Idan za mu iya amfani da hankali na wucin gadi don amsa ɗaya daga cikin manyan asirai na rayuwa fa - nada furotin? Masana kimiyya sun yi aiki a kan wannan shekaru da yawa.
Machines yanzu suna iya hasashen tsarin furotin tare da daidaitaccen ban mamaki ta amfani da ƙirar koyo mai zurfi, canza haɓakar ƙwayoyi, fasahar kere-kere, da iliminmu na mahimman hanyoyin nazarin halittu.
Kasance tare da ni a cikin bincike mai ban sha'awa na nau'in furotin AI na nadewa, inda fasahar yankan-baki ta yi karo da sarkar rayuwa kanta.
Tona Sirrin Nadewar Protein
Sunadaran suna aiki a cikin jikinmu kamar ƙananan inji don aiwatar da ayyuka masu mahimmanci kamar lalata abinci ko jigilar iskar oxygen. Dole ne a naɗe su daidai don su yi aiki yadda ya kamata, kamar yadda dole ne a yanke maɓalli daidai don shiga cikin kulle. Da zaran an ƙirƙiri sunadarin, sai a fara rikiɗar tsari mai rikitarwa.
Naɗewa sunadaran shine tsarin da dogayen sarƙoƙi na amino acid, tubalan gina jiki na sunadaran, ke ninkawa zuwa sifofi masu girma uku waɗanda ke nuna aikin furotin.
Yi la'akari da tsayin igiya na beads waɗanda dole ne a ba da oda zuwa madaidaicin tsari; wannan shine abin da ke faruwa lokacin da furotin ya ninka. Amma duk da haka, ba kamar beads ba, amino acid suna da halaye na musamman kuma suna hulɗa da juna ta hanyoyi daban-daban, suna yin naɗewar sunadaran ya zama tsari mai rikitarwa kuma mai hankali.
Hoton a nan yana wakiltar haemoglobin na ɗan adam, wanda sanannen furotin ne na naɗe
Sunadaran dole ne su ninka da sauri kuma daidai, ko kuma za su zama ɓatattu da lahani. Hakan na iya haifar da cututtuka irin su Alzheimer da Parkinson. Zazzabi, matsa lamba, da kasancewar sauran kwayoyin halitta a cikin tantanin halitta duk suna da tasiri akan tsarin nadawa.
Bayan shekaru da yawa na bincike, masana kimiyya har yanzu suna ƙoƙarin gano ainihin yadda sunadaran suna ninka.
Alhamdu lillahi, ci gaba a cikin basirar wucin gadi na inganta ci gaba a fannin. Masana kimiyya na iya hango tsarin sunadaran daidai fiye da kowane lokaci ta amfani da su mashin ilmin lissafi don bincika manyan kundin bayanai.
Wannan yana da yuwuwar canza haɓakar magunguna da haɓaka ilimin ƙwayoyin halittar mu game da rashin lafiya.
Shin Injinan Za Su Yi Kyau?
Dabarun nada Protein na al'ada suna da iyaka
Masana kimiyya sun yi ta ƙoƙarin gano furotin da ke naɗewa shekaru da yawa, amma ƙaƙƙarfan tsarin ya sa wannan ya zama batun kalubale.
Hanyoyin hasashen tsarin gina jiki na al'ada suna amfani da haɗin hanyoyin gwaji da ƙirar kwamfuta, duk da haka, waɗannan hanyoyin duk suna da nakasu.
Dabarun gwaji kamar X-ray crystallography da makaman nukiliya na maganadisu (NMR) na iya ɗaukar lokaci da tsada. Kuma, ƙirar kwamfuta wani lokaci suna dogara da zato masu sauƙi, wanda zai iya haifar da hasashe na kuskure.
AI na iya shawo kan waɗannan matsalolin
sa'ar al'amarin shine, wucin gadi hankali yana ba da sabon alkawari don ƙarin ingantaccen kuma ingantaccen tsarin tsarin gina jiki. Algorithms na koyon inji na iya bincika ɗimbin bayanai. Kuma, suna buɗe tsarin da mutane za su rasa.
Wannan ya haifar da ƙirƙirar sabbin kayan aikin software da dandamali waɗanda ke da ikon tsinkayar tsarin furotin tare da daidaito mara misaltuwa.
Mafi Alƙawari na Koyon Injin Algorithms don Hasashen Tsarin Protein
Tsarin AlphaFold wanda Google's ya gina Deepmind ƙungiyar tana ɗaya daga cikin mafi kyawun ci gaba a wannan yanki. Ya sami babban ci gaba a cikin 'yan shekarun nan ta hanyar amfani zurfin koyo algorithms don hasashen tsarin sunadaran dangane da jerin amino acid ɗin su.
Cibiyoyin sadarwa na jijiyoyi, na'urori masu goyan baya, da dazuzzukan bazuwar suna daga cikin ƙarin hanyoyin koyan inji waɗanda ke nuna alƙawarin hasashen tsarin furotin.
Waɗannan algorithms na iya koyo daga manyan bayanai masu yawa. Kuma, suna iya tsammanin alaƙar da ke tsakanin amino acid daban-daban. Don haka, bari mu ga yadda yake aiki.
Binciken Haɗin Juyin Juyin Halitta da Farko na AlphaFold Generation
Nasarar AlphaFold an gina shi akan ƙirar hanyar sadarwa mai zurfi wacce aka haɓaka ta amfani da nazarin juyin halitta. Ma'anar juyin halitta ta bayyana cewa idan amino acid guda biyu a cikin furotin suna hulɗa da juna, za su haɓaka tare don kiyaye haɗin aikin su.
Masu bincike za su iya gano wane nau'i-nau'i na amino acid da wataƙila za su iya tuntuɓar su a cikin tsarin 3D ta hanyar kwatanta jerin amino acid na yawancin sunadaran irin wannan.
Wannan bayanan yana aiki azaman ginshiƙi don haɓakawar farko na AlphaFold. Yana tsinkayar tsawon tsakanin nau'i-nau'i na amino acid da kuma kusurwoyin peptide bond da ke danganta su. Wannan hanyar ta fi duk hanyoyin da suka gabata don tsinkayar tsarin furotin daga jere, kodayake har yanzu ana iyakance daidaito ga sunadaran ba tare da fayyace samfuri ba.
AlphaFold 2: Sabbin Dabaru
AlphaFold2 software ce ta kwamfuta wanda DeepMind ya ƙirƙira wanda ke amfani da jerin amino acid na furotin don hasashen tsarin 3D na furotin.
Wannan yana da mahimmanci saboda tsarin furotin yana tsara yadda yake aiki, kuma fahimtar aikinsa zai iya taimakawa masana kimiyya su samar da magungunan da ke da alhakin gina jiki.
Cibiyar sadarwar jijiya ta AlphaFold2 tana karɓar azaman shigar da jerin amino acid ɗin sunadaran da kuma cikakkun bayanai game da yadda wannan jeri ya kwatanta da sauran jeri a cikin ma'ajin bayanai (wannan ana kiransa "jerewar jeri").
Cibiyar sadarwa ta jijiya tana yin tsinkaya game da tsarin 3D na furotin bisa wannan shigarwar.
Menene Ya Keɓance Shi Ban da AlphaFold2?
Ya bambanta da sauran hanyoyin, AlphaFold2 yana annabta ainihin tsarin 3D na furotin maimakon kawai rarrabuwa tsakanin nau'ikan amino acid ko kusurwoyin da ke haɗa su (kamar yadda algorithms suka yi).
Domin cibiyar sadarwar jijiyoyi don tsammanin cikakken tsari a lokaci ɗaya, tsarin yana ɓoye ƙarshen-zuwa-ƙarshe.
Wani maɓalli mai mahimmanci na AlphaFold2 shine yana ba da kimanta yadda yake da kwarin gwiwa a cikin hasashen sa. Ana gabatar da wannan azaman lambar launi akan tsarin da ake tsammani, tare da ja yana wakiltar babban ƙarfin gwiwa da shuɗi yana nuna ƙarancin amincewa.
Wannan yana da amfani tun yana sanar da masana kimiyya game da kwanciyar hankali na tsinkaya.
Hasashen Haɗaɗɗen Tsarin Tsari da yawa
Sabon faɗaɗa na Alphafold2, wanda aka sani da Alphafold Multimer, yana yin hasashen tsarin haɗin gwiwar jeri da yawa. Har yanzu yana da manyan kuskuren rates koda kuwa yana aiki da kyau fiye da dabarun da suka gabata. Kawai %25 na rukunin furotin 4500 an yi nasarar annabta.
Kashi 70% na yankuna masu tsattsauran ra'ayi na samuwar tuntuɓar juna an yi hasashen daidai, amma daidaitawar sunadaran biyu ba daidai ba ne. Lokacin da zurfin jeri na tsakiya ya yi ƙasa da kusan jeri 30, daidaiton hasashen Alphafold multimer ya ragu sosai.
Yadda Ake Amfani da Hasashen Alphafold
Ana ba da samfuran da aka annabta daga AlphaFold a cikin tsarin fayil iri ɗaya kuma ana iya amfani da su ta hanyoyi iri ɗaya da tsarin gwaji. Yana da mahimmanci a yi la'akari da ƙididdiga masu dacewa da aka bayar tare da samfurin don hana rashin fahimta.
Yana da taimako musamman ga sarƙaƙƙiya tsarin kamar haɗin gwiwar hommers ko sunadaran da ke ninkawa kawai a gaban wani
wanda ba a sani ba.
Wasu Kalubale
Babban matsala a cikin yin amfani da sifofin da aka annabta shine fahimtar haɓakawa, zaɓin ligand, sarrafawa, allostery, canje-canjen fassarar bayan fassarorin, da kuma motsi na ɗaure ba tare da samun damar yin amfani da bayanan furotin da biophysical ba.
Kayan aikin injiniya kuma za a iya amfani da bincike-bincike na kimiyyar lissafi don shawo kan wannan matsala.
Waɗannan binciken na iya amfana daga ƙwararrun gine-ginen kwamfuta masu inganci. Yayin da AlphaFold ya sami babban ci gaba a cikin tsinkayar tsarin gina jiki, har yanzu akwai abubuwa da yawa da za a koya a fagen ilimin halitta, kuma hasashen AlphaFold shine kawai mafari don nazarin gaba.
Menene Sauran Kayan Aikin Gaggawa?
RoseTTAFold
RoseTTAFold, wanda masu bincike na Jami'ar Washington suka kirkira, shima yana amfani da algorithms mai zurfi na koyo don tsinkayar tsarin gina jiki, amma kuma yana haɗa wani sabon salo wanda aka sani da "simulations torsion angle dynamics simulations" don inganta tsarin da aka annabta.
Wannan hanyar ta haifar da sakamako masu ƙarfafawa kuma yana iya zama da amfani wajen shawo kan iyakokin kayan aikin nada furotin AI.
trosetta
Wani kayan aiki, trRosetta, ya annabta nada furotin ta amfani da a neural network an horar da su akan miliyoyin jerin furotin da tsarin.
Hakanan yana amfani da dabarar “tushen samfuri” don ƙirƙirar ingantattun tsinkaya ta hanyar kwatanta furotin da aka yi niyya zuwa kwatankwacin sanannun sifofi.
An nuna cewa trRosetta yana da ikon yin tsinkaya sifofin ƙananan sunadaran gina jiki da rukunin furotin.
DeepMetaPSICOV
DeepMetaPSICOV wani kayan aiki ne wanda ke mai da hankali kan tsinkayar taswirar tuntuɓar furotin. Waɗannan, ana amfani da su azaman jagora don tsinkayar nada furotin. Yana amfani zurfin ilmantarwa hanyoyin yin hasashen yuwuwar mu'amalar da ta rage a cikin furotin.
Ana amfani da waɗannan daga baya don yin hasashen taswirar tuntuɓar gaba ɗaya. DeepMetaPSICOV ya nuna yuwuwar tsinkayar sifofin furotin tare da daidaito mai girma, koda lokacin da hanyoyin da suka gabata sun gaza.
Menene Nan gaba?
Makomar nadawa furotin AI yana da haske. Algorithms na tushen koyo mai zurfi, musamman AlphaFold2, kwanan nan sun sami babban ci gaba a cikin tsinkayar tsarin furotin.
Wannan binciken yana da yuwuwar canza ci gaban ƙwayoyi ta hanyar ƙyale masana kimiyya su fahimci tsari da aikin sunadaran, waɗanda ke da maƙasudin warkewa na yau da kullun.
Duk da haka, batutuwa kamar tsinkayar rukunin furotin da gano ainihin matsayin aikin da ake tsammani ya rage. Ana buƙatar ƙarin bincike don magance waɗannan batutuwa da haɓaka daidaito da amincin abubuwan nadawa furotin AI.
Duk da haka, yuwuwar fa'idodin wannan fasaha yana da yawa, kuma tana da yuwuwar haifar da samar da ingantattun magunguna masu inganci.
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