↓ Skip to main content

Computational modeling and in-vitro/in-silico correlation of phospholipid-based prodrugs for targeted drug delivery in inflammatory bowel disease

Overview of attention for article published in Perspectives in Drug Discovery and Design, November 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
16 Mendeley
Title
Computational modeling and in-vitro/in-silico correlation of phospholipid-based prodrugs for targeted drug delivery in inflammatory bowel disease
Published in
Perspectives in Drug Discovery and Design, November 2017
DOI 10.1007/s10822-017-0079-5
Pubmed ID
Authors

Arik Dahan, Milica Markovic, Shahar Keinan, Igor Kurnikov, Aaron Aponick, Ellen M. Zimmermann, Shimon Ben-Shabat

Abstract

Targeting drugs to the inflamed intestinal tissue(s) represents a major advancement in the treatment of inflammatory bowel disease (IBD). In this work we present a powerful in-silico modeling approach to guide the molecular design of novel prodrugs targeting the enzyme PLA2, which is overexpressed in the inflamed tissues of IBD patients. The prodrug consists of the drug moiety bound to the sn-2 position of phospholipid (PL) through a carbonic linker, aiming to allow PLA2 to release the free drug. The linker length dictates the affinity of the PL-drug conjugate to PLA2, and the optimal linker will enable maximal PLA2-mediated activation. Thermodynamic integration and Weighted Histogram Analysis Method (WHAM)/Umbrella Sampling method were used to compute the changes in PLA2 transition state binding free energy of the prodrug molecule (∆∆G(tr)) associated with decreasing/increasing linker length. The simulations revealed that 6-carbons linker is the optimal one, whereas shorter or longer linkers resulted in decreased PLA2-mediated activation. These in-silico results were shown to be in excellent correlation with experimental in-vitro data. Overall, this modern computational approach enables optimization of the molecular design of novel prodrugs, which may allow targeting the free drug specifically to the diseased intestinal tissue of IBD patients.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 25%
Researcher 2 13%
Student > Ph. D. Student 2 13%
Student > Doctoral Student 1 6%
Student > Bachelor 1 6%
Other 3 19%
Unknown 3 19%
Readers by discipline Count As %
Engineering 3 19%
Pharmacology, Toxicology and Pharmaceutical Science 2 13%
Nursing and Health Professions 2 13%
Medicine and Dentistry 2 13%
Chemistry 1 6%
Other 1 6%
Unknown 5 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 November 2017.
All research outputs
#22,834,739
of 25,461,852 outputs
Outputs from Perspectives in Drug Discovery and Design
#868
of 949 outputs
Outputs of similar age
#299,524
of 340,981 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#13
of 13 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 949 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 340,981 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.