Iyini indima ye-AI yokukhiqiza ekutholakaleni kwezidakamizwa?

Iyini indima ye-Generative AI ekutholakaleni kwezidakamizwa?

Impendulo emfushane: I-AI ekhiqizayo isheshisa kakhulu ukutholakala kwezidakamizwa kusenesikhathi ngokukhiqiza ama-molecule noma ukulandelana kwamaprotheni, iphakamisa imizila yokwenziwa, kanye nokuveza imibono evivinywayo, ukuze amaqembu akwazi ukwenza izivivinyo ezimbalwa "ezingaboni". Isebenza kahle kakhulu uma uphoqelela imikhawulo eqinile futhi uqinisekisa imiphumela; uma iphathwa njenge-oracle, ingadukisa ngokuzethemba.

Izinto ezibalulekile okufanele uzicabangele:

Ukusheshisa : Sebenzisa i-GenAI ukuze wandise ukwenziwa kwemibono, bese unciphisa ngokuhlunga okuqinile.

Izithiyo : Zidinga ububanzi bezindawo, imithetho ye-scaffold, kanye nemikhawulo emisha ngaphambi kwesizukulwane.

Ukuqinisekiswa : Phatha imiphumela njengemibono; qinisekisa ngezivivinyo kanye namamodeli ahambisanayo.

Ukulandelelwa : Imiyalelo yelogi, imiphumela, kanye nezizathu ukuze izinqumo zihlale zihlolwa futhi zibuyekezwa.

Ukumelana nokusetshenziswa kabi : Vimbela ukuvuza kanye nokuzethemba ngokweqile ngokuphatha, izilawuli zokufinyelela, kanye nokubuyekezwa kwabantu.

Iyini indima ye-AI yokukhiqiza ekutholakaleni kwezidakamizwa?

Izihloko ongase uthande ukuzifunda ngemva kwalesi:

🔗 Indima ye-AI ekunakekelweni kwezempilo
Indlela i-AI ethuthukisa ngayo ukuxilongwa, imisebenzi, ukunakekelwa kweziguli, kanye nemiphumela.

🔗 Ingabe i-AI izothatha indawo yodokotela bemisebe?
Ihlola ukuthi ukuzenzakalela kuthuthukisa kanjani i-radiology nokuthi yini ehlala ingumuntu.

🔗 Ingabe i-AI izothatha indawo yodokotela?
Ukubheka ngobuqotho umthelela we-AI emisebenzini nasemsebenzini wodokotela.

🔗 Amathuluzi elabhorethri e-AI amahle kakhulu okuthola isayensi
Amathuluzi elabhorethri e-AI aphezulu okusheshisa izivivinyo, ukuhlaziya, kanye nokuthola.

Indima ye-AI yokukhiqiza ekutholakaleni kwezidakamizwa, ngokuphefumula okukodwa 😮💨

I-AI ekhiqizayo isiza amaqembu emithi ukudala ama-molecule afanelekayo, ukubikezela izakhiwo, ukuphakamisa izinguquko, ukuphakamisa izindlela zokwenziwa, ukuhlola imibono yezinto eziphilayo, nokucindezela imijikelezo yokuphindaphinda - ikakhulukazi ekutholakaleni kwasekuqaleni kanye nokwenza ngcono i-lead. I-Nature 2023 (ukubuyekezwa kokutholwa kwe-ligand) Ukubuyekezwa kwe-Elsevier 2024 (amamodeli okukhiqiza ekwakhiweni kwezidakamizwa okusha)

Futhi yebo, kungadala futhi ngokuzethemba okungenangqondo. Lokho kuyingxenye yesivumelwano. Njengomfundi okhuthele kakhulu onenjini yerokhethi. Umhlahlandlela wodokotela (ingozi yokubona izinto ezingekho) i-npj Digital Medicine 2025 (ukubona izinto ezingekho + uhlaka lokuphepha)

Kungani lokhu kubaluleke ngaphezu kwalokho abantu abakuqaphelayo 💥

Umsebenzi omningi wokuthola ulwazi “ukusesha.” Isikhala samakhemikhali sokusesha, i-biology yokusesha, izincwadi zokusesha, ubudlelwano besakhiwo nomsebenzi wokusesha. Inkinga ukuthi isikhala samakhemikhali… empeleni asinamkhawulo. Ama-Akhawunti Ocwaningo Lwamakhemikhali 2015 (isikhala samakhemikhali) U-Irwin noShoichet 2009 (isikali sesikhala samakhemikhali)

Ungachitha impilo yakho yonke isikhathi eside uzama nje ukushintshashintsha "okunengqondo".

I-AI ekhiqizayo ishintsha umsebenzi kusuka ku:

  • “Ake sihlole ukuthi yini esingayicabanga”

ku:

  • “Masidale isethi enkulu nehlakaniphile yezinketho, bese sihlola ezingcono kakhulu”

Akukhona mayelana nokuqeda izivivinyo. Kumayelana nokukhetha izivivinyo ezingcono . 🧠 Imvelo 2023 (isibuyekezo sokutholakala kwe-ligand)

Futhi, futhi lokhu akuxoxwa ngakho kakhulu, kusiza amaqembu ukuthi axoxe ngemikhakha eyahlukene . Osokhemisi, izazi zezinto eziphilayo, abantu be-DMPK, ososayensi bekhompyutha… wonke umuntu unezinhlobo ezahlukene zengqondo. Uhlelo oluhle lokukhiqiza lungasebenza njengephedi yokudweba eyabiwe. Isibuyekezo se-Frontiers in Drug Discovery 2024

Yini eyenza inguqulo enhle ye-AI yokukhiqiza ekutholakaleni kwezidakamizwa? ✅

Akuzona zonke i-AI ezikhiqizayo ezidalwe zilingana. Inguqulo "enhle" yalesi sikhala ayimayelana nama-demo akhangayo kodwa imayelana nokuthembeka okungafanele (ukungafaneleki kuyimfanelo lapha). I-Nature 2023 (isibuyekezo sokutholakala kwe-ligand)

Ukusethwa okuhle kwe-AI okukhiqizayo kuvame ukuba nalokhu:

Uma i-AI yakho yokukhiqiza ingakwazi ukubhekana nemingcele, empeleni iyisikhiqizi sezinto ezintsha. Kumnandi emaphathini. Akumnandi kakhulu ohlelweni lwezidakamizwa.

Lapho i-AI ekhiqizayo ifanelana khona nomzila wokuthola izidakamizwa 🧭

Nansi imephu yengqondo elula. I-AI ekhiqizayo ingaba negalelo cishe kuzo zonke izigaba, kodwa isebenza kahle kakhulu lapho ukuphindaphinda kubiza khona futhi isikhala se-hypothesis sikhulu. I-Nature 2023 (isibuyekezo sokutholwa kwe-ligand)

Izindawo zokuthinta ezivamile:

Ezinhlelweni eziningi, impumelelo enkulu ivela ekuhlanganisweni komsebenzi , hhayi kumodeli eyodwa "eyingcweti." Imodeli iyinjini - umzila wepayipi yimoto. I-Nature 2023 (isibuyekezo sokutholwa kwe-ligand)

Ithebula Lokuqhathanisa: izindlela ezidumile zokukhiqiza i-AI ezisetshenziswa ekutholakaleni kwezidakamizwa 📊

Itafula elingaphelele kancane, ngoba impilo yangempela ayiphelele kancane.

Ithuluzi / Indlela Kuhle kakhulu (kwezithameli) Intengo-ngokufanayo Kungani kusebenza (futhi uma kungasebenzi)
Ama-generator ama-molecule amasha (AMAMATHE, amagrafu) Ikhemistri yezokwelapha + ikhemistri yezokwelapha $$-$$$ Kuhle kakhulu ekuhloleni ama-analog amasha ngokushesha 😎 - kodwa kungakhipha ukungaguquguquki okungazinzile REINVENT 4 GENTRL (Nature Biotech 2019)
Abakhiqizi bamaprotheni/isakhiwo Amaqembu e-biologics, i-structural biology $$$ Isiza ukuphakamisa ukulandelana + izakhiwo - kodwa "kubukeka sengathi kungenzeka" akufani "nemisebenzi" AlphaFold (Nature 2021) RFdiffusion (Nature 2023)
Umklamo wama-molecule wesitayela sokusabalalisa Amaqembu e-ML athuthukile $$-$$$$ Iqinile ekubekeni imingcele kanye nokwehlukahluka - ukusetha kungaba… into ephelele i-JCIM 2024 (amamodeli okusabalalisa) Ukubuyekezwa kokusabalalisa kwe-PMC 2025
Abashayeli bezindiza ababikezela impahla (inhlanganisela ye-QSAR + GenAI) I-DMPK, amaqembu ephrojekthi $$ Kuhle ekuhlolweni nasekubekweni kwezikhundla - kubi uma kuphathwa njengevangeli 😬 I-OECD (isizinda sokusebenza) I-ADMEthab 2.0
Abahleli be-Retrosynthesis I-process chem, i-CMC $$-$$$ Kusheshisa ukucabanga komzila - kusadinga abantu ukuze kwenzeke futhi kuphephe i-AiZynthFinder 2020 Coley 2018 (CASP)
Ama-copilot elebhu amaningi (idatha yombhalo + yokuhlola) Amaqembu okuhumusha $$$ Kuwusizo ekudonseni amasignali kuwo wonke amasethi edatha - kuthambekele ekuzethembeni ngokweqile uma idatha ingcolile I-Nature 2024 (imiphumela yeqembu ekuthathweni kwezithombe zamaseli) i-npj Digital Medicine 2025 (i-multimodal ku-biotech)
Abasizi bezincwadi kanye nemibono Wonke umuntu, empeleni $ Kunciphisa isikhathi sokufunda kakhulu - kodwa ukubona izinto ezingekho ngokoqobo kungaba okushelelayo, njengokunyamalala kwamasokisi Amaphethini ka-2025 (ama-LLM ekutholakaleni kwezidakamizwa) Umhlahlandlela wodokotela (ukubona izinto ezingekho ngokoqobo)
Amamodeli esisekelo angaphakathi enziwe ngokwezifiso Ama-biotech amakhulu axhaswe kahle ngemithi $$$$ Ukulawula okungcono kakhulu + ukuhlanganiswa - futhi kuyabiza futhi kuyashesha ukwakha (uxolo, kuyiqiniso) Isibuyekezo se-Frontiers in Drug Discovery 2024

Amanothi: amanani ayahlukahluka kakhulu kuye ngokuthi ingakanani, ukubala, ilayisensi, nokuthi ithimba lakho lifuna "ukuxhuma nokudlala" noma "asakhe umkhumbi-mkhathi."

Ukubheka eduze: I-AI Ekhiqizayo yokuthola izinto ezintsha kanye nomklamo omusha 🧩

Nasi isibonelo esiyinhloko sokusetshenziswa: khiqiza ama-molecule afanelekayo kusukela ekuqaleni (noma esikhaleni) afana nephrofayili eqondiwe. I-Nature Biotechnology 2019 (GENTRL) IYAVULA 4

Indlela esebenza ngayo ngokuvamile:

  1. Chaza imikhawulo

  2. Khiqiza abantu abazongenela ukhetho

  3. Hlunga ngokucindezela

  4. Khetha isethi encane yokwenziwa

    • abantu basakhetha, ngoba abantu banganuka iphunga elingenangqondo ngezinye izikhathi

Iqiniso elixakile: inani alikho nje “ama-molecule amasha.” Ama -molecule amasha anengqondo ngemikhawulo yohlelo lwakho . Leyo ngxenye yokugcina iyikho konke. I-Nature 2023 (isibuyekezo sokutholakala kwe-ligand)

Futhi, kukhona ukweqisa okuncane: uma kwenziwe kahle, kungazwakala sengathi uqashe ithimba losokhemisi abancane abangakhathali abangalali futhi abangalokothi bakhononde. Futhi, abaqondi ukuthi kungani isu elithile lokuvikela liyiphupho elibi, ngakho… bhalansi 😅.

Ukubheka eduze: Ukulungiswa kwe-lead nge-AI ekhiqizayo (ukulungiswa kwamapharamitha amaningi) 🎛️

Ukuthuthukisa i-lead yilapho amaphupho eba yinkimbinkimbi khona.

Uyafuna:

  • amandla aphezulu

  • ukukhetha kuphezulu

  • ukuzinza kwe-metabolic kuyanda

  • ukuncibilika kuphezulu

  • izimpawu zokuphepha ziphansi

  • ukuvuleka “kulungile”

  • FUTHI kusazokwenziwa

Lokhu kuyindlela yokwenza ngcono ye-multi-objective yakudala. I-AI ekhiqizayo inhle kakhulu ekuphakamiseni isethi yezixazululo zokuhwebelana kunokuba yenze sengathi kukhona inhlanganisela eyodwa ephelele. BUYISA Ukubuyekezwa kwe-Elsevier 2024 okungu-4

Izindlela ezisebenzayo amaqembu ayisebenzisa ngazo:

  • Isiphakamiso se-analog : "Yenza izinhlobo ezingu-30 ezinciphisa ukukhishwa kodwa zigcine amandla"

  • Ukuskena okushintshiwe : ukuhlola okuqondisiwe esikhundleni sokubalwa kwamandla aluhlaza

  • Ukugxuma kwe-scaffold : lapho i-core ishaya udonga (ubuthi, i-IP, noma ukuzinza)

  • Chaza iziphakamiso : “Leli qembu le-polar lingasiza ekuncibilikeni kodwa lingalimaza ukungena kwamanzi” (akulungile ngaso sonke isikhathi, kodwa kuyasiza)

Isexwayiso esisodwa: izibikezeli zezakhiwo zingaba buthakathaka. Uma idatha yakho yokuqeqesha ingahambisani nochungechunge lwakho lwamakhemikhali, imodeli ingaba nephutha ngokuqiniseka. Njengokuthi, ayilungile kakhulu. Futhi ngeke ihlazeke. Izimiso zokuqinisekisa ze-OECD QSAR (isizinda sokusebenza) Weaver 2008 (isizinda sokusebenza se-QSAR)

Ukubheka eduze: I-ADMET, ubuthi, kanye nokuhlolwa kokuthi “ngicela ungabulali uhlelo” 🧯

I-ADMET yilapho abantu abaningi abafaka izicelo behluleka khona buthule. I-AI ekhiqizayo ayixazululi i-biology, kodwa inganciphisa amaphutha angagwenywa. I-ADMETlab 2.0 Waring 2015 (ukulahlekelwa)

Izindima ezivamile:

  • ukubikezela izikweletu ze-metabolic (izindawo ze-metabolism, izitayela zokususa)

  • ukumaka izisusa ezinobuthi ezingaba khona (izaziso, ama-proxies asebenzayo)

  • ukulinganisa ububanzi bokuncibilika kanye nokuvuleka kwamanzi

  • esikisela izinguquko zokunciphisa ingozi ye-hERG noma ukuthuthukisa ukuzinza 🧪 I-FDA (ICH E14/S7B Q&A) EMA (ukubuka konke kwe-ICH E14/S7B)

Iphethini ephumelela kakhulu ivame ukufana nalokhu: sebenzisa i-GenAI ukuphakamisa izinketho, kodwa sebenzisa amamodeli akhethekile kanye nokuhlolwa ukuqinisekisa.

I-AI ekhiqizayo iyinjini yokucabanga. Ukuqinisekisa kusasebenza ekuhlolweni.

Ukubheka eduze: I-AI Ekhiqizayo ye-biologics kanye nobunjiniyela bamaprotheni 🧬✨

Ukutholakala kwezidakamizwa akugcini nje ngokutholakala kwama-molecule amancane. I-AI ekhiqizayo isetshenziselwa futhi:

Ukukhiqizwa kwamaprotheni nokulandelana kungaba namandla ngoba "ulimi" lwezinhlu luhambisana kahle ngendlela emangalisayo nezindlela ze-ML. Kodwa nansi indlela engavamile yokubuyela emuva: ihambisana kahle… kuze kube yilapho ingasebenzi. Ngoba ukuzivikela komzimba, ukubonakaliswa, amaphethini e-glycosylation, kanye nemikhawulo yokuthuthuka kungaba yingozi. AlphaFold (Nature 2021) ProteinGenerator (Nat Biotech 2024)

Ngakho-ke, izinketho ezinhle kakhulu zifaka:

  • izihlungi zokuthuthuka

  • ukuhlolwa kwengozi yokuzivikela komzimba

  • imikhawulo yokukhiqiza

  • ama-loop elebhu amanzi ukuze kuphindwe ngokushesha 🧫

Uma uzigwema lezo, uthola uhlu oluhle kakhulu oluziphatha njenge-diva ekukhiqizweni.

Ukubheka eduze: Ukuhlela ukwenziwa kanye neziphakamiso zokwenziwa kabusha 🧰

I-AI ekhiqizayo nayo ingena ngokunyenya emisebenzini yamakhemikhali, hhayi nje ekucabangeni ngama-molecule.

Abahleli be-Retrosynthesis bangenza okulandelayo:

  • phakamisa imizila eya endaweni ethile eqondiwe

  • phakamisa izinto zokuqala ezitholakala kwezentengiselwano

  • izindlela zokuhlela ngezinyathelo noma okubonwayo ukuthi kungenzeka

  • siza osokhemisi ukuthi basuse ngokushesha imibono "emihle kodwa engenakwenzeka" i -AiZynthFinder 2020 Coley 2018 (CASP)

Lokhu kungonga isikhathi sangempela, ikakhulukazi uma uhlola izakhiwo eziningi ezingaba khona. Noma kunjalo, abantu babaluleke kakhulu lapha ngoba:

  • izinguquko zokutholakala kwe-reagent

  • ukukhathazeka ngokuphepha kanye nobukhulu kuyiqiniso

  • ezinye izinyathelo zibukeka kahle ephepheni kodwa zehluleka ngokuphindaphindiwe

Isingathekiso esingaphelele, kodwa ngizosisebenzisa noma kunjalo: i-retrosynthesis I-AI ifana ne-GPS elungile kakhulu, ngaphandle kokuthi ngezinye izikhathi ikuhambisa echibini futhi iphikelela ukuthi iyindlela emfushane. 🚗🌊 Coley 2017 (retrosynthesis esizwa yikhompyutha)

Idatha, amamodeli amaningi, kanye neqiniso elibi lamalebhu 🧾🧪

I-AI ekhiqizayo iyayithanda idatha. Amalebhu akhiqiza idatha. Ephepheni, lokho kuzwakala kulula.

Cha.

Idatha yangempela yelabhorethri yile:

Izinhlelo zokukhiqiza eziningi zingahlanganisa:

Uma isebenza, iyamangalisa. Ungathola amaphethini angabonakali bese uphakamisa izivivinyo ezingaphuthelwa uchwepheshe oyedwa.

Uma yehluleka, yehluleka buthule. Ayivali umnyango. Imane ikushukumisela esiphethweni esingalungile esiqinisekile. Yingakho ukubusa, ukuqinisekiswa, kanye nokubuyekezwa kwesizinda kungeyona into ongayikhetha. Umhlahlandlela wodokotela (ukungaboni kahle) npj Digital Medicine 2025 (ukungaboni kahle + uhlaka lokuphepha)

Izingozi, imikhawulo, kanye nesigaba esithi “ungakhohliswa umphumela ocacile” ⚠️

Uma ukhumbula into eyodwa kuphela, khumbula lokhu: i-AI ekhiqizayo iyakholisa. Ingazwakala ilungile ngenkathi ingalungile. Umhlahlandlela wodokotela (ukungaqondi kahle)

Izingozi Eziyinhloko:

Izinyathelo zokunciphisa ezisiza ekusebenzeni:

  • gcina abantu besesimeni sokukhetha

  • izicelo zelogi kanye nemiphumela yokulandelela

  • qinisekisa ngezindlela eziqondile (izivivinyo, amamodeli ahlukile)

  • sebenzisa imikhawulo futhi uhlunge ngokuzenzakalelayo

  • phatha imiphumela njengemibono, hhayi amaphilisi eqiniso isiqondiso se-OECD QSAR

I-AI Ekhiqizayo iyithuluzi lamandla. Amathuluzi kagesi awakwenzi ube ngumbazi… avele enze amaphutha ngokushesha uma ungazi ukuthi wenzani.

Amaqembu asebenzisa kanjani i-AI ekhiqizayo ngaphandle kwesiphithiphithi 🧩🛠️

Amaqembu avame ukufuna ukusebenzisa lokhu ngaphandle kokuguqula inhlangano ibe umbukiso wesayensi. Indlela yokwamukelwa ewusizo ibukeka kanje:

Futhi, ungalithathi kancane isiko. Uma osokhemisi bezwa sengathi i-AI iyabacindezela, bazoyishaya indiva. Uma kubasindisa isikhathi futhi kuhlonipha ubuchwepheshe babo, bazokwamukela ngokushesha. Abantu bahlekisa kanjalo 🙂.

Iyini indima ye-AI yokukhiqiza ekutholakaleni kwezidakamizwa uma usondeza ngaphandle? 🔭

Uma sekukhululiwe, indima akuyona “ukufaka esikhundleni sososayensi.” “Ukwandisa umkhawulokudonsa wesayensi.” I-Nature 2023 (isibuyekezo sokutholakala kwe-ligand)

Kuyasiza amaqembu:

  • hlola imibono eyengeziwe ngesonto

  • phakamisa izakhiwo ezengeziwe ezifanelekayo ngomjikelezo ngamunye

  • beka phambili izivivinyo ngokuhlakanipha okukhulu

  • cindezela izihibe zokuphindaphinda phakathi komklamo nokuhlolwa

  • yabelana ngolwazi kuzo zonke izikhungo zokuthengisa izidakamizwa ngo-2025 (ama-LLM ekutholakaleni kwezidakamizwa)

Futhi mhlawumbe ingxenye engahlonishwa kakhulu: ikusiza ukuthi ungachithi ubuhlakani bomuntu obubizayo emisebenzini ephindaphindwayo. Abantu kufanele bacabange ngendlela yokusebenza, isu, kanye nokuhumusha - hhayi ukuchitha izinsuku bekhiqiza uhlu oluhlukile ngesandla. I-Nature 2023 (isibuyekezo sokutholwa kwe-ligand)

Ngakho-ke yebo, indima ye-AI ekhiqizayo ku-Drug Discovery iyi-accelerator, i-generator, isihlungi, futhi ngezinye izikhathi idala izinkinga. Kodwa iwusizo.

Isifinyezo sokuvala 🧾✅

I-AI ekhiqizayo isiba yikhono eliyinhloko ekutholakaleni kwezidakamizwa zanamuhla ngoba ingakhiqiza ama-molecule, imibono, ukulandelana, kanye nemizila ngokushesha kunabantu - futhi ingasiza amaqembu ukuthi akhethe ukuhlolwa okungcono. Isibuyekezo se-Frontiers in Drug Discovery 2024 Nature 2023 (isibuyekezo sokutholakala kwe-ligand)

Izinhlamvu ezifingqiwe:

Uma uyiphatha njengomuntu osebenzisana naye - hhayi njengomuntu okhulumayo - ingaqhubekisela phambili izinhlelo. Futhi uma uyiphatha njengomuntu okhulumayo ... kahle, ungase ugcine ulandela leyo GPS echibini futhi. 🚗🌊

Imibuzo Evame Ukubuzwa

Iyini indima ye-AI yokukhiqiza ekutholakaleni kwezidakamizwa?

I-AI ekhiqizayo ngokuyinhloko yandisa i-funnel yomqondo ekutholakaleni kwasekuqaleni kanye nokwenza ngcono i-lead ngokuphakamisa ama-molecule afanelekayo, ukulandelana kwamaprotheni, imizila yokwenziwa, kanye nezimvo zezinto eziphilayo. Inani lincane "lokufaka esikhundleni sezilingo" kodwa "likhetha ukuhlolwa okungcono" ngokukhiqiza izinketho eziningi bese lihlunga kanzima. Isebenza kahle kakhulu njenge-accelerator ngaphakathi komsebenzi oqeqeshiwe, hhayi njengomenzi wezinqumo ozimele.

I-AI ekhiqizayo isebenza kanjani kangcono kulo lonke ipayipi lokutholwa kwezidakamizwa?

Kuvame ukuletha inani elikhulu lapho isikhala se-hypothesis sikhulu khona futhi ukuphindaphinda kubiza kakhulu, njengokuhlonza ama-hit, ukwakheka okusha, kanye nokwenza ngcono ama-lead. Amaqembu ayisebenzisela futhi i-ADMET triage, iziphakamiso ze-retrosynthesis, kanye nokusekelwa kwezincwadi noma kwe-hypothesis. Izinzuzo ezinkulu zivame ukuvela ekuhlanganiseni isizukulwane nezihlungi, amamaki, kanye nokubuyekezwa kwabantu kunokulindela ukuthi imodeli eyodwa "ihlakaniphe."

Uzibeka kanjani imingcele ukuze amamodeli akhiqizayo angakhiqizi ama-molecule angenamsebenzi?

Indlela esebenzayo ukuchaza imikhawulo ngaphambi kokwenziwa: ububanzi bezakhiwo (njengokuncibilika noma imigomo ye-logP), imithetho ye-scaffold noma yesakhiwo, izici zesayithi lokubopha, kanye nemikhawulo emisha. Bese usebenzisa izihlungi ze-chemistry yezokwelapha (kufaka phakathi amaqembu e-PAINS/reactive) kanye nokuhlolwa kokwenziwa. Isizukulwane sokuqala se-Constraint sisiza kakhulu ngomklamo wama-molecule wesitayela sokusabalalisa kanye nezinhlaka ezifana ne-REINVENT 4, lapho imigomo yezinhloso eziningi ingafakwa khona ikhodi.

Amaqembu kufanele aqinisekise kanjani imiphumela ye-GenAI ukuze agweme ukubona izinto ezingekho kanye nokuzethemba ngokweqile?

Phatha konke okukhiphayo njengombono, hhayi isiphetho, bese uqinisekisa ngezivivinyo namamodeli ahambisanayo. Hlanganisa ukwenziwa kokuhlunga okunamandla, ukufaka idokhi noma ukufaka amaphuzu lapho kufanele khona, kanye nokuhlolwa kwesizinda sokusebenza kwezibikezeli zesitayela se-QSAR. Yenza ukungaqiniseki kubonakale lapho kungenzeka, ngoba amamodeli angaba nephutha ngokuqiniseka kumakhemikhali angaphandle kokusabalalisa noma izimangalo zebhayoloji ezintengantengayo. Ukubuyekezwa komuntu ngaphakathi kwe-loop kusalokhu kuyisici esiyinhloko sokuphepha.

Ungakuvimbela kanjani ukuvuza kwedatha, ingozi ye-IP, kanye nemiphumela "egcinwe ngekhanda"?

Sebenzisa ukubusa kanye nezilawuli zokufinyelela ukuze imininingwane yohlelo ebucayi ingafakwa kalula ezicelweni, bese ubhala phansi izixwayiso/imiphumela ukuze kuhlolwe kahle. Qinisekisa ukuthi abantu abazongenela ukhetho abasondelene kakhulu nama-compounds aziwayo noma izifunda ezivikelwe. Gcina imithetho ecacile mayelana nokuthi iyiphi idatha evunyelwe ezinhlelweni zangaphandle, futhi ukhethe izindawo ezilawulwayo zomsebenzi wokuzwela okuphezulu. Ukubuyekezwa kwabantu kusiza ekubambeni iziphakamiso "ezijwayelekile kakhulu" kusenesikhathi.

Isetshenziswa kanjani i-AI yokukhiqiza ukuze kwenziwe ngcono i-lead kanye nokulungisa amapharamitha amaningi?

Ekuthuthukiseni i-lead, i-AI yokukhiqiza iwusizo ngoba ingaphakamisa izixazululo eziningi zokushintshana esikhundleni sokuphishekela inhlanganisela eyodwa "ephelele". Izindlela zokusebenza ezivamile zifaka phakathi isiphakamiso se-analog, ukuskena okuqondiswayo okufakwa esikhundleni, kanye nokushintshashintsha kwe-scaffold lapho imikhawulo ye-potency, i-tox, noma i-IP ivimba inqubekela phambili. Izibikezeli zempahla zingaba buthakathaka, ngakho-ke amaqembu avame ukulinganisa abantu abazongenela ukhetho ngamamodeli amaningi bese eqinisekisa izinketho ezinhle kakhulu ngokuhlola.

Ingabe i-AI yokukhiqiza ingasiza nge-biologics kanye nobunjiniyela bamaprotheni?

Yebo - amaqembu ayisebenzisela ukukhiqiza ukulandelana kwama-antibody, imibono yokuvuthwa kwe-affinity, ukuthuthukiswa kokuzinza, kanye nokuhlola i-enzyme noma i-peptide. Ukukhiqiza amaprotheni/ukulandelana kungabonakala kunengqondo ngaphandle kokuthi kuthuthukiswe, ngakho-ke kubalulekile ukusebenzisa izihlungi zokuthuthukiswa, i-immunogenicity, kanye ne-manufacturability. Amathuluzi esakhiwo afana ne-AlphaFold angasekela ukucabanga, kodwa "isakhiwo esinokwenzeka" asisona ubufakazi bokuveza, ukusebenza, noma ukuphepha. Ama-loop e-Wet-lab ahlala ebalulekile.

I-AI yokukhiqiza isekela kanjani ukuhlela ukwenziwa kanye nokuhlelwa kabusha?

Abahleli be-Retrosynthesis bangaphakamisa imizila, izinto zokuqala, kanye nokuhlelwa kwemizila ukuze kusheshiswe ukucabanga futhi kuqedwe ngokushesha imizila engenakwenzeka. Amathuluzi nezindlela ezifana nokuhlela kwesitayela se-AiZynthFinder zisebenza kahle kakhulu uma zihambisana nokuhlolwa kokwenzeka kwangempela okuvela kosokhemisi. Ukutholakala, ukuphepha, imikhawulo yokukhulisa, kanye "nokusabela kwamaphepha" okwehluleka ekusebenzeni kusadinga ukwahlulela komuntu. Uma kusetshenziswa ngale ndlela, konga isikhathi ngaphandle kokwenza sengathi ikhemistri ixazululiwe.

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