Structural Biology

Protein structure prediction, molecular modeling and simulation, and what new structures reveal about biological function.

AI | Bioinformatics | Data Analysis | Genomics | News | OMICS | Structural Biology | Tools | Trending

Rosalind Workbench: OpenAI Connects AI, Genomics, and Scientific Workflows
ByDr. Tamanna Anwar August 29, 2026October 22, 2026

OpenAI has introduced Rosalind Workbench, a new research-preview environment available through the ChatGPT app that brings scientific tools, specialized biology models, and data workflows into a single connected space — letting researchers move from a biological question to inspectable evidence without losing the thread between disconnected tools. Scientific research rarely happens inside a single application….

Read More Rosalind Workbench: OpenAI Connects AI, Genomics, and Scientific Workflows
AI | Bioinformatics | News | Structural Biology | Trending

NovoTags: How AI-Designed Proteins Are Giving Scientists a Sharper View Inside Living Cells
ByDr. Tamanna Anwar August 9, 2026October 22, 2026

Imagine trying to identify every resident of a bustling metropolis from a rooftop, at night, with only a handful of flashlights. That’s essentially the challenge cell biologists face when trying to track individual proteins inside a cell packed with millions of molecular neighbors. A new tool called NovoTags is about to hand researchers a lot…

Read More NovoTags: How AI-Designed Proteins Are Giving Scientists a Sharper View Inside Living Cells
Bioinformatics | News | Paper Summary | PPI | RNA | Trending | Virus

Scientists Reveal How the Influenza A Virus Rewires Human Cells from the Inside
ByAnchal Negi August 8, 2026October 22, 2026

Every winter, the influenza A virus infects millions of people. In a handful of cells, it manages to do something very hard for scientists to observe: it enters a human cell, releases its own genetic material, and starts rewiring almost everything around it. We have known for decades that this rewiring happens, but seeing exactly…

Read More Scientists Reveal How the Influenza A Virus Rewires Human Cells from the Inside
AMR Alert | Drug Discovery | Health | News | Paper Summary | Structural Biology | Trending

Scientists Discover TB’s Metabolic “Control Switch” — A New Target for Tuberculosis Drugs
BySaniya Sayyed July 13, 2026October 22, 2026

The interdisciplinary team, spanning researchers from the University of Surrey, Imperial College London, IISc, and others, discovered Virulence Associated Dikinase (VadK), which evolved from pyruvate phosphate dikinase to histidine kinase. It regulates the methylcitrate cycle used by Mycobacterium tuberculosis to process energy sources from host lipids. Without ΔvadK mutants, the TB bacteria failed to grow…

Read More Scientists Discover TB’s Metabolic “Control Switch” — A New Target for Tuberculosis Drugs
Drug Discovery | Generative Biology | News | Paper Summary | Structural Biology | Tools | Trending

From Fragment to Drug Candidate: How Sesame Uses AI to Build Better Molecules
ByAnchal Negi July 2, 2026October 22, 2026

There’s a moment in drug discovery that every medicinal chemist knows well. You’ve found a hit, a molecule that binds to your target, shows early promise, but isn’t quite ready. It might be too big, too greasy, or just structurally awkward. So you strip it down. You keep the core that’s doing the good work,…

Read More From Fragment to Drug Candidate: How Sesame Uses AI to Build Better Molecules
AI | Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending

DECAF: Genesis AI-Based Framework for Faster and Computationally Efficient All-Atom Protein Cofolding
BySaniya Sayyed June 25, 2026October 22, 2026

The high computational cost of generating accurate atomic-level biomolecular structures remains a major challenge in AI-driven drug discovery. Researchers from Genesis Molecular AI, MIT, Carnegie Mellon University, and Imperial College London have developed DeCAF (Denoiser Cofolding All-Atom Flowmap), a framework that distills diffusion-based cofolding models into faster flow-based models capable of generating high-quality protein and…

Read More DECAF: Genesis AI-Based Framework for Faster and Computationally Efficient All-Atom Protein Cofolding
AI | Big Data | Bioinformatics | Drug Discovery | News | PPI | Structural Biology | Tools | Trending

Boltz Launches BoltzMol-1, BoltzProt-1, and a New API for Small Molecule Hit Discovery and De Novo Binder Design
ByAnchal Negi June 19, 2026October 22, 2026

Drug discovery has always been brutally slow. You pick a target, screen hundreds of thousands of compounds, watch most of them fail, spend months on each experiment, and pray that something sticks. For most research teams, especially in academia, that process is simply out of reach. The cost alone can run into the tens of…

Read More Boltz Launches BoltzMol-1, BoltzProt-1, and a New API for Small Molecule Hit Discovery and De Novo Binder Design
AI | Drug Discovery | Molecular Dynamics | News | Tools | Trending

What If Molecular Simulations Could Run 10,000 Times Faster?
ByAnchal Negi June 17, 2026October 22, 2026

Conventional molecular dynamics (MD) simulations provide atomistic insights into molecular behavior but are fundamentally limited by their femtosecond time steps, making it computationally challenging to capture the slow conformational changes and relaxation processes that drive chemical and biological functions. Addressing this longstanding challenge, researchers at Chalmers University of Technology and the University of Gothenburg in Sweden have…

Read More What If Molecular Simulations Could Run 10,000 Times Faster?
AI | Bioinformatics | LLM | News | Proteomics | Structural Biology | Tools | Trending

BioReason-Pro Allows Structured Reasoning for Protein Function Predictions
BySaniya Sayyed June 12, 2026October 22, 2026

A team of scientists from the University Health Network – Canada’s Hospital, Arc Institute and Vector Institute developed BioReason-Pro to tackle one of the greatest challenges in biology: protein function prediction. Unlike existing AI tools, which give baffling black-box predictions, BioReason-Pro generates structured reasoning that explains why a protein is assigned a function. By integrating…

Read More BioReason-Pro Allows Structured Reasoning for Protein Function Predictions
AI | Machine Learning | News | Paper Summary | Structural Biology | Tools | Trending

PPIscreenML: A Rigorous Machine Learning Approach to Screening Protein-Protein Interactions with AF2
ByAnchal Negi June 11, 2026October 22, 2026

Every second, thousands of proteins inside your cells are bumping into each other, forming fleeting partnerships, and splitting apart again. These protein-protein interactions (PPIs) are the invisible handshakes that keep your heart beating, your immune system fighting, and your DNA replicating. Get them wrong, and disease follows. But here’s the problem: figuring out which proteins…

Read More PPIscreenML: A Rigorous Machine Learning Approach to Screening Protein-Protein Interactions with AF2
AI | News | Paper Summary | PLM | Structural Biology | Tools | Trending

Meet FrustrAI-Seq: Proteome-Wide Frustration Profiling Without Structural Inputs
ByAnchal Negi June 4, 2026October 22, 2026

Proteins are remarkable molecules. They fold, bend, bind, and catalyze, all while balancing an internal tension that most biology textbooks barely mention. That tension has a name: local energetic frustration. And a new study from researchers at Helmholtz Munich, the Technical University of Munich, and the Barcelona Supercomputing Center has just made it dramatically easier…

Read More Meet FrustrAI-Seq: Proteome-Wide Frustration Profiling Without Structural Inputs
AI | Bioengineering | Bioinformatics | LLM | Machine Learning | News | Protein Design | Structural Biology | Trending

How Biologists Can Design Proteins Without Programming Using OpenProtein.AI
BySaniya Sayyed April 23, 2026October 22, 2026

OpenProtein.AI is an open-access platform founded by MIT alumni Tristan Bepler and Tim Lu, which provides open-source AI models and a no-code interface for protein engineering. With a motivation to democratize access to advanced protein language models like PoET and PoET-2, they aim to enable biologists without coding expertise to design and analyze proteins by…

Read More How Biologists Can Design Proteins Without Programming Using OpenProtein.AI
AI | News | Protein Design | Structural Biology | Trending

MIT Researchers Develop VibeGen: An AI Tool that Designs Novel Proteins by Modeling their Dynamics
BySaniya Sayyed April 4, 2026October 22, 2026

Researchers at Mellon University and MIT introduce VibeGen, a generative AI framework for end-to-end de novo protein design conditioned on dynamics. The model generates de novo proteins that not only fold but also exhibit the required dynamics. Proteins and biomolecular structures are the backbones of many functions in our bodies. They catalyze reactions, transmit signals,…

Read More MIT Researchers Develop VibeGen: An AI Tool that Designs Novel Proteins by Modeling their Dynamics
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending

IntelliFold-2: An Open Source Alternative to AlphaFold 3 With Better Accuracy and Robustness
BySaniya Sayyed March 30, 2026October 22, 2026

The innovators behind intelliFold-2 at IntelliGen AI emphasize that IntelliFold-2 is designed as a state-of-the-art open source alternative to AlphaFold3 with stronger performance in therapeutically relevant tasks like antibody-antigen docking and protein-ligand co-folding. The architectural refinements, like latent scaling and atom attention, along with algorithmic innovations such as policy-guided diffusion and difficulty-aware loss reweighting, help…

Read More IntelliFold-2: An Open Source Alternative to AlphaFold 3 With Better Accuracy and Robustness
AI | Bioinformatics | News | Paper Summary | Protein Design | Structural Biology | Tools | Trending

Transforming All-Atom De Novo Design of Protein Using RFdiffusion3
BySaniya Sayyed March 26, 2026October 22, 2026

A major collaboration led by David Baker’s group at the Institute for Protein Design (UW) introduced RFdiffusion3 (RFD3), a next-generation version of the originally developed RFdiffusion. It is a generative diffusion model for general-purpose de novo protein design that works at the all-atom level, allowing precise modelling of hydrogen bonds, ligands, and nucleic acid interactions….

Read More Transforming All-Atom De Novo Design of Protein Using RFdiffusion3
Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending

Beyond the Sequence: How FoldMason is Redefining Multiple Protein Structure Alignment at Scale
BySaniya Sayyed February 4, 2026October 22, 2026

The authors at Seoul National University developed FoldMason, a free, open-source, progressive Multiple Structural Alignment (MSTA) method published in Science that uses a structural alphabet from Foldseek and aligns hundreds of thousands of protein structures. Achieving two orders of magnitude faster than other methods, when applied to Flaviviridae glycoproteins, it supported phylogenetic analysis below the…

Read More Beyond the Sequence: How FoldMason is Redefining Multiple Protein Structure Alignment at Scale
Bioinformatics | Cancer | News | Paper Summary | Structural Biology | Trending

De Novo Peptide Binder Generation: How moPPIt Targets ‘Undruggable’ Proteins
BySaniya Sayyed February 2, 2026October 22, 2026

Authors from the University of Pennsylvania and others innovated the motif-specific PPI targeting algorithm (moPPIt), a computational framework that integrates BindEvaluator along with Multi-Objective Guided Discrete Flow Matching (MOG-DFM) to design peptides that can selectively bind functional motifs without needing structural priors. It works directly from sequence data instead of requiring known 3D structures, making…

Read More De Novo Peptide Binder Generation: How moPPIt Targets ‘Undruggable’ Proteins
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Structural Biology | Tools | Trending

Redefining SBDD: PackDock Speeds Up Accurate Protein-Ligand Docking with Diffusion Models
BySaniya Sayyed January 10, 2026October 22, 2026

Researchers from the University of Shanghai, China, created PackDock, a diffusion-based side-chain packing model that predicts diverse side-chain conformations in protein binding pockets, both with and without ligands. PackDock is compatible with other docking algorithms and achieves near-rigid docking accuracy while being significantly faster than traditional docking methods. The Promise and Limits of Drug Design…

Read More Redefining SBDD: PackDock Speeds Up Accurate Protein-Ligand Docking with Diffusion Models
AI | Bioinformatics | Cancer | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Tools | Trending

Beyond Tertiary Structures: SMRTnet’s Novel Approach to RNA Drug Discovery
ByJainab Shaikh January 8, 2026October 22, 2026

Researchers from Tsinghua University and Peking University in China developed the SMRTnet tool, which employs a deep-learning approach to identify interactions between small molecules and RNA, eliminating the need for RNA tertiary structure information. By combining RNA secondary structure and multimodal neural networks, the research showed that SMRTnet outperformed other prediction tools and validated its…

Read More Beyond Tertiary Structures: SMRTnet’s Novel Approach to RNA Drug Discovery
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending

Designing Protein Binders with BoltzGen: A Unified Generative Approach
BySaniya Sayyed January 3, 2026October 22, 2026

Researchers at MIT introduce an all-atom generative model, BoltzGen. The model incorporates a design specification language that allows researchers to control constraints like covalent bonds, binding sites, and structural motifs for designing proteins and peptides that can bind to diverse biomolecular targets. With strong structural reasoning and state-of-the-art folding performance, BoltzGen is experimentally validated across…

Read More Designing Protein Binders with BoltzGen: A Unified Generative Approach
AI | Bioinformatics | Drug Discovery | LLM | Molecular Dynamics | News | Tools | Trending

Towards Fully Autonomous Molecular Dynamics: The DynaMate Framework
BySaniya Sayyed January 1, 2026October 22, 2026

Researchers from École Polytechnique Fédérale de Lausanne (EPFL) and the National Centre of Competence in Research (NCCR) Catalysis, Switzerland, introduced DynaMate, an autonomous AI system that can fully set up, run, and analyze molecular dynamics simulations for proteins and protein-ligand complexes. DynaMate employs a multi-agent large language model architecture to plan simulation workflows, prepare molecular systems, and…

Read More Towards Fully Autonomous Molecular Dynamics: The DynaMate Framework
AI | Bioinformatics | Drug Discovery | Foundation Model | News | Paper Summary | Structural Biology | Trending

Placing Every Atom Right: PEARL’s Deep Learning Approach to Drug Discovery
ByAnchal Negi December 22, 2025October 22, 2026

Genesis Molecular AI and NVIDIA have introduced PEARL (Placing Every Atom in the Right Location), a deep learning foundation model designed for large-scale protein–ligand cofolding in computational drug discovery. By leveraging synthetic training data, SO(3)-equivariant diffusion architectures, and controllable inference, PEARL achieves more accurate and physically valid binding pose predictions, outperforming AlphaFold 3 and other leading…

Read More Placing Every Atom Right: PEARL’s Deep Learning Approach to Drug Discovery
AI | Bioinformatics | Drug Discovery | Molecular Dynamics | News | Paper Summary | Structural Biology | Tools | Trending

From Boltz-1 to Boltz-2: Did We Finally Bridge the Gap Between Structure and Affinity?
ByDeotima Chakraborty June 10, 2025October 22, 2026

In modern biology, accurately simulating biomolecular interactions is a major difficulty. Our capacity to predict biomolecular complex structures has significantly improved with recent developments like AlphaFold3 and Boltz-1, yet these models are still unable to predict binding affinity, a crucial characteristic that underlies molecular function and therapeutic efficacy. Here, researchers from MIT introduce Boltz-2, a…

Read More From Boltz-1 to Boltz-2: Did We Finally Bridge the Gap Between Structure and Affinity?
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Trending

D-I-TASSER Outperforms AlphaFold? A New Frontier in Protein Structure Modeling
ByDeotima Chakraborty May 29, 2025October 22, 2026

The requirement and utility of conventional force field-based folding simulations have been called into question by the overwhelming success of deep learning techniques in protein structure prediction. Researchers from the University of Michigan and the National University of Singapore presented a hybrid method called deep-learning-based iterative threading assembly refinement (D-I-TASSER), which combines iterative threading fragment…

Read More D-I-TASSER Outperforms AlphaFold? A New Frontier in Protein Structure Modeling
Bioinformatics | Drug Discovery | News | Paper Summary | Protein Design | Structural Biology | Tools | Trending

Unlocking Biomolecular Secrets with AF3Score: A Leap Forward in Structural Evaluation
ByAnchal Negi May 26, 2025October 22, 2026

Researchers from Changping Laboratory in Beijing introduced AF3Score, a novel adaptation of AlphaFold3 designed to evaluate biomolecular structures with unprecedented accuracy. This innovation addresses a critical gap in computational biology: the need for reliable, unbiased scoring methods to assess the quality of protein structures, complexes, and designed biomolecules. By reimagining AlphaFold3’s architecture, the team created…

Read More Unlocking Biomolecular Secrets with AF3Score: A Leap Forward in Structural Evaluation
AI | Bioinformatics | News | Paper Summary | Protein Design | Structural Biology | Trending

Overlapping Genes, Unfolding Insights: Synthetic Biology Meets AI
ByDeotima Chakraborty May 22, 2025October 22, 2026

Given that the sharing of codon nucleotides dramatically reduces the size of protein sequences, viruses in nature often generate overlapping genes (OLG) in alternate reading frames of the same nucleotide sequence. The question of whether amino acid sequences are sufficiently degenerate with regard to protein folding to permit the extensive overlap of arbitrary pairs of…

Read More Overlapping Genes, Unfolding Insights: Synthetic Biology Meets AI
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Trending

PhysDock: A New Era in Protein-Ligand Docking with AI and Physics
ByAnchal Negi May 19, 2025October 22, 2026

In a breakthrough that could transform drug discovery, a team of researchers from ShanghaiTech University has introduced PhysDock, a novel AI-powered model designed to predict how small molecules (ligands) bind to proteins with atomic-level precision. Protein-ligand docking plays a central role in structure-based drug design. It helps researchers understand how drugs interact with their biological…

Read More PhysDock: A New Era in Protein-Ligand Docking with AI and Physics
AI | Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending

Advancing Enzyme Design: RFdiffusion2 Enables Atomic-Level Scaffold Generation
ByDeotima Chakraborty May 15, 2025October 22, 2026

In de novo enzyme design, the functional groups surrounding reaction transition states are described in the optimal active site. There are drawbacks to the generative AI technique RFdiffusion, which has been used to build highly active enzymes. The active site’s geometry can only be defined at the residue level, necessitating the construction of side chain…

Read More Advancing Enzyme Design: RFdiffusion2 Enables Atomic-Level Scaffold Generation
AI | Bioinformatics | Data Analysis | Drug Discovery | Education | Genomics | Machine Learning | News | Structural Biology | Tools | Trending

45 Days Hands-on Skill Development Summer Training/Internship on “From Base Pairs to Big Data: Bioinformatics Bootcamp for the Next Generation”
ByCBIRT May 3, 2025October 22, 2026

Are you ready to transform your understanding of bioinformatics and gain hands-on experience with cutting-edge tools and technologies? The Centre of Bioinformatics Research & Technology (CBIRT) is thrilled to announce its Summer Training/Internship Program—From Base Pairs to Big Data: Bioinformatics Bootcamp for the Next Generation. This intensive 1.5-month program (15 May to 30 June 2025) is designed to equip students…

Read More 45 Days Hands-on Skill Development Summer Training/Internship on “From Base Pairs to Big Data: Bioinformatics Bootcamp for the Next Generation”
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Trending

Building Better Models: How AI and Experimentation Shape GPCR Research in AlphaFold Era
ByDeotima Chakraborty April 30, 2025October 22, 2026

The GPCR Dock competitions are a set of community-wide evaluations of ligand docking and computational structural modeling for G protein-coupled receptors, a key class of therapeutic targets in the human proteome. To shape and guide the development of computational modeling approaches for GPCRs, the assessments are intended to offer an objective summary of advancements and…

Read More Building Better Models: How AI and Experimentation Shape GPCR Research in AlphaFold Era
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Trending

Fast, Accurate, and Flexible: How FLOWR is Transforming Molecular Design
ByAnchal Negi April 23, 2025October 22, 2026

In a recent breakthrough in AI-driven drug discovery, researchers from Pfizer, AstraZeneca, and Chalmers University unveiled a new generative framework called FLOWR, designed to revolutionize structure-based ligand generation. Their collaborative work bridges machine learning, computational chemistry, and pharmaceutical research and is set to address some of the most persistent challenges in early-stage drug design. Why…

Read More Fast, Accurate, and Flexible: How FLOWR is Transforming Molecular Design
Bioinformatics | Drug Discovery | News | Paper Summary | Protein Design | Structural Biology | Trending

Designer Miniproteins: New Frontier in GPCR-Targeted Drug Development
ByDeotima Chakraborty April 14, 2025October 22, 2026

G protein-coupled receptors (GPCRs) are essential membrane proteins with dynamic conformations that are also major targets for drug development and discovery. However, designing protein agonists and antagonists has proven difficult. In this article, researchers outline computational de novo design techniques and a high throughput “receptor diversion” microscopy-based screen for producing GPCR binding miniproteins with high…

Read More Designer Miniproteins: New Frontier in GPCR-Targeted Drug Development
AI | Bioinformatics | Deep Learning | Drug Discovery | Molecular Dynamics | News | Paper Summary | Structural Biology | Trending

MolAI: The Deep Learning Model Transforming Molecular Descriptor Generation
ByAnchal Negi April 12, 2025October 22, 2026

Recent years have witnessed significant advancements in the fields of artificial intelligence (AI) and machine learning (ML), catalyzing a revolution in cheminformatics and drug discovery. These advancements have enabled scientists to predict molecular properties, design novel compounds with desired characteristics, and estimate drug/bio-macromolecular interactions with unprecedented accuracy. At the heart of these breakthroughs lies the…

Read More MolAI: The Deep Learning Model Transforming Molecular Descriptor Generation
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending

Dyna-1: Unraveling Protein Dynamics with Deep Learning and NMR Data
ByDeotima Chakraborty April 5, 2025October 22, 2026

There are more than 100 NMR relaxation datasets in the Biological Magnetic Resonance Data Bank (BMRB), which show an observable motion in µs-ms. NMR signals can be broadened beyond detection by millisecond motions, leaving residues unassigned in chemical shift datasets of about 10,000 proteins. Deep learning models were taught to predict missing assignments caused by…

Read More Dyna-1: Unraveling Protein Dynamics with Deep Learning and NMR Data
AI | Bioinformatics | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Tools | Trending

UNC Researchers Unveil DELi, a Powerful Open-Source Tool for DNA-Encoded Library Informatics
ByAnchal Negi March 22, 2025October 22, 2026

The entire process of drug discovery costs more than a billion dollars and takes over a decade to complete. This is an expensive and time-consuming process. However, to help improve efficiency, DNA Encoded Library (DEL) technology has been introduced, which enables researchers to screen billions of small molecules for possible drug candidates. The most challenging…

Read More UNC Researchers Unveil DELi, a Powerful Open-Source Tool for DNA-Encoded Library Informatics
AI | Bioinformatics | Deep Learning | News | Paper Summary | Protein Design | RNA | Structural Biology | Tools

RNA-BAnG: A Deep Learning Breakthrough for Designing Protein-Binding RNA Sequences
ByDeotima Chakraborty March 19, 2025October 22, 2026

One of the most significant challenges in computational and experimental biology is creating RNA molecules that interact with particular proteins. The practical use of current computational methods is limited by their requirement for a significant number of empirically confirmed RNA sequences for every individual protein or a thorough understanding of RNA structure. Researchers have developed…

Read More RNA-BAnG: A Deep Learning Breakthrough for Designing Protein-Binding RNA Sequences
AI | Bioinformatics | Machine Learning | Molecular Dynamics | News | Paper Summary | Structural Biology | Tools | Trending

Microsoft’s BioEmu-1: A Game Changer for Protein Dynamics and Drug Discovery
ByDeotima Chakraborty March 5, 2025October 22, 2026

Microsoft researchers introduce BioEmu-1, an updated version of BioEmu that advances the knowledge of how proteins function by offering a window into the diverse range of structures that each protein can take on or structural ensembles. BioEmu is a generative deep learning system that tackles the scientific challenge of forecasting dynamical dynamics in proteins following…

Read More Microsoft’s BioEmu-1: A Game Changer for Protein Dynamics and Drug Discovery
AI | Bioinformatics | Chromatin | Foundation Model | News | Paper Summary | Structural Biology | Tools | Trending

MIT’s ChromoGen: A Diffusion Model for DNA Sequence to 3D Structure Prediction in Minutes
ByDeotima Chakraborty February 19, 2025October 22, 2026

Microscopic imaging and high-throughput sequencing methods show that chromatin structures differ greatly between cells, although characterization is still difficult because of the labor-intensive nature of the investigations. Researchers from the Massachusetts Institute of Technology present ChromoGen, a generative model that effectively predicts three-dimensional, single-cell chromatin conformations de novo with both region and cell type specificity….

Read More MIT’s ChromoGen: A Diffusion Model for DNA Sequence to 3D Structure Prediction in Minutes
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools

NuFold: A Revolutionary Leap in RNA Tertiary Structure Prediction
ByAnchal Negi February 1, 2025October 22, 2026

RNA, often overshadowed by its protein counterpart, plays an essential role in the molecular machinery of life. Predicting RNA’s three-dimensional (3D) structure is a vital challenge in understanding its function, but it’s a task riddled with complexities. Enter NuFold, an innovative RNA structure prediction method that promises to advance our understanding of RNA folding mechanisms….

Read More NuFold: A Revolutionary Leap in RNA Tertiary Structure Prediction
AI | Bioinformatics | Molecular Dynamics | News | Paper Summary | Structural Biology | Tools | Trending

MDGEN: Unlocking New Frontiers in Molecular Dynamics with Generative AI
ByDeotima Chakraborty January 29, 2025October 22, 2026

As a paradigm for developing adaptable multi-task surrogate models of MD from data, researchers from the Massachusetts Institute of Technology present generative modeling of molecular trajectories. Researchers demonstrate how such generative models can be tailored to a variety of tasks, including forward simulation, transition path sampling, and trajectory upsampling, by conditioning on carefully selected frames…

Read More MDGEN: Unlocking New Frontiers in Molecular Dynamics with Generative AI
Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending

Enhancing Drug Discovery with NRGSuite-Qt: A PyMOL Plugin for Virtual Screening and Docking
ByAnchal Negi January 28, 2025October 22, 2026

Drug discovery and protein engineering are some of the most challenging aspects of cutting-edge scientific research. It is also a field that holds great promise in addressing some of the burning issues in global healthcare. Unfortunately, the intricacies of protein molecule interactions, dynamics, and the effects of mutations are exceedingly painstaking and slow. Researchers from…

Read More Enhancing Drug Discovery with NRGSuite-Qt: A PyMOL Plugin for Virtual Screening and Docking
AI | Bioinformatics | Cancer Research | Genomics | News | Paper Summary | Structural Biology | Tools | Trending

IRB Barcelona Unveils Oncodrive3D to Identify Cancer Driver Genes Using 3D Protein Structures
ByDeotima Chakraborty January 25, 2025October 22, 2026

Finding the genes that can cause tumors in various tissues is one of the main objectives of cancer genomics. Computational techniques that use various positive selection signals in the pattern of gene mutations seen in tumors have been created for this goal. One indication of positive selection is the accumulation of mutations in regions of…

Read More IRB Barcelona Unveils Oncodrive3D to Identify Cancer Driver Genes Using 3D Protein Structures
AI | Bioinformatics | News | Paper Summary | PLM | Proteomics | Structural Biology | Trending

Exploring the Uncharted: How FoldTuned Language Models Reveal Hidden Sequence-Structure Insights
ByDeotima Chakraborty January 22, 2025October 22, 2026

The study of the entire protein sequence-structure map has historically been hampered by the combinatorial scale of amino acid sequence space. The wide unexplored landscape of far-from natural sequences that appear to have escaped evolution but are consistent with the principles of biophysics is not yet known. Experimental methods such as directed evolution are not…

Read More Exploring the Uncharted: How FoldTuned Language Models Reveal Hidden Sequence-Structure Insights
AI | Bioinformatics | Deep Learning | News | Paper Summary | Protein Design | Structural Biology | Trending

University of Washington Researchers Revolutionize Beta-Barrel and Transmembrane Nanopore Design Using Deep Learning Tools
ByDeotima Chakraborty January 11, 2025October 22, 2026

A team of researchers from the University of Washington has made significant strides in protein design by addressing long-standing challenges in creating beta-barrel structures. Using advanced deep learning tools, including RoseTTAFold-based design techniques, the team successfully developed transmembrane nanopores with conductances ranging from 200 to 500 pS. This innovative approach combines the precision of parametric…

Read More University of Washington Researchers Revolutionize Beta-Barrel and Transmembrane Nanopore Design Using Deep Learning Tools
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending

Scaling Structure-Based Molecular Design with ECloudGen’s Electron Cloud Approach
ByAnchal Negi January 7, 2025October 22, 2026

In a groundbreaking step toward more effective molecular design, researchers from Zhejiang University and others have introduced ECloudGen, a cutting-edge framework that integrates quantum chemistry with deep learning. This innovative approach focuses on utilizing electron clouds as latent variables to unlock new possibilities in structure-based molecular design. Understanding the Role of Electron Clouds in Chemistry…

Read More Scaling Structure-Based Molecular Design with ECloudGen’s Electron Cloud Approach
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending

MIT Unveils Boltz-1: An Open-Source Tool for Biomolecular Structure Prediction
ByDeotima Chakraborty January 4, 2025October 22, 2026

Developing an understanding of biomolecular interactions is essential for developing domains such as protein design and drug development. The open-source deep learning model Boltz-1, which researchers from MIT present in this research, combines advances in model design, speed optimization, and data processing to predict the 3D structures of biomolecular complexes with an accuracy of AlphaFold3….

Read More MIT Unveils Boltz-1: An Open-Source Tool for Biomolecular Structure Prediction
AI | Antibiotic Resistance | Big Data | Bioinformatics | Drug Discovery | Genomics | LLM | News | Protein Design | Structural Biology | Trending

Top 10 Bioinformatics Breakthroughs of 2024!
ByDr. Tamanna Anwar January 1, 2025October 22, 2026

In 2024, bioinformatics has once again proven to be a cornerstone of innovation, driving discoveries that are reshaping our understanding of life at a molecular level. Did you know that the number of genetic variants uncovered this year alone surpassed expectations by millions? These breakthroughs are paving the way for revolutionary applications in healthcare, drug…

Read More Top 10 Bioinformatics Breakthroughs of 2024!
AI | Bioinformatics | Deep Learning | Molecular Dynamics | News | Paper Summary | Tools | Trending

Predicting Protein Dynamics with BioEmu: A New Frontier in Biomolecular Research
ByDeotima Chakraborty December 24, 2024October 22, 2026

A major field of study is the scientific problem of predicting dynamical mechanisms in proteins after structural revolutions, with molecular dynamics simulations offering important information on conformational states and binding configurations. In this work, researchers from Microsoft Research create a generative deep learning system called Biomolecular Emulator (BioEmu), which can produce thousands of statistically distinct…

Read More Predicting Protein Dynamics with BioEmu: A New Frontier in Biomolecular Research
AI | Bioinformatics | Machine Learning | News | Paper Summary | Structural Biology | Tools | Trending

How Does NeuralPLexer3 Combine Physics and Machine Learning for Superior Biomolecular Predictions?
ByAnchal Negi December 22, 2024October 22, 2026

The quest to understand biomolecular interactions is central to advancing drug discovery, molecular biology, and bioengineering. A significant step in this journey is accurately predicting the 3D structures of biomolecular complexes. Researchers from Iambic Therapeutics recently unveiled NeuralPLexer3 (NP3), a groundbreaking model designed to set a new benchmark in structure prediction by leveraging flow-based models….

Read More How Does NeuralPLexer3 Combine Physics and Machine Learning for Superior Biomolecular Predictions?
AI | Bioinformatics | News | Paper Summary | Protein Design | Structural Biology | Tools | Trending

Unlocking Protein Design with PLAID: A Sequence-Centric Generative Model for All-Atom Structures
ByDeotima Chakraborty December 18, 2024October 22, 2026

The potential influence of generative models for protein design is drawing the attention of the scientific world. However, there are numerous modalities that mediate protein activity, and it is still difficult to generate multiple modalities at once. A technique for multimodal protein synthesis called PLAID (Protein Latent Induced Diffusion) has been proposed by researchers from…

Read More Unlocking Protein Design with PLAID: A Sequence-Centric Generative Model for All-Atom Structures

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.

Structural Biology

RNA-BAnG: A Deep Learning Breakthrough for Designing Protein-Binding RNA Sequences

NuFold: A Revolutionary Leap in RNA Tertiary Structure Prediction

Training

Services

Resources

Company