatments for, among others, certain types of strokes, hand-foot-and-mouth disease, and an infection that causes reproductive failure in pigs.

The AIMS award program is a great opportunity for university research scientists to easily access AI-assisted structure-based virtual screening technology:

  • Customized small molecule virtual screen using AtomNet™ technology
  • 72 small molecules predicted to bind to a specific target protein – QC verified by mass spectrophotometry, resuspended and diluted to a convenient concentration, aliquoted into microtiter plates, and delivered at no cost to the researcher
  • Support from Atomwise’s medicinal chemists and structural biologists
  • Opportunity to receive up to $30K USD to subsidize assay work

If you have a target protein with an X-ray crystal, Cryo-EM, or NMR structure, or with close sequence homology to a protein with available structures, and an assay in place to evaluate 72 potential hits, then you should consider applying.

Full details are on the AIMs awards page and the closing date is 29 April 2019.



Encouraging early results for the drug delaying onset of Motor Neurone discovered by artificial intelligence

Motor neurone disease (MND) describes a group of diseases that affect the nerves (motor neurones) in the brain and spinal cord, is is likely that there are multiple molecular targets. Amyotrophic lateral sclerosis (ALS) also known as Lou Gehrig's disease is the most common form of MND. Edaravone was recently approved for the treatment of ALS but the mechanism is unknown. It is a free radical scavenger and oxidative stress has been hypothesised to be part of the process that kills neurones in people with ALS. However new treatments are urgently needed.

For this reason I was particularly interested to read about a potential novel treatment for ALS arising from work between Benevolnet.ai and Sheffield Institute for Translational Neuroscience.

The study, led by Dr. Richard Mead and Dr. Laura Ferraiuolo at SITraN, assessed the efficacy of a drug candidate proposed by BenevolentAI's artificial Intelligence technology for Motor Neuron Disease (MND), also known as Amyotrophic Lateral Sclerosis (ALS). SITraN found there are significant and reproducible indications that the drug prevents the death of motor neurones in patient cell models, and delayed the onset of the disease in the gold standard model of ALS…Dr. Richard Mead of SITraN commented: "This is an exciting development in our research for a treatment for ALS. BenevolentAI came to us with some newly identified compounds discovered by their technology - two of which were new to us in the field and, following this research, are now looking very promising. Our plan now is to conduct further detailed testing and continue to quickly progress towards a potential treatment for ALS."

SITraN expect to publish an abstract at the Motor Neurone Disease Association 28th International Symposium in Boston in December 2017.