Protease classification

Protease Classification. In order to rationally design an inhibitor for a protease it is first necessary to place it into one of four families of proteases (see Table V). For a new enzyme, a study of its inhibition profile with a series of general protease inhibitors is sufficient to classify it into one of the four families. The inhibitors usually used are diiso-propylphosphofluoridate (DFP) or phenylmethane sulfonyl fluoride (PMSF) for serine proteases, 1,10-phenanthroline for metalloproteases, thiol reagents such as iodoacetate or N-ethylmaleimide for thiol proteases, and pepstatin or diazo compounds such as diazoacetyl-norleucine methyl ester for carboxyl proteases. 

Figure 19.16 Chemical depiction of the protease classification system showing both the metabolic machinery and the transition state that Is thought to be operative for each case. (A) represents both serine (X=0) and cysteine (X=S) proteases with each of these specific amino acids being Implicated, respectively. (B) exemplifies an aspartic protease with the latter playing a key catalytic function within the active site. (C) depicts the metallo proteases with Zn++ representing one of the most common. Suspected transition states / for each protease reaction are shown within brackets.

The example of amprenavir, an HIV-1 protease inhibitor, shows that intestinal metabolism can also be used as a strategy to enhance the bioavailability of compounds. In the biopharmaceutics classification system (BCS), amprenavir can be categorized as a class II compound it is poorly soluble but highly permeable [51]. Fosamprenavir, the water-soluble phosphate salt of amprenavir, on the other hand, shows poor transepithelial transport. However, after oral administration of fosamprenavir, this compound is metabolized into amprenavir in the intestinal lumen and in the enterocytes mainly by alkaline phosphatases, resulting in an increased intestinal absorption [51, 174],... 

Enzymes that act on peptide bonds (i.e., peptidases and proteases) hydrolyze peptide bonds in peptides and proteins. We examine first their classification before outlining their localizations and some physiological roles. 

Based on their sequence homology, disulfide connectivity, and cysteine location within the sequence and chemistry of the reactive site. Pis can be assigned to distinct families, as classified by Laskowski and Kato. Kunitz-type, Bowman—Birk-type, Potato type I and type II, and squash inhibitors are members of these families shown in Table 3. For inhibitors not falling into these classifications more families have been proposed. Pis can also be classified by their target/mode of action. Plants have been found to express Pis that target serine proteinases, cysteine proteinases, aspartic proteinases, and metallo-proteinases. Serine and cysteine protease inhibitors are the best-studied PIs. ... 

Classincation of the Proteases. The classification of the proteases is based on their mechanism of catalysis (4), The four primary classes of proteases are the serine, aspartic, cysteine, and metalloproteases (5). This classification is based on the primary functional group found in the en me s active site. There are likely to be other proteases eventually characterized which will not precisely fit into this categorization scheme and additional categories will be needed. One example of a potential new category is the ATP-dependent proteinases (6), a group of proteinases which require ATP for activity. 

The use of enzymes and whole cells as catalysts in organic chemistry is described. Emphasis is put on the chemical reactions and the importance of providing enantiopure synthons. In particular kinetics of resolution is in focus. Among the topics covered are enzyme classification, structure and mechanism of action of enzymes. Examples are given on the use of hydrolytic enzymes such as esterases, proteases, lipases, epoxide hydrolases, acylases and amidases both in aqueous and low-water media. Reductions and oxidations are treated both using whole cells and pure enzymes. Moreover, use of enzymes in sngar chemistiy and to prodnce amino acids and peptides are discnssed. 

Regardless of toxic risks, various inhibitors of pancreatic and brush border membrane-bound proteases are listed in Table 5.2 and Table 5.3, respectively. Beside this overview, a classification of inhibitory agents based on their chemical structure is shown below. 

Enzymes are proteinaceous catalysts peculiar to living matter. Hundreds have been obtained in purified and crystalline form. Their catalytic efficiency is extremely high—one mole of a pure enzyme may catalyze the transformation of as many as 10,000 to 1,000,000 moles of substrate per minute. While some enzymes are highly specific for only one substrate, others can attack many related substrates. Avery broad classification of enzymes would include hydrolytic enzymes (esterases, proteases), phosphorylases, oxidoreductive enzymes (dehydrogenases, oxidases, peroxidases), transferring enzymes, decarboxylases and others. 

Proteases are classified according to their catalytic mechanism. There are serine, cysteine, aspartic, and metalloproteases. This classification is determined through reactivity toward inhibitors that act on particular amino acid residues in the active site region of the enzyme. The serine proteases are widely distributed among microbes. The enzymes have a reactive serine residue in the active site and are generally inhibited by DFP or PMSF. They... 

Reaction with Diazo Reagents. The classification of the acid proteases on the basis of their pH optima as suggested by Hartley (43) was useful in the absence of other information on the nature of active site residues. Since Hartley s proposal, however, it has been discovered— first with porcine pepsin—that in the presence of Cu ions these enzymes can be specifically inactivated with diazotized dipeptide esters. An ester linkage is formed between one specific aspartic acid side chain and the inhibitor (50). 

Propylthiouracil, 736 Prospective study, 964 Prostaglandin F, 646 Prostaglandin II2 fPGHi), 645 Prostaglandin receptors, 646 Prostaglandins, 533, 642-643 biosynthesis, 400 classification, 645 colon cancer and, 912 conversion of arachidonic acid lo, 644-645 function, 646 Proteases, 60,63,88 action, 123-124, 444 bloixl clotting, 530-531 ca]duin>activated, 793 Protein C, 524,535 Protein deficiency, 116 Proiein density, 422 Protein efficiency ratio (PER), 469 71 Protein lunase B, 792 Protein kinase C, 786,793 Protein kinases, 54,161, IflS Protein nutrition, 458-459, 475 AIDS and. 480... 

The structural classification of the zincins discussed above has been based on the three-dimensional data on zinc proteases currently available. These data (Fig. 2) are from zinc-dependent endopeptidases. It is therefore not mandatory for these enzymes to interact with the ter-minii of their protein substrates. However, for the zinc-dependent amino- and carboxypepti-dases that possess the HexxH consensus [3-5], this additional requirement for substrate recognition may result in a three-dimensional structure which is considerably modified from the astacin scaffold observed for the endoproteases. 

Unknown elements of primary sequence and zinc consensus determine the tertiary fold, indicating that the parallel structural and sequence categories classifing the zinc proteases is a result of the fortuitious selection of the proteases used for structural analysis. 

Lin, T.-H., Wang, G.-M. and Hsu, Y.-H. (2002) Classification of some active HlV-1 protease inhibitors and their inactive analogues using some uncorrelated three-dimensional molecular descriptors and a fuzzy c-means algorithm. 

Patankar, S.J. and Jurs, P.C. (2003a) Classification of HIV protease inhibitors on the basis of their antiviral potency using radial basis function neural networks./. Comput. Aid. Mol. Des., 17, 155-171. 

Lang, S.A., Kozyukov, A.V., Balakin, K.V., Skorenko, A.V., Ivashchenko, A.A. and Savchuk, N.P. (2002) Classification scheme for the design of serine protease targeted compound libraries. J Comput Aided Mol Design, 16, 803-807. 

---