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Химический IT кентавр – хемоинформатика

В 21 веке мы сталкиваемся с бурным развитием мультидисциплинарных наук, где информационные технологии играют ключевую роль. Одной из привлекающих внимание областей, где эти технологии активно применяются, является хемоинформатика (от анг. chemoinformatics). Определение, данное И.Гастайгером, звучит так, хемоинформатика — это применение методов информатики для решения химических задач [1].

Зачем нужна хемоинформатика?

В настоящее время по данным одной из наиболее крупных химических баз данных PubChem человечеству известно более 100 миллионов органических молекул [2]. Казалось бы очень большое число, однако размер всего химического пространства оценивается в ошеломляющие 10^180 веществ, которые потенциально могут быть синтезированы [3]. Это на сотню порядков больше числа атомов во вселенной. Иметь методы навигации в известных и неизвестных областях химического пространства критически важно, т.к. среди непознанных 10^180 веществ наверняка существует множество полезных соединений — это новые лекарства, красители, агрохимикаты, ароматы для парфюмерии, материалы для электроники и другие важные для людей материалы.

Масштаб даже известной нам части химического пространства требует использования методов анализа больших данных. Это послужило одной из причин возникновения дисциплины на стыке химии и IT - хемоинформатики. Но чем именно занимается хемоинформатика в прикладном смысле? Основные направления приведены на схеме ниже.

1. Предсказание свойств

Существует множество свойств, которые успешно прогнозируются с помощью методов машинного обучения и/или компьютерного моделирования. К ним относятся различные физико-химические параметры (растворимость, липофильность), биологическая активность, реакционная способность и многие другие [4,5,6,7]. В этой статье мы рассмотрим предсказание токсичности ввиду важности этого параметра. Ежегодно синтезируется порядка нескольких миллионов новых веществ, при этом профиль безопасности устанавливается лишь для около 10 тыс. Это значит, что за 1 год мы устанавливаем токсичность соединений, синтезированных всего за 1 день.

Налицо серьезное отставание скорости экспериментальной проверки токсичности новых молекул от скорости их синтеза. Но даже если весь научно-технический потенциал человечества был бы направлен на токсикологическое профилирование для всех новых веществ - смогли бы мы это сделать? Разберем пример. Для регистрации пестицида в США требуется провести порядка 80 тестов на определение токсичности, их суммарная стоимость оценивается более чем в 20 миллионов долларов [8]. Токсичность очень многогранное понятие, которое требует десятков экспериментов. Стоимость некоторых из них в соответствии с данными U.S. Environmental Protection Agency (EPA):

Острая токсичность (рыбы) 17.000$
Хроническая токсичность (дафнии) 180.000$
Канцерогенность (крысы и мыши) 2.100.000$.

В соответствии с приведенными выше данными тотальное экспериментальное определение токсичности для всех новых соединений видится, действительно, мало реалистичным с точки зрения колоссальных затрат ресурсов на эту задачу.

Кроме того, токсичность в большинстве случаев оценивается на лабораторных животных, масштаб использования которых сейчас во всем мире достигает почти 200 миллионов в год [9]. Существует даже серия мультфильмов, посвященная их защите. Особую известность получил кролик Ральф. Этически предпочтительно избегать тестов на животных, что закреплено, например, в регламенте Евросоюза REACH [10].

Современные подходы позволяют создать альтернативные решения, которые на порядки снижают стоимость профилирования, а также не вызывают этических вопросов связанных с проведением опытов на животных — это предсказание токсичности in silico, то есть за счет применения вычислительных технологий. Разумеется, есть определенная ошибка в предсказательном моделировании, однако по меньшей мере это способствует приоритезации исследований и минимизации расхода животных. Более того – использование этих методов снижает риски для добровольцев, участвующих в клинических испытаниях.

Уже существует ряд цифровых инструментов, позволяющих предсказать токсичность веществ. Среди них ряд методов, разработанных российскими учеными [11, 12]. С помощью основанной на этих методах цифровой платформе Синтелли можно прогнозировать более 40 параметров токсичности [13].

2. Дизайн веществ и материалов

Существуют инструменты, позволяющие сгенерировать молекулу с заданными свойствами. Этому находится много применений, однако в данной статье мы сосредоточимся на лекарствах. Разработка препарата — это сложный процесс, длительность которого составляет в среднем 10–15 лет, а стоимость может достигать 3-х миллиардов $ [14], однако применение методов хемоинформатики способно ощутимо сократить как временные, так и материальные расходы (рис. 1). R&D департаменты крупных фармацевтических компаний уже не могут существовать без таких специалистов, как хемоинформатик, вычислительный и цифровой химик. Дело в том, что хемоинформатика значительно оптимизирует решение основных задач фармы: поиск активных молекул, определение токсичности, растворимости в воде, проницаемости через клеточную мембрану, метаболизма, взаимодействия с белками плазмы крови и др. Дизайн лекарств с помощью компьютерных технологий (Computer-aided drug design) развивается внушительными темпами и особенно впечатляющими являются следующие 2 примера:

§ Компания Insilico Medicine в 2023 года заявила об успешном прохождении доклинических исследований молекулы INS018-055 для лечения идиопатического легочного фиброза. Интересно, что с помощью ИИ не только была сгенерирована активная молекула, но и идентифицирована мишень для лечения. К текущему моменту молекула успешно преодолела I фазу клинических исследований, тем самым подтвердив безопасность применения [15]. Продолжается II фаза клинических исследований.

§ В 2020 году британская фармацевтическая компания Exscienta заявила об успешном окончании доклинических исследований молекулы DSP-1181 для лечения обсессивно-компульсивного расстройства (ОКР) [16].

«Этот год был первым, когда было разработано лекарство с помощью искусственного интеллекта, но к концу десятилетия все новые препараты могут быть созданы с помощью алгоритмов» - Эндрю Хопкинс, генеральный директор Exscienta.

Рисунок 1. Стратегии разработки лекарственного препарата.

Еще одной привлекающей внимание программой является PASS, разработанная отечественными учеными и позволяющая прогнозировать целый ряд параметров, характеризующих биологическую активность соединений [17, 18]. Также стоит отметить метод USPEX, который позволяет предсказывать кристаллическую структуру веществ при различных температурах и давлениях, исходя из знания только химического состава материала [19].

3. Идентификация веществ

Данная область связана с обработкой результатов исследования веществ и их смесей физико-химическими методами анализа. Строго говоря, она называется хемометрика и считается производным хемоинформатики. Для наглядности разберем пример (рис. 2). Вы хотите определить есть ли пестициды в почве на дачном участке. Вы собираете почву и отдаете ее в лабораторию, где с ней проводят специальную пробоподготовку и анализируют на приборе (ВЭЖХ-МС). Сначала с помощью хроматографа (ВЭЖХ) смесь веществ разделяется так, что вещества попадают последовательно в следующий блок прибора - масс-спектрометрический детектор. Последний выдает некую информацию о каждом веществе из пробы (масс-спектры). На этом этапе еще нельзя сделать заключение о том, что содержится в почве. Масс-спектры, выданные прибором, нужно проанализировать. В некоторых случаях, для этого достаточно квалифицированного специалиста, однако более эффективным является подход, когда компьютер автономно сравнивает масс-спектры для каждого вещества из вашей пробы с аннотированными масс-спектрами из базы данных (которые, к слову, требует курирования данных хемоинформатиками). Если они совпадают, то вещество идентифицировано.

Рисунок 2. Алгоритм идентификации малых молекул

Но есть 1 проблема. Базы данных (БД) не всеобъемлющи. Так, одна из самых крупных БД NIST содержит масс-спектры для 350.000 веществ, что составляет 0.2% от числа известных нам молекул (~10^8) [20]. Как следствие, мы наблюдаем поразительную неосведомленность об окружающем нас мире:

v При анализе бытовой пыли были идентифицированы 33 вещества из 5.000 [21]

v При анализе сточных вод - 1.2% веществ [22]

Фактически, мы до сих пор толком не знаем, что нас окружает. Однако у человечества есть надежда приблизиться к решению этой задачи. Разработан ряд хемоинформатических инструментов, способствующих идентификации структуры вещества, исходя из масс-спектра [23, 24, 25]. Безусловно, стоит оговориться, что это лишь прогноз и в ряде случаев определить структуру по одному лишь масс-спектру невозможно априори, но тем не менее это полезный инструмент в отсутствие альтернатив. Также существует и обратный подход, который предполагает предсказание масс-спектров и, как следствие, расширение баз данных для сопоставления с анализируемыми образцами. Данную задачу можно решить с помощью методов разработанных российскими учеными, которые позволяют прогнозировать и другие не менее важные для идентификации веществ спектральные данные (ЯМР, ИК) [13].

Есть и другой важный для нас пример — лекарства. Как понять соответствует ли фактический состав препарата заявленному? На практике для решения этой задачи широко применяется метод ИК-спектроскопии. Для экспресс-анализа были разработаны специальные портативные версии ИК-спектрометра весом до 2 кг [26]. Лекарство можно анализировать непосредственно в блистере (недеструктивно), время анализа составляет 5-10 секунд. Но, как и в ранее описанной масс-спектрометрии, полученные ИК-спектры нужно анализировать и здесь приходит на помощь хемометрика. В результате, такая гибридная технология позволяет быстро и эффективно осуществлять контроль качества препаратов на производстве, а также мониторинг фальсифицированных и недоброкачественных лекарственных средств, находящихся в обращении.

В заключение, хемоинформатика возникла как ответ на необходимость эффективного анализа огромного объема химических данных, который стал невозможен с использованием исключительно экспериментальных методов из-за их продолжительности, трудоемкости и дороговизны. Несмотря на споры о точности методов in silico, достижения хемоинформатики, особенно в области разработки лекарств, неоспоримы. Ожидается, что в ближайшее время мы увидим множество прорывов в молекулярных науках благодаря применению методов предсказательного моделирования.

Литература

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29 июн. 2024 г.

07.09.23 16:24 CherryTeam

Cherry Team atlyginimų skaičiavimo programa yra labai naudingas įrankis įmonėms, kai reikia efektyviai valdyti ir skaičiuoti darbuotojų atlyginimus. Ši programinė įranga, turinti išsamias funkcijas ir patogią naudotojo sąsają, suteikia daug privalumų, kurie padeda supaprastinti darbo užmokesčio skaičiavimo procesus ir pagerinti finansų valdymą. Štai keletas pagrindinių priežasčių, kodėl Cherry Team atlyginimų skaičiavimo programa yra naudinga įmonėms: Automatizuoti ir tikslūs skaičiavimai: Atlyginimų skaičiavimai rankiniu būdu gali būti klaidingi ir reikalauti daug laiko. Programinė įranga Cherry Team automatizuoja visą atlyginimų skaičiavimo procesą, todėl nebereikia atlikti skaičiavimų rankiniu būdu ir sumažėja klaidų rizika. Tiksliai apskaičiuodama atlyginimus, įskaitant tokius veiksnius, kaip pagrindinis atlyginimas, viršvalandžiai, premijos, išskaitos ir mokesčiai, programa užtikrina tikslius ir be klaidų darbo užmokesčio skaičiavimo rezultatus. Sutaupoma laiko ir išlaidų: Darbo užmokesčio valdymas gali būti daug darbo jėgos reikalaujanti užduotis, reikalaujanti daug laiko ir išteklių. Programa Cherry Team supaprastina ir pagreitina darbo užmokesčio skaičiavimo procesą, nes automatizuoja skaičiavimus, generuoja darbo užmokesčio žiniaraščius ir tvarko išskaičiuojamus mokesčius. Šis automatizavimas padeda įmonėms sutaupyti daug laiko ir pastangų, todėl žmogiškųjų išteklių ir finansų komandos gali sutelkti dėmesį į strategiškai svarbesnę veiklą. Be to, racionalizuodamos darbo užmokesčio operacijas, įmonės gali sumažinti administracines išlaidas, susijusias su rankiniu darbo užmokesčio tvarkymu. Mokesčių ir darbo teisės aktų laikymasis: Įmonėms labai svarbu laikytis mokesčių ir darbo teisės aktų, kad išvengtų baudų ir teisinių problemų. Programinė įranga Cherry Team seka besikeičiančius mokesčių įstatymus ir darbo reglamentus, užtikrindama tikslius skaičiavimus ir teisinių reikalavimų laikymąsi. Programa gali dirbti su sudėtingais mokesčių scenarijais, pavyzdžiui, keliomis mokesčių grupėmis ir įvairių rūšių atskaitymais, todėl užtikrina atitiktį reikalavimams ir kartu sumažina klaidų riziką. Ataskaitų rengimas ir analizė: Programa Cherry Team siūlo patikimas ataskaitų teikimo ir analizės galimybes, suteikiančias įmonėms vertingų įžvalgų apie darbo užmokesčio duomenis. Ji gali generuoti ataskaitas apie įvairius aspektus, pavyzdžiui, darbo užmokesčio paskirstymą, išskaičiuojamus mokesčius ir darbo sąnaudas. Šios ataskaitos leidžia įmonėms analizuoti darbo užmokesčio tendencijas, nustatyti tobulintinas sritis ir priimti pagrįstus finansinius sprendimus. Pasinaudodamos duomenimis pagrįstomis įžvalgomis, įmonės gali optimizuoti savo darbo užmokesčio strategijas ir veiksmingai kontroliuoti išlaidas. Integracija su kitomis sistemomis: Cherry Team programinė įranga dažnai sklandžiai integruojama su kitomis personalo ir apskaitos sistemomis. Tokia integracija leidžia automatiškai perkelti atitinkamus duomenis, pavyzdžiui, informaciją apie darbuotojus ir finansinius įrašus, todėl nebereikia dubliuoti duomenų. Supaprastintas duomenų srautas tarp sistemų padidina bendrą efektyvumą ir sumažina duomenų klaidų ar neatitikimų riziką. Cherry Team atlyginimų apskaičiavimo programa įmonėms teikia didelę naudą - automatiniai ir tikslūs skaičiavimai, laiko ir sąnaudų taupymas, atitiktis mokesčių ir darbo teisės aktų reikalavimams, ataskaitų teikimo ir analizės galimybės bei integracija su kitomis sistemomis. Naudodamos šią programinę įrangą įmonės gali supaprastinti darbo užmokesčio skaičiavimo procesus, užtikrinti tikslumą ir atitiktį reikalavimams, padidinti darbuotojų pasitenkinimą ir gauti vertingų įžvalgų apie savo finansinius duomenis. Programa Cherry Team pasirodo esanti nepakeičiamas įrankis įmonėms, siekiančioms efektyviai ir veiksmingai valdyti darbo užmokestį. https://cherryteam.lt/lt/
08.10.23 01:30 davec8080

The "Shibarium for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH. The Plot Thickens. Someone posted the actual transactions!!!! https://bscscan.com/tx/0xa846ea0367c89c3f0bbfcc221cceea4c90d8f56ead2eb479d4cee41c75e02c97 It seems the article is true!!!! And it's also FUD. Let me explain. Check this link: https://bscscan.com/token/0x5a752c9fe3520522ea88f37a41c3ddd97c022c2f So there really is a "Shibarium" token. And somebody did a rug pull with it. CONFIRMED. But the "Shibarium" token for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH.
24.06.24 04:31 tashandiarisha

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26.06.24 18:46 Jacobethannn098

LEGAL RECOUP FOR CRYPTO THEFT BY ADRIAN LAMO HACKER
26.06.24 18:46 Jacobethannn098

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04.07.24 04:49 ZionNaomi

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13.07.24 21:13 michaelharrell825

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17.07.24 02:26 thompsonrickey

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18.07.24 20:13 austinagastya

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27.08.24 12:50 James889900

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27.08.24 13:06 James889900

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02.09.24 20:24 [email protected]

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06.09.24 01:35 Celinagarcia

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06.09.24 01:44 Celinagarcia

HOW TO RECOVER MONEY LOST IN BITCOIN/USDT TRADING OR TO CRYPTO INVESTMENT !! Hi all, friends and families. I am writing From Alberton Canada. Last year I tried to invest in cryptocurrency trading in 2023, but lost a significant amount of money to scammers. I was cheated of my money, but thank God, I was referred to Hack Recovery Wizard they are among the best bitcoin recovery specialists on the planet. they helped me get every penny I lost to the scammers back to me with their forensic techniques. and I would like to take this opportunity to advise everyone to avoid making cryptocurrency investments online. If you have already lost money on forex, cryptocurrency or Ponzi schemes, please contact [email protected] or WhatsApp: +1 (757) 237–1724 at once they can help you get back the crypto you lost to scammers. BEST WISHES. Celina Garcia.
16.09.24 00:10 marcusaustin

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16.09.24 00:11 marcusaustin

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23.09.24 18:56 matthewshimself

At first, I was admittedly skeptical about Worldcoin (ref: https://worldcoin.org/blog/worldcoin/this-is-worldcoin-video-explainer-series), particularly around the use of biometric data and the WLD token as a reward mechanism for it. However, after following the project closer, I’ve come to appreciate the broader vision and see the value in the underlying tech behind it. The concept of Proof of Personhood (ref: https://worldcoin.org/blog/worldcoin/proof-of-personhood-what-it-is-why-its-needed) has definitely caught my attention, and does seem like a crucial step towards tackling growing issues like bots, deepfakes, and identity fraud. Sam Altman’s vision is nothing short of ambitious, but I do think he & Alex Blania have the chops to realize it as mainstay in the global economy.
01.10.24 14:54 Sinewclaudia

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02.10.24 22:27 Emily Hunter

Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.
18.10.24 09:34 freidatollerud

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31.10.24 00:13 ytre89

Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.
02.11.24 14:44 diannamendoza732

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