Skip to main content

New Drug Approvals 2011 - Pt. XXVI - Icatibant (FirazyrTM)

Wikipedia: Icatibant

On the August 25th 2011, the FDA approved Icatibant (trade name: FirazyrTM), a bradykinin B2 receptor (B2R) antagonist indicated for the treatment of acute attacks of hereditary angioedema (HAE) in patients aged 18 or older.

HAE is a rare genetic disease and is caused by low levels of C1-esterase inhibitor (C1-INH), the major endogenous inhibitor and regulator of the protease plasma kallikrein and the key regulator of the Factor XII/kallikrein cascade. One component this cascade is the production of bradykinin by plasma kallikrein. During HAE attacks, disregulated activity of plasma kallikrein leads to excessive bradykinin production; bradykinin is a potent vasodilator, which s thought to be responsible for the characteristic HAE symptoms of localised swelling, inflammation and pain.

Icatibant treats the clinical symptoms of HAE attack by selective- and competitively binding, as an antagonist, to the B2 bradykinin receptor (B2R) (Uniprot: P30411; ChEMBL ID: CHEMBL3157; PFAM: PF00001), with similar affinity to bradykinin (1-10 nM for the B2R, while affinity for the B1R is 100-fold lower). Icatibant is the first in class agent against this target. The -tibant stem covers bradykinin antagonists.

B2R is a Rhodopsin-like receptor, 391 amino acid long, which belongs to the G protein-coupled receptor (GPCR) A3 family and is encoded by the BDKRB2 gene in humans. The amino acid sequence of B2R is:

There are no known experimental structures of B2R, however there are several relevant homologous structures of other members of the rhodopsin-like GPCR family (see here for a current list).
Icatibant is the third drug approved in the US to treat HAE attacks. Previous drugs include Ecallantide (approved in December 2009 under the trade name Kalbitor), which is a potent, selective, reversible inhibitor of plasma kallikrein, and C1-INH (approved in October 2009 under the trade name Berinert), which is a freeze-dried human C1-esterase inhibitor concentrate.

Icatibant (IUPAC: (2S)-2-[[(3aS,7aS)-1-[2-[(2S)-2-[[(2S)-2-[[2-[[(4R)-1-[1-[2-[[(2R)-2-amino-5-(diaminomethylideneamino)pentanoyl]amino]-5-(diaminomethylideneamino)pentanoyl]pyrrolidine-2-carbonyl]-4-hydroxypyrrolidine-2-carbonyl]amino]acetyl]amino]-3-thiophen-2-ylpropanoyl]amino]-3-hydroxypropanoyl]-3,4-dihydro-1H-isoquinoline-3-carbonyl]-2,3,3a,4,5,6,7,7a-octahydroindole-2-carbonyl]amino]-5-(diaminomethylideneamino)pentanoic acid; ChEMBL ID: CHEMBL375218; PubChem: 71364; ChemSpider: 5293384) is a synthetic decapeptide that differs from bradykinin (a nonapeptide with an amino acid sequence RPPGFSPFR) at the amino acids' positions 3, 5, 7 and 8, which have been replaced by four non-natural amino acids, and also in one additional amino acid (a D-arginine) at the N-terminus of the bradykinin arginine at position 1. Thus, Icatibant amino acid sequence is D-Arg-Arg-Pro-Hyp-Gly-Thi-Ser-D-Tic-Oic-Arg. These modifications prevent Icatibant from being metabolised by major bradykinin-metabolizing enzymes, which makes it more stable that bradykinin. Icatibant has a molecular weight of 1304.5 Da.

Icatibant can be self-administrated through an injection in the abdominal area, thus providing a new option for the treatment of acute HAE attacks. The recommended dose is 30 mg administrated subcutaneously. In the case of inadequate response or recurrence of symptoms, additional dose may be administrated at intervals of at least 6 hours, with no more than 3 doses administrated in any 24-hour period (recommended daily dose equivalent 69.0 umol). 

Following a 30 mg subcutaneous dose, the absolute bioavailability of Icatibant is ca. 97%, with a plasma clearance of 245 mL/min, a mean elimination half-life of 1.4 hours and a volume of distribution of 29 L. Icatibant is extensively metabolised by proteolytic enzymes to inactive metabolites that are primarily excreted in the urine, with <10% of the dose eliminated as unchanged drug. As would be anticipated for a peptide drug, Icatibant is not an inhibitor of major cytochrome P450 (CYP) isoenzymes and is not an inducer of CYP 1A2 and 3A4.

The full prescribing information can be found here.

Icatibant is marketed by Shire Human Genetic Therapies Inc. and the product website is (Since 2008, Icatibant has been approved for use in the European Union; the european SPC can be found here).


Unknown said…
First of all I've got to say I'm really enjoying this new series of drug approval posts.

With regards to the links in this post. I believe that the structure that you've shown is the same as as that described in Shire's literature:

But would argue that none of the other sources accurately describe the structure.

The PubChem record has 5 undefined stereocentres (based on the image and the InChI displayed on the page)

The CHEMBL record has 2 undefined stereocentres.

Sadly, the ChemSpider record that was associated with the name Icatibant (previously - 16736634) was also missing a stereocentre. But on the basis looking at the structure that you provided in the blog post and the Shire documentation I have curated the database to make ChemSpider record the record for Icatibant.
Shaun said…
Hi Dave,

This compound was redrawn last week after we noticed that the stereocentres were missing. It should be loaded for the next release. thanks,
Louisa (ChEMBL chemical curator)

Popular posts from this blog

A python client for accessing ChEMBL web services

Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEMBL d

ChEMBL 29 Released

  We are pleased to announce the release of ChEMBL 29. This version of the database, prepared on 01/07/2021 contains: 2,703,543 compound records 2,105,464 compounds (of which 2,084,724 have mol files) 18,635,916 activities 1,383,553 assays 14,554 targets 81,544 documents Data can be downloaded from the ChEMBL FTP site: .  Please see ChEMBL_29 release notes for full details of all changes in this release: New Deposited Datasets EUbOPEN Chemogenomic Library (src_id = 55, ChEMBL Document IDs CHEMBL4649982-CHEMBL4649998): The EUbOPEN consortium is an Innovative Medicines Initiative (IMI) funded project to enable and unlock biology in the open. The aims of the project are to assemble an open access chemogenomic library comprising about 5,000 well annotated compounds covering roughly 1,000 different proteins, to synthesiz

Identifying relevant compounds in patents

  As you may know, patents can be inherently noisy documents which can make it challenging to extract drug discovery information from them, such as the key targets or compounds being claimed. There are many reasons for this, ranging from deliberate obfuscation through to the long and detailed nature of the documents. For example, a typical small molecule patent may contain extensive background information relating to the target biology and disease area, chemical synthesis information, biological assay protocols and pharmacological measurements (which may refer to endogenous substances, existing therapies, reaction intermediates, reagents and reference compounds), in addition to description of the claimed compounds themselves.  The SureChEMBL system extracts this chemical information from patent documents through recognition of chemical names, conversion of images and extraction of attached files, and allows patents to be searched for chemical structures of interest. However, the curren

Julia meets RDKit

Julia is a young programming language that is getting some traction in the scientific community. It is a dynamically typed, memory safe and high performance JIT compiled language that was designed to replace languages such as Matlab, R and Python. We've been keeping an an eye on it for a while but we were missing something... yes, RDKit! Fortunately, Greg very recently added the MinimalLib CFFI interface to the RDKit repertoire. This is nothing else than a C API that makes it very easy to call RDKit from almost any programming language. More information about the MinimalLib is available directly from the source . The existence of this MinimalLib CFFI interface meant that we no longer had an excuse to not give it a go! First, we added a BinaryBuilder recipe for building RDKit's MinimalLib into Julia's Yggdrasil repository (thanks Mosè for reviewing!). The recipe builds and automatically uploads the library to Julia's general package registry. The build currently targe

New Drug Warnings Browser

As mentioned in the announcement post of  ChEMBL 29 , a new Drug Warnings Browser has been created. This is an updated version of the entity browsers in ChEMBL ( Compounds , Targets , Activities , etc). It contains new features that will be tried out with the Drug Warnings and will be applied to the other entities gradually. The new features of the Drug Warnings Browser are described below. More visible buttons to link to other entities This functionality is already available in the old entity browsers, but the button to use it is not easily recognised. In the new version, the buttons are more visible. By using those buttons, users can see the related activities, compounds, drugs, mechanisms of action and drug indications to the drug warnings selected. The page will take users to the corresponding entity browser with the items related to the ones selected, or to all the items in the dataset if the user didn’t select any. Additionally, the process of creating the join query is no