Druggability and drug-likeness concepts in drug design: are biomodelling and predictive tools having their say?

A Diversity‐Oriented Approach to Large Libraries of Artificial Macrocycles

“…Drug discovery has always been facing increasingly challenging biological targets, pushing forward the boundaries of what is called "druggability" and pursuing chemists to explore undermined areas of chemical space. [1][2][3] Macrocyclic compounds, which have given a rise to a considerable hype in both medicinal and synthetic chemistry recently, represent a prominent example of such an area. [4][5][6][7] Originating mostly from natural compounds which violate the well-known drug-likeness rules (i. e. rule-of-five), both natural and synthetic macrocycles are now considered as a very promising tool to address "difficult" biological targets lacking a strong binding site, e. g. protein-protein interactions.…”

“…Drug discovery has always been facing increasingly challenging biological targets, pushing forward the boundaries of what is called “druggability” and pursuing chemists to explore undermined areas of chemical space [1–3] . Macrocyclic compounds, which have given a rise to a considerable hype in both medicinal and synthetic chemistry recently, represent a prominent example of such an area [4–7] .…”

“…Importantly, a huge variety of the commercially available vicinal diamine derivatives, [53] as well as their highly confident chemical reactivity, are the main prerequisites of high diversity of the macrocyclic scaffolds that can be constructed. A possibility to further extend the size of the resulting library 4 by the "postpairing" modifications is also envisaged by introducing a protected amino function into one of the capping reagents (3). It should be mentioned that albeit similar approaches to the synthesis of macrocycles were precedent in the literature (see, for example, the work of Nelson and co-workers cited above [40] ), they were not applied to the construction of large compound libraries.…”

“…Yield 503 mg (70 % from 5(7,7,1) (772 mg, 1.87 mmol)). Beige amorphous glassy solid.1 H NMR (400 MHz, CD 3 CN) δ 8.25 (br s, 1H), 8.06 (dd, J = 7.8, 2.0 Hz, 1H), 7.51-7.41 (m, 1H), 7.10-7.01 (m, 2H), 6.04 (d, J = 8.3 Hz, 1H), 5.93 (dt, J = 15.1, 7.3 Hz, 1H), 5.81 (dt, J = 15.1, 6.0 Hz, 1H), 4.65 (dd, J = 10.7, 4.9 Hz, 1H), 4.46 (dd, J = 10.7, 6.7 Hz, 1H), 4.09-3.98 (m, 1H),3.71 (ddd, J = 13.7, 6.5, 3.4 Hz, 1H), 3.26 (ddd, J = 13.7, 8.8, 4.7 Hz, 1H), 2.45 (dd, J = 13.3, 7.5 Hz, 1H), 2.19 (dd, J = 13.3, 7.5 Hz, 1H), 2.12-2.04 (m, 1H), 1.90-1.85 (m, 1H), 1.69-1.54 (m, 6H), 1.49-1.37 (m, 2H), 1.29-1.21 (m, 1H), 0.88 (dd, J = 6.5, 4.7 Hz, 6H) 13. C NMR (151 MHz, CD 3 CN) δ 175.8, 164.6, 157.3, 134.0, 132.8, 131.4, 126.3, 121.9, 121.2, 113.7, 69.2, 55.7, 48.0, 42.3, 42.1, 41.1, 36.8, 33.7, 24.6, 23.8, 23.1, 22.3, 21.5.…”

Partitioning Pattern of Natural Products Based on Molecular Properties Descriptors Representing Drug-Likeness

“…Chemometric methods assigned to the new drug design paths and discovery are sufficient to support the computer-aided drug design using the advantage of representation of natural compounds variety from diverse classes by descriptors that capture their structural similarity faces and drug-like properties [1][2][3][4]. Piles of molecular descriptors produced and assessed by different methods and approaches [5][6][7][8] have been described in the literature for the drugability and drug-likeness properties of small molecules [9][10][11][12][13][14][15][16]. Targeting drug-like properties as proposed by Lipinsky [17] and relies on a well-known rule-of-five which is described on five simple physicochemical parameters (molecular weight ≤ 500, log P ≤ 5, H-bond donors ≤ 5, H-bond acceptors ≤ 10, Topological Polar Surface Area < 140 A 2 good intestinal absorption).…”