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Molecular glue refers to a small molecule that promotes or enhances the interaction between two or more proteins within a cell. Instead of directly inhibiting or activating a protein’s function like traditional drugs, molecular glues work by essentially “sticking” proteins together. This induced proximity can lead to various outcomes, most notably the targeted degradation of a disease-causing protein.
Mechanism of Action:
Induced Proximity: Molecular glues bind to the surface of one protein, inducing a conformational change or creating a new binding surface that allows it to interact with another protein that it wouldn’t normally interact with strongly, or at all.
Formation of Ternary Complexes: The molecular glue forms a bridge, creating a complex of at least three components: the glue molecule and the two interacting proteins.Diverse Outcomes: This induced protein-protein interaction can lead to different cellular effects, including:
Targeted Protein Degradation (Molecular Glue Degraders): By bringing a target protein into close proximity with an E3 ubiquitin ligase, the ligase can tag the target protein with ubiquitin. This tag signals the cell’s proteasome (the protein degradation machinery) to break down the target protein. This is a major area of interest as it allows for the degradation of previously “undruggable” proteins that lack traditional binding sites for inhibitors.
Stabilization of Protein-Protein Interactions: Some molecular glues can strengthen existing, weak interactions between proteins, potentially enhancing their normal function or leading to new functional outcomes.
Inhibition of Protein Function: By inducing an interaction, a molecular glue might sterically hinder a protein’s active site or block its interaction with its natural binding partners.Key Differences from PROTACs (Proteolysis Targeting Chimeras):
Size and Structure: Molecular glues are typically smaller, single molecules compared to PROTACs, which are larger, bifunctional molecules with two distinct binding domains connected by a linker.
Mechanism: PROTACs are designed with one end that binds to the target protein and another end that binds to an E3 ligase, physically linking them together. Molecular glues, on the other hand, work by modifying the surface of one protein to promote interaction with another.Advantages of Molecular Glues:
Targeting “Undruggable” Proteins: They can induce the degradation of proteins that lack well-defined binding pockets required for traditional small molecule inhibitors.
Potent Activity: By triggering catalytic protein degradation, a single molecular glue molecule can lead to the destruction of many target protein molecules.
Potentially Better Drug Properties: Their smaller size often leads to better cell permeability, oral absorption, and blood-brain barrier penetration compared to larger molecules like PROTACs.Examples of Molecular Glues:
Thalidomide, Lenalidomide, and Pomalidomide (IMiDs): These drugs are well-known examples that work by binding to the E3 ligase cereblon and promoting the degradation of specific transcription factors like IKZF1 and IKZF3, which are important in multiple myeloma.
Cyclosporin A and FK506: These immunosuppressants function as molecular glues by forming ternary complexes with cyclophilin/FKBP12 and calcineurin, inhibiting calcineurin activity.
Rapamycin: This immunosuppressant acts as a molecular glue by stabilizing the interaction between FKBP12 and mTOR, inhibiting mTOR signaling.
Indisulam: An anticancer aryl-sulfonamide that promotes the interaction between the RNA binding protein RBM39 and the DCAF15 E3 ligase, leading to RBM39 degradation.
(R)-CR8: A CDK inhibitor found to act as a molecular glue degrader of cyclin K.Challenges in Discovery:
– Identifying molecular glues often relies on serendipity or requires sophisticated screening methods to detect the formation of ternary complexes and the resulting biological effects.
– Predicting how a small molecule will alter protein surfaces to induce new interactions is complex.Despite the challenges, molecular glues represent a promising frontier in drug discovery, offering new avenues to target disease-causing proteins and develop novel therapeutics for various conditions, including cancer, inflammatory diseases, and neurodegenerative disorders.
This answer was prepared using Gemini AI.
“Dark protein” refers to proteins that lack a defined three-dimensional structure. These proteins are part of what’s known as the dark proteome. Unlike typical proteins, dark proteins can’t be easily detected or analyzed using standard methods because their structure is unknown.
Dark proteins are mostly composed of intrinsically disordered proteins (IDPs), which are crucial for various biological functions such as signaling, transcription, and post-translational modifications. They are often found in the extracellular matrix and on the endoplasmic reticulum.
The study of dark proteins is still relatively new, and scientists are working to uncover their roles and potential implications in health and disease. It’s an exciting area of research with much to discover!
See this:
‘Dark proteins’ hiding in our cells could hold clues to cancer and other diseases
The DNA fiber technique, also known as DNA fiber analysis or DNA fiber spreading, is a powerful method used to study DNA replication and other DNA-related processes at the single-molecule level. This technique allows researchers to visualize and analyze the dynamics of DNA replication, including replication fork progression, origin firing, and fork stalling.
How It’s Performed:
1. Labeling DNA: Cells are first incubated with nucleotide analogs that can be incorporated into newly synthesized DNA. These analogs are often halogenated nucleotides, such as BrdU (bromodeoxyuridine) or IdU (iododeoxyuridine).
2. Lysing Cells: The cells are then lysed to release the DNA. This step is crucial to ensure that the DNA fibers are intact and can be spread out for analysis.
3. Spreading DNA: The DNA is spread onto a glass slide. This can be done using various techniques, such as the “DNA combing” method, where the DNA fibers are stretched and aligned on the slide.
4. Fixing and Staining: The DNA fibers are fixed onto the slide and stained with fluorescent antibodies that specifically bind to the incorporated nucleotide analogs. This allows the newly synthesized DNA to be visualized under a fluorescence microscope.
5. Imaging and Analysis: The stained DNA fibers are imaged using a fluorescence microscope. The images are then analyzed to measure various parameters of DNA replication, such as the length of replication tracks, the distance between replication origins, and the speed of replication fork progression.
This technique provides valuable insights into the mechanisms of DNA replication and the factors that influence it, such as DNA damage, replication stress, and the activity of replication proteins.
FENZOR, also known as Fanzor, is indeed similar to CRISPR in that it is a genome-editing tool. However, it has some unique features that set it apart:
1. Origin: Fanzor is the first RNA-guided DNA-cutting enzyme found in eukaryotes, whereas CRISPR systems were originally discovered in prokaryotes (bacteria and archaea).
2. Mechanism: Like CRISPR, Fanzor uses RNA as a guide to target specific DNA sequences. This allows for precise genome editing.
3. Size and Delivery: Fanzor proteins are more compact than CRISPR-Cas systems, which could make them easier to deliver into cells and tissues for therapeutic purposes.
4. Potential: Researchers believe that with further refinement, Fanzor could become a valuable tool for human genome editing, potentially offering more precise and efficient editing capabilities compared to current CRISPR technologies.
In summary, while Fanzor shares the fundamental principle of RNA-guided DNA editing with CRISPR, its discovery in eukaryotes and its compact size could provide new advantages in the field of genetic medicine.
You may find this article useful:
Physiological and Genetic Adaptations to Diving in Sea Nomads
https://doi.org/10.1016/j.cell.2018.03.054
Sea nomads, particularly the Bajau people of Southeast Asia, are known for their incredible breath-holding abilities and freediving skills. Studies have shown that they may have a genetic adaptation that contributes to this talent.
The variant is found in the gene called PDE10A. This gene plays a role in regulating thyroid hormone levels. The specific variant in the Bajau people is associated with larger spleens.
The spleen is an organ that stores red blood cells, which carry oxygen throughout the body. When we dive, our spleen contracts, releasing red blood cells and extra oxygen into our bloodstream. A larger spleen may provide sea nomads with a larger reserve of oxygen-rich red blood cells, allowing them to stay underwater for longer periods.
Gene sharing is a term used in biology to describe a situation where a single gene codes for a protein that has multiple, distinct functions. This means that the same genetic instructions can be used to create a molecule that plays different roles in the cell or organism.
For example, the gene for the protein crystallin can be found in the eye lens, where it helps to refract light, and also in the liver, where it plays a role in detoxification.
Gene sharing is a common phenomenon in evolution, and it is thought to be an important way for organisms to create new functions from existing genes. When a gene is duplicated, one copy can continue to perform its original function, while the other copy is free to evolve new functions. This can lead to the development of new and complex traits.
Pharmacogenetics is the branch of pharmacology concerned with the effect of genetic factors on reactions to drugs. It involves variations in drug response due to genetic makeup. The activity of drug-metabolizing enzymes often varies widely among healthy people, making drug metabolism highly variable.
Pharmacogenomics, on the other hand, is the branch of genetics concerned with the way in which an individual’s genetic attributes affect the likely response to therapeutic drugs. It is the study of the role of the genome in drug response. Pharmacogenomics analyzes how the genetic makeup of a patient affects their response to drugs. It deals with the influence of acquired and inherited genetic variation on drug response, by correlating DNA mutations with pharmacokinetic (drug absorption, distribution, metabolism, and elimination), pharmacodynamic (effects mediated through a drug’s biological targets), and/or immunogenic endpoints.
Pharmacogenomics aims to develop rational means to optimize drug therapy, with regard to the patients’ genotype, to achieve maximum efficiency with minimal adverse effects. It is hoped that by using pharmacogenomics, pharmaceutical drug treatments can deviate from what is dubbed as the “one-dose-fits-all” approach. Pharmacogenomics also attempts to eliminate trial-and-error in prescribing, allowing physicians to take into consideration their patient’s genes, the functionality of these genes, and how this may affect the effectiveness of the patient’s current or future treatments.
Although both terms relate to drug response based on genetic influences, there are differences between the two. Pharmacogenetics focuses more on single drug-gene interactions, while pharmacogenomics embraces a more genome-wide association approach, incorporating genomics and epigenetics while dealing with the effects of multiple genes on drug response.
Source: Conversation with Bing, 4/11/2024
In the context of biology, genetic circuits refer to intricate networks of genes within a living organism that interact and respond to specific stimuli, ultimately controlling various cellular functions. It’s like a complex electrical circuit, but on a cellular level, using genes and molecules instead of wires and electrons.
Here’s a breakdown of the key points:
Function:
Genetic circuits orchestrate cellular processes by turning specific genes on or off in response to internal or external cues.
Examples of cues include chemical signals, temperature changes, or the presence of certain molecules.
They act like decision-making systems within cells, determining how the cell reacts to its environment.
Components:
Genes: These are the basic units, carrying the instructions for making proteins.
Regulatory elements: These are specialized DNA sequences that control when and how much a gene is expressed.
Proteins: These molecules interact with regulatory elements and carry out the instructions encoded in genes.
Types:
Natural: These are circuits that evolved within organisms and perform essential functions like development, metabolism, and immune response.
Synthetic: These are circuits engineered by scientists to perform specific tasks in the lab, often using modified or entirely new genetic components.
Applications:
Creating biosensors: Detecting specific molecules or environmental conditions.
Engineering microbes: Producing useful chemicals or performing environmental cleanup.
Developing new therapies: Delivering drugs or regulating gene expression in specific cells.
Additional notes:
Genetic circuits are like miniature computers inside cells, processing information and making decisions based on complex logic.
They are still an active area of research, with scientists constantly discovering new details and developing new applications.
Source: Gemini
Hachimoji DNA, meaning “eight-letter DNA” in Japanese, is a fascinating experiment in synthetic biology. It’s a laboratory-created modification of DNA with some key differences from the natural kind:
More building blocks: Natural DNA uses four nucleotides (A, T, C, G) to store genetic information. Hachimoji DNA doubles that number, incorporating four additional synthetic nucleotides. This allows for more complex “words” and potentially holds more information per strand.
New base pairs: These eight nucleotides form four distinct base pairs, two natural (A:T and C:G) and two completely new ones made by the synthetic nucleotides. This expands the vocabulary of DNA beyond its natural limits.
Similar structure: Despite the additions, Hachimoji DNA maintains the iconic double helix structure of natural DNA. This suggests it might be compatible with some biological processes.
Potential applications: Researchers are exploring various applications for Hachimoji DNA, including:
– Increased data storage: Doubling the information density offers exciting possibilities for storing digital data using biological molecules.
– Exploring alternative life forms: Understanding how Hachimoji DNA functions could shed light on potential forms of life with different genetic codes.
– Novel biomolecules: Hachimoji principles could be used to design other functional biomolecules with specific properties.Current stage: While promising, Hachimoji DNA is still in its early stages. Researchers are currently studying its stability, interaction with enzymes, and potential for encoding and replicating information.
Overall, Hachimoji DNA represents a creative approach to pushing the boundaries of biology and exploring new possibilities for life’s building blocks. As research progresses, we might see even more surprising applications emerge from this synthetic genetic code.
Source: Gemini
A pipeline is a series of connected tubes for transporting gas, oil, or water, usually over long distances. In biology research, this word is used meaning workflow of specific complex experimentation.
What is RNA pipeline? answered by Bard:
An RNA pipeline is essentially a series of computational steps used to analyze data generated from RNA sequencing (RNA-seq) experiments. These experiments measure the abundance of different RNA molecules in a biological sample, providing valuable insights into gene expression, alternative splicing, and other cellular processes. However, raw RNA-seq data is complex and needs processing before it can be meaningfully interpreted. That’s where the RNA pipeline comes in.
Here’s a simplified breakdown of a typical RNA pipeline:
1. Input: The pipeline starts with raw RNA-seq data, usually in the form of FASTQ files containing millions of short DNA sequences representing RNA fragments.
2. Quality Control (QC): The first step is to assess the quality of the data. This involves checking for sequencing errors, adapter contamination, and other potential issues that could affect downstream analysis.
3. Preprocessing: This step often includes adapter trimming, where low-quality sequences and adapter sequences are removed to improve data quality.
4. Alignment: Here, the RNA sequences are aligned to a reference genome or transcriptome. This allows researchers to identify where the RNA originated from and quantify its abundance in different regions. Different alignment algorithms like STAR, HiSAT2, and Salmon are used depending on the research question.
5. Quantification: After alignment, the number of RNA sequences aligning to each gene or transcript is counted. This provides a measure of gene expression levels. Tools like RSEM and FeatureCounts are commonly used for this step.
6. Downstream Analysis: This involves interpreting the gene expression data and drawing biological conclusions. This may involve differential expression analysis, identifying differentially expressed genes between different conditions, functional enrichment analysis, understanding the biological functions of differentially expressed genes, and pathway analysis, tracing the interaction between genes involved in specific biological processes.
7. Output: The final output of the pipeline can be various depending on the analysis performed. It can include gene expression matrices, differentially expressed gene lists, functional enrichment results, and pathway diagrams.
Important points to remember:
The specific tools and steps involved in an RNA pipeline may vary depending on the research question, organism, and desired level of detail.
Building and running an RNA pipeline requires bioinformatics expertise and computational resources.
Several pre-built pipelines like nf-core/rnaseq are available, simplifying the analysis for researchers with less bioinformatics experience.Enhancers are non-coding DNA sequences that act as control switches for our genes. They sit far away from the genes they regulate, sometimes even on different chromosomes! Their job is to tell RNA polymerase, the enzyme that makes RNA copies of genes, to get to work and crank out more mRNA from a specific gene.
magine enhancers as the conductors of a gene expression orchestra. They don’t play the instruments themselves (code for protein), but they coordinate the timing and intensity of which genes are expressed, influencing how cells behave and develop.In 2010, scientists discovered a surprising twist: enhancers can also produce their own RNA molecules called enhancer RNAs (eRNAs). Unlike mRNAs that code for proteins, eRNAs are non-coding.
But here’s the interesting part: eRNA production is linked to enhancer activity. When an enhancer is turned on and boosting gene expression, it tends to produce more eRNA. This suggests that eRNAs might play a role in the whole gene expression dance.
However, unlike mRNA transcripts of genes, eRNAs are not directly translated into proteins. They work in more subtle ways, influencing gene expression through different mechanisms:Looping DNA: eRNAs can form loops in the DNA, bringing enhancers closer to their target genes for more efficient activation.
Modifying chromatin: eRNAs can recruit proteins that change the packaging of DNA, making it easier for RNA polymerase to access the gene.
Interacting with proteins: eRNAs can directly interact with proteins involved in gene expression, influencing their activity or recruiting them to specific genes.
So, are eRNAs mRNA transcripts of enhancer sequences? Not quite. eRNAs are not translated into proteins, and their sequences can be different from the actual enhancer DNA due to splicing and other processing steps. They’re more like messengers or signals that reflect enhancer activity and play a role in regulating gene expression in their own unique way.
The field of eRNA research is still young, but it’s already offering exciting insights into the complex world of gene regulation. Understanding how these molecules work could lead to new therapeutic approaches for diseases caused by gene expression errors.Source: Bard
Template Switching Mutation Explained
Template switching is a fascinating mechanism that can introduce various mutations into DNA during replication. Here’s a breakdown of the process:
1. Replication Fork Stalling:
Imagine the DNA double helix being unzipped during replication, with two replication forks moving along each strand. Sometimes, these forks encounter obstacles like protein knots or DNA damage, causing them to stall.
2. Misalignment and Dissociation:
Due to the stalled fork, the newly synthesized DNA strand (nascent strand) can become misaligned with its template strand. This misalignment can lead to the nascent strand dissociating from its original template.
3. Template Switching:
With the nascent strand untethered, it can search for and re-anneal with a different DNA molecule in the vicinity. This “new” template can be either the complementary strand of the original template or another nearby DNA segment.
4. Resumption of Synthesis:
DNA polymerase resumes synthesis using the new template, incorporating its sequence into the growing nascent strand. This can lead to several types of mutations depending on the nature of the new template:
Insertions: If the new template is longer than the original gap, extra nucleotides get incorporated.
Deletions: If the new template is shorter, part of the original sequence gets skipped.
Inversions: If the new template is the opposite strand of the original gap, the inserted sequence will be reversed.
Duplications: If the new template is a nearby repeated sequence, it can be copied multiple times.5. Fork Rejoining:
Eventually, the stalled replication fork restarts and rejoins with the completed nascent strand. This completes the template switching event, leaving behind a mutated DNA sequence.
As you can see, template switching is a complex process with the potential to introduce diverse mutations. Its role in various genetic diseases and genome evolution is an ongoing area of research.
Source: Bard
Both base calling and gene calling are essential steps in analyzing genetic data, but they address different aspects.
Base Calling:
Definition: Base calling is the process of translating raw data from a sequencing machine into a sequence of nucleotides (A, C, G, T or U).
Input: Electrical signals, light intensity signals, or chromatogram peaks generated during sequencing.
Output: A string of letters representing the sequence of nucleotides in the DNA or RNA molecule.
Examples of algorithms: Phred, Bonito, PoreCNN
Importance: Base calling is the first step in processing and analyzing genetic data. It is crucial for accurate downstream analyses like variant calling, gene expression studies, and genome assembly.Gene Calling:
Definition: Gene calling is the process of identifying and annotating genes within a DNA sequence.
Input: A DNA sequence generated after base calling.
Output: Annotations of predicted genes, including their location, start/stop codon, coding region, and potential function.
Examples of algorithms: GeneMark, Augustus, SNAP
Importance: Gene calling helps us understand the functional elements in a genome, predict protein sequences, and identify disease-causing mutations.Relationship:
Direct: Base calling is a prerequisite for gene calling. To identify genes, we need a reliable sequence of nucleotides as input.
Indirect: Base calling errors can propagate to gene calling errors. Therefore, accurate base calling is crucial for reliable gene predictions.
Complementary: While base calling focuses on individual nucleotides, gene calling looks at larger patterns and identifies functional units within the sequence.Together, base calling and gene calling form the foundation for various downstream analyses in genomics and contribute significantly to our understanding of genes, genomes, and their functions.
Source: Bard.