Kinase embeddings

Prepare protein sequence embeddings and preprocess target values

Setup

import pandas as pd, seaborn as sns

from katlas.imports import *
from sklearn.preprocessing import StandardScaler
from matplotlib import pyplot as plt

from sklearn import set_config
set_config(transform_output = "pandas")

Preprocess target

We will standardize each kinase’s PSSMs individually, so that each PSSM will have a mean of 0.

# load target
target = pd.read_csv('train_data/combine_freq_PSPA.csv').set_index('kinase')
# standardize 0s,0t,0y
v0 = StandardScaler().fit_transform(target.iloc[:,-3:].T).T

# standardize all other positions
vv = StandardScaler().fit_transform(target.iloc[:,:-3].T).T

# combine the two
v = pd.concat([vv,v0],axis=1)
v
-5P -5G -5A -5C -5S -5T -5V -5I -5L -5M -5F -5Y -5W -5H -5K -5R -5Q -5N -5D -5E -5s -5t -5y -4P -4G -4A -4C -4S -4T -4V -4I -4L -4M -4F -4Y -4W -4H -4K -4R -4Q -4N -4D -4E -4s -4t -4y -3P -3G -3A -3C -3S -3T -3V -3I -3L -3M -3F -3Y -3W -3H -3K -3R -3Q -3N -3D -3E -3s -3t -3y -2P -2G -2A -2C -2S -2T -2V -2I -2L -2M -2F -2Y -2W -2H -2K -2R -2Q -2N -2D -2E -2s -2t -2y -1P -1G -1A -1C -1S -1T -1V -1I -1L -1M -1F -1Y -1W -1H -1K -1R -1Q -1N -1D -1E -1s -1t -1y 1P 1G 1A 1C 1S 1T 1V 1I 1L 1M 1F 1Y 1W 1H 1K 1R 1Q 1N 1D 1E 1s 1t 1y 2P 2G 2A 2C 2S 2T 2V 2I 2L 2M 2F 2Y 2W 2H 2K 2R 2Q 2N 2D 2E 2s 2t 2y 3P 3G 3A 3C 3S 3T 3V 3I 3L 3M 3F 3Y 3W 3H 3K 3R 3Q 3N 3D 3E 3s 3t 3y 4P 4G 4A 4C 4S 4T 4V 4I 4L 4M 4F 4Y 4W 4H 4K 4R 4Q 4N 4D 4E 4s 4t 4y 0s 0t 0y
SRC 0.288615 0.937824 0.905363 -1.058492 -0.441744 -0.555355 0.256155 0.045162 0.954054 -0.944880 -0.328132 -1.512938 -1.448017 -0.798808 1.100126 0.223695 0.158774 -0.068449 1.668183 2.463463 -0.474204 -0.879959 -0.490435 0.479723 1.257423 0.593137 -0.978465 -0.233169 -0.670626 0.204287 -0.265573 1.435646 -0.994667 -0.459998 -1.415922 -1.415922 -0.978465 0.350106 0.285298 0.058468 0.042266 1.613869 2.294357 0.058468 -0.784040 -0.476201 0.251267 0.947354 1.206363 -1.302788 -0.444820 -0.736205 0.299831 -0.461008 0.558840 -1.140907 -0.752393 -1.335164 -1.416104 -0.946650 0.526464 0.008446 0.477900 0.008446 1.821510 3.764078 -0.088682 -0.849522 -0.396256 0.816792 1.431673 0.719706 -1.189660 -0.574780 -0.914582 0.363722 -0.315883 0.331360 -1.189660 -0.623323 -1.497100 -1.367652 -0.833677 0.671163 -0.299702 0.201912 0.363722 2.192183 2.483442 0.234274 -0.623323 -0.380607 0.541714 0.153368 0.849154 -1.011668 -0.801315 -0.801315 2.062734 1.399311 2.192183 -1.286747 -0.202615 -1.416195 -1.302928 -0.704228 -0.315883 -0.801315 -0.218796 -0.315883 0.946241 1.787656 -0.445331 -0.251158 -0.056985 -0.847837 2.153449 0.855596 -1.107408 -0.361142 -1.042515 0.709587 0.222892 0.806926 -1.091184 -0.458481 -1.496764 -1.366978 -0.815391 0.222892 -0.361142 0.482463 -0.231356 1.715424 2.656368 0.044437 -0.636936 -0.052902 0.183643 0.868580 1.064276 -1.006844 -0.354522 -0.664375 0.787040 0.004254 1.308897 -0.957920 -0.550219 -1.414545 -1.267772 -0.908996 -0.044670 -0.012054 0.199951 0.020562 1.178433 2.287379 0.118410 -0.582835 -0.256674 0.797607 0.535536 0.781228 -1.020510 -0.496368 -0.823957 0.895884 0.338983 2.468309 -0.987751 0.142430 -1.151545 -1.331719 -0.545506 0.126050 0.437260 -0.430850 -0.332574 0.895884 1.076058 -0.348953 -0.840336 -0.185159 0.623344 1.116021 0.935373 -1.133872 -0.378433 -0.936801 0.656189 -0.148517 1.165289 -0.838265 -0.394856 -1.281675 -1.265252 -0.805420 1.214557 0.935373 -0.197785 -0.345588 0.968218 1.822192 -0.411278 -0.903956 -0.394856 -0.701944 -0.712257 1.414201
EPHA3 0.067908 0.886947 0.696473 -1.093984 -0.427324 -0.617799 0.201240 -0.236850 0.486951 -0.941604 -0.293993 -1.246363 -1.246363 -0.636846 1.458369 0.753615 0.410761 0.277430 1.305990 2.086933 -0.560656 -0.941604 -0.389230 0.214614 1.467628 0.746195 -0.943475 -0.487833 -0.715654 0.461419 -0.089147 0.898076 -0.810579 -0.297983 -1.399116 -1.380131 -0.791594 0.803151 0.613300 -0.241028 -0.203058 1.790374 1.695448 -0.127117 -0.715654 -0.487833 0.384444 0.953685 1.086508 -1.190457 -0.735064 -0.773013 0.441368 0.023925 1.067534 -1.114558 -0.526342 -1.380204 -1.342254 -0.697114 0.801888 0.213672 0.194697 0.004950 1.219331 2.149092 0.156748 -0.848912 -0.089924 0.460343 1.162407 0.934711 -1.057634 -0.564291 -0.981735 -0.146848 0.004950 0.232646 -1.114558 -0.810962 -1.456103 -1.266355 -0.886861 1.124458 0.118798 0.365469 -0.070949 1.352154 2.566535 0.308545 -0.431468 0.156748 -0.659165 0.004950 0.365469 -1.228406 -0.981735 -0.829937 0.782913 0.707014 2.187041 -1.342254 -0.279671 -1.456103 -1.266355 -0.981735 -0.184797 -0.431468 -0.317620 1.048559 2.851156 2.016269 -0.260696 -0.108898 0.365469 -0.999870 1.603924 1.014744 -0.961859 -1.037882 -1.322969 1.375854 0.330536 0.862698 -0.809812 -0.638760 -1.437003 -1.189928 -0.695777 -0.277650 -0.790806 0.577611 -0.448702 1.908017 3.580527 -0.144609 -0.828818 0.330536 -0.098097 0.341678 1.010901 -1.035010 -0.901165 -1.035010 0.666729 -0.327545 0.743212 -0.977648 -0.346666 -1.417423 -1.168855 -0.805562 0.188713 -0.327545 -0.155459 0.073989 2.750882 2.980330 0.112230 -0.537873 0.265195 0.524962 0.428830 0.794130 -0.840106 -0.840106 -0.897785 1.255561 0.544188 3.178192 -0.840106 -0.109506 -1.378443 -1.359216 -0.705522 -0.205638 0.294246 -0.282543 -0.551711 1.005619 0.794130 -0.301769 -0.494032 -0.013375 0.335763 0.817219 0.952026 -0.973796 -0.222726 -0.742698 0.643895 -0.184209 0.701669 -0.819731 -0.261242 -1.301186 -1.166379 -0.761956 0.701669 0.374279 -0.164951 0.104664 1.163867 1.876421 -0.319017 -0.588632 -0.164951 -0.683583 -0.730373 1.413956
FES 0.326894 0.640167 1.204058 -1.030623 -0.341422 -0.717350 0.326894 -0.049034 0.828130 -1.114162 -0.383192 -1.448320 -1.364781 -0.821774 1.579985 0.013621 0.264239 0.076275 1.642640 2.310956 -0.466731 -0.926198 -0.550271 0.678069 1.136762 0.490421 -0.864810 -0.552064 -0.531214 0.594670 -0.239318 1.220161 -0.906509 -0.176769 -1.427752 -1.386052 -0.948208 0.657219 0.261075 -0.218469 0.010878 1.741404 1.762253 -0.051671 -0.739711 -0.510365 0.176670 0.926839 1.551979 -1.156963 -0.677688 -0.990259 0.343374 -0.344280 0.989353 -1.115287 -0.761040 -1.490371 -1.490371 -0.844392 0.864325 0.239184 0.489240 -0.052548 1.677007 2.552204 -0.094224 -0.781878 -0.010872 0.572592 1.218571 0.760134 -1.115287 -0.802716 -1.094449 0.385050 -0.219252 0.489240 -1.136125 -0.906907 -1.532047 -1.240315 -0.948583 1.322761 -0.302604 0.385050 0.155832 1.739521 2.677232 0.260022 -0.531822 -0.135900 0.051642 0.155832 0.906001 -1.115287 -0.969421 -1.094449 1.260247 0.968515 2.177119 -1.281991 0.009966 -1.552885 -1.302829 -0.698526 0.093318 -0.469308 -0.031710 0.197508 1.656169 1.572817 -0.406794 -0.156738 0.030804 -0.570568 1.728059 1.289230 -1.030294 -0.758638 -1.155673 0.850401 0.139916 0.578745 -1.134777 -0.633258 -1.531813 -1.427329 -0.758638 -0.027256 -0.779534 0.578745 -0.215326 2.187784 3.190822 0.202606 -0.654155 -0.069050 0.374255 0.688411 0.876905 -1.049918 -0.966143 -1.028975 0.876905 0.164818 1.337667 -0.966143 -0.149338 -1.573511 -1.091806 -0.840481 0.269537 -0.400663 -0.275000 0.122931 2.007866 2.154472 -0.086507 -0.337831 -0.107450 0.107815 0.696230 0.801304 -1.005970 -0.795822 -1.090029 0.759274 0.465067 2.167266 -0.816836 -0.228422 -1.510325 -1.279162 -0.816836 0.191874 0.170860 -0.018274 -0.396540 1.620881 1.536822 -0.207407 -0.459585 0.107815 0.257037 1.077542 1.308967 -1.047357 -0.479314 -0.836971 1.014427 -0.311005 1.266890 -1.026318 -0.332044 -1.341897 -1.236704 -0.836971 1.035465 0.488462 -0.058542 -0.163735 1.014427 1.498315 -0.226851 -0.668662 -0.395160 -0.693206 -0.720917 1.414123
NTRK3 0.246599 0.825353 0.917953 -1.211859 -0.517355 -0.563656 0.223449 -0.054352 1.126304 -1.165559 -0.494205 -1.535961 -1.535961 -0.957208 1.728208 0.570701 0.038248 0.246599 1.589307 2.191211 -0.517355 -0.702556 -0.447905 0.611505 1.327439 1.050303 -0.912740 -0.866550 -0.843456 0.519127 -0.081333 1.581479 -0.889645 -0.196806 -1.536294 -1.443916 -0.935834 0.565316 0.542222 -0.150617 -0.081333 1.281249 1.535290 -0.081333 -0.751077 -0.242996 0.310085 1.071751 1.833417 -1.236327 -0.890115 -1.005519 0.563974 -0.174611 1.094832 -1.213246 -0.728550 -1.559458 -1.420973 -0.705469 1.071751 0.310085 0.033116 0.263924 1.094832 1.833417 0.194681 -0.497742 -0.243853 0.308897 1.254642 1.162374 -1.005920 -1.075121 -1.236590 0.124361 0.101294 0.839437 -1.075121 -0.567648 -1.582594 -1.328858 -1.052054 1.139307 -0.175510 0.101294 0.170495 1.900517 2.384923 0.147428 -0.383112 -0.152443 -0.106309 0.908638 1.323843 -1.052054 -1.190456 -1.236590 0.493432 0.124361 1.831316 -1.490326 -0.290844 -1.651795 -1.328858 -0.798317 0.078227 -0.360045 -0.014041 0.908638 1.831316 1.393044 0.078227 -0.198576 0.747169 -0.797266 1.696953 1.073398 -0.912740 -1.236064 -1.282254 1.881710 0.611505 1.581479 -1.051307 -0.081333 -1.674862 -1.490105 -0.704888 0.218897 -0.704888 0.057234 -0.312279 1.004114 1.789331 0.126518 -0.266090 0.472938 0.158406 0.947407 1.689996 -0.909067 -1.117920 -1.117920 0.970613 0.088788 1.202672 -1.001890 -0.352125 -1.628450 -1.233950 -1.071508 0.552906 -0.143271 -0.027242 0.042376 1.272290 1.922056 0.251229 -0.398536 -0.096859 0.396704 1.094985 1.327746 -0.813649 -0.860201 -1.139513 1.164813 0.326876 2.538099 -0.976581 -0.441233 -1.605034 -1.418826 -0.836925 0.303600 0.210496 -0.278300 -0.301576 1.118261 1.025157 -0.045540 -0.511061 -0.278300 0.097329 1.216607 1.146652 -1.045268 -0.532265 -1.138541 0.890151 -0.112536 1.263243 -0.695494 -0.555584 -1.558271 -1.278451 -0.882040 1.169970 0.237238 -0.182491 -0.019263 1.100015 1.636336 -0.089218 -0.578902 -0.089218 -0.648459 -0.764176 1.412635
ALK -0.000966 0.532096 1.154002 -1.222566 -0.378551 -0.600660 0.132300 -0.200864 0.776416 -1.067090 -0.689504 -1.378042 -1.244777 -0.689504 1.487166 0.665362 0.154511 0.265565 1.909173 2.442235 -0.489606 -0.889402 -0.667293 0.169237 1.363510 0.899070 -0.870223 -0.450016 -0.936572 0.301934 -0.317319 1.518323 -0.781759 -0.427900 -1.445244 -1.401011 -0.980804 0.832722 0.943303 -0.206738 -0.206738 1.341394 2.093344 -0.074041 -0.848107 -0.516364 0.146070 0.764946 1.428027 -1.135887 -1.025373 -0.936962 0.433405 -0.318087 1.273308 -1.157989 -0.760141 -1.467427 -1.379016 -0.738038 1.140692 0.344994 0.278686 -0.052854 1.317513 2.908908 0.013454 -0.804346 -0.273881 0.299645 1.183215 0.763520 -1.047799 -0.893174 -0.981531 0.078753 -0.142140 0.454270 -1.069888 -0.848995 -1.533762 -1.312870 -0.981531 1.337840 -0.097961 0.388002 0.167110 2.110964 2.508570 0.189199 -0.628103 0.056664 0.189199 0.608895 0.918144 -1.224513 -1.047799 -1.246602 1.315751 0.896055 2.177232 -1.379137 -0.628103 -1.555851 -1.334959 -1.025709 -0.009604 -0.407210 -0.385121 0.233378 1.845893 1.912161 -0.186318 -0.274675 0.608895 -0.870654 1.538540 1.229102 -0.826449 -1.069579 -1.202195 1.405924 0.477611 1.162794 -0.936962 -0.384395 -1.533735 -1.312708 -0.782243 0.322892 -0.428600 0.300789 -0.472806 1.052281 2.599470 0.168173 -0.649627 0.212378 0.369469 0.657155 1.365304 -0.869792 -1.068959 -1.179607 1.188266 0.192432 1.321044 -0.847662 -0.205902 -1.467292 -1.268125 -0.936181 0.767803 0.280950 -0.050994 -0.006735 0.789932 1.520211 -0.028865 -0.515717 -0.006735 0.171369 0.304228 0.525659 -0.692214 -0.825073 -1.046505 1.832106 0.813520 2.673546 -0.913646 -0.227208 -1.400795 -1.201507 -0.780787 0.259941 0.990666 -0.426496 -0.426496 0.459230 0.636375 -0.249351 -0.404353 -0.072206 0.238907 0.615570 1.235957 -0.979710 -0.603047 -0.979710 0.704197 0.194593 1.324584 -0.891084 -0.204227 -1.312061 -1.179120 -0.846770 1.501837 0.571257 -0.204227 -0.115600 0.947920 1.058704 -0.292853 -0.514420 -0.270697 -0.688690 -0.725365 1.414055
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VRK2 0.913815 0.836508 0.449975 0.527282 -0.158815 -0.158815 -0.158815 -0.767604 -0.777268 -0.661308 -0.158815 0.643242 0.382332 0.933142 -0.129825 0.285698 -0.458378 -0.545348 -0.187805 -0.796594 0.053779 0.053779 -0.120161 1.238276 1.354168 0.658818 0.687791 -0.239341 -0.239341 -0.036531 -0.722223 -0.722223 -0.239341 -0.258657 0.320801 0.581557 0.204910 -0.326260 0.233883 -0.654619 -0.490440 -0.896060 -0.490440 -0.017216 -0.017216 0.069703 1.617455 1.392879 0.416463 0.133302 -0.061981 -0.061981 -0.315849 -0.374434 -0.335378 -0.061981 -0.120566 0.416463 0.367642 0.738680 -0.638067 0.367642 -0.647831 -0.032689 -1.028633 -0.930992 -0.393963 -0.393963 -0.052217 0.658854 3.601795 0.199955 0.170027 -0.009542 -0.009542 -0.548250 -0.857508 0.209931 1.087825 0.050314 -0.209064 -0.039471 0.409453 -0.308824 0.499237 -0.009542 -0.029494 -0.787676 -0.977221 -1.047054 -1.047054 -1.007149 0.689069 -0.112765 -0.201857 -0.201857 0.223808 0.223808 1.391911 0.293102 0.986044 0.223808 -0.686917 0.283203 -0.597824 2.421426 0.372295 0.500985 -0.370143 -0.132563 -1.102683 -1.795625 -0.865102 -0.865102 -0.677018 1.216846 0.411378 -0.261544 -0.740747 -0.006649 -0.006649 3.470116 1.675657 -0.924271 0.340008 -0.404285 -0.006649 0.574511 -0.648984 -0.006649 3.694424 1.104692 -1.148578 -2.229333 -1.739934 -1.811305 -1.811305 -0.740747 -1.547487 0.847371 -0.244845 0.216091 0.105867 0.105867 0.616904 2.210136 2.160034 1.809323 1.568835 1.198083 1.969648 0.105867 -0.254865 -0.765902 -0.545454 -1.417223 -2.028463 -2.309032 -1.657711 -1.657711 -0.485332 -1.216215 1.073850 0.200009 -0.231889 -0.171624 -0.171624 -0.171624 -0.342374 -0.402639 -0.543257 0.501334 0.742393 3.755636 1.857293 -0.523169 2.389633 -0.523169 0.491290 -1.708378 -1.979570 -1.366877 -1.366877 -0.292154 0.050297 0.827835 0.296833 -0.243651 -0.243651 -0.243651 -0.613456 -0.784135 -0.471223 -0.376401 0.097708 0.249422 1.671749 0.666638 -0.746206 -0.471223 -0.651384 -0.234169 -0.243651 -1.286690 0.306316 0.306316 2.136376 -0.134920 1.286619 -1.151698
WNK4 -0.787779 -0.171271 -0.107219 -0.087202 0.056916 0.056916 -0.167268 0.261085 0.409207 0.056916 0.589355 0.869586 0.689437 0.593358 0.713457 1.746308 -0.759756 -0.363430 -1.112046 -0.935901 -0.543578 -0.543578 -0.463512 -0.640355 0.075796 -0.112449 -0.186110 -0.112449 -0.112449 -0.153372 -0.096080 -0.362079 -0.042880 -0.186110 0.464564 0.231304 0.640533 1.573576 3.001786 -0.149280 -0.177926 -0.873616 -0.783585 -0.501217 -0.501217 -0.996385 -0.076874 0.231143 -0.080874 -0.020871 -0.076874 -0.076874 -0.008870 -0.036872 -0.192880 0.127138 -0.504898 0.003131 -0.596903 0.459156 1.595219 3.991352 -0.520899 -0.508898 -1.348945 -1.032927 -0.360890 -0.360890 -0.600903 0.917850 4.265395 1.354307 0.234341 -0.276232 -0.276232 0.090227 -0.440933 -0.720925 -0.552106 -0.276232 -0.259762 -0.663279 1.465480 0.234341 1.959583 -0.877390 -0.778570 -1.527959 -1.527959 -0.609751 -0.609751 -1.124442 -1.161009 0.607030 0.511573 0.316508 -0.231336 -0.231336 -0.281140 -0.318492 -0.231336 1.590658 -0.343394 0.308207 -0.708623 0.299906 1.794024 4.271769 0.059187 -0.712773 -1.563590 -1.123656 -1.181760 -1.181760 -0.488656 -1.683890 -0.145187 -0.681278 1.008839 0.075796 0.075796 0.075796 0.628256 1.160254 2.449327 0.464564 0.988378 0.083981 -0.308879 -0.055157 2.228343 0.542318 0.010320 -1.667521 -1.671613 -1.336045 -1.336045 -0.906354 -1.487522 0.483187 0.129790 0.179681 0.125632 0.125632 0.558024 2.121287 0.765905 0.948840 0.125632 0.262833 -0.186189 0.113159 -0.132140 3.023489 -0.988608 -0.643526 -0.872195 -1.159070 -1.271326 -1.271326 -0.951190 -0.995206 -0.404314 -0.559371 -0.035530 0.002186 0.002186 -0.173824 0.002186 0.245248 0.291346 2.923121 1.334837 1.749719 1.058249 0.345826 0.743945 -0.869484 -0.563561 -0.735381 -0.986825 -1.309510 -1.309510 -0.756335 -0.567130 -0.202433 -0.153807 0.137950 0.044750 0.044750 0.044750 0.693100 -0.072763 0.364873 0.826822 0.583691 0.891657 0.413499 0.802509 1.110475 -0.660330 -0.332103 -0.976401 -0.745426 -0.794052 -0.794052 -0.660330 0.514442 0.883617 -1.398059
YANK2 -0.069665 0.063579 -0.005842 -0.045031 -0.069665 -0.069665 -0.234261 -0.192832 -0.205148 -0.193951 -0.101016 0.009834 -0.162600 0.031108 0.167712 0.195704 -0.139086 -0.039433 -0.010321 -0.140206 0.381574 0.381574 0.447636 -0.046635 0.037552 -0.047674 -0.123546 -0.123546 -0.123546 -0.252425 -0.315825 -0.263858 -0.165120 -0.227481 -0.167199 -0.239953 -0.123546 -0.045596 0.085362 -0.180710 -0.118350 -0.014415 0.254775 1.038440 1.038440 0.124857 -0.313425 -0.360362 -0.326835 -0.324824 -0.360362 -0.360362 -0.395229 -0.442165 -0.415344 -0.412662 -0.421379 -0.358350 -0.462951 -0.375113 -0.303367 0.137165 -0.422049 -0.347622 -0.112939 -0.185355 3.159876 3.159876 0.243778 -0.063168 -0.323353 -0.219643 -0.047702 -0.219643 -0.219643 -0.292422 -0.306978 0.188830 -0.074994 0.002334 -0.047702 -0.315166 -0.066807 -0.367931 -0.172336 -0.247845 -0.172336 -0.419786 -0.226011 0.209755 0.209755 3.192793 0.301826 0.160395 -0.064230 -0.010748 -0.064230 -0.064230 -0.304306 -0.329264 -0.101074 0.084331 -0.137917 0.095028 -0.275782 -0.026199 0.204369 0.696406 0.003514 -0.105828 -0.330453 -0.211604 -0.002429 -0.002429 0.484854 -0.544935 -0.456711 -0.330677 -0.021321 -0.091213 -0.091213 0.132211 0.566455 0.024509 0.729153 0.840292 -0.043091 -0.237870 -0.190894 -0.213809 -0.086630 -0.039653 -0.351301 -0.475043 -0.091213 0.037113 0.037113 0.898726 -0.678916 -0.668713 -0.626626 -0.534799 -0.553610 -0.553610 -0.575611 -0.550741 -0.575292 -0.544045 -0.532567 -0.229665 -0.458595 -0.418102 -0.569871 -0.530335 -0.557755 -0.587089 -0.553610 -0.378884 -0.293752 -0.293752 11.265940 -0.543125 -0.506080 -0.350320 -0.270336 -0.173513 -0.173513 -0.023648 0.010872 -0.079216 -0.137310 -0.042170 -0.103632 -0.019438 -0.168461 -0.173513 -0.197929 -0.309907 -0.392418 -0.417676 -0.351162 0.975736 0.975736 2.471022 -0.168368 -0.304390 -0.333419 -0.362448 -0.297755 -0.297755 -0.356642 -0.213156 -0.322637 -0.281167 -0.355813 -0.236379 -0.165051 -0.152610 0.179980 0.192421 -0.297755 -0.315172 -0.456170 -0.344201 0.189103 0.189103 4.510281 0.213252 1.104115 -1.317366
YANK3 0.036918 0.227998 0.064757 0.002751 -0.064317 -0.064317 -0.118731 -0.074440 -0.044070 -0.066848 -0.065582 -0.064317 -0.044070 -0.112403 0.026794 0.307720 -0.174410 -0.097218 0.128029 -0.093422 0.122967 0.122967 0.043245 0.055050 0.259423 0.032073 -0.042904 -0.092486 -0.092486 -0.126346 -0.177137 -0.217045 -0.085230 -0.213417 -0.165044 -0.142067 -0.210998 -0.069509 0.225562 -0.157788 -0.092486 0.229190 0.130027 0.472261 0.472261 0.009096 -0.236397 -0.265901 -0.285289 -0.311421 -0.355255 -0.355255 -0.350197 -0.378015 -0.371271 -0.384759 -0.450510 -0.355255 -0.407519 -0.434494 -0.282760 1.072728 -0.359470 -0.377172 -0.279388 -0.242298 2.736742 2.736742 -0.063589 0.000460 -0.119404 -0.157008 0.082719 -0.140556 -0.140556 -0.239268 -0.219291 0.164979 0.021612 -0.034794 -0.124105 -0.140556 -0.135856 -0.182861 0.967597 -0.184037 -0.172285 -0.310951 -0.200488 0.129725 0.129725 1.005201 0.546474 0.190063 -0.171457 -0.142075 -0.116526 -0.116526 -0.167625 -0.309422 -0.145908 0.064873 -0.199561 -0.070538 -0.249382 -0.116526 0.100641 0.727873 0.055930 0.027826 -0.148463 -0.177844 0.054653 0.054653 0.308867 -0.465117 -0.361424 -0.328094 -0.112066 -0.086143 -0.086143 0.073101 0.637242 -0.052813 0.532314 0.758217 -0.086143 -0.126879 -0.326860 -0.266372 0.017551 0.102727 -0.281185 -0.354017 0.055818 -0.009607 -0.009607 0.775500 -0.689165 -0.652955 -0.644131 -0.490467 -0.609138 -0.609138 -0.609138 -0.570190 -0.540978 -0.558322 -0.536718 -0.387315 -0.317938 -0.567451 -0.651738 -0.621005 -0.626178 -0.618875 -0.630438 -0.552237 -0.278076 -0.278076 12.039666 -0.463843 -0.388116 -0.340672 -0.189218 -0.233925 -0.233925 -0.038677 0.055298 -0.233925 -0.247610 -0.174620 -0.121703 -0.103455 -0.165497 -0.188306 -0.091594 -0.261296 -0.305090 -0.383554 -0.240311 1.003254 1.003254 2.343530 -0.131072 -0.287017 -0.247593 -0.356229 -0.247593 -0.247593 -0.343088 -0.322937 -0.325566 -0.294902 -0.371999 -0.290522 -0.211673 -0.227443 -0.141585 -0.111798 -0.200284 -0.242336 -0.308044 0.001219 0.300844 0.300844 4.306364 0.817024 0.591165 -1.408189
YSK4 -0.032950 0.568875 0.640203 0.595623 -0.015118 -0.015118 -0.371756 -0.893337 -0.746225 -0.394045 0.158742 -0.001744 0.689240 0.283565 -0.336092 -0.015118 -0.532242 0.069583 0.408388 -0.411877 0.457426 0.457426 -0.563448 0.108431 0.381554 0.090522 0.242754 0.090522 0.090522 -0.540794 -0.831827 -0.352743 -0.124394 0.054702 0.099477 0.520354 0.126341 -0.478111 -0.334833 -0.209465 0.229322 0.327825 0.211412 0.292006 0.292006 -0.285581 -0.156075 0.392044 -0.111147 0.180883 -0.111147 -0.111147 -1.077095 -0.960282 -0.758107 -0.165061 -0.241438 0.091028 0.531320 0.171898 -0.358250 -0.236945 0.082042 0.989583 1.187265 0.046100 0.203347 0.203347 0.207840 -0.756930 0.055572 0.179110 0.117341 -0.286534 -0.286534 -1.004006 -1.118041 -1.260585 -0.381564 1.975165 3.410109 2.341028 1.077137 -1.659709 -1.322355 -0.286534 0.340660 0.725529 -0.300789 -0.604883 -0.604883 -0.348303 0.278396 -0.303281 -0.345162 -0.629020 -0.098531 -0.098531 -0.991987 -1.071095 0.422652 0.152753 -0.396350 1.116011 -0.373083 0.753044 0.064339 -0.172986 -0.098531 0.743737 1.441750 -0.177639 -0.610407 -0.610407 1.004329 -2.088449 -1.134681 -1.347178 0.244082 -1.134681 -1.134681 0.713553 2.270221 3.723111 1.869935 1.192908 1.894644 5.171060 0.229257 -1.525083 -1.416364 -1.268110 -1.164332 -1.648628 -1.554734 -0.393410 -0.393410 -1.105030 -0.860170 -0.401302 -0.802812 -0.468220 -0.774132 -0.774132 -0.195767 -0.774132 -1.132623 -0.917529 -0.974887 -0.554258 -0.783692 1.113919 3.594675 5.755180 -0.057151 1.348133 -0.812371 -1.247340 0.535554 0.535554 -1.352497 0.768778 0.442187 -0.233993 -0.169595 -0.017799 -0.017799 -0.192594 -0.670981 -0.463987 -0.500786 -0.040799 -0.017799 0.198394 0.290392 0.883775 0.529585 -0.008600 0.635382 -0.509985 -0.606583 0.276592 0.276592 -0.850376 0.963629 0.645691 -0.036261 -0.109986 -0.036261 -0.036261 -0.626058 -0.506256 -0.460178 -0.340375 -0.552333 -0.404884 -0.192926 0.350793 1.074215 0.171089 0.737847 0.180305 0.019032 -0.446354 0.244814 0.244814 -0.884094 0.450034 0.936061 -1.386095

390 rows × 210 columns

# get the index column out and rename it with 'kinase'
target = v.reset_index().rename(columns={'index':'kinase'})
target
kinase -5P -5G -5A -5C -5S -5T -5V -5I -5L -5M -5F -5Y -5W -5H -5K -5R -5Q -5N -5D -5E -5s -5t -5y -4P -4G -4A -4C -4S -4T -4V -4I -4L -4M -4F -4Y -4W -4H -4K -4R -4Q -4N -4D -4E -4s -4t -4y -3P -3G -3A -3C -3S -3T -3V -3I -3L -3M -3F -3Y -3W -3H -3K -3R -3Q -3N -3D -3E -3s -3t -3y -2P -2G -2A -2C -2S -2T -2V -2I -2L -2M -2F -2Y -2W -2H -2K -2R -2Q -2N -2D -2E -2s -2t -2y -1P -1G -1A -1C -1S -1T -1V -1I -1L -1M -1F -1Y -1W -1H -1K -1R -1Q -1N -1D -1E -1s -1t -1y 1P 1G 1A 1C 1S 1T 1V 1I 1L 1M 1F 1Y 1W 1H 1K 1R 1Q 1N 1D 1E 1s 1t 1y 2P 2G 2A 2C 2S 2T 2V 2I 2L 2M 2F 2Y 2W 2H 2K 2R 2Q 2N 2D 2E 2s 2t 2y 3P 3G 3A 3C 3S 3T 3V 3I 3L 3M 3F 3Y 3W 3H 3K 3R 3Q 3N 3D 3E 3s 3t 3y 4P 4G 4A 4C 4S 4T 4V 4I 4L 4M 4F 4Y 4W 4H 4K 4R 4Q 4N 4D 4E 4s 4t 4y 0s 0t 0y
0 SRC 0.288615 0.937824 0.905363 -1.058492 -0.441744 -0.555355 0.256155 0.045162 0.954054 -0.944880 -0.328132 -1.512938 -1.448017 -0.798808 1.100126 0.223695 0.158774 -0.068449 1.668183 2.463463 -0.474204 -0.879959 -0.490435 0.479723 1.257423 0.593137 -0.978465 -0.233169 -0.670626 0.204287 -0.265573 1.435646 -0.994667 -0.459998 -1.415922 -1.415922 -0.978465 0.350106 0.285298 0.058468 0.042266 1.613869 2.294357 0.058468 -0.784040 -0.476201 0.251267 0.947354 1.206363 -1.302788 -0.444820 -0.736205 0.299831 -0.461008 0.558840 -1.140907 -0.752393 -1.335164 -1.416104 -0.946650 0.526464 0.008446 0.477900 0.008446 1.821510 3.764078 -0.088682 -0.849522 -0.396256 0.816792 1.431673 0.719706 -1.189660 -0.574780 -0.914582 0.363722 -0.315883 0.331360 -1.189660 -0.623323 -1.497100 -1.367652 -0.833677 0.671163 -0.299702 0.201912 0.363722 2.192183 2.483442 0.234274 -0.623323 -0.380607 0.541714 0.153368 0.849154 -1.011668 -0.801315 -0.801315 2.062734 1.399311 2.192183 -1.286747 -0.202615 -1.416195 -1.302928 -0.704228 -0.315883 -0.801315 -0.218796 -0.315883 0.946241 1.787656 -0.445331 -0.251158 -0.056985 -0.847837 2.153449 0.855596 -1.107408 -0.361142 -1.042515 0.709587 0.222892 0.806926 -1.091184 -0.458481 -1.496764 -1.366978 -0.815391 0.222892 -0.361142 0.482463 -0.231356 1.715424 2.656368 0.044437 -0.636936 -0.052902 0.183643 0.868580 1.064276 -1.006844 -0.354522 -0.664375 0.787040 0.004254 1.308897 -0.957920 -0.550219 -1.414545 -1.267772 -0.908996 -0.044670 -0.012054 0.199951 0.020562 1.178433 2.287379 0.118410 -0.582835 -0.256674 0.797607 0.535536 0.781228 -1.020510 -0.496368 -0.823957 0.895884 0.338983 2.468309 -0.987751 0.142430 -1.151545 -1.331719 -0.545506 0.126050 0.437260 -0.430850 -0.332574 0.895884 1.076058 -0.348953 -0.840336 -0.185159 0.623344 1.116021 0.935373 -1.133872 -0.378433 -0.936801 0.656189 -0.148517 1.165289 -0.838265 -0.394856 -1.281675 -1.265252 -0.805420 1.214557 0.935373 -0.197785 -0.345588 0.968218 1.822192 -0.411278 -0.903956 -0.394856 -0.701944 -0.712257 1.414201
1 EPHA3 0.067908 0.886947 0.696473 -1.093984 -0.427324 -0.617799 0.201240 -0.236850 0.486951 -0.941604 -0.293993 -1.246363 -1.246363 -0.636846 1.458369 0.753615 0.410761 0.277430 1.305990 2.086933 -0.560656 -0.941604 -0.389230 0.214614 1.467628 0.746195 -0.943475 -0.487833 -0.715654 0.461419 -0.089147 0.898076 -0.810579 -0.297983 -1.399116 -1.380131 -0.791594 0.803151 0.613300 -0.241028 -0.203058 1.790374 1.695448 -0.127117 -0.715654 -0.487833 0.384444 0.953685 1.086508 -1.190457 -0.735064 -0.773013 0.441368 0.023925 1.067534 -1.114558 -0.526342 -1.380204 -1.342254 -0.697114 0.801888 0.213672 0.194697 0.004950 1.219331 2.149092 0.156748 -0.848912 -0.089924 0.460343 1.162407 0.934711 -1.057634 -0.564291 -0.981735 -0.146848 0.004950 0.232646 -1.114558 -0.810962 -1.456103 -1.266355 -0.886861 1.124458 0.118798 0.365469 -0.070949 1.352154 2.566535 0.308545 -0.431468 0.156748 -0.659165 0.004950 0.365469 -1.228406 -0.981735 -0.829937 0.782913 0.707014 2.187041 -1.342254 -0.279671 -1.456103 -1.266355 -0.981735 -0.184797 -0.431468 -0.317620 1.048559 2.851156 2.016269 -0.260696 -0.108898 0.365469 -0.999870 1.603924 1.014744 -0.961859 -1.037882 -1.322969 1.375854 0.330536 0.862698 -0.809812 -0.638760 -1.437003 -1.189928 -0.695777 -0.277650 -0.790806 0.577611 -0.448702 1.908017 3.580527 -0.144609 -0.828818 0.330536 -0.098097 0.341678 1.010901 -1.035010 -0.901165 -1.035010 0.666729 -0.327545 0.743212 -0.977648 -0.346666 -1.417423 -1.168855 -0.805562 0.188713 -0.327545 -0.155459 0.073989 2.750882 2.980330 0.112230 -0.537873 0.265195 0.524962 0.428830 0.794130 -0.840106 -0.840106 -0.897785 1.255561 0.544188 3.178192 -0.840106 -0.109506 -1.378443 -1.359216 -0.705522 -0.205638 0.294246 -0.282543 -0.551711 1.005619 0.794130 -0.301769 -0.494032 -0.013375 0.335763 0.817219 0.952026 -0.973796 -0.222726 -0.742698 0.643895 -0.184209 0.701669 -0.819731 -0.261242 -1.301186 -1.166379 -0.761956 0.701669 0.374279 -0.164951 0.104664 1.163867 1.876421 -0.319017 -0.588632 -0.164951 -0.683583 -0.730373 1.413956
2 FES 0.326894 0.640167 1.204058 -1.030623 -0.341422 -0.717350 0.326894 -0.049034 0.828130 -1.114162 -0.383192 -1.448320 -1.364781 -0.821774 1.579985 0.013621 0.264239 0.076275 1.642640 2.310956 -0.466731 -0.926198 -0.550271 0.678069 1.136762 0.490421 -0.864810 -0.552064 -0.531214 0.594670 -0.239318 1.220161 -0.906509 -0.176769 -1.427752 -1.386052 -0.948208 0.657219 0.261075 -0.218469 0.010878 1.741404 1.762253 -0.051671 -0.739711 -0.510365 0.176670 0.926839 1.551979 -1.156963 -0.677688 -0.990259 0.343374 -0.344280 0.989353 -1.115287 -0.761040 -1.490371 -1.490371 -0.844392 0.864325 0.239184 0.489240 -0.052548 1.677007 2.552204 -0.094224 -0.781878 -0.010872 0.572592 1.218571 0.760134 -1.115287 -0.802716 -1.094449 0.385050 -0.219252 0.489240 -1.136125 -0.906907 -1.532047 -1.240315 -0.948583 1.322761 -0.302604 0.385050 0.155832 1.739521 2.677232 0.260022 -0.531822 -0.135900 0.051642 0.155832 0.906001 -1.115287 -0.969421 -1.094449 1.260247 0.968515 2.177119 -1.281991 0.009966 -1.552885 -1.302829 -0.698526 0.093318 -0.469308 -0.031710 0.197508 1.656169 1.572817 -0.406794 -0.156738 0.030804 -0.570568 1.728059 1.289230 -1.030294 -0.758638 -1.155673 0.850401 0.139916 0.578745 -1.134777 -0.633258 -1.531813 -1.427329 -0.758638 -0.027256 -0.779534 0.578745 -0.215326 2.187784 3.190822 0.202606 -0.654155 -0.069050 0.374255 0.688411 0.876905 -1.049918 -0.966143 -1.028975 0.876905 0.164818 1.337667 -0.966143 -0.149338 -1.573511 -1.091806 -0.840481 0.269537 -0.400663 -0.275000 0.122931 2.007866 2.154472 -0.086507 -0.337831 -0.107450 0.107815 0.696230 0.801304 -1.005970 -0.795822 -1.090029 0.759274 0.465067 2.167266 -0.816836 -0.228422 -1.510325 -1.279162 -0.816836 0.191874 0.170860 -0.018274 -0.396540 1.620881 1.536822 -0.207407 -0.459585 0.107815 0.257037 1.077542 1.308967 -1.047357 -0.479314 -0.836971 1.014427 -0.311005 1.266890 -1.026318 -0.332044 -1.341897 -1.236704 -0.836971 1.035465 0.488462 -0.058542 -0.163735 1.014427 1.498315 -0.226851 -0.668662 -0.395160 -0.693206 -0.720917 1.414123
3 NTRK3 0.246599 0.825353 0.917953 -1.211859 -0.517355 -0.563656 0.223449 -0.054352 1.126304 -1.165559 -0.494205 -1.535961 -1.535961 -0.957208 1.728208 0.570701 0.038248 0.246599 1.589307 2.191211 -0.517355 -0.702556 -0.447905 0.611505 1.327439 1.050303 -0.912740 -0.866550 -0.843456 0.519127 -0.081333 1.581479 -0.889645 -0.196806 -1.536294 -1.443916 -0.935834 0.565316 0.542222 -0.150617 -0.081333 1.281249 1.535290 -0.081333 -0.751077 -0.242996 0.310085 1.071751 1.833417 -1.236327 -0.890115 -1.005519 0.563974 -0.174611 1.094832 -1.213246 -0.728550 -1.559458 -1.420973 -0.705469 1.071751 0.310085 0.033116 0.263924 1.094832 1.833417 0.194681 -0.497742 -0.243853 0.308897 1.254642 1.162374 -1.005920 -1.075121 -1.236590 0.124361 0.101294 0.839437 -1.075121 -0.567648 -1.582594 -1.328858 -1.052054 1.139307 -0.175510 0.101294 0.170495 1.900517 2.384923 0.147428 -0.383112 -0.152443 -0.106309 0.908638 1.323843 -1.052054 -1.190456 -1.236590 0.493432 0.124361 1.831316 -1.490326 -0.290844 -1.651795 -1.328858 -0.798317 0.078227 -0.360045 -0.014041 0.908638 1.831316 1.393044 0.078227 -0.198576 0.747169 -0.797266 1.696953 1.073398 -0.912740 -1.236064 -1.282254 1.881710 0.611505 1.581479 -1.051307 -0.081333 -1.674862 -1.490105 -0.704888 0.218897 -0.704888 0.057234 -0.312279 1.004114 1.789331 0.126518 -0.266090 0.472938 0.158406 0.947407 1.689996 -0.909067 -1.117920 -1.117920 0.970613 0.088788 1.202672 -1.001890 -0.352125 -1.628450 -1.233950 -1.071508 0.552906 -0.143271 -0.027242 0.042376 1.272290 1.922056 0.251229 -0.398536 -0.096859 0.396704 1.094985 1.327746 -0.813649 -0.860201 -1.139513 1.164813 0.326876 2.538099 -0.976581 -0.441233 -1.605034 -1.418826 -0.836925 0.303600 0.210496 -0.278300 -0.301576 1.118261 1.025157 -0.045540 -0.511061 -0.278300 0.097329 1.216607 1.146652 -1.045268 -0.532265 -1.138541 0.890151 -0.112536 1.263243 -0.695494 -0.555584 -1.558271 -1.278451 -0.882040 1.169970 0.237238 -0.182491 -0.019263 1.100015 1.636336 -0.089218 -0.578902 -0.089218 -0.648459 -0.764176 1.412635
4 ALK -0.000966 0.532096 1.154002 -1.222566 -0.378551 -0.600660 0.132300 -0.200864 0.776416 -1.067090 -0.689504 -1.378042 -1.244777 -0.689504 1.487166 0.665362 0.154511 0.265565 1.909173 2.442235 -0.489606 -0.889402 -0.667293 0.169237 1.363510 0.899070 -0.870223 -0.450016 -0.936572 0.301934 -0.317319 1.518323 -0.781759 -0.427900 -1.445244 -1.401011 -0.980804 0.832722 0.943303 -0.206738 -0.206738 1.341394 2.093344 -0.074041 -0.848107 -0.516364 0.146070 0.764946 1.428027 -1.135887 -1.025373 -0.936962 0.433405 -0.318087 1.273308 -1.157989 -0.760141 -1.467427 -1.379016 -0.738038 1.140692 0.344994 0.278686 -0.052854 1.317513 2.908908 0.013454 -0.804346 -0.273881 0.299645 1.183215 0.763520 -1.047799 -0.893174 -0.981531 0.078753 -0.142140 0.454270 -1.069888 -0.848995 -1.533762 -1.312870 -0.981531 1.337840 -0.097961 0.388002 0.167110 2.110964 2.508570 0.189199 -0.628103 0.056664 0.189199 0.608895 0.918144 -1.224513 -1.047799 -1.246602 1.315751 0.896055 2.177232 -1.379137 -0.628103 -1.555851 -1.334959 -1.025709 -0.009604 -0.407210 -0.385121 0.233378 1.845893 1.912161 -0.186318 -0.274675 0.608895 -0.870654 1.538540 1.229102 -0.826449 -1.069579 -1.202195 1.405924 0.477611 1.162794 -0.936962 -0.384395 -1.533735 -1.312708 -0.782243 0.322892 -0.428600 0.300789 -0.472806 1.052281 2.599470 0.168173 -0.649627 0.212378 0.369469 0.657155 1.365304 -0.869792 -1.068959 -1.179607 1.188266 0.192432 1.321044 -0.847662 -0.205902 -1.467292 -1.268125 -0.936181 0.767803 0.280950 -0.050994 -0.006735 0.789932 1.520211 -0.028865 -0.515717 -0.006735 0.171369 0.304228 0.525659 -0.692214 -0.825073 -1.046505 1.832106 0.813520 2.673546 -0.913646 -0.227208 -1.400795 -1.201507 -0.780787 0.259941 0.990666 -0.426496 -0.426496 0.459230 0.636375 -0.249351 -0.404353 -0.072206 0.238907 0.615570 1.235957 -0.979710 -0.603047 -0.979710 0.704197 0.194593 1.324584 -0.891084 -0.204227 -1.312061 -1.179120 -0.846770 1.501837 0.571257 -0.204227 -0.115600 0.947920 1.058704 -0.292853 -0.514420 -0.270697 -0.688690 -0.725365 1.414055
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385 VRK2 0.913815 0.836508 0.449975 0.527282 -0.158815 -0.158815 -0.158815 -0.767604 -0.777268 -0.661308 -0.158815 0.643242 0.382332 0.933142 -0.129825 0.285698 -0.458378 -0.545348 -0.187805 -0.796594 0.053779 0.053779 -0.120161 1.238276 1.354168 0.658818 0.687791 -0.239341 -0.239341 -0.036531 -0.722223 -0.722223 -0.239341 -0.258657 0.320801 0.581557 0.204910 -0.326260 0.233883 -0.654619 -0.490440 -0.896060 -0.490440 -0.017216 -0.017216 0.069703 1.617455 1.392879 0.416463 0.133302 -0.061981 -0.061981 -0.315849 -0.374434 -0.335378 -0.061981 -0.120566 0.416463 0.367642 0.738680 -0.638067 0.367642 -0.647831 -0.032689 -1.028633 -0.930992 -0.393963 -0.393963 -0.052217 0.658854 3.601795 0.199955 0.170027 -0.009542 -0.009542 -0.548250 -0.857508 0.209931 1.087825 0.050314 -0.209064 -0.039471 0.409453 -0.308824 0.499237 -0.009542 -0.029494 -0.787676 -0.977221 -1.047054 -1.047054 -1.007149 0.689069 -0.112765 -0.201857 -0.201857 0.223808 0.223808 1.391911 0.293102 0.986044 0.223808 -0.686917 0.283203 -0.597824 2.421426 0.372295 0.500985 -0.370143 -0.132563 -1.102683 -1.795625 -0.865102 -0.865102 -0.677018 1.216846 0.411378 -0.261544 -0.740747 -0.006649 -0.006649 3.470116 1.675657 -0.924271 0.340008 -0.404285 -0.006649 0.574511 -0.648984 -0.006649 3.694424 1.104692 -1.148578 -2.229333 -1.739934 -1.811305 -1.811305 -0.740747 -1.547487 0.847371 -0.244845 0.216091 0.105867 0.105867 0.616904 2.210136 2.160034 1.809323 1.568835 1.198083 1.969648 0.105867 -0.254865 -0.765902 -0.545454 -1.417223 -2.028463 -2.309032 -1.657711 -1.657711 -0.485332 -1.216215 1.073850 0.200009 -0.231889 -0.171624 -0.171624 -0.171624 -0.342374 -0.402639 -0.543257 0.501334 0.742393 3.755636 1.857293 -0.523169 2.389633 -0.523169 0.491290 -1.708378 -1.979570 -1.366877 -1.366877 -0.292154 0.050297 0.827835 0.296833 -0.243651 -0.243651 -0.243651 -0.613456 -0.784135 -0.471223 -0.376401 0.097708 0.249422 1.671749 0.666638 -0.746206 -0.471223 -0.651384 -0.234169 -0.243651 -1.286690 0.306316 0.306316 2.136376 -0.134920 1.286619 -1.151698
386 WNK4 -0.787779 -0.171271 -0.107219 -0.087202 0.056916 0.056916 -0.167268 0.261085 0.409207 0.056916 0.589355 0.869586 0.689437 0.593358 0.713457 1.746308 -0.759756 -0.363430 -1.112046 -0.935901 -0.543578 -0.543578 -0.463512 -0.640355 0.075796 -0.112449 -0.186110 -0.112449 -0.112449 -0.153372 -0.096080 -0.362079 -0.042880 -0.186110 0.464564 0.231304 0.640533 1.573576 3.001786 -0.149280 -0.177926 -0.873616 -0.783585 -0.501217 -0.501217 -0.996385 -0.076874 0.231143 -0.080874 -0.020871 -0.076874 -0.076874 -0.008870 -0.036872 -0.192880 0.127138 -0.504898 0.003131 -0.596903 0.459156 1.595219 3.991352 -0.520899 -0.508898 -1.348945 -1.032927 -0.360890 -0.360890 -0.600903 0.917850 4.265395 1.354307 0.234341 -0.276232 -0.276232 0.090227 -0.440933 -0.720925 -0.552106 -0.276232 -0.259762 -0.663279 1.465480 0.234341 1.959583 -0.877390 -0.778570 -1.527959 -1.527959 -0.609751 -0.609751 -1.124442 -1.161009 0.607030 0.511573 0.316508 -0.231336 -0.231336 -0.281140 -0.318492 -0.231336 1.590658 -0.343394 0.308207 -0.708623 0.299906 1.794024 4.271769 0.059187 -0.712773 -1.563590 -1.123656 -1.181760 -1.181760 -0.488656 -1.683890 -0.145187 -0.681278 1.008839 0.075796 0.075796 0.075796 0.628256 1.160254 2.449327 0.464564 0.988378 0.083981 -0.308879 -0.055157 2.228343 0.542318 0.010320 -1.667521 -1.671613 -1.336045 -1.336045 -0.906354 -1.487522 0.483187 0.129790 0.179681 0.125632 0.125632 0.558024 2.121287 0.765905 0.948840 0.125632 0.262833 -0.186189 0.113159 -0.132140 3.023489 -0.988608 -0.643526 -0.872195 -1.159070 -1.271326 -1.271326 -0.951190 -0.995206 -0.404314 -0.559371 -0.035530 0.002186 0.002186 -0.173824 0.002186 0.245248 0.291346 2.923121 1.334837 1.749719 1.058249 0.345826 0.743945 -0.869484 -0.563561 -0.735381 -0.986825 -1.309510 -1.309510 -0.756335 -0.567130 -0.202433 -0.153807 0.137950 0.044750 0.044750 0.044750 0.693100 -0.072763 0.364873 0.826822 0.583691 0.891657 0.413499 0.802509 1.110475 -0.660330 -0.332103 -0.976401 -0.745426 -0.794052 -0.794052 -0.660330 0.514442 0.883617 -1.398059
387 YANK2 -0.069665 0.063579 -0.005842 -0.045031 -0.069665 -0.069665 -0.234261 -0.192832 -0.205148 -0.193951 -0.101016 0.009834 -0.162600 0.031108 0.167712 0.195704 -0.139086 -0.039433 -0.010321 -0.140206 0.381574 0.381574 0.447636 -0.046635 0.037552 -0.047674 -0.123546 -0.123546 -0.123546 -0.252425 -0.315825 -0.263858 -0.165120 -0.227481 -0.167199 -0.239953 -0.123546 -0.045596 0.085362 -0.180710 -0.118350 -0.014415 0.254775 1.038440 1.038440 0.124857 -0.313425 -0.360362 -0.326835 -0.324824 -0.360362 -0.360362 -0.395229 -0.442165 -0.415344 -0.412662 -0.421379 -0.358350 -0.462951 -0.375113 -0.303367 0.137165 -0.422049 -0.347622 -0.112939 -0.185355 3.159876 3.159876 0.243778 -0.063168 -0.323353 -0.219643 -0.047702 -0.219643 -0.219643 -0.292422 -0.306978 0.188830 -0.074994 0.002334 -0.047702 -0.315166 -0.066807 -0.367931 -0.172336 -0.247845 -0.172336 -0.419786 -0.226011 0.209755 0.209755 3.192793 0.301826 0.160395 -0.064230 -0.010748 -0.064230 -0.064230 -0.304306 -0.329264 -0.101074 0.084331 -0.137917 0.095028 -0.275782 -0.026199 0.204369 0.696406 0.003514 -0.105828 -0.330453 -0.211604 -0.002429 -0.002429 0.484854 -0.544935 -0.456711 -0.330677 -0.021321 -0.091213 -0.091213 0.132211 0.566455 0.024509 0.729153 0.840292 -0.043091 -0.237870 -0.190894 -0.213809 -0.086630 -0.039653 -0.351301 -0.475043 -0.091213 0.037113 0.037113 0.898726 -0.678916 -0.668713 -0.626626 -0.534799 -0.553610 -0.553610 -0.575611 -0.550741 -0.575292 -0.544045 -0.532567 -0.229665 -0.458595 -0.418102 -0.569871 -0.530335 -0.557755 -0.587089 -0.553610 -0.378884 -0.293752 -0.293752 11.265940 -0.543125 -0.506080 -0.350320 -0.270336 -0.173513 -0.173513 -0.023648 0.010872 -0.079216 -0.137310 -0.042170 -0.103632 -0.019438 -0.168461 -0.173513 -0.197929 -0.309907 -0.392418 -0.417676 -0.351162 0.975736 0.975736 2.471022 -0.168368 -0.304390 -0.333419 -0.362448 -0.297755 -0.297755 -0.356642 -0.213156 -0.322637 -0.281167 -0.355813 -0.236379 -0.165051 -0.152610 0.179980 0.192421 -0.297755 -0.315172 -0.456170 -0.344201 0.189103 0.189103 4.510281 0.213252 1.104115 -1.317366
388 YANK3 0.036918 0.227998 0.064757 0.002751 -0.064317 -0.064317 -0.118731 -0.074440 -0.044070 -0.066848 -0.065582 -0.064317 -0.044070 -0.112403 0.026794 0.307720 -0.174410 -0.097218 0.128029 -0.093422 0.122967 0.122967 0.043245 0.055050 0.259423 0.032073 -0.042904 -0.092486 -0.092486 -0.126346 -0.177137 -0.217045 -0.085230 -0.213417 -0.165044 -0.142067 -0.210998 -0.069509 0.225562 -0.157788 -0.092486 0.229190 0.130027 0.472261 0.472261 0.009096 -0.236397 -0.265901 -0.285289 -0.311421 -0.355255 -0.355255 -0.350197 -0.378015 -0.371271 -0.384759 -0.450510 -0.355255 -0.407519 -0.434494 -0.282760 1.072728 -0.359470 -0.377172 -0.279388 -0.242298 2.736742 2.736742 -0.063589 0.000460 -0.119404 -0.157008 0.082719 -0.140556 -0.140556 -0.239268 -0.219291 0.164979 0.021612 -0.034794 -0.124105 -0.140556 -0.135856 -0.182861 0.967597 -0.184037 -0.172285 -0.310951 -0.200488 0.129725 0.129725 1.005201 0.546474 0.190063 -0.171457 -0.142075 -0.116526 -0.116526 -0.167625 -0.309422 -0.145908 0.064873 -0.199561 -0.070538 -0.249382 -0.116526 0.100641 0.727873 0.055930 0.027826 -0.148463 -0.177844 0.054653 0.054653 0.308867 -0.465117 -0.361424 -0.328094 -0.112066 -0.086143 -0.086143 0.073101 0.637242 -0.052813 0.532314 0.758217 -0.086143 -0.126879 -0.326860 -0.266372 0.017551 0.102727 -0.281185 -0.354017 0.055818 -0.009607 -0.009607 0.775500 -0.689165 -0.652955 -0.644131 -0.490467 -0.609138 -0.609138 -0.609138 -0.570190 -0.540978 -0.558322 -0.536718 -0.387315 -0.317938 -0.567451 -0.651738 -0.621005 -0.626178 -0.618875 -0.630438 -0.552237 -0.278076 -0.278076 12.039666 -0.463843 -0.388116 -0.340672 -0.189218 -0.233925 -0.233925 -0.038677 0.055298 -0.233925 -0.247610 -0.174620 -0.121703 -0.103455 -0.165497 -0.188306 -0.091594 -0.261296 -0.305090 -0.383554 -0.240311 1.003254 1.003254 2.343530 -0.131072 -0.287017 -0.247593 -0.356229 -0.247593 -0.247593 -0.343088 -0.322937 -0.325566 -0.294902 -0.371999 -0.290522 -0.211673 -0.227443 -0.141585 -0.111798 -0.200284 -0.242336 -0.308044 0.001219 0.300844 0.300844 4.306364 0.817024 0.591165 -1.408189
389 YSK4 -0.032950 0.568875 0.640203 0.595623 -0.015118 -0.015118 -0.371756 -0.893337 -0.746225 -0.394045 0.158742 -0.001744 0.689240 0.283565 -0.336092 -0.015118 -0.532242 0.069583 0.408388 -0.411877 0.457426 0.457426 -0.563448 0.108431 0.381554 0.090522 0.242754 0.090522 0.090522 -0.540794 -0.831827 -0.352743 -0.124394 0.054702 0.099477 0.520354 0.126341 -0.478111 -0.334833 -0.209465 0.229322 0.327825 0.211412 0.292006 0.292006 -0.285581 -0.156075 0.392044 -0.111147 0.180883 -0.111147 -0.111147 -1.077095 -0.960282 -0.758107 -0.165061 -0.241438 0.091028 0.531320 0.171898 -0.358250 -0.236945 0.082042 0.989583 1.187265 0.046100 0.203347 0.203347 0.207840 -0.756930 0.055572 0.179110 0.117341 -0.286534 -0.286534 -1.004006 -1.118041 -1.260585 -0.381564 1.975165 3.410109 2.341028 1.077137 -1.659709 -1.322355 -0.286534 0.340660 0.725529 -0.300789 -0.604883 -0.604883 -0.348303 0.278396 -0.303281 -0.345162 -0.629020 -0.098531 -0.098531 -0.991987 -1.071095 0.422652 0.152753 -0.396350 1.116011 -0.373083 0.753044 0.064339 -0.172986 -0.098531 0.743737 1.441750 -0.177639 -0.610407 -0.610407 1.004329 -2.088449 -1.134681 -1.347178 0.244082 -1.134681 -1.134681 0.713553 2.270221 3.723111 1.869935 1.192908 1.894644 5.171060 0.229257 -1.525083 -1.416364 -1.268110 -1.164332 -1.648628 -1.554734 -0.393410 -0.393410 -1.105030 -0.860170 -0.401302 -0.802812 -0.468220 -0.774132 -0.774132 -0.195767 -0.774132 -1.132623 -0.917529 -0.974887 -0.554258 -0.783692 1.113919 3.594675 5.755180 -0.057151 1.348133 -0.812371 -1.247340 0.535554 0.535554 -1.352497 0.768778 0.442187 -0.233993 -0.169595 -0.017799 -0.017799 -0.192594 -0.670981 -0.463987 -0.500786 -0.040799 -0.017799 0.198394 0.290392 0.883775 0.529585 -0.008600 0.635382 -0.509985 -0.606583 0.276592 0.276592 -0.850376 0.963629 0.645691 -0.036261 -0.109986 -0.036261 -0.036261 -0.626058 -0.506256 -0.460178 -0.340375 -0.552333 -0.404884 -0.192926 0.350793 1.074215 0.171089 0.737847 0.180305 0.019032 -0.446354 0.244814 0.244814 -0.884094 0.450034 0.936061 -1.386095

390 rows × 211 columns

Extract kinase features

We will use two models, T5 and ESM2, to extract protein embeddings from the amino acid sequence for each kinase.

# load a df that contains sequence info
info = pd.read_excel('train_data/combine_info_PSPA.xlsx')

Uncheck below to run to extract embeddings

For ESM2:

# # get esm embeddings from full kinase sequence
# feat = get_esm(info,'human_uniprot_sequence')

# import gc
# gc.collect()
# # get esm embeddings from kinase domain sequence
# feat_kd = get_esm(info,'kinasecom_domain')

# gc.collect()

For T5 model:

# # get T5 embeddings from full kinase sequence
# feat_t5 = get_t5(info,'human_uniprot_sequence')

# gc.collect()
# # get T5 embeddings from kinase domain sequence
# feat_kd_t5 = get_t5(info,'kinasecom_domain')

# gc.collect()

Save

# # for esm
# feat.astype(float).to_parquet('train_data/esm_combine.parquet')
# feat_kd.astype(float).to_parquet('train_data/esm_combine_kd.parquet')

# # for t5
# feat_t5.astype(float).to_parquet('train_data/t5_combine.parquet')
# feat_kd_t5.astype(float).to_parquet('train_data/t5_combine_kd.parquet')

Or directly load the embeddings

# # for esm
feat= pd.read_parquet('train_data/esm_combine.parquet')
feat_kd = pd.read_parquet('train_data/esm_combine_kd.parquet')

# for t5
feat_t5 = pd.read_parquet('train_data/t5_combine.parquet')
feat_kd_t5 = pd.read_parquet('train_data/t5_combine_kd.parquet')

ESM plot

sns.set(rc={"figure.dpi":300, 'savefig.dpi':300})
sns.set_context('notebook')
sns.set_style("ticks")

ESM2 kinase colored by family

plot_cluster(feat,'umap',complexity=10,hue=info.group,legend=True)
/usr/local/lib/python3.9/dist-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(f"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.")

To visualize PSPA categories, we only look at those with more than 10 kinases

cnt = info.pspa_category_big.str.split('_').str[0].value_counts()

cnt_10 = cnt[cnt>10]

cnt_10_bool = info.pspa_category_big.isin(cnt_10.index)

pspa_cat10 = info[cnt_10_bool].pspa_category_big

ESM2 kinase colored by PSPA category

plot_cluster(feat,'umap',complexity=10,
             hue=pspa_cat10,
             legend=True)
/usr/local/lib/python3.9/dist-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(f"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.")

ESM2 kinase domain colored by family

plot_cluster(feat_kd,'umap',complexity=13,hue=info.group,legend=True)
/usr/local/lib/python3.9/dist-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(f"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.")

ESM2 kinase domain colored by PSPA category

plot_cluster(feat_kd,'umap',complexity=13,hue=pspa_cat10,legend=True)
/usr/local/lib/python3.9/dist-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(f"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.")

T5 plot

T5 kinase colored by family

plot_cluster(feat_t5,'umap',complexity=15,hue=info.group,legend=True)
/usr/local/lib/python3.9/dist-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(f"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.")

T5 kinase colored by PSPA category

plot_cluster(feat_t5,'umap',complexity=15,hue=pspa_cat10,legend=True)
/usr/local/lib/python3.9/dist-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(f"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.")

T5 kinase domain colored by family

plot_cluster(feat_kd_t5,'umap',complexity=13,hue=info.group,legend=True)
/usr/local/lib/python3.9/dist-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(f"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.")

T5 kinase domain colored by PSPA category

plot_cluster(feat_kd_t5,'umap',complexity=13,hue=pspa_cat10,legend=True)
/usr/local/lib/python3.9/dist-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.
  warn(f"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.")

Save Dataframes

target = {'combine': target}
kinase_all = {'esm':feat,'t5':feat_t5, 'esm_kd':feat_kd, 't5_kd': feat_kd_t5}
dfs = {}
for i, t in target.items():
    for j, k in kinase_all.items():
        # df = t.merge(k).reset_index(drop=True)
        df = pd.concat([t,k],axis=1).set_index('kinase')
        dfs[i+'_'+j] = df
        # break

Uncomment to save:

# for key, df in dfs.items():
#     df.astype(float).to_parquet(f'train_data/{key}.parquet')