Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов
Приведен обзор и анализ возможностей применения технологии CUDA для ускорения расчетов в области структурной биологии и биоинформатики. На примере работы с программой HEX 6.1 выполнен сравнительный анализ прироста производительности и качества результатов жесткого докинга низкомолекулярных соединени...
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| Опубліковано в: : | Цитология и генетика |
|---|---|
| Дата: | 2012 |
| Автори: | , , |
| Формат: | Стаття |
| Мова: | Російська |
| Опубліковано: |
Інститут клітинної біології та генетичної інженерії НАН України
2012
|
| Теми: | |
| Онлайн доступ: | https://nasplib.isofts.kiev.ua/handle/123456789/126471 |
| Теги: |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов / О.Н. Демчук, П.А. Карпов, Я.Б. Блюм // Цитология и генетика. — 2012. — Т. 46, № 3. — С. 55-64. — Бібліогр.: 54 назв. — рос. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of Ukraine| _version_ | 1860246651869855744 |
|---|---|
| author | Демчук, О.Н. Карпов, П.А. Блюм, Я.Б. |
| author_facet | Демчук, О.Н. Карпов, П.А. Блюм, Я.Б. |
| citation_txt | Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов / О.Н. Демчук, П.А. Карпов, Я.Б. Блюм // Цитология и генетика. — 2012. — Т. 46, № 3. — С. 55-64. — Бібліогр.: 54 назв. — рос. |
| collection | DSpace DC |
| container_title | Цитология и генетика |
| description | Приведен обзор и анализ возможностей применения технологии CUDA для ускорения расчетов в области структурной биологии и биоинформатики. На примере работы с программой HEX 6.1 выполнен сравнительный анализ прироста производительности и качества результатов жесткого докинга низкомолекулярных соединений различных классов на поверхности FtsZ белка из Arabidopsis thaliana. Идентифицировано несколько потенциальных сайтов связывания бензимидазолов с растительным FtsZ.
Наводиться огляд та аналіз можливостей застосування технології CUDA для прискорення обчислень в галузі структурної біології та біоінформатики. На прикладі роботи з програмою Hex 6.1 здійснено порівняльний аналіз приросту продуктивності та якості результатів жорсткого докінгу низькомолекулярних сполук різних класів на поверхні FtsZ-білка із Arabidopsis thaliana. Ідентифіковано декілька потенційних сайтів зв’язування бензімідазолів із рослинним FtsZ.
The opportunities to apply the CUDA technology for faster computations in structural biology and bioinformatics are reviewed and analyzed. Using HEX 6.1 software, we performed a comparative analysis of the efficiency and the increase in quality after CUDA application. The work was conducted on the example of rigid docking of low-molecular-weight compounds of different classes on the surface of the Arabidopsis thaliana FtsZ. Several potential binding sites of benzimidazoles to the plant FtsZ were identified.
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| first_indexed | 2025-12-07T18:37:20Z |
| format | Article |
| fulltext |
55ISSN 0564–3783. Öèòîëîãèÿ è ãåíåòèêà. 2012. ¹ 3
УДК 577.112.7(577.332+004.42)
О.Н. ДЕМЧУК, П.А. КАРПОВ, Я.Б. БЛЮМ
Институт пищевой биотехнологии и геномики НАН Украины, Киев
E-mail: demom79@gmail.com
ДОКИНГ НИЗКОМОЛЕКУЛЯРНЫХ
ЛИГАНДОВ НА МОЛЕКУЛЕ
РАСТИТЕЛЬНОГО FtsZ-БЕЛКА:
ПРИМЕНЕНИЕ ТЕХНОЛОГИИ CUDA
ДЛЯ УСКОРЕНИЯ РАСЧЕТОВ
Ïðèâåäåí îáçîð è àíàëèç âîçìîæíîñòåé ïðèìå-
íåíèÿ òåõíîëîãèè CUDA äëÿ óñêîðåíèÿ ðàñ÷åòîâ â
îáëàñòè ñòðóêòóðíîé áèîëîãèè è áèîèíôîðìàòèêè.
Íà ïðèìåðå ðàáîòû ñ ïðîãðàììîé Hex 6.1 âûïîëíåí
ñðàâíèòåëüíûé àíàëèç ïðèðîñòà ïðîèçâîäèòåëüíîñ-
òè è êà÷åñòâà ðåçóëüòàòîâ æåñòêîãî äîêèíãà íèçêî-
ìîëåêóëÿðíûõ ñîåäèíåíèé ðàçëè÷íûõ êëàññîâ íà ïî-
âåðõíîñòè FtsZ áåëêà èç Arabidopsis thaliana. Èäåí-
òèôèöèðîâàíî íåñêîëüêî ïîòåíöèàëüíûõ ñàéòîâ ñâÿ-
çûâàíèÿ áåíçèìèäàçîëîâ ñ ðàñòèòåëüíûì FtsZ.
Ââåäåíèå. Ìîäåëèðîâàíèå ìåæìîëåêóëÿð-
íûõ âçàèìîäåéñòâèé ÿâëÿåòñÿ îäíîé èç íàè-
áîëåå âîñòðåáîâàííûõ âû÷èñëèòåëüíûõ çàäà÷
ñòðóêòóðíîé áèîèíôîðìàòèêè [1]. Òðàäèöèîí-
íî äëÿ ðàñ÷åòîâ òàêîãî òèïà ðåñóðñîçàòðàòíûõ
çàäà÷ in silico ïðèìåíÿþòñÿ âû÷èñëèòåëüíûå
ïëàòôîðìû, îñíîâàííûå íà èñïîëüçîâàíèè
êàê îäèíî÷íûõ CPU (Central Processing Unit), òàê
è ìíîãîïðîöåññîðíîé âû÷èñëèòåëüíîé ñðå-
äû (êëàñòåðíûå ðåøåíèÿ, ãðèä) [2, 3]. Ñðàâíè-
òåëüíî íåäàâíî, áëàãîäàðÿ ïîÿâëåíèþ òåõíî-
ëîãèé ðàñ÷åòîâ ñ èñïîëüçîâàíèåì ãðàôè÷åñêèõ
ïðîöåññîðîâ (GPU – Graphics Processing Unit)
[4] è, â ÷àñòíîñòè, òåõíîëîãèè CUDA (Com-
pute Unified Device Architecture), GPU âû÷èñ-
ëåíèÿ ñòàëè ïðèìåíÿòüñÿ äëÿ ðåøåíèÿ øè-
ðîêîãî ñïåêòðà íàó÷íûõ çàäà÷ [3], â òîì ÷èñ-
ëå äëÿ âûïîëíåíèÿ áèîèíôîðìàöèîííûõ è
ìîëåêóëÿðíî-áèîëîãè÷åñêèõ ðàñ÷åòîâ [5].Ýòî
ïîëîæèòåëüíî ñêàçàëîñü íà ñêîðîñòè ðåàëè-
çàöèè îòäåëüíûõ âû÷èñëèòåëüíûõ îïåðàöèé
è ïðèâåëî ê çíà÷èòåëüíîìó ñîêðàùåíèþ ðàñ-
÷åòíîãî âðåìåíè, íåîáõîäèìîãî äëÿ âûïîëíåíèÿ
ðÿäà àëãîðèòìîâ è áèîèíôîðìàöèîííûõ èñ-
ñëåäîâàíèé â öåëîì.
Òàê, ïðèìåíåíèå GPU äëÿ âûðàâíèâàíèÿ
ïîñëåäîâàòåëüíîñòåé ÄÍÊ è áåëêîâ ñîêðà-
ùàåò âðåìÿ ðàñ÷åòîâ ñ 10 [6, 7] äî 100 ðàç [8]
ïî ñðàâíåíèþ ñ ðàñ÷åòàìè, âûïîëíåííûìè
ïðè èñïîëüçîâàíèè öåíòðàëüíîãî ïðîöåññîðà
(CPU). Ïîêàçàíî, ÷òî ïðèìåíåíèå GPU ïî-
çâîëÿåò ñîêðàòèòü âðåìÿ, íåîáõîäèìîå äëÿ
âûïîëíåíèÿ ðàñ÷åòîâ ìîëåêóëÿðíîé äèíàìè-
êè â 10–100 ðàç [9, 10], êâàíòîâîé õèìèè äî
130 ðàç [11], à âåéâëåò-àíàëèçà ìàññ-ñïåêòðî-
ãðàôè÷åñêèõ äàííûõ – áîëåå ÷åì â 200 ðàç
[12]. Ïðèìåíåíèå GPU äëÿ ðàñ÷åòà äîñòóïíîé
ïîâåðõíîñòè áåëêà â 100–300 ðàç ñîêðàùàåò
âðåìÿ âû÷èñëåíèé â çàâèñèìîñòè îò ðàçìå-
ðîâ ìîäåëèðóåìîé ñèñòåìû [13].
Íåóäèâèòåëüíî, ÷òî êîëè÷åñòâî ïðèêëàä-
íûõ ïðîãðàìì, ïîääåðæèâàþùèõ âîçìîæ-
íîñòü ìîëåêóëÿðíûõ ðàñ÷åòîâ ñ ïðèìåíåíèåì
GPU, ñòðåìèòåëüíî âîçðàñòàåò [14]. Áåçóñëîâ-
íûì ëèäåðîì â îáëàñòè ðàçâèòèÿ òåõíîëîãèè
GPU âû÷èñëåíèé â íàñòîÿùåå âðåìÿ ÿâëÿåòñÿ
ôèðìà nVidia è ðàçðàáîòàííàÿ ýòîé êîìïàíèåé
òåõíîëîãèÿ CUDA [15]. Ïðàêòè÷åñêè ïîëíûé
ñïèñîê ïðèëîæåíèé, ïîääåðæèâàþùèõ òåõíî-
ëîãèþ CUDA, ïðåäñòàâëåí íà ñòðàíèöå «CUDA
Zone» îôèöèàëüíîãî web-ñàéòà êîìïàíèè
nVidia (http://www.nvidia.ru/).  íàñòîÿùåå âðå-© Î.Í. ÄÅÌ×ÓÊ, Ï.À. ÊÀÐÏÎÂ, ß.Á. ÁËÞÌ, 2012
56 ISSN 0564–3783. Öèòîëîãèÿ è ãåíåòèêà. 2012. ¹ 3
Î.Í. Äåì÷óê, Ï.À. Êàðïîâ, ß.Á. Áëþì
ìÿ ñïèñîê íàñ÷èòûâàåò áîëåå 20 ïðîãðàìì,
ïðåäíàçíà÷åííûõ äëÿ ðåøåíèÿ çàäà÷ áèîèí-
ôîðìàòèêè è ñòðóêòóðíîé áèîëîãèè.
Òàê, äëÿ îäíîãî èç íàèáîëåå âîñòðåáîâàííûõ
â áèîèíôîðìàòèêå èíñòðóìåíòîâ – BLAST
(The Basic Local Alignment Search Tool, NCBI-
BLAST www.ncbi.nlm.nih.gov) ïðåäñòàâëåíû
ðåøåíèÿ ñ ïîääåðæêîé òåõíîëîãèè CUDA:
GPU-BLAST (http://eudoxus.cheme.cmu.edu/
gpublast/), ðàáîòàþùèé â ÷åòûðå ðàçà áûñòðåå
ïðè èäåíòè÷íîñòè ðåçóëüòàòîâ ïîèñêà òðàäè-
öèîííîìó BLASTn [16], è CUDA-BLASTP
[17], ïðåäíàçíà÷åííûé äëÿ ñêàíèðîâàíèÿ
áîëüøèõ ìàññèâîâ àìèíîêèñëîòíûõ ïîñëåäî-
âàòåëüíîñòåé. Êðîìå òîãî, â ñîñòàâ óïîìÿ-
íóòûõ ðåøåíèé âõîäèò ïîäïðîãðàììà äëÿ
êîíâåðòàöèè ïîñëåäîâàòåëüíîñòåé â ôîðìàò,
êîòîðûé îïòèìèçèðîâàí äëÿ èñïîëüçîâàíèÿ
â ïðèëîæåíèÿõ BLAST, àäàïòèðîâàííûõ äëÿ
CUDA (http://www.nvidia.com/object/blastp_on_
tesla.html) [17].
Äðóãàÿ ïðîãðàììà, CUDASW++ (http://cu-
dasw.sourceforge.net/), ïðåäíàçíà÷åíà äëÿ ïî-
èñêà â áàçàõ äàííûõ àìèíîêèñëîòíûõ ïî-
ñëåäîâàòåëüíîñòåé ñ ïðèìåíåíèåì àëãîðèòìà
Ñìèòà-Âàòåðìàíà [18, 19]. Óñòàíîâëåíî, ÷òî
ïðè èñïîëüçîâàíèè ãðàôè÷åñêèõ óñêîðèòåëåé
NVIDIA GeForce (GTX 280 è GTX 295) âðåìÿ
ïîèñêà ñ ïîìîùüþ ïðîãðàììû CUDASW++
ñîêðàùàåòñÿ â 10–50 ðàç ïî ñðàâíåíèþ ñ
NCBI-BLAST [18].
Äëÿ òàêîé çàäà÷è, êàê ïîèñê êîíñåðâàòèâ-
íûõ ìîòèâîâ ïîñëåäîâàòåëüíîñòåé, íà îñíîâå
ïàêåòà MEME (V. 3.5.4) [20] ñîçäàíà âåðñèÿ
äëÿ CUDA – CUDA-MEME (mCUDA-
MEME) (http://www.nvidia.com/object/meme_
on_tesla.html) [21, 17].
Äëÿ îïòèìèçàöèè ðàñ÷åòîâ ñ èñïîëüçîâà-
íèåì ñêðûòûõ ìîäåëåé Ìàðêîâà (ÍÌÌ) ðàñ-
ïàðàëëåëèâàíèå íà GPU ðåàëèçîâàíî â ïðî-
ãðàììå GPU-HMMER (http://www.mpihmmer.
org/) (http://www.nvidia.com/object/hmmer_on_
tesla.html), ñêîðîñòü ðàáîòû êîòîðîé â 60–100
ðàç âûøå, ÷åì ó HMMER v.3.0 [22, 23].
Îäíàêî íàèáîëåå âîñòðåáîâàííîé òåõíî-
ëîãèÿ CUDA ÿâëÿåòñÿ â îáëàñòè ñòðóêòóð-
íîé áèîèíôîðìàòèêè [25], ãäå ñîñðåäîòî÷åíî
íàèáîëüøåå êîëè÷åñòâî ïðîãðàìì (NAMD
2.7 beta, VMD 1.8.7, Amber Alpha patch,
HOOMD 0.8.1, Autodock 0.9, CHARMM Beta,
GROMACS 4.0, LAMMPS Alpha è äð.),
ïðåäíàçíà÷åííûõ äëÿ ðåøåíèÿ ñòðóêòóðíûõ
ìîëåêóëÿðíî-áèîëîãè÷åñêèõ çàäà÷, òàêèõ êàê
ìîëåêóëÿðíîå ìîäåëèðîâàíèå, ìîëåêóëÿðíûé
äîêèíã, ñèìóëÿöèÿ ìîëåêóëÿðíîé äèíàìèêè
è ò.ä. [27–30]. Â 2007 ã. ãðóïïà èññëåäîâàòå-
ëåé èç óíèâåðñèòåòà Èëëèíîéñà â Óðáàíà-
Øàìïåéí (UIUC – «Biophysics Groupe») âû-
ïóñòèëà ïîïóëÿðíûé ïðîãðàììíûé ïàêåò äëÿ
ðàñ÷åòîâ ìîëåêóëÿðíîé äèíàìèêè NAMD ñ
ïîääåðæêîé òåõíîëîãèè CUDA (http://www.
ks.uiuc.edu/Research/gpu/) [31]. Ïðè îñóùå-
ñòâëåíèè ðàñ÷åòîâ ñ èñïîëüçîâàíèåì ïàêåòà
NAMD è ðåñóðñà NCSA ÷åòûðå ãðàôè÷åñêèõ
óñêîðèòåëÿ Tesla (http://www.nvidia.com/) ïðåâ-
çîøëè ïî âû÷èñëèòåëüíîé ìîùíîñòè êëàñòåð
èç 16 ÷åòûðåõúÿäåðíûõ CPU (http://www.ncsa.
illinois.edu/UserInfo/Resources/Hardware/Inte
l64TeslaCluster/).
 íàñòîÿùåå âðåìÿ ðåàëèçîâàíà èíòåãðà-
öèÿ NAMD ñ ïîïóëÿðíîé ïðîãðàììîé VMD
(«Biophysics Groupe» – www.ks.uiuc.edu/Re-
search/vmd/), ÷òî ïðè èñïîëüçîâàíèè CUDA
ïîçâîëÿåò îñóùåñòâëÿòü àíàëèç, 3D-âèçóàë-
çàöèþ è àíèìàöèþ áîëüøèõ ìîëåêóëÿðíûõ
ñèñòåì. VMD (Visual Molecular Dynamics)
òàêæå èìååò ïîääåðæêó CUDA ñ ðàñïàðàë-
ëåëèâàíèåì íà GPU îò nVidia. «Biophysics
Groupe» óäàëîñü èíòåãðèðîâàòü òåõíîëîãèþ
CUDA â ïðèëîæåíèÿ äëÿ ñèìóëÿöèè ìîëå-
êóëÿðíîé äèíàìèêè [32], îòîáðàæåíèÿ ìîëå-
êóëÿðíûõ îðáèòàëåé [26, 33], ðàñ÷åòû ïîçè-
öèðîâàíèÿ èîíîâ [9], ñèìóëÿöèþ êóëîíîâ-
ñêèõ âçàèìîäåéñòâèé [5] è îáðàáîòêó äàííûõ
ìèêðîñêîïèè [34]. Ýòî ïîçâîëèëî óâåëè÷èòü
ñêîðîñòü ðàáîòû ñîîòâåòñòâóþùèõ ïðèëîæå-
íèé îò 20 äî 100 ðàç (http://www.ks.uiuc.edu/
Research/gpu/).
Íåäàâíî áûëà ðàçðàáîòàíà CUDA-âåðñèÿ
ïàêåòà ñèëîâûõ ïîëåé AMBER (http://ambermd.
org/gpus/). Ïðèìåíåíèå GPU Tesla ïðè ìîäå-
ëèðîâàíèè ìîëåêóëÿðíîé äèíàìèêè â ïîëå
Amber äëÿ ñèñòåì ñ èñïîëüçîâàíèåì ÿâíîãî
è íåÿâíîãî ðàñòâîðèòåëÿ ðàñ÷åòíîå âðåìÿ ñî-
êðàùàëîñü áîëåå ÷åì â 10 ðàç ïî ñðàâíåíèþ ñ
ñåðâåðîì íà îñíîâå ÷åòûðåõúÿäåðíîãî CPU [35].
Ïàêåò ñèëîâûõ ïîëåé Gromacs (http://www.
gromacs.org/) ðàçðàáîòàí äëÿ ìîäåëèðîâàíèÿ
äèíàìèêè è ìèíèìèçàöèè ýíåðãèè áåëêîâ, íó-
êëåèíîâûõ êèñëîò è ëèïèäîâ, à òàêæå ïðåä-
57ISSN 0564–3783. Öèòîëîãèÿ è ãåíåòèêà. 2012. ¹ 3
Äîêèíã íèçêîìîëåêóëÿðíûõ ëèãàíäîâ íà ìîëåêóëå ðàñòèòåëüíîãî FtsZ-áåëêà
íàçíà÷åí äëÿ ìîäåëèðîâàíèÿ äèíàìèêè ìî-
ëåêóëÿðíûõ ñèñòåì, õàðàêòåðèçóþùèõñÿ áîëü-
øèì êîëè÷åñòâîì ñëîæíûõ âçàèìîäåéñòâèé
è ñâÿçåé. Íà÷èíàÿ ñ âåðñèè 4.5, â Gromacs
âêëþ÷åíà ïîääåðæêà CUDA [36]. Íåñìîòðÿ íà
íåêîòîðûå îãðàíè÷åíèÿ (ðàçìåð àíàëèçèðóå-
ìîé ñèñòåìû íå áîëåå 200 000 àòîìîâ, çà-
âèñèìîñòü îò òèïà/ìîäåëè ãðàôè÷åñêîé êàðòû,
ñîâìåñòèìîñòü RAM) (http://www.gromacs.org/
Downloads/Installation_Instructions/GPUs)
ïî ñðàâíåíèþ ñ ðàñ÷åòàìè íà CPU, ðåøåíèå
Gromacs äëÿ GPU ïîçâîëÿåò çíà÷èòåëüíî ñî-
êðàòèòü âðåìÿ ðàñ÷åòîâ [36, 37]. Ñëåäóåò
îòìåòèòü, ÷òî ïðè èñïîëüçîâàíèè CUDA ìî-
ãóò íàáëþäàòüñÿ íåçíà÷èòåëüíûå îòëè÷èÿ â
ðåçóëüòàòàõ ðàñ÷åòîâ, âûïîëíåííûõ ñ ïîìî-
ùüþ ðàçíûõ ãðàôè÷åñêèõ óñêîðèòåëåé, ÷òî
ñâÿçàíî ñ èçìåíåíèÿìè, âíåñåííûìè â ðàáîòó
ðÿäà àëãîðèòìîâ ñ öåëüþ àäàïòàöèè ðàáîòû
Gromacs íà GPU [36].
Òàêèì îáðàçîì, â íàñòîÿùåå âðåìÿ òåõíî-
ëîãèè âû÷èñëåíèé ñ ïðèìåíåíèåì ãðàôè÷åñ-
êèõ ïðîöåññîðîâ âûõîäÿò íà íîâûé óðîâåíü
èíòåãðàöèè ñ óæå ñóùåñòâóþùèìè òåõíîëî-
ãèÿìè ñóïåðêîìïüþòèíãà (êëàñòåðíûå òåõíî-
ëîãèè, ãðèä). Ñåé÷àñ â ìèðå ñóùåñòâóþò áîëåå
700 êëàñòåðîâ, ðàáîòàþùèõ íà îñíîâàíèè GPU
(http://www.nvidia.ru/object/what_is_cuda_
new_ru.html). Óäà÷íûì ïðèìåðîì òàêîé âû-
÷èñëèòåëüíîé èíôðàñòðóêòóðû, èñïîëüçóþùåé
ïðåèìóùåñòâà ãðàôè÷åñêèõ àäàïòåðîâ ñ ïîä-
äåðæêîé òåõíîëîãèè CUDA â ñî÷åòàíèè ñ
òåõíîëîãèåé ãðèä, ÿâëÿåòñÿ ïðîåêò GPUGRID.
net (http://www.gpugrid.net/) [38], ïðåäñòàâ-
ëåííûé ðàñïðåäåëåííûìè âû÷èñëèòåëüíûìè
ðåñóðñàìè GPU ñåðâåðîâ, êîòîðûå îñíàùåíû
ãðàôè÷åñêèìè ïðîöåññîðàìè îò nVidia (â òîì
÷èñëå âû÷èñëèòåëüíûõ ðåñóðñîâ ïîëüçîâàòå-
ëåé ïðîåêòà). Ïðîåêò ïðåäíàçíà÷åí äëÿ âû-
ïîëíåíèÿ ðåñóðñîçàòðàòíûõ ðàñ÷åòîâ ìîäåëè-
ðîâàíèÿ ïîëíîàòîìíûõ ìàêðîìîëåêóëÿðíûõ
ñèñòåì, ðåøåíèÿ âîïðîñîâ ìîëåêóëÿðíîé áèî-
ëîãèè, áèîèíôîðìàòèêè, ìåäèöèíû, ìàòåðèà-
ëîâåäåíèÿ [38], è ïðåäîñòàâëÿåò èññëåäîâà-
òåëÿì íîâûé êëàññ îòíîñèòåëüíî íåäîðîãèõ,
íî íå ìåíåå ýôôåêòèâíûõ ñóïåðêîìïüþòåðîâ.
Âàæíîé îáëàñòüþ ñòðóêòóðíîé áèîëîãèè è
áèîèíôîðìàòèêè ÿâëÿåòñÿ ìîäåëèðîâàíèå
ìåæìîëåêóëÿðíûõ âçàèìîäåéñòâèé, èëè ìîëå-
êóëÿðíûé äîêèíã (ñòûêîâêà). Áóäó÷è íåîòúåì-
ëåìûì ýòàïîì ðàöèîíàëüíîãî äèçàéíà íîâûõ
ëåêàðñòâåííûõ ïðåïàðàòîâ, áèîëîãè÷åñêè àê-
òèâíûõ âåùåñòâ, ðåêîíñòðóêöèè ñòðóêòóðû
ìàêðîìîëåêóëÿðíûõ êîìïëåêñîâ è ìåõàíèç-
ìîâ èõ ôîðìèðîâàíèÿ [30], ìîëåêóëÿðíûé
äîêèíã ÿâëÿåòñÿ íàáîðîì ñëîæíûõ ðàñ÷åòîâ
(àëãîðèòìîâ) âçàèìîäåéñòâèé 3D-ñòðóêòóð áå-
ëîê-áåëêîâûõ èëè ëèãàíä-áåëêîâûõ êîìïëåê-
ñîâ, íà÷èíàÿ ñ ìîäåëèðîâàíèÿ îòäåëüíûõ íå-
ñâÿçàííûõ ñòðóêòóð ñîîòâåòñòâóþùèõ áåëêîâ
è ëèãàíäîâ [39]. Ýòî òðåáóåò ïðèìåíåíèÿ çíà-
÷èòåëüíûõ âû÷èñëèòåëüíûõ ðåñóðñîâ, òàêèõ
êàê ñóïåðêîìïüþòåðû è ðàñïàðàëëåëåííûå âû-
÷èñëèòåëüíûå ñèñòåìû [40].  íàñòîÿùåå âðå-
ìÿ èìåþòñÿ íåñêîëüêî ïðèìåðîâ óñïåøíî-
ãî ïðèìåíåíèÿ GPU äëÿ ñîêðàùåíèÿ âðåìåíè
âûïîëíåíèÿ äîêèíãà [41–43]. Òàê, åñòü äàííûå
îá óñïåøíîì ïðèìåíåíèè CUDA äëÿ îïòèìè-
çàöèè ðàáîòû ïðîãðàììû AutoDock [43; http://
www.vpac.org/files/OptimizingAutodockwith
CUDA.pdf] (www.gpuautodock.sf.net), ðàáîòàþ-
ùåé íà îñíîâå Ëàìàðêîâñêîãî ãåíåòè÷åñêîãî
àëãîðèòìà (LGA) [45].
Äðóãèì ïðèìåðîì ÿâëÿåòñÿ ïàêåò Hex
(http://hex.loria.fr/), ïðåäíàçíà÷åííûé äëÿ âû-
ïîëíåíèÿ è âèçóàëèçàöèè ðåçóëüòàòîâ ãèáêî-
ãî ìîëåêóëÿðíîãî äîêèíãà áåëêîâ è ÄÍÊ, à
òàêæå æåñòêîãî äîêèíãà íèçêîìîëåêóëÿðíûõ
ëèãàíäîâ è áåëêîâûõ ìèøåíåé [42, 43] íà
îñíîâå ïðèìåíåíèÿ ïîëÿðíîãî àëãîðèòìà áûñ-
òðûõ ïðåîáðàçîâàíèé Ôóðüå (FFT) [43]. Íà-
÷èíàÿ ñ âåðñèè 6.0, â ïàêåò Hex âêëþ÷åíà
ïîääåðæêà òåõíîëîãèè CUDA [42, 43].
Ïîýòîìó öåëüþ íàøåãî èññëåäîâàíèÿ ñòàë
àíàëèç ðåàëüíîãî ïðèðîñòà ñêîðîñòè âû÷èñ-
ëåíèé è ïðîèçâîäèòåëüíîñòè äîêèíãà çà ñ÷åò
GPU-îïòèìèçàöèè ðàáîòû ñôåðè÷åñêîãî
ïîëÿðíîãî àëãîðèòìà ïðåîáðàçîâàíèé Ôóðüå,
ÿâëÿþùåãîñÿ îñíîâíûì ðåñóðñîçàòðàòíûì
ýòàïîì ðàñ÷åòîâ ìîëåêóëÿðíîé ñòûêîâêè â
ïðîãðàììå Hex [43], ïðè èñïîëüçîâàíèè CUDA
âåðñèè ïðîãðàììíîãî ïàêåòà Hex 6.1 íà ïðè-
ìåðå äîêèíãà òðåõìåðíûõ ìîäåëåé íèçêîìî-
ëåêóëÿðíûõ ñîåäèíåíèé êëàññîâ áåíçèìèäà-
çîëîâ, äèíèòðîàíèëèíîâ è ôåíèëêàðáàìàòîâ
íà ìîäåëè öèòîçîëüíîé ôîðìû ðàñòèòåëüíîãî
áåëêà FtsZ2-2 (UniProt: Q9LXJ0, At3g52750)
èç Arabidopsis thaliana [46].
Ìàòåðèàëû è ìåòîäû. Ìîëåêóëÿðíûé äî-
êèíã îñóùåñòâëÿëè ñ èñïîëüçîâàíèåì ðàíåå
58 ISSN 0564–3783. Öèòîëîãèÿ è ãåíåòèêà. 2012. ¹ 3
Î.Í. Äåì÷óê, Ï.À. Êàðïîâ, ß.Á. Áëþì
ðåêîíñòðóèðîâàííîé íàìè ìîäåëè öèòîçîëü-
íîé ôîðìû ðàñòèòåëüíîãî áåëêà FtsZ2-2 èç
Arabidopsis thaliana [47] è òðåõìåðíûõ ìîäå-
ëåé íèçêîìîëåêóëÿðíûõ ñîåäèíåíèé êëàññà
áåíçèìèäàçîëîâ – áåíîìèëà (ìåòèë-N-[1-(áó-
òèëêàðáàìîèë)áåíçèìèäàçîë-2-èë]êàðáà-
ìàò) (CID: 28780), íîêîäàçîëà (ìåòèë-N-[6-
(òèîôåí-2-êàðáîíèë)-1H-áåíçèìèäàçîë-
2-èë]êàðáàìàò) (CID: 4122) è ÷åòûðåõ 2,5,6-òðåõ-
çàìåùåííûõ áåíçèìèäàçîëîâ, êîòîðûå îêà-
çàëèñü ëèäåðàìè ïî àíòèáàêòåðèàëüíîé àê-
òèâíîñòè â èññëåäîâàíèÿõ ãðóïïû È. Îäæèìû –
1a-G4, 1a-G7, 1b-G1 è 1b-G2 [48], à òàêæå
ïðåäñòàâèòåëåé äèíèòðîàíèëèíîâ: îðèçàëèíà
(4-(äèïðîïèëàìèíî)-3,5-äèíèòðîáåíçåí-
ñóëüôîíàìèä) (CID: 29393), ïåíäèìåòàëèíà
(3,4-äèìåòèë-2,6-äèíèòðî-N-ïåíòàí-3-èëà-
íèëèí) (CID: 38479), òðèôëþðàëèíà (2,6-äè-
íèòðî-N,N-äèïðîïèë-4-(òðèôòîðìåòèë)
àíèëèí) (CID: 5569) è ýòàëôëþðàëèíà (N-ýòèë-
N-(2-ìåòèëïðîï-2-ýíèë)-2,6-äèíèòðî-4-
(òðèôòîðìåòèë)àíèëèí) (CID: 41381) è ñîåäè-
íåíèé êëàññà ôîñôîðîàìèäîâ – àìèïðîôîñ-
ìåòèëà (N-[ìåòîêñè-(4-ìåòèë-2-íèòðîôåíîê-
ñè)ôîñôèíîòèîë]-ïðîïàí-2-àìèí) (CID: 100524)
è êðåìàðòà (N-[ýòîêñè-(5-ìåòèë-2-íèòðîôåíîê-
ñè)ôîñôèíîòèîë]áóòàí-2-àìèí) (CID: 37419).
Èñõîäíûå ìîäåëè ïðîñòðàíñòâåííûõ ñòðóê-
òóð ãåðáèöèäîâ âçÿòû èç ðåïîçèòîðèÿ áàçû
äàííûõ «PubChemCompound» (NCBI – http://
www.ncbi.nlm.nih.gov/pccompound/) [49]. Ôàé-
ëû êîîðäèíàò òðåõçàìåùåííûõ áåíçèìèäàçî-
ëîâ, êàê è ôàéëû òîïîëîãèè âñåõ èñïîëü-
çóåìûõ ëèãàíäîâ, ïîëó÷åíû ñ ïîìîùüþ ñåð-
âåðà PRODRG2 (http://davapc1.bioch.dundee.
ac.uk/prodrg/) [50].
Âû÷èñëèòåëüíûé ñåðâåð ñîáðàëè íà îñíîâå
ìàòåðèíñêîé ïëàòû ASUS P5K-SE/EPU (www.
asus.com), ïîñòðîåííîé íà ÷èïñåòå Intel P35
(www.intel.com) ïëàòôîðìû LGA775 (FC-
LGA6), ñ èíñòàëëÿöèåé 4 Ãá îïåðàòèâíîé ïà-
ìÿòè Kingston DDR2-SDRAM 400 ÌÃö. Â
êà÷åñòâå CPU èñïîëüçîâàëè öåíòðàëüíûé ïðî-
öåññîð Intel Core 2 Quad Q6600 (2400 ÌÃö),
èìåþùèé ÷åòûðå ëîãè÷åñêèõ ÿäðà ñ îáúåìàìè
êýøåé L1 êîäà, L1 äàííûõ è L2, ðàâíûìè
32 Êá, 32 Êá è 2×4096 Ìá ñîîòâåòñòâåííî,
è ïîääåðæèâàþùèé íàáîðû èíñòðóêöèé
x86, x86-64, MMX, SSE, SSE2, SSE3, SSSE3
(http://ark.intel.com/).
Ïðè âûïîëíåíèè ìîëåêóëÿðíûõ ðàñ÷åòîâ
èñïîëüçîâàëè âèäåîàäàïòåðû ASUS EN9800GT
(www.asus.com) è ZOTAC GeForce GTX 470
(www.zotac.com), ðàáîòàþùèå â ïðîãðàììíîé
ñðåäå 32-áèòíîé âåðñèè ïàêåòà äëÿ ðàçðà-
áîò÷èêîâ «cudatoolkit 3.2.7 win32» è «cuda-
toolkit 3.2.16 win32» ñîîòâåòñòâåííî. Âèäåî-
àäàïòåð ASUS EN9800GT ïîñòðîåí íà ÷èïñåòå
nVIDIA GeForce® 9800 GT è îñíàùåí 512 Má
îïåðàòèâíîé ïàìÿòè GDDR3 SDRAM ñ ðàç-
ðÿäíîñòüþ 256-áèò. ×àñòîòà ïàìÿòè ñîñòàâëÿåò
1800 ÌÃö ñ ïîëîñîé ïðîïóñêàíèÿ 57,6 Ãá/ñ.
Ýòà âèäåîêàðòà èìååò 112 Stream-ïðîöåññî-
ðîâ, õàðàêòåðèçóåòñÿ ÷àñòîòîé ÿäðà 1200 ÌÃö
è ÷àñòîòîé øåéäåðíîãî áëîêà 1500 ÌÃö ñî
ñêîðîñòüþ íàëîæåíèÿ òåêñòóð 33,6 ìëðä òåê-
ñåëåé çà 1 ñ. Âèäåîàäàïòåð ZOTAC GeForce
GTX 470 ïîñòðîåí íà ÷èïñåòå nVIDIA
GeForce® GTX 470 è îñíàùåí 1280 Má îïå-
ðàòèâíîé ïàìÿòè GDDR5 SDRAM ñ ðàç-
ðÿäíîñòüþ 320-áèò, êîòîðàÿ ðàáîòàåò íà ÷àñ-
òîòå 3348 ÌÃö ñ ïðîïóñêíîé ñïîñîáíîñòüþ
133,9 Ãá/ñ. Âèäåîêàðòà èìååò 448 Stream-
ïðîöåññîðîâ, ðàáîòàþùèõ íà ÷àñòîòå 1215 ÌÃö
ñî ñêîðîñòüþ íàëîæåíèÿ òåêñòóð 34 ìëðä òåê-
ñåëåé çà 1 ñ.
Äîêèíã íèçêîìîëåêóëÿðíûõ ñîåäèíåíèé
ðàññ÷èòûâàëè ïóòåì ïîî÷åðåäíîãî èñïîëüçî-
âàíèÿ âû÷èñëèòåëüíûõ ìîùíîñòåé öåíòðàëü-
íîãî ïðîöåññîðà (CPU ðåæèì) è âèäåîàäàï-
òåðîâ (GPU ðåæèì), óñòàíîâëåííûõ íà óêà-
çàííóþ ïëàòôîðìó.
Æåñòêèé äîêèíã [51] âûïîëíÿëè ñ èñïîëü-
çîâàíèåì ïðîãðàììíîãî ïàêåòà Hex 6.1 (http://
hex.loria.fr/) [43, 52] ïðè ïîääåðæêå òåõíî-
ëîãèè CUDA (http://www.nvidia.com/), êîòî-
ðûé ïîçâîëÿåò ïðîâîäèòü âû÷èñëåíèÿ êàê â
CPU, òàê è â GPU ðåæèìàõ [43]. Ïðè âû-
ïîëíåíèè ðàñ÷åòîâ âî âñåõ âàðèàíòàõ èñ-
ïîëüçîâàëè ñòàíäàðòíûé íàáîð ïàðàìåòðîâ
êîíòðîëÿ (ïóíêò «Docking» èç ìåíþ «Con-
trols»): Correlation Type – Shape + Electrostatic;
FFT Mode – 3D; Post Processing – None; Grid
Dimensions – 0.5 Å; Distance Range – 60 Å;
Scan Step – 0.5 Å; Solutions – 500. Ïàðà-
ìåòð FFT Mode-3D ñâèäåòåëüñòâóåò îá èñ-
ïîëüçîâàíèè â ïðîöåññå äîêèíãà àëãîðèòìà
áûñòðîãî ïðåîáðàçîâàíèÿ Ôóðüå (FFT – fast
Fourier transform) â ðåæèìå òðåõìåðíîé êîð-
ðåëÿöèè ïî ôîðìå è ýëåêòðîñòàòè÷åñêîìó
59ISSN 0564–3783. Öèòîëîãèÿ è ãåíåòèêà. 2012. ¹ 3
Äîêèíã íèçêîìîëåêóëÿðíûõ ëèãàíäîâ íà ìîëåêóëå ðàñòèòåëüíîãî FtsZ-áåëêà
âçàèìîäåéñòâèþ. Óñòàíîâêè ïàðàìåòðà Solu-
tions ïîçâîëÿþò ñîõðàíÿòü èíôîðìàöèþ î
ïåðâûõ 500 îðèåíòàöèÿõ ëèãàíäà [42, 53].
Îñòàëüíûå ïàðàìåòðû ïàêåòà Hex èñïîëüçî-
âàëè â ðåæèìå ïî óìîë÷àíèþ (http://hex.loria.
fr/manual/hex_manual.html).
Ðåçóëüòàòû èññëåäîâàíèé è èõ îáñóæäåíèå.
Âëèÿíèå àïïàðàòíîé ïëàòôîðìû íà ñêîðîñòü
ìîëåêóëÿðíûõ âû÷èñëåíèé. Àíàëèç ëîã-ôàé-
ëîâ ïðîöåññà äîêèðîâàíèÿ â ïðîãðàììå Hex
6.1 ïîçâîëÿåò âûäåëèòü äâà îñíîâíûõ ýòàïà,
êîòîðûå â ñâîþ î÷åðåäü ìîæíî ðàçäåëèòü
åùå íà íåñêîëüêî ïîäýòàïîâ.  òå÷åíèå ïåð-
âîãî ýòàïà ïðîèñõîäèò êîíòóðèðîâàíèå ïî-
âåðõíîñòåé ìîëåêóë áåëêà-ìèøåíè (FtsZ2-2
èç Arabidopsis thaliana) è ëèãàíäà, îòáîð ïî-
âåðõíîñòåé ìîëåêóë, èõ âíóòðåííèõ îáúåìîâ,
à òàêæå ÷åòûðåõêðàòíûé ðàñ÷åò êîýôôèöèåí-
òîâ ïîâåðõíîñòåé ïðè ñòàíäàðòíîì çíà÷åíèè
(N = 25) óðîâíÿ ïðîñòðàíñòâåííîé (3D) äå-
òàëèçàöèè.
Âòîðîé ýòàï çàêëþ÷àåòñÿ â ïîèñêå âîç-
ìîæíûõ ïðîñòðàíñòâåííûõ îðèåíòàöèé ëè-
ãàíäà îòíîñèòåëüíî ïîâåðõíîñòè áåëêà ñ èñ-
ïîëüçîâàíèåì 3D àëãîðèòìà áûñòðûõ ïðå-
îáðàçîâàíèé Ôóðüå (3D FFT) [43] è îöåíêå
êàæäîé èç ñãåíåðèðîâàííûõ êîíôîðìàöèé ëè-
ãàíäà â ñîñòàâå êîìïëåêñà. Ïîñëåäóþùèé ïðî-
öåññ âêëþ÷àåò ðàñ÷åò êîýôôèöèåíòà âåêòîðà
ðîòàöèè, çàïóñê ïðîöåññà âåðèôèêàöèè è îöåí-
êó âûáîðêè êîíôîðìàöèé, ïîëó÷åííûõ â ðå-
çóëüòàòå ðàáîòû àëãîðèòìà îäíîìåðíûõ (1-D)
áûñòðûõ ïðåîáðàçîâàíèé Ôóðüå (1D FFT) [43].
Íà ãèñòîãðàììå ïîêàçàíî âðåìÿ âûïîëíå-
íèÿ (ýòàïû) äîêèíãà ïðè èñïîëüçîâàíèè ðàç-
íûõ àïïàðàòíûõ ïëàòôîðì êàê ñ èñïîëüçîâà-
íèåì ÿäåð öåíòðàëüíîãî ïðîöåññîðà (CPU),
òàê è ãðàôè÷åñêèõ óñêîðèòåëåé (GPU) ðàçíûõ
ïîêîëåíèé. Îñíîâíîå âðåìÿ âûïîëíåíèÿ ïåð-
âîãî ýòàïà ïðèõîäèòñÿ íà ðàñ÷åò êîýôôè-
öèåíòîâ ïîâåðõíîñòåé, ïîñêîëüêó ïðåäøåñò-
âóþùèå ïîäãîòîâèòåëüíûå ñòàäèè äëÿòñÿ î÷åíü
êîðîòêèé ïðîìåæóòîê âðåìåíè – ïîðÿäêà íå-
ñêîëüêèõ ñåêóíä – è íå âíîñÿò ñóùåñòâåííîãî
âêëàäà â îáùåå âðåìÿ ðàñ÷åòà äîêèíãà. Óñòà-
íîâëåíî, ÷òî âûïîëíåíèå îòäåëüíûõ ñòàäèé
ïåðâîãî ýòàïà õàðàêòåðèçóåòñÿ îäèíàêîâîé
äëèòåëüíîñòüþ êàê ïðè ðàñ÷åòàõ íà CPU, òàê
è GPU. Ó÷èòûâàÿ íåçíà÷èòåëüíóþ îáùóþ
ïðîäîëæèòåëüíîñòü ïåðâîãî ýòàïà ïî ñðàâíå-
íèþ ñî âòîðûì (â ñðåäíåì 35 ñ ïðîòèâ 30–35
ìèí â ñëó÷àå ñ CPU è 2–4 ìèí â ñëó÷àå ñ
GPU), ìîæíî ñäåëàòü âûâîä îá îòñóòñòâèè ñó-
ùåñòâåííûõ ïðåèìóùåñòâ èñïîëüçîâàíèÿ ãðà-
ôè÷åñêèõ ïðîöåññîðîâ ïðè ïðîâåäåíèè ðàñ÷å-
òîâ íà ïåðâîì ýòàïå äîêèíãà.
Êàê áûëî îòìå÷åíî, âòîðîé ýòàï (ðèñó-
íîê) ïðåäñòàâëåí äâóìÿ ïîäýòàïàìè: 1) ïî-
Ñðàâíåíèå äëèòåëüíîñòè âûïîëíåíèÿ îòäåëüíûõ îïåðàöèé ñ ïîìîùüþ ïðîãðàììíîãî ïàêåòà Hex 6.1 âî
âðåìÿ ðàñ÷åòîâ äîêèíãà íèçêîìîëåêóëÿðíûõ ëèãàíäîâ íà ìîëåêóëå FtsZ áåëêà ñ èñïîëüçîâàíèåì âû-
÷èñëèòåëüíîé ìîùíîñòè ÿäðà öåíòðàëüíîãî ïðîöåññîðà (CPU) è ÿäåð ãðàôè÷åñêèõ óñêîðèòåëåé (GPU):
ïî âåðòèêàëè – âðåìÿ ðàñ÷åòà, ñ; ïî ãîðèçîíòàëè – ãåðáèöèäû; 1 – GPU; 2 – GPU 9800GT; 3 – GPU
470GTX
60 ISSN 0564–3783. Öèòîëîãèÿ è ãåíåòèêà. 2012. ¹ 3
Î.Í. Äåì÷óê, Ï.À. Êàðïîâ, ß.Á. Áëþì
Ðåçóëüòàòû äîêèíãà íèçêîìîëåêóëÿðíûõ ëèãàíäîâ
íà ìîëåêóëå ðàñòèòåëüíîãî FtsZ-áåëêà
Ïðèìå÷àíèå. Eìèí – ýëåêòðîñòàòè÷åñêàÿ ýíåðãèÿ íàèëó÷øåé îðèåíòàöèè ëèãàíäà íà ïîâåðõíîñòè áåë-
êà-ìèøåíè, Eìàêñ – ýëåêòðîñòàòè÷åñêàÿ ýíåðãèÿ íàèõóäøåé èç 500 îðèåíòàöèé ëèãàíäà.
Ëèãàíä Óñòðîéñòâî ðàñ÷åòà
Îáùåå âðåìÿ
äîêèíãà
Êîëè÷åñòâî
íàèëó÷øèõ
îðèåíòàöèé
Åìèí Åìàêñ Êîëè÷åñòâî
íàéäåííûõ
êëàñòåðîâêÄæ/ìîëü
Áåíçèìèäàçîëû
Áåíîìèë
Íîêîäàçîë
1a-G4
1a-G7
1b-G1
1b-G2
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
34 ìèí, 35 ñ
4 ìèí, 30 ñ
2 ìèí, 21 ñ
33 ìèí, 43 ñ
4 ìèí, 02 ñ
2 ìèí, 19 ñ
32 ìèí, 10 ñ
3 ìèí, 47 ñ
2 ìèí, 17 ñ
31 ìèí, 8 ñ
3 ìèí, 33 ñ
2 ìèí, 10 ñ
31 ìèí, 31 ñ
3 ìèí, 36 ñ
2 ìèí, 11 ñ
32 ìèí, 17 ñ
3 ìèí, 56 ñ
2 ìèí, 16 ñ
1782
1681
1685
970
940
1002
3863
3501
3503
3110
2894
2899
2534
2419
2423
2605
2477
2479
–167,6
–167,6
–167,6
–188,1
–188,1
–183,0
–220,1
–220,1
–220,1
–206,4
–206,4
–206,4
–213,3
–213,3
–213,3
–226,6
–226,6
–226,6
–119,1
–119,7
–119,7
–140,0
–140,1
–140,0
–146,6
–115,48
–115,48
–154,5
–155,4
–155,4
–151,6
–152,1
–152,1
–160,5
–161,1
–161,1
103
102
102
55
56
56
113
113
113
116
116
116
139
139
139
126
126
126
Äèíèòðîàíèëèíû
Îðèçàëèí
Ïåíäèìåòàëèí
Òðèôëþðàëèí
Ýòàëôëþðàëèí
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
30 ìèí, 56 ñ
3 ìèí, 42 ñ
2 ìèí, 08 ñ
31 ìèí, 58 ñ
4 ìèí, 33 ñ
2 ìèí, 11 ñ
34 ìèí, 51 ñ
4 ìèí, 18 ñ
2 ìèí, 43 ñ
30 ìèí, 04 ñ
3 ìèí, 42 ñ
2 ìèí, 05 ñ
9718
4980
4979
3937
3130
3133
1478
1424
1429
1490
1430
1433
–293,1
–293,1
–293,1
–161,6
–161,6
–161.6
–193,6
–193,6
–193,6
–184,0
–184,0
–184,0
–186,4
–202,0
–202,0
–114,9
–116,5
–116,5
–147,2
–147,4
–147,4
–144,1
–144,6
–144,5
78
78
78
81
81
81
44
44
44
59
59
59
Ôîñôîðîàìèäû
Àìèïðîôîñìåòèë
Êðåìàðò
CPU
GPU 9800GT
GPU 470GTX
CPU
GPU 9800GT
GPU 470GTX
34 ìèí, 25 ñ
4 ìèí, 34 ñ
2 ìèí, 26 ñ
29 ìèí, 58 ñ
4 ìèí, 01 ñ
2 ìèí, 51 ñ
6798
4673
4675
218
193
194
–209,8
–209,8
–209,8
–147,8
–147,8
–147,8
–141,5
–147,2
–147,2
–120,8
–121,9
–121,9
65
65
65
8
7
7
61ISSN 0564–3783. Öèòîëîãèÿ è ãåíåòèêà. 2012. ¹ 3
Äîêèíã íèçêîìîëåêóëÿðíûõ ëèãàíäîâ íà ìîëåêóëå ðàñòèòåëüíîãî FtsZ-áåëêà
èñê ïî 3-D àëãîðèòìó áûñòðûõ ïðåîáðà-
çîâàíèé Ôóðüå (3D FFT); 2) îöåíêà îðèåí-
òàöèé ëèãàíäà ïî àëãîðèòìó îäíîìåðíûõ áûñ-
òðûõ ïðåîáðàçîâàíèé Ôóðüå (1D FFT). Èç-çà
íåçíà÷èòåëüíîé ïðîäîëæèòåëüíîñòè (â ïðåäå-
ëàõ äî 2 ñ êàê äëÿ CPU, òàê è äëÿ îáåèõ GPU)
ïðè ïîñòðîåíèè ãèñòîãðàììû âðåìÿ ðàñ÷åòà
êîýôôèöèåíòîâ âåêòîðîâ ðîòàöèè áûëî èñ-
êëþ÷åíî. Íà îñíîâàíèè àíàëèçà ðåçóëüòàòîâ
ðàñ÷åòîâ íàìè ñäåëàí âûâîä î òîì, ÷òî íàè-
áîëåå ïðîäîëæèòåëüíîé è ðåñóðñîçàòðàòíîé
ñòàäèåé ðàñ÷åòà äîêèíãà ÿâëÿåòñÿ 3D FFT-
ïîèñê. Ïðè èñïîëüçîâàíèè CUDA èìåííî íà
ýòîé ñòàäèè äîêèíãà ðÿäà íèçêîìîëåêóëÿðíûõ
ñîåäèíåíèé íà ìîëåêóëå ðàñòèòåëüíîãî áåëêà
FtsZ2-2 èç A. thaliana ïðîèñõîäèò çíà÷è-
òåëüíûé ïðèðîñò ïðîèçâîäèòåëüíîñòè ðàñ÷å-
òîâ çà ñ÷åò ñóùåñòâåííîãî (â ñðåäíåì â
8 ðàç) ñîêðàùåíèÿ âðåìåíè ðàñ÷åòà. Òàê, ïðè
èñïîëüçîâàíèè öåíòðàëüíîãî ïðîöåññîðà îá-
ùåå âðåìÿ ðàñ÷åòà äîêèíãà ñîñòàâëÿåò îò 30
äî 35 ìèí, òîãäà êàê èñïîëüçîâàíèå ðåæèìà
CUDA ñîêðàùàåò ýòî âðåìÿ äî 2–4,5 ìèí â
çàâèñèìîñòè îò èñïîëüçóåìîãî âèäåîàäàïòåðà.
Íåñìîòðÿ íà òî, ÷òî êîëè÷åñòâî ïðîöåññîðîâ â
÷èïñåòå 470GTX â 4 ðàçà áîëüøå, ÷åì â ÷èïñåòå
9800GT, ïåðåõîä íà áîëåå íîâûé ãðàôè÷åñ-
êèé óñêîðèòåëü îáåñïå÷èâàåò ïðèðîñò ïðîèç-
âîäèòåëüíîñòè äîêèíãà âñåãî â 1,5–2 ðàçà.
Îöåíêà è àíàëèç ðåçóëüòàòîâ äîêèíãà. Ïî
óñëîâèÿì äîêèíãà ïðîãðàììà Hex ñîõðàíÿëà
òîëüêî ïåðâûå 500 ëó÷øèõ îðèåíòàöèé ëè-
ãàíäà. Ýòè îðèåíòàöèè îðãàíèçóþòñÿ â êëàñ-
òåðû, êàæäûé èç êîòîðûõ ïðåäñòàâëÿåò ñîáîé
êîîðäèíàòû ëèãàíäà íà ïîâåðõíîñòè áåëêà-
ìèøåíè â îäíîì èç âîçìîæíûõ ïîëîæåíèé.
Êàê ïîêàçàíî â òàáëèöå, ïðè äîâîëüíî áîëü-
øîì êîëè÷åñòâå (500 ïîëîæåíèé) äîïóñòèìûõ
îðèåíòàöèé ëèãàíäà îíè ôîðìèðóþò âñåãî 40–
140 êëàñòåðîâ.  ñëó÷àå ñ êðåìàðòîì íàéäåíî
âñåãî îêîëî 200 âîçìîæíûõ îðèåíòàöèé, äëÿ
êîòîðûõ äèôôåðåíöèðîâàëîñü 7–8 êëàñòåðîâ.
Íàìè îáíàðóæåíû îòëè÷èÿ â êîëè÷åñòâå
íàéäåííûõ ëó÷øèõ îðèåíòàöèé ëèãàíäîâ (íàè-
áîëåå ñóùåñòâåííûå â ñëó÷àå îðèçàëèíà, ïåíäè-
ìåòàëèíà è àìèïðîôîñìåòèëà) â çàâèñèìîñòè
îò èñïîëüçóåìûõ àïïàðàòíûõ óñòðîéñòâ (òàá-
ëèöà). Òàê, ïðè àíàëèçå ðåçóëüòàòîâ ðàñ÷åòîâ
ñ èñïîëüçîâàíèåì öåíòðàëüíîãî ïðîöåññîðà
(Intel Core 2 Quad Q6600) êîëè÷åñòâî òàêèõ
îðèåíòàöèé âñåãäà áûëî âûøå ïî ñðàâíåíèþ
ñ ðàñ÷åòàìè íà ãðàôè÷åñêèõ óñêîðèòåëÿõ. Ýòî
ìîæíî îáúÿñíèòü íåêîòîðûìè îòëè÷èÿìè â
ïðîãðàììíîì êîäå àëãîðèòìîâ, îïòèìèçè-
ðîâàííûõ ïîä òåõíîëîãèþ CUDA [42, 43, 53],
îäíàêî ñëåäóåò îòìåòèòü, ÷òî óïîìÿíóòûå îò-
ëè÷èÿ íå âëèÿþò íà êîíå÷íûé ðåçóëüòàò ðàñ-
÷åòîâ, òàê êàê äëÿ êàæäîãî èç ÷åòûðåõ òðåõ-
çàìåùåííûõ áåíçèìèäàçîëîâ è âñåõ âîñüìè
ãåðáèöèäîâ ðàçëè÷íûå àïïàðàòíûå óñòðîéñ-
òâà ãåíåðèðîâàëè îäèíàêîâîå êîëè÷åñòâî êëà-
ñòåðîâ ñ êîíå÷íûìè ëó÷øèìè ïîçèöèÿìè
ëèãàíäîâ.
Êðîìå òîãî, ïðè èñïîëüçîâàíèè ïðîãðàìì-
íîãî ïàêåòà Hex 6.1 äëÿ ïåðâûõ 500 îðèåíòà-
öèé ëèãàíäà, êàê ïðàâèëî, íàáëþäàëè ñîâïà-
äåíèå ýíåðãåòè÷åñêèõ ïîêàçàòåëåé ëó÷øåé è
õóäøåé êîíôîðìàöèé, ðàññ÷èòàííûõ êàê ñ
èñïîëüçîâàíèåì öåíòðàëüíîãî ïðîöåññîðà, òàê
è ãðàôè÷åñêèõ óñêîðèòåëåé. Ïðè ýòîì îá-
íàðóæåííûå ÷àñòíûå îòëè÷èÿ ÿâëÿþòñÿ íå-
çíà÷èòåëüíûìè, è îíè íå ìîãóò ïîâëèÿòü íà
êîíå÷íûå ðåçóëüòàòû ðàñ÷åòà äîêèíãà íèçêî-
ìîëåêóëÿðíûõ ñîåäèíåíèé ñ ìîëåêóëîé öåëå-
âîãî áåëêà.
Àíàëèç ïîëó÷åííûõ òðåõìåðíûõ ìîäåëåé
êîìïëåêñîâ FtsZ-ëèãàíä, ñãåíåðèðîâàííûõ ïðè
ïîìîùè ïðîãðàììíîãî ïàêåòà Hex 6.1, ïî-
çâîëèë íàì èäåíòèôèöèðîâàòü â ñëó÷àå áåí-
çèìèäàçîëîâ íåñêîëüêî ïîòåíöèàëüíûõ ñàéòîâ
èõ ñâÿçûâàíèÿ ñ ïîâåðõíîñòüþ ìîëåêóëû áåë-
êà FtsZ2-2 èç A. thaliana. Ñëåäóåò îòìåòèòü,
÷òî áîëüøèíñòâî êëàñòåðîâ êàæäîãî èç áåí-
çèìèäàçîëüíûõ ñîåäèíåíèé ëîêàëèçîâàíû â
ðàéîíå ñïèðàëè Í7 ìåæäó N- è Ñ-êîíöåâûìè
äîìåíàìè, êîòîðûé àíàëîãè÷åí èçâåñòíîìó
ñàéòó ñâÿçûâàíèÿ òàêñîëà ìîëåêóëîé -òóáó-
ëèíà [54]. Â äàëüíåéøåì âñå èäåíòèôèöèðî-
âàííûå íàìè ñàéòû ïîäëåæàò îöåíêå íà ñðîä-
ñòâî ñ âåùåñòâàìè áåíçèìèäàçîëüíîé ïðèðîäû.
Âûâîäû. Íà ïðèìåðå äîêèíãà ðÿäà ñîåäè-
íåíèé êëàññà áåíçèìèäàçîëîâ, äèíèòðîàíèëè-
íîâ è ôåíèëêàðáàìàòîâ íà ìîëåêóëó áåëêà
FtsZ áûëà ïîäòâåðæäåíà àóòåíòè÷íîñòü ðå-
çóëüòàòîâ ðàñ÷åòîâ, âûïîëíåííûõ ñ ïîìîùüþ
GPU, ðåçóëüòàòàì, ïîëó÷åííûì ñ èñïîëüçîâà-
íèåì öåíòðàëüíîãî ïðîöåññîðà. Ïîêàçàíî, ÷òî
èñïîëüçîâàíèå ðàñïàðàëëåëèâàíèÿ íà GPU
è, â ÷àñòíîñòè, òåõíîëîãèè CUDA (nVidia –
www.nvidia.com) ïîçâîëÿåò çíà÷èòåëüíî ñî-
62 ISSN 0564–3783. Öèòîëîãèÿ è ãåíåòèêà. 2012. ¹ 3
Î.Í. Äåì÷óê, Ï.À. Êàðïîâ, ß.Á. Áëþì
êðàòèòü âðåìÿ, íåîáõîäèìîå äëÿ âûïîëíåíèÿ
ðÿäà ìîëåêóëÿðíûõ ðàñ÷åòîâ ïðè çíà÷èòåëü-
íîì ñîêðàùåíèè ñåáåñòîèìîñòè èññëåäîâà-
íèé â îáëàñòè ñòðóêòóðíîé áèîëîãèè è áèî-
èíôîðìàòèêè. Èäåíòèôèöèðîâàíû òàêæå ïî-
òåíöèàëüíûå ñàéòû ñâÿçûâàíèÿ áåíçèìèäà-
çîëîâ ñ ïîâåðõíîñòüþ ìîëåêóëû áåëêà FtsZ2-2
èç A. thaliana.
O.M. Demchuk,
P.A. Karpov, Ya.B. Blume
DOCKING OF LOW-MOLECULAR LIGANDS
ON THE PLANT FtsZ-PROTEIN WITH
APPLICATION OF CUDA-ACCELERATED
CALCULATIONS
This article provides review and analysis of oppor-
tunities for application of the CUDA technology for
acceleration of computations in structural biology and
bioinformatics. On the example of work with the Hex
6.1 program, comparative analysis of increase in the
speed and quality of results of hard-docking of a num-
ber of low-molecular compounds on the surface of the
FtsZ protein from Arabidopsis thaliana was performed.
Several potential benzimidazole – plant FtsZ protein
binding sites were identified.
Î.Ì. Äåì÷óê,
Ï.À. Êàðïîâ, ß.Á. Áëþì
ÄÎʲÍà ÍÈÇÜÊÎÌÎËÅÊÓËßÐÍÈÕ Ë²ÃÀÍIJÂ
ÍÀ ÏÎÂÅÐÕͲ ÐÎÑËÈÍÍÎÃÎ FtsZ Á²ËÊÀ:
ÇÀÑÒÎÑÓÂÀÍÍß ÒÅÕÍÎËÎò¯ CUDA
ÄËß ÏÐÈÑÊÎÐÅÍÍß ÎÁ×ÈÑËÅÍÜ
Íàâîäèòüñÿ îãëÿä òà àíàë³ç ìîæëèâîñòåé çàñòî-
ñóâàííÿ òåõíîëî㳿 CUDA äëÿ ïðèñêîðåííÿ îá-
÷èñëåíü â ãàëóç³ ñòðóêòóðíî¿ á³îëî㳿 òà á³î³íôîð-
ìàòèêè. Íà ïðèêëàä³ ðîáîòè ç ïðîãðàìîþ Hex 6.1
çä³éñíåíî ïîð³âíÿëüíèé àíàë³ç ïðèðîñòó ïðîäóê-
òèâíîñò³ òà ÿêîñò³ ðåçóëüòàò³â æîðñòêîãî äîê³íãó
íèçüêîìîëåêóëÿðíèõ ñïîëóê ð³çíèõ êëàñ³â íà ïî-
âåðõí³ FtsZ-á³ëêà ³ç Arabidopsis thaliana. ²äåíòèô³-
êîâàíî äåê³ëüêà ïîòåíö³éíèõ ñàéò³â çâ’ÿçóâàííÿ
áåíç³ì³äàçîë³â ³ç ðîñëèííèì FtsZ.
ÑÏÈÑÎÊ ËÈÒÅÐÀÒÓÐÛ
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Ïîñòóïèëà 26.10.11
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/NLD (Gebruik deze instellingen om Adobe PDF-documenten te maken die zijn geoptimaliseerd voor prepress-afdrukken van hoge kwaliteit. De gemaakte PDF-documenten kunnen worden geopend met Acrobat en Adobe Reader 5.0 en hoger.)
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| id | nasplib_isofts_kiev_ua-123456789-126471 |
| institution | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| issn | 0564-3783 |
| language | Russian |
| last_indexed | 2025-12-07T18:37:20Z |
| publishDate | 2012 |
| publisher | Інститут клітинної біології та генетичної інженерії НАН України |
| record_format | dspace |
| spelling | Демчук, О.Н. Карпов, П.А. Блюм, Я.Б. 2017-11-24T16:24:50Z 2017-11-24T16:24:50Z 2012 Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов / О.Н. Демчук, П.А. Карпов, Я.Б. Блюм // Цитология и генетика. — 2012. — Т. 46, № 3. — С. 55-64. — Бібліогр.: 54 назв. — рос. 0564-3783 DOI: 10.3103/S0095452712030048 https://nasplib.isofts.kiev.ua/handle/123456789/126471 577.112.7(577.332+004.42) Приведен обзор и анализ возможностей применения технологии CUDA для ускорения расчетов в области структурной биологии и биоинформатики. На примере работы с программой HEX 6.1 выполнен сравнительный анализ прироста производительности и качества результатов жесткого докинга низкомолекулярных соединений различных классов на поверхности FtsZ белка из Arabidopsis thaliana. Идентифицировано несколько потенциальных сайтов связывания бензимидазолов с растительным FtsZ. Наводиться огляд та аналіз можливостей застосування технології CUDA для прискорення обчислень в галузі структурної біології та біоінформатики. На прикладі роботи з програмою Hex 6.1 здійснено порівняльний аналіз приросту продуктивності та якості результатів жорсткого докінгу низькомолекулярних сполук різних класів на поверхні FtsZ-білка із Arabidopsis thaliana. Ідентифіковано декілька потенційних сайтів зв’язування бензімідазолів із рослинним FtsZ. The opportunities to apply the CUDA technology for faster computations in structural biology and bioinformatics are reviewed and analyzed. Using HEX 6.1 software, we performed a comparative analysis of the efficiency and the increase in quality after CUDA application. The work was conducted on the example of rigid docking of low-molecular-weight compounds of different classes on the surface of the Arabidopsis thaliana FtsZ. Several potential binding sites of benzimidazoles to the plant FtsZ were identified. ru Інститут клітинної біології та генетичної інженерії НАН України Цитология и генетика Оригинальные работы Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов Докінг низькомолекулярних лігандів на поверхні рослинного FtsZ білка: застосування технології cuda для прискорення обчислень Docking small ligands to molecule of the plant FtsZ protein: Application of the CUDA technology for faster computations Article published earlier |
| spellingShingle | Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов Демчук, О.Н. Карпов, П.А. Блюм, Я.Б. Оригинальные работы |
| title | Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов |
| title_alt | Докінг низькомолекулярних лігандів на поверхні рослинного FtsZ білка: застосування технології cuda для прискорення обчислень Docking small ligands to molecule of the plant FtsZ protein: Application of the CUDA technology for faster computations |
| title_full | Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов |
| title_fullStr | Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов |
| title_full_unstemmed | Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов |
| title_short | Докинг низкомолекулярных лигандов на молекуле растительного FtsZ-белка: применение технологии cuda для ускорения расчетов |
| title_sort | докинг низкомолекулярных лигандов на молекуле растительного ftsz-белка: применение технологии cuda для ускорения расчетов |
| topic | Оригинальные работы |
| topic_facet | Оригинальные работы |
| url | https://nasplib.isofts.kiev.ua/handle/123456789/126471 |
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