SwePub
Sök i LIBRIS databas

  Extended search

id:"swepub:oai:DiVA.org:uu-429769"
 

Search: id:"swepub:oai:DiVA.org:uu-429769" > Predicting the perm...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Predicting the permeability of macrocycles from conformational sampling – limitations of molecular flexibility

Poongavanam, Vasanthanathan (author)
Uppsala universitet,Organisk kemi
Atilaw, Yoseph (author)
Uppsala universitet,Organisk kemi
Ye, Sofie (author)
Uppsala universitet,Oorganisk kemi
show more...
Ermondi, Giuseppe (author)
University of Torino
Wieske, Hermina, 1994- (author)
Uppsala universitet,Organisk kemi
Erdélyi, Máté, 1975- (author)
Uppsala universitet,Organisk kemi
Caron, Giulia (author)
University of Torino
Kihlberg, Jan (author)
Uppsala universitet,Organisk kemi
show less...
 (creator_code:org_t)
Elsevier BV, 2020
2020
English.
In: Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0022-3549 .- 1520-6017. ; 110:1, s. 301-313
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • Macrocycles constitute superior ligands for targets that have flat binding sites but often require long synthetic routes, emphasizing the need for property prediction prior to synthesis. We have investigated the scope and limitations of machine learning classification models and of regression models for predicting the cell permeability of a set of de novo-designed, drug-like macrocycles. 2D-Based classification models, which are fast to calculate, discriminated between macrocycles that had low-medium and high permeability and may be used as virtual filters in early drug discovery projects. Importantly, stereo- and regioisomer were correctly classified. QSPR studies of two small sets of comparator drugs suggested that use of 3D descriptors, calculated from biologically relevant conformations, would allow development of more precise regression models for late phase drug projects. However, a 3D permeability model could only be developed for a rigid series of macrocycles. Comparison of NMR based conformational analysis with in silico conformational sampling indicated that this shortcoming originates from the inability of the molecular mechanics force field to identify the relevant conformations for flexible macrocycles. We speculate that a Kier flexibility index of ≤10 constitutes a current upper limit for reasonably accurate 3D prediction of macrocycle cell permeability.

Subject headings

NATURVETENSKAP  -- Kemi -- Organisk kemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences -- Organic Chemistry (hsv//eng)

Keyword

Permeability
Machine learning
Nuclear magnetic resonance (NMR)
spectroscopy
Quantitative structure-property relationship(s) (QSPR)
Membrane translocation
Macrocycle
Chemistry with specialization in Organic Chemistry
Kemi med inriktning mot organisk kemi

Publication and Content Type

ref (subject category)
art (subject category)

Find in a library

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view