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Cambridge MedChem Consulting

First Disclosures at ACS San Francisco

The ACS session organised by Division of Medicinal Chemistry includes a day of first disclosures of potential clinical candidates for the first time. Beth Halford was there and tweeted a series of hands drawn structures as they were disclosed. I've redrawn the structures and converted them into a single sdf file. I've also used Jupyter Notebook to calculate the physicochemical properties and plot them as shown in the image below.

test2png

As can be seen, many of the compounds are on the large size with molecular weights >450, a third of them have ionisable groups which serves to bring down the calculated LogD. All molecules contain an aromatic ring, indeed many contain multiple rings. Interestingly we see a number of examples where a biphenyl ring system bears multiple ortho substituents presumably locking the two aryl rings orthogonal, no mention of atrope isomers though. This might also reduce the planarity and increase the 3D shape.

The sdf file is available here FirstDisclosures.sdf.zip if anyone spots any errors in the structures please let me know.

Drug Discovery Resources Updates

I've been updating the Drug Discovery Resources section.

In particular I've added a section on target prediction tools, updated the section on Analysis of HTS data, and expanded the section on aggregation in bioassays to include a recent publication giving an example of target specific aggregation.

The crystal structure showing the interaction is available (PDB 5MU8) and is displayed below using 3Dmol.js, the ligand (JNJ525) is shown in red..

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In addition I've updated the section on molecular interactions.

European Lead factory Newsletter

The latest issue of the European Lead Factory Newsletter has just been published.

Highlights include the European Lead Factory recently reached the milestone of having received over 1,000 chemical library proposals for consideration. To date, 143,529 novel compounds, out of the 200,000 prospected compounds for the Public Compound Collection, have been synthesized, which means that the ELF compound collection grows daily by approximately 250 novel compounds to eventually constitute the 500,000 Joint European Compound Library (JECL).

Parkinson’s UK and the University of Sheffield have launched a joint venture biotech company, Keapstone Therapeutics. Parkinson’s UK has allocated 1 million GBP over the next sixteen months to further develop compounds that boost the internal cellular defence mechanisms against oxidative stress. These compounds were discovered by European Lead Factory.

19th RSC / SCI Medicinal Chemistry Symposium

The 19th RSC / SCI Medicinal Chemistry Symposium takes place 10th-13th September 2017 at Churchill College, Cambridge, UK. This biennial meeting is one of the highlights of the drug discover calendar. The full lecture timetable can be downloaded here.

CMC - second announcement copy

Call for Posters
Contributions from the whole field of medicinal chemistry are invited. Flash presentation sessions are planned which will involve a two-minute presentation of poster highlights. Poster abstract submissions should be sent to the secretariat by 16th April if you wish to take advantage of the early-bird registration fee and indicate whether or not you would like to be included for consideration in the flash presentation session. The final deadline for submission of posters is 21st July.

Registration is now open and delegates are encouraged to book early to ensure places at this very popular meeting. Discounted rates are available to RSC and SCI student members, and some student bursaries are available. Applications are invited from PhD and post-doctoral students studying at European academic institutions, preferably members of the RSC, SCI or EFMC. Those submitting abstracts for poster presentation will be favoured. To apply for a student bursary, please complete and return the bursary application form by 21st July.

The Ecstasy and Agony of Assay Interference Compounds

There is an editorial in ACS Central Science DOI that I would encourage everyone involved in hit identification to read.

A couple of quotes will give you an idea of the content

Alarmingly, up to 80–100% of initial hits from screening can be artefacts if appropriate control experiments are not employed.

it is important to realize that no PAINS-containing drug has ever been developed starting from a protein-reactive PAINS target-based screening hit

They also emphasise the critical need for experimental validation for any screening hit.

Such validation experiments include classic dose response curves, lack of incubation effects, imperviousness to mild reductants, and specificity versus counter-screening targets. If a molecule is flagged as a potential PAINS or aggregator using published patterns but is well-behaved by these criteria, it may be a true, well-behaved ligand. Ultimately, genuine SAR combined with careful mechanistic study provides the most convincing evidence for a specific interaction. Covalent and spectroscopic interference molecules act via specific physical mechanisms, for which controls are known. Colloidal aggregation, fortunately, is readily identified by rapid mechanistic tests and by counter-screening.

In addition you need to consider compound identify and purity, reproducing the activity with an authentic sample is essential.

Whilst time-consuming this validation work will save a fortune in the future.

The BMCS Mastering MedChem III: 3rd RSC-BMCS symposium on mastering medicinal chemistry

This meeting is aimed at all those who wish to become better drug hunters and heed warnings from the past. (22 March 2017 09:00-19:00, Cardiff Bay, United Kingdom).

In the main there are two types of drug discovery programmes: those that hit serious problems and those that are going to hit serious problems. The difference between success and failure is how we, as medicinal chemists, tackle and resolve the problems

Sounds a great meeting both for those starting out in their careers and for those looking to pick up new tips.

WHO publishes list of bacteria for which new antibiotics are urgently needed

The World Health Organisation has published a list of the top 12 bacteria for which antibiotics are urgently needed in an effort to focus research.

The list highlights in particular the threat of gram-negative bacteria that are resistant to multiple antibiotics. These bacteria have built-in abilities to find new ways to resist treatment and can pass along genetic material that allows other bacteria to become drug-resistant as well.

WHO priority pathogens list for R&D of new antibiotics

Priority 1: CRITICAL

  • Acinetobacter baumannii, carbapenem-resistant
  • Pseudomonas aeruginosa, carbapenem-resistant
  • Enterobacteriaceae, carbapenem-resistant, ESBL-producing

Priority 2: HIGH

  • Enterococcus faecium, vancomycin-resistant
  • Staphylococcus aureus, methicillin-resistant, vancomycin-intermediate and resistant
  • Helicobacter pylori, clarithromycin-resistant
  • Campylobacter spp., fluoroquinolone-resistant
  • Salmonellae, fluoroquinolone-resistant
  • Neisseria gonorrhoeae, cephalosporin-resistant, fluoroquinolone-resistant

Priority 3: MEDIUM

  • Streptococcus pneumoniae, penicillin-non-susceptible
  • Haemophilus influenzae, ampicillin-resistant
  • Shigella spp., fluoroquinolone-resistant

Update

The Community for Open Antibiotic Drug Discovery (CO-ADD) screen compounds for antimicrobial activity for academic research groups for free. The screening includes the top 5 pathogens listed in the WHO priority list, as well as the fungi C. neoformans and C. albicans. Details on how to send compounds are here. All they require is 1mg (or 50uL at 10 mg/mL) of pure compound which will be used for primary screening, hit confirmation, and if active will be used for a broader antimicrobial screening, cytotoxicity and a check for its purity.

Predicting bioactivities

Small molecules can potentially bind to a variety of bimolecular targets and whilst counter-screening against a wide variety of targets is feasible it can be rather expensive and probably only realistic for when a compound has been identified as of particular interest. For this reason there is considerable interest in building computational models to predict potential interactions. With the advent of large data sets of well annotated biological activity such as ChEMBL and BindingDB this has become possible.

These predictions may aid understanding of molecular mechanisms underlying the molecules bioactivity and predicting potential side effects or cross-reactivity.

A variety of options are summarised on this page.


Peptidyl-Prolyl cis-trans Isomerase (PPIase) assays

Having worked wit Selcia on a number of projects I always keep an eye out for news on their work on Peptidyl-Prolyl cis-trans Isomerases (PPIase). These are very interesting class of enzymes whose principal function is to catalyse the cis-trans isomerisation of the X-Pro peptide bonds in polypeptide chains (where X is any amino acid). This transformation is thought to be a mechanism to modulate protein function.

PPIase

PPIase enzyme targets are of increasing interest in drug discovery due to the extensive potential of small molecule inhibitors in a range of therapeutic areas, including infection, inflammation, cancer and neuroprotection.

Selcia have now expanded the range of Peptidyl-Prolyl cis-trans Isomerase (PPIase) assays they can offer.

Open Source Malaria Competition

The Open Source Malaria group are running a competition to develop a computational model that predicts which molecules will block the malaria parasite's ion pump, PfATP4.

PfATP4 is an important target for the development of new drugs for malaria. We are providing a dataset of actives and inactives. The challenge is to use the data to develop a model that allows us to (better) design compounds that will be active against that target.

The competition will close on 31st March 2017.

The details of the competition can be found here https://github.com/OpenSourceMalaria/OSMToDo_List/issues/421 and the video below gives more information

There is a Jupyter notebook that can be used to to access the information here http://www.macinchem.org/reviews/osm/osmipython.php or you can access the information in this google document https://docs.google.com/spreadsheets/d/1Rvy6OiM291d1GNcyT6eSwC3lSuJ1jaR7AJa8hgGsc/edit#gid=510297618, but remember the competition is a predictive model for series 4 only.

More details on Open Source Malaria