AIMC Topic: Nucleic Acid Conformation

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How large is the universe of RNA-like motifs? A clustering analysis of RNA graph motifs using topological descriptors.

PLoS computational biology
Identifying novel and functional RNA structures remains a significant challenge in RNA motif design and is crucial for developing RNA-based therapeutics. Here we introduce a computational topology-based approach with unsupervised machine-learning alg...

Predicting RNA Structure Utilizing Attention from Pretrained Language Models.

Journal of chemical information and modeling
RNA possesses functional significance that extends beyond the transport of genetic information. The functional roles of noncoding RNA can be mediated through their tertiary and secondary structure, and thus, predicting RNA structure holds great promi...

Predict the degree of secondary structures of the encoding sequences in DNA storage by deep learning model.

Scientific reports
DNA storage has been widely considered as a promising alternative for exponentially growing data. However, the inherent complex secondary structures severely compromise the processes of synthesis, PCR amplification, and sequencing, interfering with r...

Comprehensive datasets for RNA design, machine learning, and beyond.

Scientific reports
RNA molecules are essential in regulating biological processes such as gene expression, cellular differentiation, and development. Accurately predicting RNA secondary structures and designing sequences that fold into specific configurations remain si...

RiNALMo: general-purpose RNA language models can generalize well on structure prediction tasks.

Nature communications
While RNA has recently been recognized as an interesting small-molecule drug target, many challenges remain to be addressed before we take full advantage of it. This emphasizes the necessity to improve our understanding of its structures and function...

Quantifying complexity in DNA structures with high resolution Atomic Force Microscopy.

Nature communications
DNA topology is essential for regulating cellular processes and maintaining genome stability, yet it is challenging to quantify due to the size and complexity of topologically constrained DNA molecules. By combining high-resolution Atomic Force Micro...

Deep generalizable prediction of RNA secondary structure via base pair motif energy.

Nature communications
Deep learning methods have demonstrated great performance for RNA secondary structure prediction. However, generalizability is a common unsolved issue on unseen out-of-distribution RNA families, which hinders further improvement of the accuracy and r...

AffiGrapher: Contrastive Heterogeneous Graph Learning with Aromatic Virtual Nodes for RNA-Small Molecule Binding Affinity Prediction.

Journal of chemical information and modeling
RNA molecules exhibit diverse structures and functions, making them promising drug targets. However, predicting RNA-small molecule binding affinity remains challenging due to limited experimental data and the structural variability introduced by mult...

Melting Profile of DNA in Crowded Solution: Model-Based Study.

International journal of molecular sciences
Recent advances in molecular dynamics (MD) simulations and the introduction of artificial intelligence (AI) have resulted in a significant increase in accuracy for structure prediction. However, the cell is a highly crowded environment consisting of ...

Loop Nucleotide Chemical Shifts as a Tool to Characterize DNA G-Quadruplexes.

Chemphyschem : a European journal of chemical physics and physical chemistry
DNA G-quadruplexes are known to play myriad functional roles in the cellular context and their structural diversity has diverse applications in various fields of science. Solution-state NMR spectroscopy has been instrumental in characterization of DN...