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Breakthrough in Virtual Screening: OpenVS a Game-Changer for AI-Powered Drug Discovery

In a recent study published in Nature Communications, researchers at the University of Washington, University of California, San Francisco, and University of Michigan, along...

Shaping the Future of Enzyme Catalysis: Advances in the Computational Design of Serine Hydrolases

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...

How Scripps Research Is Pioneering New Approaches to Slow Cancer Growth

To fight cancer, we must stop their metastasis or uncontrolled multiplication. Hence, it is important to understand what proteins these cancer cells need for...

Are We Closer to Mapping the Full Conformational Landscape of Proteins?

Proteins perform enormous tasks in our cells as molecular machines. These functions rely on the structural plasticity or the ability to adopt multiple shapes...

Unlocking Protein Secrets: AlphaFold-SFA’s Breakthrough in Cryptic Pocket Discovery

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...

Navigating the AlphaFold Universe with DPCstruct’s Domain-Level Classification

AlphaFold is a database of protein structures and predictions. It contains predictions for ~214 million proteins. AlphaFold2, developed by DeepMind, has dramatically scaled our...

Revolutionary One-Step Approach: Predicting and Screening Protein-Ligand Complexes with Geometric Deep Learning

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: Streamlining Complex Protein Analysis Through Conversational AI

ProteinGPT was developed jointly by specialists from the University of California in Los Angeles and the Georgia Institute of Technology and Meta AI. The...

CellTracksColab: A Breakthrough Platform for Cell Tracking Data Analysis

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...

WebAtlas: A Powerful Tool for Integrated Single Cell and Spatial Transcriptomic Data Analysis

A recent study by Tong Li and colleagues from the Wellcome Sanger Institute and other institutions introduces WebAtlas, an innovative pipeline aimed at addressing...

DeepEnzyme Improves Enzyme Turnover Prediction Accuracy Leveraging Deep Learning and Protein 3D-Structure Features

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...

Streamlining Gene Identification: UnigeneFinder’s Automated Approach to Reference-Free Transcriptome Analysis

The availability of genome data is of great importance in this day and age. But, transcriptome data (which is a subset of the entire...

Revolutionizing Molecular Representation: A Deep Dive into Fragment and Geometry-Aware Tokenization

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...

A DNA Damage Repair Superhero ‘DdrC’

A recent study published in Nucleic Acids Research has unveiled a critical role played by DdrC. The researchers found out that it can work...

Revolutionizing Drug Discovery: Predicting Pharmacokinetics from SMILES Using Diffusion Models and Deep Learning

The use of artificial intelligence (AI) in all phases of medication development is growing rapidly. Drug pharmacokinetic (PK) datasets are frequently acquired independently of...

Breaking Down Cancer Genomes: The Innovative Visualization Toolkit GenomeSpy

Trying to visualize available genomic data is of great interest. Currently, there exists a lot of specialized visualization tools, but most need to be...

Oxford Researchers Breakthrough in Predicting Protein Function from Sequence Alone Using Statistics-Informed Graph Networks

Understanding the complex mechanisms behind many essential biological activities is essential for developing new drugs and has broad ramifications in the disciplines of biotechnology,...

Shaping the Future of Drug Design: GFlowNets and Cell Morphology-Guided Approach

Scientists from McGill University, Genentech, and Université de Montréal have developed GFlowNets, a new way to speed up the process of discovering drugs. Their...

Unleashing the Power of Protein Language Models for Accurate Peptide Sequencing

Protein structure is important and should be studied to understand many biological processes and disease progressions. There are many advancements using machine learning techniques,...

Exploring PreciousGPT: A Revolutionary Approach to Artificial Multi-Omics Sample Generation Across Species and Tissues

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...

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How Are Transformer Models Bridging the Gap Between Data and Drug Discovery?

How Are Transformer Models Bridging the Gap Between Data and Drug Discovery?

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A recently published work by researchers from the Wuhan Textile University, China, and Michigan State University, USA, has addressed the use of transformer models...
Unlocking Molecular Dynamics: Dynaformer, a Graph-Based Deep Learning Model for Binding Affinity Prediction

Unlocking Molecular Dynamics: Dynaformer, a Graph-Based Deep Learning Model for Binding Affinity Prediction

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One major obstacle in structure-based drug design is accurately predicting the affinities of protein-ligand interaction. The accuracy of data-driven affinity prediction methods has improved...
Can We Measure Protein Interactions at Unprecedented Scale? MP3-seq Says Yes!

Can We Measure Protein Interactions at Unprecedented Scale? MP3-seq Says Yes!

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Numerous biological processes are regulated by protein-protein interactions (PPIs), and modified PPIs have uses in gene and cell therapy. Here, researchers from the University...
ChatMol: Pioneering Conversational Molecular Design with AI

ChatMol: Pioneering Conversational Molecular Design with AI

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ChatMol, an innovative AI model designed by Tsinghua University, PingAn Technology, and Beijing University of Posts and Telecommunications researchers, shapes the contours of the...
AlphaProteo: Google DeepMind's AI Revolution in Protein Design

AlphaProteo: Google DeepMind’s AI Revolution in Protein Design

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Protein-binding protein computational design is a key skill with many applications in biotechnology and biological research. While some target proteins have been successfully targeted...