Visual exploration of large normal mode spaces to study protein flexibility
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00116311" target="_blank" >RIV/00216224:14330/20:00116311 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1016/j.cag.2020.05.025" target="_blank" >http://dx.doi.org/10.1016/j.cag.2020.05.025</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.cag.2020.05.025" target="_blank" >10.1016/j.cag.2020.05.025</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Visual exploration of large normal mode spaces to study protein flexibility
Popis výsledku v původním jazyce
When studying the function of proteins, biochemists utilize normal mode decomposition to enable the analysis of structural changes on time scales that are too long for molecular dynamics simulation. Such a decomposition yields a high-dimensional parameter space that is too large to be analyzed exhaustively. We present a novel approach to reducing and exploring this vast space through the means of interactive visualization. Our approach enables the inference of relevant protein function from single structure dynamics through protein tunnel analysis while considering normal mode combinations spanning the whole normal modes space. Our solution, based on multiple linked 2D and 3D views, enables the quick and flexible exploration of individual modes and their effect on the dynamics of tunnels with relevance for the protein function. Once an interesting motion is identified, the exploration of possible normal mode combinations is steered via a visualization-based recommendation system. This helps to quickly identify a narrow, yet relevant set of normal modes that can be investigated in detail. Our solution is the result of close cooperation between visualization and the domain. The versatility and efficiency of our approach are demonstrated in several case studies.
Název v anglickém jazyce
Visual exploration of large normal mode spaces to study protein flexibility
Popis výsledku anglicky
When studying the function of proteins, biochemists utilize normal mode decomposition to enable the analysis of structural changes on time scales that are too long for molecular dynamics simulation. Such a decomposition yields a high-dimensional parameter space that is too large to be analyzed exhaustively. We present a novel approach to reducing and exploring this vast space through the means of interactive visualization. Our approach enables the inference of relevant protein function from single structure dynamics through protein tunnel analysis while considering normal mode combinations spanning the whole normal modes space. Our solution, based on multiple linked 2D and 3D views, enables the quick and flexible exploration of individual modes and their effect on the dynamics of tunnels with relevance for the protein function. Once an interesting motion is identified, the exploration of possible normal mode combinations is steered via a visualization-based recommendation system. This helps to quickly identify a narrow, yet relevant set of normal modes that can be investigated in detail. Our solution is the result of close cooperation between visualization and the domain. The versatility and efficiency of our approach are demonstrated in several case studies.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10200 - Computer and information sciences
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Computers & Graphics
ISSN
0097-8493
e-ISSN
—
Svazek periodika
90
Číslo periodika v rámci svazku
August
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
11
Strana od-do
73-83
Kód UT WoS článku
000558004700010
EID výsledku v databázi Scopus
2-s2.0-85085769658