Peptide design x Deep learning

You know recurrent neural network (RNN) is universally used in machine learning for natural language, handwriting, speech and also chemistry.
Recently there are lots of reports that use RNN against SMILES strings to solve chemoinformatics problems. Today I read a short article published from Prof. Gisbert Schneider’s group.
URL is below.

They applied RNN ( LSTM ) for designing of antimicrobial peptides(AMPs). The strategy is basic. First added tag to peptide sequence and padded fixed length. Then encoded one hot vector.
I think key point of their method is selection of training peptides. They removed the sequences that containing Cys because Cys residues potentially forming S-S bridges. It will complicate problems.

Finally they evaluate trained model and the model generate novel peptides that have suitable hydrophobic nature and length.
I think their strategy (remove Cys residues) is nice and fit to RNN.
BTW, regarding the method machine learns peptides as bunch of strings but does not lean features of each amino acid. This is same as SMILES in chemoinformatics area.
I have no answer about it.

If reader who is interested in the approach you can get source code from following URL.


Applications of Fluorine atom in Drug discovery

Some years ago, there was good review in drug discovery about the applications of fluorine. The perspective was published by researchers in BMS. There were many informations about fluorine based on their experience and published data. I think this is still useful for Med Chem.
It was published in 2015 from ACS.

And recently same author who is researcher in BMS reported new review about the review!
I skimmed the review today (59 page! Too long for me ;-)). There are some examples that were reported in previous review but there are lots of new insights and examples of fluorine. The article mainly focused on
Bioisosteric replacement of molecules with fluorine. Bioisosteric replacement is often used in drug discovery to not only maintain potency but also improve metabolic stability, solubility or any parameters.
For example, the author describes about replacement from tert-butyl group to tri-fluoro cyclopropane analogue in “Table3”. It was interesting for me because it is not simple replacement, from tert-Bu to try-fluoro-dimethly group. Also there are some same replacement examples in different protein targets.

Strategy of metabolic block with fluorine atoms is some time easy to understand and medicinal chemists try to introduce fluorine atoms in their compounds. But application of fluorine is not limited in the strategy. An interesting examples are described in the article.
Introduction Fluorine atom in aromatic ring in Compound 174 can improve solubility of the compound from 15mg/mL to >500 mg/ml. The effect of the fluorine is not clear but the author describes the fluorine atom polarizing the adjacent N−H affects the solubility.

And I surprised because fluorine atom strategy is also effective for peptide drug discovery. In table 29, fluoro- derivatives of 36-residue peptide derived from amino terminus of human parathyroid hormone (hPTH) have binding potency for PTH receptor. If there are lots of cost effective fluorinated amino acids are available, can we design more potent peptide derivatives ?

New finding of fluorine effects creates new strategy for drug design. And sometime it is needed new chemistry to make fluorinated building blocks or conduct fluorination reactions.

Medicinal chemists need to catch up both new strategy for drug design and synthetic chemistry I think.

Rational design of GPCR biased Ligand

GPCR is one of druggable target. GPCR activation controls many networks of signaling pathways, which for most receptors are mediated by both G proteins and beta-arrestins. Different signaling pathways give different effects. To avoid side effects from G protein signals, designing beta-arrestins selective ligand is useful strategy for drug discovery. And there are lots of reports about biased-ligand from a few years ago.

I am interested in these area and following article found.
“structure-inspired design of b-arrestin-biased ligands for aminergic GPCRs”

The authors design selective biased ligand of D2 receptor by using homology modeling/SBDD and MD.

At first they focused in to TM5 and EL2 region where are important for G protein/beta arrestin selectivity. And design new molecule from Aripiprazole, replace from di-chloro to indole moiety (Compound 1). The compound 1 was biased.
Next they tried to design substituted analogue of compound1 and got clear SAR of the substituents. Also they performed MD simulation about the indole motif and revealed the effect of the substituents.

Finally they could rationally design more selective biased ligand than initial compound 1 Fig5. Bias index is 20 vs 2 (compound7 vs compound1)

It was interesting for me because all molecules have quite similar structure but little difference affect protein-ligand contacts and can control their signaling pathway!

And computational approach helps rational biased drug design. I feel Low-molecular drug discovery is still exciting area of science.

BTW, in the article Aripiprazole is used for starting point.
Aripiprazole is one of major drug for schizophrenia and bipolar disorder. And Rexulti is also approved drug for schizophrenia and major depression. Structural difference of these molecules is a tail part, di chloro benzene or benzothiophene.

These compounds show different pharmacological profiles.
Also there are difference in metabolic profiles.
Receptor Rexulti Abilify(Ki nM)
5-HT1A 0.12 5.6
5-HT2A 0.47 8.7
5-HT2B 1.9 0.4
D2 0.3 1.6
D3 1.1 5.4
H1 19 27.9
a1b 0.17 34.4
a2c 0.59 37.6

I am now interested in the patent strategy. I will check it.

Think about HTS

Recently there are many approaches for starting drug discovery, i.e. FBDD, SBDD, LBDD, phenotypic, HTS and etc.
High Throughput Screening (HTS) was common strategy for drug discovery when I joined my company. That’s right even now but it is not always appropriate strategy.

For pharma, it requires a lot of investment to maintain their own large compounds screening deck and screening capability. And now there are lots of CROs which has their own library and can perform HTS. HTS can be outsourced now.

I searched HTS trends in Google Trends. It shows decreasing of trends and I think the trend shows HTS is matured technology now.

To perform HTS, it requires compound library. Some years ago compound library design is competitive area but it moves to pre competitive area I think. For example European Lead Factory ( ELF ), J-CLIC ( Japan Compound Library Consortium ) is involved multiple companies. Also many drug likeness indicators or filters such as LE, LLE, QED, PAINS are published in journal and the information spread rapidly. Everyone can apply these roles simply.

Hit rate of HTS is not so high but need lots of investment. However if HTS provides novel and drug like seed compounds it is good starting point for drug discovery. Also HTS can be applied structure unknown targets.
My opinion HTS is matured tech but not dead tech. We(I?) need HTS for seed finding.
If reader who has comments I appreciate it.

Business trip to India

I visited India this week and I came back to Japan today. When I went to Narita Air Port day before departure, the weather chill came to Japan and trains were disrupted due to a snow. The Bus from Air port to hotel was also stacked so I went to hotel by walk. It was hard to me to go to air port and hotel…

I was surprised in my flight. The window is a bit strange. This window has no curtain but has button. And when I pushed the button window color is changed!!!

I found movie in youtube.

Amazing! What’s happen ??? I searched internet and found answer.
The window system is developed by GENTEX, named “Electrochromic technology”.
This technology uses electrochromic gel that is sandwiched between thin panels. And the gel changes color by passing electronic current. Chem station also describes the technology and the site estimates the material is WO3. Because WO3 is colorless at neutral state but it turned blue when it is cationic state. Also inorganic material is durable compared to organic material.
Science! Science! Science! 😉

Of course I enjoyed Indian traditional food curry, masara dosa, biriyani and tandoori chicken etc….

And I got Torkoal which is regional exclusive Pokemon in my free time. 😉


Screen Shot 2017-12-31 at 22.09.25





Back to my home

I and my family visited Okinawa and back to home today. That place was warm and comfortable. We enjoyed the travel. My son excited his first experience of taking airplane. 😉
We enjoyed Okinawa’s soul food. Okinawa was very warm and conforta

Goya Chample and orion beer!

Visited Churaumi Aquarium and saw Whale shark. Body weight of the shark is over 5000kg! @_@

And we could see beautiful sea
Following movie took by my dorone!
Kouri Bridge!

Sunset beach!

I think this family vacation was really successful.