Sampling-Based Motion Planning for Tracking Evolution of Dynamic Tunnels in Molecular Dynamics Simulations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00326510" target="_blank" >RIV/68407700:21230/19:00326510 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14330/19:00107165

Výsledek na webu

<a href="https://doi.org/10.1007/s10846-018-0877-6" target="_blank" >https://doi.org/10.1007/s10846-018-0877-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10846-018-0877-6" target="_blank" >10.1007/s10846-018-0877-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sampling-Based Motion Planning for Tracking Evolution of Dynamic Tunnels in Molecular Dynamics Simulations

Popis výsledku v původním jazyce

Proteins are involved in many biochemical processes. The behavior of proteins is highly influenced by the presence of internal void space, in literature denoted as tunnels or cavities. Tunnels are paths leading from an inner protein active site to its surface. The knowledge about tunnels and their evolution over time, captured in molecular dynamics simulations, provides an insight into important protein properties (e.g., their stability or activity). For each individual snapshot of molecular dynamics, tunnels can be detected using Voronoi diagrams and then aggregated over time to trace their behavior. However, this approach is suitable only when a given tunnel is detected in all snapshots of molecular dynamics. This is often not the case of traditionally used approaches to tunnel computation. When a tunnel becomes too narrow in a particular snapshot, the existing approaches cannot detect this case and the tunnel completely disappears from the results. On the other hand, this situation can be quite common as tunnels move, disappear and appear again, split, or merge. Therefore, in this paper we propose a method which enables to trace also tunnels in those missing snapshots. We call them dynamic tunnels and we use the sampling-based motion planning to compute them. The Rapidly Exploring Random Tree (RRT) algorithm is used to explore the void space in each frame of the protein dynamics. The void space is represented by a tree structure that is transferred to the next frame of the dynamics and updated to remove collisions and to cover newly emerged free regions of the void space. If the void space reaches the surface of the protein, a dynamic tunnel is reconstructed by tracking back in the tree towards a desired place (i.e., the active site).

Název v anglickém jazyce

Sampling-Based Motion Planning for Tracking Evolution of Dynamic Tunnels in Molecular Dynamics Simulations

Popis výsledku anglicky

Proteins are involved in many biochemical processes. The behavior of proteins is highly influenced by the presence of internal void space, in literature denoted as tunnels or cavities. Tunnels are paths leading from an inner protein active site to its surface. The knowledge about tunnels and their evolution over time, captured in molecular dynamics simulations, provides an insight into important protein properties (e.g., their stability or activity). For each individual snapshot of molecular dynamics, tunnels can be detected using Voronoi diagrams and then aggregated over time to trace their behavior. However, this approach is suitable only when a given tunnel is detected in all snapshots of molecular dynamics. This is often not the case of traditionally used approaches to tunnel computation. When a tunnel becomes too narrow in a particular snapshot, the existing approaches cannot detect this case and the tunnel completely disappears from the results. On the other hand, this situation can be quite common as tunnels move, disappear and appear again, split, or merge. Therefore, in this paper we propose a method which enables to trace also tunnels in those missing snapshots. We call them dynamic tunnels and we use the sampling-based motion planning to compute them. The Rapidly Exploring Random Tree (RRT) algorithm is used to explore the void space in each frame of the protein dynamics. The void space is represented by a tree structure that is transferred to the next frame of the dynamics and updated to remove collisions and to cover newly emerged free regions of the void space. If the void space reaches the surface of the protein, a dynamic tunnel is reconstructed by tracking back in the tree towards a desired place (i.e., the active site).

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA17-07690S" target="_blank" >GA17-07690S: Metody identifikace a vizualizace tunelů pro flexibilní ligandy v dynamických proteinech</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Intelligent and Robotic Systems

ISSN

0921-0296

e-ISSN

1573-0409

Svazek periodika

93

Číslo periodika v rámci svazku

3-4

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

23

Strana od-do

763-785

Kód UT WoS článku

000459439400024

EID výsledku v databázi Scopus

2-s2.0-85048538078