Enzymes can mediate discrete chemical reactions with sub-angstrom precision by employing complex, polar active sites to ensure a precise and effective response. Using the...
To fight cancer, we must stop their metastasis or uncontrolled multiplication. Hence, it is important to understand what proteins these cancer cells need for...
Proteins perform enormous tasks in our cells as molecular machines. These functions rely on the structural plasticity or the ability to adopt multiple shapes...
Rare events in proteins, which are essential for comprehending intricate phenomena like transitory structural changes and protein-ligand interactions, are frequently missed by unbiased molecular...
AlphaFold is a database of protein structures and predictions. It contains predictions for ~214 million proteins. AlphaFold2, developed by DeepMind, has dramatically scaled our...
Deep learning is being utilized in the course of drug development to understand the structure of the protein-ligand complex, utilizing the technique of virtual...
ProteinGPT was developed jointly by specialists from the University of California in Los Angeles and the Georgia Institute of Technology and Meta AI. The...
Understanding complex cellular behaviors quantitatively is essential for gaining in-depth insights into cell biology. Tracking the movement and interactions (movies) of cells over time...
A recent study by Tong Li and colleagues from the Wellcome Sanger Institute and other institutions introduces WebAtlas, an innovative pipeline aimed at addressing...
In synthetic biology, turnover numbers (kcat) — a critical measure of an enzyme's efficiency—have a variety of applications. On the other hand, kcat measurement...
Targeted and efficient treatments for identified protein targets necessitate the use of structure-based drug design (SBDD); this is still a challenge owing to the...
The use of artificial intelligence (AI) in all phases of medication development is growing rapidly. Drug pharmacokinetic (PK) datasets are frequently acquired independently of...
Trying to visualize available genomic data is of great interest. Currently, there exists a lot of specialized visualization tools, but most need to be...
Understanding the complex mechanisms behind many essential biological activities is essential for developing new drugs and has broad ramifications in the disciplines of biotechnology,...
Scientists from McGill University, Genentech, and Université de Montréal have developed GFlowNets, a new way to speed up the process of discovering drugs. Their...
Protein structure is important and should be studied to understand many biological processes and disease progressions. There are many advancements using machine learning techniques,...
When it comes to training and assessing genomic analytic tools, managing differential expression, and investigating data architecture, synthetic data production in omics replicates real-world...
The COVID-19 pandemic has undoubtedly caused a lasting impact on the world. Millions of people worldwide are still struggling with the aftermath of COVID-19,...
Enzymes that have been specially engineered can improve the application of biocatalysts in industrial biotransformations and help address the biotechnological problems of the twenty-first...
Protein design is important for personalized medicine and drug discovery. Generative models for protein structures prove to be especially useful in these areas. Traditional...
The goal of de novo protein design (DNPD) is to build novel protein sequences from scratch without using pre-existing protein templates. Nevertheless, existing deep...
A recent study in the Journal of Clinical Oncology reveals a groundbreaking artificial intelligence (AI) tool, 'DeepHRD', that can predict how vulnerable a cancer...
Personalized Drug Therapy is growing rapidly nowadays. For that, accurate representations of the protein structures are important. Recently, the use of machine learning and...
A major component of the expanding significance of precise nucleic acid quantification in molecular biology is its emphasis on the field's application in genomic...
Recently, Nature Medicine published a pioneering study that has found that protein signatures from blood samples can predict the appearance of over 60 common...
Molecular docking, which predicts the binding configurations between ligands and proteins, is an essential step in the drug discovery process. Advances in deep learning-based...
Scientists from Tencent Quantum Lab and China Pharmaceutical University, China, introduced an innovative hybrid quantum computing pipeline developed to address the challenges of real-world...
Machine learning (ML) is revolutionizing biological waste treatment, addressing long-standing challenges in process stability and product quality. ML's crucial role in optimizing anaerobic digestion,...
Scientists from the University of North Carolina at Charlotte (UNC Charlotte) recently employed an advanced computational technique on the H5N1 virus and its interaction...
The use of directed evolution techniques is essential for sustainability, medicines, and protein research. These techniques, however, struggle to optimize several attributes and are...
Diffusion models are versatile in generative modeling but need fine-tuning for specific applications in Biology to optimize downstream reward functions. Diffusion models are known...
The ground-breaking study introduces functional genomics analysis's foundation model, Genomics-FM. This versatile and data-efficient model overcomes the limitations of traditional AI approaches. Genomics is...
The Stony Brook University scientists tied to the Institute of Chemical Biology and Drug Discovery (ICB & DD) discovered that Fatty Acid Binding Proteins...
Recent advances in chemistry, material science, and biological research have been greatly aided by large language models (LLMs), which act as flexible foundation models...
A team of scientists from the German Center for Neurodegenerative Diseases (DZNE) and Helmholtz AI have conducted an innovative study that presents DrugDiff —...
In computational biology, the ability to predict and design protein structures with atomic precision has been a long-standing goal. Proteins, as the fundamental components...
Researchers from the AI for Science Interdisciplinary Research Center, Northwestern Polytechnical University, China, have introduced a ground-breaking tool that may change how single-cell RNA...
Small molecule drug design depends on protein-ligand interactions, and achieving experimental precision necessitates a wide and well-curated dataset. The scarcity of current datasets makes...
In recent years, the integration of artificial intelligence (AI) and machine learning (ML) into various scientific domains has significantly advanced, and chemistry is no...
Researchers from the Department of Biological Chemistry at Hebrew University, Jerusalem, and the Department of Pharmaceutical Chemistry at the University of California, San Francisco,...
In an effort to provide a comprehensive solution for protein research, researchers present HelixProtX, a system built around the large multimodal model that facilitates...
Antibiotic resistance is increasing as a global problem, meaning previously effective treatments for bacterial infections have ceased to work. It is vital to accurately...
A recent study by Akihisa Osakabe and his colleagues, researchers at the University of Tokyo, elucidated the intriguing dance between plants and their "jumping...
Global environmental concerns and the need for sustainable development require new technologies for producing fine chemicals and managing waste efficiently. Nowadays, using enzymes in...
The rise of antimicrobial resistance has made treating intracellular infections a significant challenge, as conventional antibiotics often fail to neutralize pathogens hidden within human...
Single-molecule Next-Generation Protein Sequencing (NGPS) provides a powerful alternative to mass spectrometry for analyzing protein variants, allowing detailed identification of proteoforms and amino acid...
Cellarity, Inc., and NVIDIA have unveiled MOLRL (Molecule Optimization with Latent Reinforcement Learning), a groundbreaking framework for molecular optimization. This approach leverages the latent...
In an extraordinary feat of chemical synthesis, chemists from Scripps Research have produced 25 picrotoxane molecules. This groundbreaking work combines cutting-edge computational modeling and...
The complex molecular machinery that make up nature, proteins have evolved over billions of years and are essential to the continuation of life. However,...
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies. Read More
This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
Cookie
Duration
Description
cookielawinfo-checkbox-analytics
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional
11 months
The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy
11 months
The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.