Computational investigations of non-steroidal anti-inflammatory drugs

Dnr:

SNIC 2015/6-168

Type:

SNAC Small

Principal Investigator:

Yasmin Khan

Affiliation:

Uppsala universitet

Start Date:

2015-12-09

End Date:

2018-01-16

Primary Classification:

10203: Bioinformatik (beräkningsbiologi) (tillämpningar under 10610)

Webpage:

Allocation

Abstract

Non-steroidal anti-inflammatory drugs (NSAIDs) such as aspirin and ibuprofen are common household drugs used for treating fevers and aches. These drugs target the cyclooxygenases 1 and 2 in various combinations of selectivity and affinity. The variance in selectivity and affinity cause differences in use and side-effects. Traditional non-selective NSAIDs are used to treat fevers and common pain, while COX-2-selective inhibitors are used by patients with chronic pain, such as reumatid arthritis. Recently, NSAIDs have also been considered as possible drugs for treating cancer patients. However, these drugs do come with side-effects. Common ones for traditional NSAIDs include ulcers and GI-toxicity, while newer generation COX-2 selective NSAIDs have been retracted from the market due to increases in myocardiac infarctions. The key to reduce side-effects seems to be the ability of tuning the selectivity between the two isoforms. But to do this, we need to understand how the inhibitors bind these enzymes, and what changes can be made to increase or lessen their potency towards each of the isoforms. By using a combination of various computational methods, including molecular docking and molecular dynamics simulations, we predict the affinities of diverse NSAIDs to both COX-1 and COX-2. We are thus able to describe the differences between the two isoforms, and how these affect the affinities of the drugs.