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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
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Nucleic Acid Structure01:25

Nucleic Acid Structure

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The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
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Ligand Binding and Linkage00:49

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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Labeling DNA Probes03:31

Labeling DNA Probes

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DNA probes are fragments of DNA labeled with a reporter tag to enable their detection or purification. The resulting labeled DNA probes can then hybridize to target nucleic acid sequences through complementary base-pairing, and may be used to recover or identify these regions.
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Author Spotlight: Advancements in DNA Nanosensors – Addressing Sensitivity and Selectivity Challenges in Molecular Detection
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Structure-based deep learning for binding site detection in nucleic acid macromolecules.

Igor Kozlovskii1, Petr Popov1

  • 1iMolecule, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia.

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|December 3, 2021
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Summary
This summary is machine-generated.

Structure-based drug design for RNA benefits from identifying small molecule binding sites. A new deep learning method, BiteNet, accurately detects these sites in nucleic acid structures, advancing drug discovery.

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Area of Science:

  • Computational biology and drug discovery
  • Structural bioinformatics and molecular modeling

Background:

  • Structure-based drug design (SBDD) targeting RNA is an emerging field with approved therapeutics.
  • Accurate identification of small molecule binding sites on RNA is crucial for SBDD.
  • RNA's structural complexity and dynamics, alongside limited structural data for deep learning, pose challenges.

Purpose of the Study:

  • To develop the first structure-based deep learning approach for detecting binding sites in nucleic acid structures.
  • To address the challenge of identifying small molecule binding pockets on RNA molecules.

Main Methods:

  • Compiled a dataset of approximately 2000 nucleic acid-small molecule structures with ~2500 binding sites.
  • Developed and applied BiteNet, a novel deep learning model for binding site detection.
  • Evaluated BiteNet's performance on arbitrary nucleic acid complexes, including case studies like HIV-1 TAR RNA and ATP-aptamer.

Main Results:

  • Created a significantly larger dataset (~40x) of nucleic acid-small molecule binding sites.
  • BiteNet demonstrated state-of-the-art performance in detecting binding sites.
  • The model proved effective for analyzing diverse conformations and mutant variants.

Conclusions:

  • BiteNet represents a breakthrough in structure-based deep learning for nucleic acid binding site detection.
  • This approach can significantly aid the identification of potential drug candidates targeting RNA.
  • The method's ability to handle various structural forms enhances its utility in drug discovery research.