Articles tagged with Amino Acid Sequences
Researchers developed an AI platform, PeptiVerse, to predict key properties of peptides, enabling early assessment of drug potential. The open-source platform allows users to evaluate ordinary and chemically modified peptides, streamlining the discovery process.
A new chemical tagging approach has been developed to accurately sequence short peptides without relying on databases, opening possibilities for food science, nutrition, and biomedical research. The method successfully identified all 132 peptides with zero errors, highlighting its accuracy and reliability.
Researchers discovered a single amino acid change that allows coronaviruses to interact with human and bat immune systems differently, shifting the body's response to infection. This alteration enables benign animal viruses to adapt to humans and cause severe disease.
Researchers at Graz University of Technology have developed a new approach to understand protein function and stability, identifying amino acids crucial for both with high accuracy. The FSA method combines machine-learning-generated sequences with natural sequences, revealing functional and structural significance of amino acids.
Researchers at Rice University have engineered living cells to use a 21st amino acid that illuminates protein changes in real time, providing a new perspective on the inner workings of life. This breakthrough addresses a long-standing challenge in biology by allowing scientists to track subtle protein changes within living systems.
Researchers analyzed blood samples from dogs in the Dog Aging Project and found that post-translationally modified amino acids are strongly linked to age, suggesting a promising indicator of physiological aging. The study also highlighted an important role of the kidney in the relationship between age and blood metabolites.
Researchers discovered bulky amino acids reduce pore size, blocking transport of certain molecules in aquaporin 10.2. This provides a framework for predicting functions of uncharacterized aquaglyceroporins.
Researchers found that gamma-aminobutyric acid can induce the formation of nanocavities in montmorillonite clay, which could facilitate life's first chemistry. This discovery adds a new dimension to the concept of the 'warm little pond' and introduces an unusual suspect in the origin of life.
A new machine learning model accurately predicts the fitness of AAV capsids based on their amino acid sequence, enabling more efficient and cost-effective gene therapies. The model's robustness and generalizability have been demonstrated through tests on independent datasets, offering a promising tool for capsid engineering.
Researchers at the University of Birmingham have identified a three-amino acid sequence that reduces psoriasis severity, comparable to steroid cream. The study found that topical application resulted in a clear reduction in disease and was confirmed using Psoriasis Area and Severity Index scoring.
Researchers developed new AI models, InstaNovo and InstaNovo+, to vastly improve accuracy and discovery in protein science. These models excel in tasks such as de novo peptide sequencing, identifying microorganisms, and discovering novel peptides, with implications for personalized medicine, cancer immunology, and beyond.
A recent study published by researchers at the University of Liverpool has confirmed that Mesozoic fossils, including dinosaur bones and teeth, still preserve their original organic materials. The team used advanced mass spectrometry techniques to identify preserved collagen remnants in a well-preserved Edmontosaurus fossil.
A team led by biologist Thomas Mayer found that a small binding-pocket on cyclin B helps regulate the sequence of cell division events. Without this pocket, malformations occur due to incorrect kinase phosphorylation, leading to potential tumours or infertility.
Researchers developed ProteinReDiff, an AI-powered method to redesign proteins for improved ligand binding. The approach uses initial protein sequences and ligand SMILES strings, reducing reliance on detailed structural data.
Scientists investigated the role of ancient VR type-1 (ancV1R) receptor in pheromone detection using knockout mice. The study found that ancV1R-deficient female mice had impaired pheromone detection and exhibited abnormal sexual behavior.
A recent study revises our understanding of the universal genetic code's evolution, suggesting that early life preferred smaller amino acids over larger ones. The researchers found that amino acids with aromatic ring structures were incorporated into the code later than previously thought, offering clues about other extinct genetic codes.
Researchers have shed new light on gene expression by visualizing ribosomes in unprecedented detail. The study reveals a molecular mechanism for mRNA delivery to the ribosome, advancing our understanding of gene expression at the molecular level.
Researchers found that plants have multiple enzymes for adding methyl groups to DNA, allowing them to override genetic instructions. The study reveals the evolutionary history of these enzymes and their unique structures, providing insights into plant resilience to environmental changes.
Researchers found specific gene mutations in barley affect starch synthesis, forming elongated starch granules with altered properties. Mutations disrupt enzymes, altering glucose chain formation and branching.
Researchers found that folded peptides are more electrically conductive than their unfolded counterparts due to the formation of a specific secondary structure called the 3_10 helix. This discovery has implications for the design and development of molecular electronic devices.
Biomolecular condensates exhibit unique material properties tied to protein sequences, including viscoelastic behavior and aging processes. The study quantifies interaction timescales, explaining how proteins within condensates arrange into fibrils over time.
Researchers have devised an algorithm to rationally engineer enzymes for improved performance, taking into account evolutionary history. The new method successfully introduced up to 84 mutations over a sequence of 280, resulting in improved activity and stability at higher temperatures.
Researchers at Tokyo University of Science developed menthyl esters with potent anti-inflammatory and anti-obesity effects. The compounds outperformed menthol in inflammatory assays and suppressed genes involved in immune responses. They also inhibited adipogenesis, showing promise for addressing metabolic disorders.
Researchers at Xi'an Jiaotong-Liverpool University developed a new method that enables the efficient production of cysteine-rich peptides and microproteins in their naturally folded 3D structure. The approach uses organic solvents to mimic nature's oxidative folding process, resulting in speeds of over 100,000 times faster than aqueous...
Researchers from Nano Life Science Institute discovered how genetically designed peptides form single-molecule thick crystals on graphite surfaces. The behavior is directly related to their molecular architecture, with negatively charged and positively charged peptides forming unique oblique lattices.
Researchers have found that antibody sequences contain an unusual number of codons without corresponding tRNAs, which can be bridged by the inosine wobble modification. This modification allows for more efficient production of antibodies, with implications for vaccine efficacy and rationally designed vaccines.
A team of researchers successfully synthesized a 1.5-million-year-old antibiotic called paleomycin, which displays potent properties against human pathogens. By tracing the evolutionary path of glycopeptide antibiotics, the team gained insights into the development of new drugs and uncovered a common precursor molecule.
Researchers discuss CRISPR's limitations in generating accurate cancer models, including variable mutations and indels. Despite these challenges, the technology holds promise for cancer research due to its potential for natural selection and Darwinian evolution.
Researchers used AI to discover 464 types of enzymes in E. coli and verified their predictions through in vitro enzyme assay. The developed AI can predict a total of 5360 enzyme EC numbers, enabling accurate analysis of metabolic processes and development of eco-friendly microbial factories.
Researchers tested AlphaFold2's ability to predict protein structure changes from single point mutations. They found that AlphaFold can accurately predict deformation at the chromophore-binding site, leading to accurate predictions of fluorescence in fluorescent proteins.
Researchers found that tumor-resident T-cell receptor sequences showed high complementarity with the cancer testis antigen DDX53, suggesting an immune response that selects for DDX53-negative cells. This association was correlated with worse disease-free survival rates, highlighting a potential early esophageal cancer antigen.
Researchers discovered that intrinsically disordered regions (IDRs) in proteins play a critical role in chromatin regulation and gene expression. IDRs form droplets called condensates that separate from surrounding fluid, allowing proteins to congregate and carry out cellular activities.
A new gene-editing technique combines peptide nucleic acids and prokaryotic Argonautes to introduce targeted breaks in the genome. The approach, called PNP editing, offers advantages over CRISPR-based methods, including improved specificity and targeting.
A team of scientists has successfully elucidated the structure and function of LITE-1, a biomolecule used by Caenorhabditis elegans to detect danger. The researchers used artificial intelligence to predict the structure of LITE-1, which is a channel protein that forms a pore in the cell membrane allowing charged particles to pass through.
Scientists develop a method to construct crystalline artificial steric zippers in peptide β-sheets, paving the way for novel therapeutic strategies and materials. The research utilizes metal ions to prevent aggregation and form needle-shaped crystals with specific structural characteristics.
A study by Michigan Medicine researchers reveals that modifications to amino acids in sperm may be linked to infertility. The team analyzed the molecular sequence composition of protamines, finding non-arginine amino acids with unexpected post-translational modifications that affect sperm shape and function.
Researchers at Hokkaido University unveil unprecedented carrier protein-mediated ring-forming step in actinopyridazone biosynthesis. The dihydropyridazinone ring is formed through a novel machinery involving Apy3, Apy4, and Apy6 proteins.
The study uses AI-assisted methods to discover novel deaminase proteins with unique functions through structural prediction and classification, expanding the utility of base editors. New DNA base editors with remarkable features were developed, enabling tailor-made applications for various breeding efforts.
Scientists have identified a molecular control centre responsible for processing newly formed proteins correctly when they leave the cell's protein factories. The ribosomal gatekeeper NAC ensures the excision of methionine from specific proteins, preventing cell death.
BioAutoMATED is an all-in-one AutoML platform designed for biologists, enabling easy analysis and interpretation of biological sequences. The platform uses three existing AutoML tools to generate models that can predict biological functions from sequence information.
Researchers have developed a new way to identify proteins based on their amino acid content, which can predict protein function and facilitate the development of new biological drugs. The method shows promise in cancer research, where it can help design more targeted treatments by linking survivin and PRC2 proteins.
Researchers identified four fungal proteins responsible for suppressing host plant immunity in infectious diseases, leading to distinct host specificity in over 70% of plant diseases. Understanding the mechanism of this specificity may lead to new crop protection technologies.
Researchers have developed a system that uses generative diffusion to create new proteins, advancing the field of generative biology. The system, called ProteinSGM, learns from image representations to generate fully new proteins, which are biophysically real and functional.
Researchers have identified mechanisms behind the emergence of new and contagious coronavirus variants by analyzing over three million genome sequences. The study found that concordant substitutions occurring at other sites influence the likelihood of a substitution occurring at a specific site, leading to unexpected variant emergence.
Researchers developed machine-learning algorithms to generate proteins with specific structural features, enabling the creation of biologically inspired materials. The models can produce millions of new protein ideas in a few days, allowing scientists to explore unique applications.
A new study has created a comprehensive map of the human proteome, identifying over 1 million peptides from 17,717 different protein groups. The researchers also found that most alternative splicing detected at the RNA stage is also present in the proteins, validating long-held ideas about this process.
Researchers developed synthetic peptide nanonets that selectively entrap bacteria, rendering them vulnerable to antimicrobial components. The nanonets displayed both trapping and killing functionalities, demonstrating potential as an anti-infective strategy.
Scientists have reconstructed the evolutionary history of flavin-containing monooxygenases (FMOs), a class of detoxifying enzymes present in all lifeforms. The study reveals that a single ancestral gene diverged into two distinct functions, with one gene triggering a different breakdown reaction.
A new AI-based classification system, AMP-BERT, was developed to identify candidate antimicrobial peptides. The model uses a deep neural network-based architecture and can extract structural and functional information from peptide sequences.
A team of researchers has discovered the role of amino acid sequences in regulating ATP production in photosynthetic organisms. The study found that specific domains of the γ subunit of chloroplast F0F1 are involved in redox regulation, crucial for photosynthesis.
Scientists developed an AI system, ProGen, that can generate artificial enzymes from scratch, working as well as those found in nature. The AI model learned aspects of evolution and was able to tune its generation for specific effects, creating proteins with unique properties.
Researchers at Princeton University's Hecht Lab discovered a de novo protein that catalyzes the synthesis of quantum dots at room temperature. This breakthrough opens doors to making nanomaterials in a more sustainable way, with potential benefits for the environment.
Researchers at UIC have developed a new method to study ribosome function by attaching peptides to tRNAs, providing high-resolution structures of the ribosome and its interactions with nascent chains. This breakthrough sheds light on protein synthesis and antibiotic resistance.
Researchers developed a tool that encodes patient data as DNA sequences to link health databases accurately. The platform uses BLAST and machine learning algorithms to integrate data from multiple administrative databases, overcoming typographical errors and inconsistencies.
Researchers developed a new software tool called ProteinMPNN to create protein molecules more accurately and quickly than before. The team used machine learning algorithms, including AlphaFold, to generate new protein shapes and sequences, paving the way for novel vaccines, treatments, and sustainable biomaterials.
Researchers analyzed proteins from eight species and found that low-complexity regions (LCRs) share similar roles across species, helping proteins join larger-scale assemblies. They also discovered species-specific LCR sequences corresponding to unique functions, such as forming plant cell walls.
Researchers have identified two effective antibodies that neutralize all known strains of COVID-19, including Delta and Omicron variants. These breakthrough antibodies could eliminate the need for repeated booster vaccinations and strengthen immune systems, especially in at-risk populations.
Scientists at the University of Freiburg have successfully characterized epigenetic modifications using nanopore analysis. The technique allows for rapid detection of protein fragments with varying levels of acetylation, enabling more accurate diagnosis and treatment of diseases like cancer.
Researchers at Chalmers University of Technology developed a computer model to predict enzyme efficiency. This helps find efficient cell factories for producing biotech products like biofuels and medicines, and studies difficult diseases.
Researchers from Johannes Gutenberg University Mainz used AlphaFold to predict the structures of new protein knots, discovering the most complex knot and composite knots. These findings provide insight into folding mechanisms and evolutionary processes in proteins.