KGSrna: efficient 3D kinematics-based sampling for nucleic acids

TY - GEN

T1 - KGSrna

T2 - Annual International Conference, RECOMB 2015

AU - Fonseca, Rasmus

AU - van den Bedem, Henry

AU - Bernauer, Julie

N1 - Conference code: 19

PY - 2015

Y1 - 2015

N2 - Noncoding ribonucleic acids (RNA) play a critical role in a wide variety of cellular processes, ranging from regulating gene expression to post-translational modification and protein synthesis. Their activity is modulated by highly dynamic exchanges between three-dimensional conformational substates, which are difficult to characterize experimentally and computationally. Here, we present an innovative, entirely kinematic computational procedure to efficiently explore the native ensemble of RNA molecules. Our procedure projects degrees of freedom onto a subspace of conformation space defined by distance constraints in the tertiary structure. The dimensionality reduction enables efficient exploration of conformational space. We show that the conformational distributions obtained with our method broadly sample the conformational landscape observed in NMR experiments. Compared to normal mode analysis-based exploration, our procedure diffuses faster through the experimental ensemble while also accessing conformational substates to greater precision. Our results suggest that conformational sampling with a highly reduced but fully atomistic representation of noncoding RNA expresses key features of their dynamic nature.

AB - Noncoding ribonucleic acids (RNA) play a critical role in a wide variety of cellular processes, ranging from regulating gene expression to post-translational modification and protein synthesis. Their activity is modulated by highly dynamic exchanges between three-dimensional conformational substates, which are difficult to characterize experimentally and computationally. Here, we present an innovative, entirely kinematic computational procedure to efficiently explore the native ensemble of RNA molecules. Our procedure projects degrees of freedom onto a subspace of conformation space defined by distance constraints in the tertiary structure. The dimensionality reduction enables efficient exploration of conformational space. We show that the conformational distributions obtained with our method broadly sample the conformational landscape observed in NMR experiments. Compared to normal mode analysis-based exploration, our procedure diffuses faster through the experimental ensemble while also accessing conformational substates to greater precision. Our results suggest that conformational sampling with a highly reduced but fully atomistic representation of noncoding RNA expresses key features of their dynamic nature.

U2 - 10.1007/978-3-319-16706-0_11

DO - 10.1007/978-3-319-16706-0_11

M3 - Article in proceedings

SN - 978-3-319-16705-3

T3 - Lecture Notes in Bioinformatics

SP - 80

EP - 95

BT - Research in Computational Molecular Biology

A2 - Przytycka, Teresa

PB - Springer

Y2 - 12 April 2015 through 15 April 2015

ER -