TITLE: No Title
AUTHORS: 

[DESCRIPTION]
<p>This protocol is for the ProteSEEKER™ kit, designed to identify the specific type of proteases present in cell or tissue lysates, and allows determining the minimal number of individual protease inhibitors required for a sample. </p>

[GUIDELINES]
<p><strong>INTRODUCTION </strong></p>
<p>ProteSEEKER™ is a simple kit designed to identify the specific type of proteases present in your cell or tissue lysates, and allows you to determine the minimal number of individual protease inhibitors required for your sample.  For researchers using commercial protease inhibitor, a common problem is that some biological samples have elevated levels of proteases compared to the established norms.  In this scenario, the general protease inhibitor cocktails are inefficient resulting in degradation of your proteins.  One option is to increase the amount of general protease inhibitor cocktail used, which is very cost ineffective, or to identify the elevated protease and then supplement your extraction or lysis buffer with extra protease inhibitors specific for that protease.</p>
<p> </p>
<p>ProteSEEKER™ consists of twelve ready to use individual protease inhibitors (see below) at a 100X concentration and a sensitive Protease Screening Kit.  The concentration of the protease inhibitors are adjusted to inhibit &gt;90% activity of individual protease in crude tissue extracts at 1X concentration.  The principle of ProteSEEKER™ is that small quantities of your samples are supplemented with each one of the 12 inhibitors supplied.  Each sample is screened with the Protease Screening kit and the results used to determine which protease species is present in your sample.  </p>
<p> </p>
<p>The Protease Screening kit is based on a ready to use dye‐labeled protein, the protease substrate, which is digested by proteases to release dye‐labeled peptides.  The absorbance of which is measured at 574nm for determination of protease activity.  </p>
<p> </p>
<p><strong>ITEM(S) SUPPLIED (Cat. # 786‐325)</strong></p>
<table>
<tbody>
<tr>
<td><strong>Description</strong></td>
<td><strong>Size</strong></td>
</tr>
<tr>
<td>Protease Substrate (Lyophilized; 150µl)</td>
<td>1</td>
</tr>
<tr>
<td>Incubation Buffer</td>
<td>5ml</td>
</tr>
<tr>
<td>Precipitation Agent</td>
<td>5ml</td>
</tr>
<tr>
<td>Assay Buffer</td>
<td>6ml </td>
</tr>
</tbody>
</table>
<p> </p>
<p><em><strong>Protease Inhibitor Set</strong></em></p>
<table>
<tbody>
<tr style="height: 20px;">
<td style="height: 20px;"><strong>Inhibitor</strong></td>
<td style="height: 20px;"><strong>Inhibits</strong></td>
<td style="height: 20px;"><strong>Size</strong></td>
</tr>
<tr style="height: 48px;">
<td style="height: 48px;">
<p><strong>AEBSF [100X]</strong></p>
<p>4‐(2‐Aminoethyl)‐ benzenesulfonyl‐fluoride, hydrochloride</p>
</td>
<td style="height: 48px;">Irreversible inhibitor of serine proteases‐  trypsin, chymotrypsin, plasmin, plasma kallikrein, &amp; thrombin</td>
<td style="height: 48px;">25µl</td>
</tr>
<tr style="height: 32px;">
<td style="height: 32px;">
<p><strong>ALLN [100X]</strong></p>
<p>(N‐Acetyl‐Leu‐Leu‐Nle‐CHO (Calpain Inhibitor I))</p>
</td>
<td style="height: 32px;">Cell‐permeable, peptide aldehyde inhibitor of Calapin and other neutral cysteine proteases</td>
<td style="height: 32px;">25µl</td>
</tr>
<tr style="height: 20px;">
<td style="height: 20px;"><strong>Antipain‐dihydrochloride [100X]</strong></td>
<td style="height: 20px;">Inhibits papain, trypsin and to small extent plasmin</td>
<td style="height: 20px;">25µl</td>
</tr>
<tr style="height: 20px;">
<td style="height: 20px;"><strong>Aprotinin [100X]</strong></td>
<td style="height: 20px;">Inhibits serine proteases‐ plasmin, kallikrein, trypsin, chymotrypsin</td>
<td style="height: 20px;">25µl</td>
</tr>
<tr style="height: 20px;">
<td style="height: 20px;"><strong>Bestatin [100X]</strong></td>
<td style="height: 20px;">Inhibitor of amino‐peptidases and other exopeptidases (does not inhibit carboxypeptidases)</td>
<td style="height: 20px;">25µl</td>
</tr>
<tr style="height: 20px;">
<td style="height: 20px;"><strong>Chymostatin [100X]</strong></td>
<td style="height: 20px;">Specific inhibitor of α, β, γ, δ chymotrypsin</td>
<td style="height: 20px;">25µl</td>
</tr>
<tr style="height: 48px;">
<td style="height: 48px;">
<p><strong>E‐64 [100X]</strong></p>
<p>(N‐(N‐(L‐3 Trans‐carboxirane‐ 2‐carbonyl)‐L‐leucyl)‐ agmatine)</p>
</td>
<td style="height: 48px;">Inhibitor of papain and other cystein proteases like cathepsin B &amp; L</td>
<td style="height: 48px;">25µl</td>
</tr>
<tr style="height: 20px;">
<td style="height: 20px;"><strong>EDTA‐Na<sub>2</sub> [100X]</strong></td>
<td style="height: 20px;">Inhibits metalloproteases</td>
<td style="height: 20px;">25µl</td>
</tr>
<tr style="height: 20px;">
<td style="height: 20px;"><strong>Leupeptin [100X]</strong></td>
<td style="height: 20px;">Inhibits Serine &amp; Cystein proteases e.g. Plasmin, Trypsin, Papain &amp; Cathepsin B </td>
<td style="height: 20px;">25µl </td>
</tr>
<tr style="height: 20px;">
<td style="height: 20px;"><strong>Pepstatin [100X]</strong></td>
<td style="height: 20px;">Inhibits Aspartic proteases, such as pepsin, renin, cathepsin D, chymosin </td>
<td style="height: 20px;">25µl </td>
</tr>
<tr style="height: 20px;">
<td style="height: 20px;"><strong> Phosphoramidon [100X]</strong></td>
<td style="height: 20px;">Specifically inhibits thermolysin,collagenase &amp; other metalloendoproteinases </td>
<td style="height: 20px;">25µl </td>
</tr>
<tr style="height: 32px;">
<td style="height: 32px;">
<p><strong>PMSF [100X]</strong></p>
<p>Phenylmethylsulfonyl fluoride</p>
</td>
<td style="height: 32px;">Inhibits serine proteases; chymotrypsin, trypsin &amp; thrombin, also inhibits cystein proteases such as papain (reversible by DTT) </td>
<td style="height: 32px;">25µl </td>
</tr>
</tbody>
</table>
<p> </p>
<p> </p>
<p><strong>STORAGE CONDITIONS</strong></p>
<p>The kit is shipped at ambient temp. Upon arrival, store it at 4°C and the kit components are stable for 1 year.</p>
<p> </p>
<p><strong>ADDITIONAL ITEMS REQUIRED </strong></p>
<p>Microtiter plates, microcentrifuge tubes, plate reader, spectrophotometer and centrifuge.  </p>
<p> </p>
<p><em><strong> NOTE:</strong></em> The assay is designed for microtiter plate. The use of microtiter plate requires use of a centrifuge adapted for microtiter plates.  Alternatively, the assay may be performed in microcentrifuge tubes and the final reaction product is transferred to microtiter plates for the measurement of optical density.  </p>
<p> </p>
<p><strong>CALCULATION OF PERCENT INHIBITION</strong></p>
<p>Inhibition of protease is dependent on the nature and concentration of both inhibitors and protease activity. Changing either the test sample size (i.e. protease concentration) or the volume of inhibitor (i.e. inhibitor concentration) into the reaction mixture may change the percent inhibition. For increasing percent inhibition, concentration of inhibitor in the reaction mixture may be increased. Calculate the percent inhibition of protease activity as follows:</p>
<p> </p>
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" /></p>
<p>Use the result and the Protease Inhibitor Set table above to determine the protease species present in your sample.  Individual protease inhibitors are available in larger quantities for preparative scale use.  </p>
<p> </p>

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