Structural Biology

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

AI | Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending
Unlocking the Potential of Equivariant Diffusion Models for Structure-Based Drug Design with DiffSBDD
ByAnchal Negi December 15, 2024October 22, 2026
In the quest to create better and faster methods for drug discovery, a team of innovative researchers from various institutions has developed a groundbreaking technique that leverages equivariant diffusion models for structure-based drug design (SBDD). This study, published in Nature Computational Science by École Polytechnique Fédérale de Lausanne, Switzerland, addresses the growing need for computational…
Read More Unlocking the Potential of Equivariant Diffusion Models for Structure-Based Drug Design with DiffSBDD
AI | Bioinformatics | Deep Learning | LLM | Molecular Dynamics | News | Paper Summary | Trending
Harnessing AI for Molecular Discovery: The Promise of Molecular Dynamics Language Models
ByDeotima Chakraborty December 14, 2024October 22, 2026
Although molecular dynamics (MD) simulations provide accurate representations of the motion of molecular systems, molecular biology and materials science are challenged by the computational demands of these simulations. Since deep learning techniques have proven successful in many domains, it is unclear if they can be used to improve the effectiveness of MD simulations. Researchers from…
Read More Harnessing AI for Molecular Discovery: The Promise of Molecular Dynamics Language Models
AI | News | Paper Summary | Structural Biology
Streamlining High-Throughput Protein Complex Modeling with AlphaPulldown2
ByDeotima Chakraborty December 11, 2024October 22, 2026
AlphaPulldown version 2.0, a noteworthy computational biology program that transforms protein structure modeling, is presented by researchers from the European Molecular Biology Laboratory, Hamburg, and the University of Basel. It offers an automated Snakemake pipeline, advanced data compression techniques, and expanded support for multiple modeling backends. This versatile tool can predict protein interactions efficiently, making…
Read More Streamlining High-Throughput Protein Complex Modeling with AlphaPulldown2
AI | Bioinformatics | Deep Learning | News | Paper Summary | Protein Design | Structural Biology | Tools | Trending
AI-Driven Macrocycle Design: How RFpeptides Generate High-Affinity Protein Binders for Diagnostics and Therapeutics
ByDeotima Chakraborty December 7, 2024October 22, 2026
Large-scale screening techniques that are resource-intensive and offer limited control on binding mode are usually used to produce macrocyclic binders to therapeutic proteins. There are currently no reliable methods for the de novo design of protein-binding macrocycles, despite significant advancements in deep-learning methods for protein design and physics-based methods for peptide design. In this work,…
Read More AI-Driven Macrocycle Design: How RFpeptides Generate High-Affinity Protein Binders for Diagnostics and Therapeutics
AI | Bioinformatics | Deep Learning | News | Paper Summary | PLM | Protein Design | Proteomics | Structural Biology | Tools | Trending
Can InterPLM Decode the Hidden Language of Protein Modeling and Design AI?
ByAnchal Negi December 6, 2024October 22, 2026
The emergence of Protein Language Models (PLMs) is changing biological research for the better through efficient prediction of functional annotations and protein structures. However, the actual features and mechanisms of these models still largely remain unclear. This posed a critical question that sparked the curiosity of Elana Simon and James Zou, who are both researchers…
Read More Can InterPLM Decode the Hidden Language of Protein Modeling and Design AI?
AI | Bioinformatics | Drug Discovery | LLM | News | Paper Summary | Structural Biology | Tools | Trending
Unlocking Chemical Space: TamGen’s Generative AI Approach for Target-Aware Molecule Generation in Drug Discovery
ByDeotima Chakraborty December 1, 2024October 22, 2026
Novel compounds can be discovered in the wide chemical space due to generative drug design that enables one to develop molecules that are effective against their pathogenic target proteins. However, designs tend to focus narrowly on certain specific drug-related qualities, thereby limiting the practicality for which created compounds can be used or their abilities to…
Read More Unlocking Chemical Space: TamGen’s Generative AI Approach for Target-Aware Molecule Generation in Drug Discovery
AI | Bioinformatics | Deep Learning | LLM | News | Paper Summary | Structural Biology | Tools | Trending
RhoFold+: Transforming RNA 3D Structure Prediction with Deep Learning
ByDeotima Chakraborty November 28, 2024October 22, 2026
Although RNA 3D structures are important in understanding their functions and in the design of new drugs, their accurate prediction is still a challenge. Structural flexibility makes computational predictive efforts even more problematic because of the scarcity of experimental input. In this study, researchers from The Chinese University of Hong Kong, Harvard University, Fudan University,…
Read More RhoFold+: Transforming RNA 3D Structure Prediction with Deep Learning
AI | Bioinformatics | Drug Discovery | Machine Learning | News | Paper Summary | PLM | Structural Biology | Tools | Trending
From Concept to Reality: Efficient Protein Pocket Design with PocketGen
ByAnchal Negi November 24, 2024October 22, 2026
Protein pockets have been an integral part of drug discovery for several years and are also targeted during the design of novel molecules. Pockets refer to the parts of proteins where small molecules or ligands would be able to attach and mediate the desired effect. Creating the same, however, has been one of the daunting…
Read More From Concept to Reality: Efficient Protein Pocket Design with PocketGen
AI | Bioinformatics | News | Paper Summary | Protein Design | Proteomics | Structural Biology | Trending
Innovating Through Collaboration: The Protein Engineering Tournament’s Impact on Computational Design
ByNeermita Bhattacharya November 21, 2024October 22, 2026
Protein engineering heavily relies on generating sequences using computational models. Limitations such as lack of benchmarking opportunities, scarcity of large protein function datasets, and limited access to experimental protein characterization slow down the progress in this field. To overcome these challenges, the Protein Engineering Tournament was established to prioritize computational methods in protein engineering. The…
Read More Innovating Through Collaboration: The Protein Engineering Tournament’s Impact on Computational Design
AI | Bioinformatics | Drug Discovery | LLM | Machine Learning | News | Paper Summary | Structural Biology | Tools | Trending
How BALM is Redefining Binding Affinity Prediction for Unseen Targets and Drugs
ByAnchal Negi November 18, 2024October 22, 2026
In the fast-paced world of drug discovery, one of the most crucial aspects is understanding protein-ligand interactions. With the correct algorithms for predicting protein-ligand interactions, effective drug candidates may be recognized much more quickly than through traditional approaches involving costly testing. Researchers from the University of Edinburgh proposed BALM, which stands for Binding Affinity Learning…
Read More How BALM is Redefining Binding Affinity Prediction for Unseen Targets and Drugs
Bioinformatics | Drug Discovery | Molecular Dynamics | News | Paper Summary | Structural Biology | Tools | Trending
Unlock Molecular Conformations with Moltiverse Using Enhanced Sampling Molecular Dynamics Simulations
ByDeotima Chakraborty November 14, 2024October 22, 2026
For drug development to be effective, it is essential to accurately predict the various bound-state conformations of small compounds, especially in situations where intricate protein-ligand interactions are unknown. Although there are established techniques, it is still difficult to efficiently explore the large conformational space. In this work, researchers present Moltiverse, a novel methodology for conformer…
Read More Unlock Molecular Conformations with Moltiverse Using Enhanced Sampling Molecular Dynamics Simulations
AI | Bioinformatics | Drug Discovery | News | Structural Biology | Tools | Trending
AlphaFold3 Goes Open Source: A New Chapter in AI-Powered Protein Science
ByDr. Tamanna Anwar November 12, 2024October 22, 2026
In a significant move for the scientific community, Google DeepMind has finally released the open-source code for AlphaFold3, their groundbreaking protein structure prediction tool. This decision, announced on November 11, marks a crucial shift in accessibility to cutting-edge AI technology in biological research. The Journey to Open Source The path to this release hasn’t been…
Read More AlphaFold3 Goes Open Source: A New Chapter in AI-Powered Protein Science
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
PharmacoNet: Revolutionizing Ultra-Large-Scale Virtual Screening for Drug Discovery with Deep Learning-Powered Pharmacophore Modeling
ByDeotima Chakraborty November 10, 2024October 22, 2026
Virtual screening techniques, which concentrate on binding affinities, are becoming more and more popular for early-stage drug development. Although deep learning-based methods predict binding affinities, limited training data raises questions about their generalization capabilities in large chemical spaces. In this study, scientists from the Department of Chemistry, KAIST, Republic of Korea, provide PharmacoNet, the first…
Read More PharmacoNet: Revolutionizing Ultra-Large-Scale Virtual Screening for Drug Discovery with Deep Learning-Powered Pharmacophore Modeling
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
Beyond Virtual Screening: How Rag2Mol Transforms AI-Driven Drug Discovery
ByAnchal Negi November 8, 2024October 22, 2026
The process of drug discovery has always necessitated a large amount of time and effort as it requires a careful combination of both chemical and biological expertise. Lately, however, the introduction of artificial intelligence and machine learning has changed this paradigm. One such advancement is Rag2Mol, a novel model that aims to improve and facilitate…
Read More Beyond Virtual Screening: How Rag2Mol Transforms AI-Driven Drug Discovery
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
RAPIDDOCK: Revolutionizing Drug Discovery with Transformer-Based High-Speed Molecular Docking
ByDeotima Chakraborty November 6, 2024October 22, 2026
Small molecule drug discovery could be revolutionized by molecular docking tools. Still, current molecular docking methods are slow to screen targets, leading to missed candidates and unexpected side effects in clinical trials, despite the potential benefits of this approach. Researchers from the University of Warsaw and others present RAPIDDOCK, an effective transformer-based model for blind…
Read More RAPIDDOCK: Revolutionizing Drug Discovery with Transformer-Based High-Speed Molecular Docking
AI | Bioinformatics | Machine Learning | News | Paper Summary | Structural Biology | Trending
The Encyclopedia of Domains: Mapping the Diversity of Protein Domains in the AlphaFold Database
ByDeotima Chakraborty November 4, 2024October 22, 2026
Information about the function and three-dimensional structures of proteins can be found in the AlphaFold Protein Structure Database (AFDB). Almost all of the proteins in UniProt have full-length predictions provided by it, demonstrating the intricate connections between domains and folding units. Characterizing 200 million structures is still a struggle, despite AFDB’s potential. Here, researchers introduce…
Read More The Encyclopedia of Domains: Mapping the Diversity of Protein Domains in the AlphaFold Database
AI | Bioinformatics | News | Paper Summary | PPI | Structural Biology | Tools | Trending
Decoding Complex Interactions: How AlphaBridge Enhances Macromolecular Structure Interpretation
ByDeotima Chakraborty November 2, 2024October 22, 2026
Scientists can now model interactions and assess the possibility that proteins will form multimers or interact with other proteins or nucleic acids thanks to artificial intelligence (AI), which is transforming the prediction of macromolecular structures. As a result, there is an increasing demand for effective assessment tools. In this study, researchers from the Netherlands Cancer…
Read More Decoding Complex Interactions: How AlphaBridge Enhances Macromolecular Structure Interpretation
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
DeltaDock: Streamlining Molecular Docking with a Unified, Reliable Framework
ByAnchal Negi October 26, 2024October 22, 2026
DeltaDock is a novel two-stage framework capable of performing molecular docking, which has not been achieved before. It does so by combining the strengths of geometric deep learning (GDL) methods with reliability associated with traditional sampling approaches. The DeltaDock framework incorporates in its architecture a pocket prediction stage followed by a site-centered docking stage. Researchers…
Read More DeltaDock: Streamlining Molecular Docking with a Unified, Reliable Framework
AI | Bioinformatics | Deep Learning | News | Paper Summary | PPI | Structural Biology | Trending
Computing the Human Interactome: A Deep Dive into Protein Interactions
ByAnchal Negi October 16, 2024October 22, 2026
A recent study by a team of researchers has made significant strides in unraveling this complex puzzle of human interaction. The human interactome encompasses all the protein-protein interactions (PPIs) that are essential for protein function and remains an outstanding challenge. It is critical to understand these interactions to understand disease pathology and new effective interventions….
Read More Computing the Human Interactome: A Deep Dive into Protein Interactions
AI | Bioinformatics | News | Structural Biology
The Protein Revolution: 2024 Nobel Prize in Chemistry Pioneers Protein Design and AI-Powered Predictions
ByDr. Tamanna Anwar October 10, 2024October 22, 2026
In a groundbreaking announcement that has sent ripples through the scientific community, the Royal Swedish Academy of Sciences has awarded the 2024 Nobel Prize in Chemistry to three visionaries who have revolutionized our understanding and manipulation of proteins – the fundamental building blocks of life. The Laureates: Architects of Protein Innovation These innovators haven’t just…
Read More The Protein Revolution: 2024 Nobel Prize in Chemistry Pioneers Protein Design and AI-Powered Predictions
AI | Bioinformatics | Machine Learning | News | Paper Summary | Protein Design | Proteomics | Structural Biology | Tools | Trending
ProteusAI: Making Protein Design and Engineering Accessible to All
ByNeermita Bhattacharya October 8, 2024October 22, 2026
Protein structure prediction is a pretty big challenge in the field of bioinformatics as it depends on a multitude of factors. Imagine trying to understand a random paragraph in a novel from just its sentences, without any context of the chapters before it. In the same way, the primary structure (sequence of amino acids) isn’t…
Read More ProteusAI: Making Protein Design and Engineering Accessible to All
AI | Bioinformatics | News | Paper Summary | PPI | Proteomics | Structural Biology | Tools | Trending
BindCraft: Redefining Protein Binder Design with AI and One-Shot Precision
ByDeotima Chakraborty October 8, 2024October 22, 2026
All important biological processes revolve around protein-protein interactions (PPIs’). Designing PPIs’ is difficult, nonetheless, because of the intricate structural characteristics that define them. Researchers propose BindCraft, an automated, open-source workflow with 10–100% experimental success rates for designing new protein binders. BindCraft generates nanomolar binders without the need for high-throughput screening or experimental optimization by using…
Read More BindCraft: Redefining Protein Binder Design with AI and One-Shot Precision
AI | Bioinformatics | Neural Network | News | Paper Summary | Protein Design | Proteomics | Structural Biology | Tools | Trending
The Future of Protein Engineering: Exploring the Potential of CodonMPNN
ByDeotima Chakraborty October 4, 2024October 22, 2026
Making synthetic protein sequences from protein structures is a powerful use of protein engineering technology. It can be challenging to create designed proteins, though, because poor codon sequences can result in low expression rates in organisms like yeast. Scientists from CSAIL-MIT and Harvard Medical School present CodonMPNN, a system that produces a codon sequence conditional…
Read More The Future of Protein Engineering: Exploring the Potential of CodonMPNN
AI | Bioinformatics | Drug Discovery | Learn Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending
MedChem Game: Gamifying Drug Discovery with AI on Your Android
ByNeermita Bhattacharya October 3, 2024October 22, 2026
Improved computational tools and artificial intelligence significantly improve drug discovery. This process has automated activities like molecular docking and predictive modeling to discover candidates for drugs with enhanced efficiency and a better prospect of correct predictions. Thus, several cheminformatics tools are currently untouchable for those without relevant specialized expertise. What if there was a way…
Read More MedChem Game: Gamifying Drug Discovery with AI on Your Android
AI | Bioinformatics | Neural Network | News | Paper Summary | Structural Biology | Tools | Trending
How ChemNet is Revolutionizing Protein-Small Molecule Conformational Modeling
ByDeotima Chakraborty September 30, 2024October 22, 2026
Modeling of protein-small molecule systems offers advantages in speed and generality for exploring interactions with small molecules in the folded state; the modeling of conformational heterogeneity in protein-small molecule systems is deemed an outstanding issue at the atomic level. Researchers from the University of Washington created a graph neural network named ChemNet that was taught…
Read More How ChemNet is Revolutionizing Protein-Small Molecule Conformational Modeling
AI | Bioinformatics | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending
Unleashing the Power of Dynamics: A 4D Diffusion Approach to Protein Structure Prediction
ByDeotima Chakraborty September 25, 2024October 22, 2026
The ability to anticipate the structure of proteins is essential for improving biological research, developing new pharmaceuticals, and designing experiments. It also helps to comprehend the structure-function link of proteins. Protein structures are dynamic, although this fact has not gotten much attention despite the fact that deep learning techniques and the increased availability of experimental…
Read More Unleashing the Power of Dynamics: A 4D Diffusion Approach to Protein Structure Prediction
Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
Unveiling Druggable Pockets with PocketVec: A Comprehensive Approach with Binding Site Descriptors
ByDeotima Chakraborty September 24, 2024October 22, 2026
Target-based drug development depends heavily on characterizing druggable pockets, which are protein areas with the capacity to bind organic small molecules. Nevertheless, the process of obtaining pocket descriptors is complex, and the effectiveness of current approaches is frequently restricted. Researchers present PocketVec, a method for creating pocket descriptors by virtually screening lead-like compounds inversely. PocketVec…
Read More Unveiling Druggable Pockets with PocketVec: A Comprehensive Approach with Binding Site Descriptors
AI | Bioinformatics | Foundation Model | News | Paper Summary | Protein Design | Structural Biology | Tools | Trending
ProteinBench: Unveiling the True Potential of Protein Foundation Models
ByDeotima Chakraborty September 18, 2024October 22, 2026
A notable progress in protein prediction and generative tasks, such as 3D structure prediction, protein design, and conformational dynamics, has been made in recent years with the rapid development of protein foundation models. Nevertheless, the lack of a consistent evaluation methodology means that the potential and constraints of these models are still little understood. Researchers…
Read More ProteinBench: Unveiling the True Potential of Protein Foundation Models
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Protein Design | Structural Biology | Trending
How Are Transformer Models Bridging the Gap Between Data and Drug Discovery?
ByAnchal Negi September 16, 2024October 22, 2026
A recently published work by researchers from the Wuhan Textile University, China, and Michigan State University, USA, has addressed the use of transformer models in the context of drug discovery and related domains. Transformers are deep learning models designed primarily for language-based tasks, and their scope is expanding into various scientific areas. This blog post…
Read More How Are Transformer Models Bridging the Gap Between Data and Drug Discovery?
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending
Unlocking Molecular Dynamics: Dynaformer, a Graph-Based Deep Learning Model for Binding Affinity Prediction
ByCBIRT September 13, 2024October 22, 2026
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 recently, but its limitations remain. This is partly because these methods rely solely on static crystal structures, whereas thermodynamic ensembles between proteins and ligands typically dictate the real binding affinities. Using…
Read More Unlocking Molecular Dynamics: Dynaformer, a Graph-Based Deep Learning Model for Binding Affinity Prediction
Bioinformatics | Drug Discovery | News | Paper Summary | PPI | Proteomics | Structural Biology | Trending
Can We Measure Protein Interactions at Unprecedented Scale? MP3-seq Says Yes!
ByDeotima Chakraborty September 12, 2024October 22, 2026
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 of Washington present a simple, highly scalable yeast two-hybrid method for assessing PPIs called massively parallel PPI measurement by sequencing (MP3-seq). DNA barcodes in MP3-seq are linked to particular protein pairs,…
Read More Can We Measure Protein Interactions at Unprecedented Scale? MP3-seq Says Yes!
AI | Bioinformatics | News | Paper Summary | Protein Design | Structural Biology | Trending
AlphaProteo: Google DeepMind’s AI Revolution in Protein Design
ByDeotima Chakraborty September 9, 2024October 22, 2026
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 by recent approaches, the problem of creating high-affinity binders on demand without requiring repeated rounds of experimental testing has not yet been fully overcome. The first AI system for creating unique,…
Read More AlphaProteo: Google DeepMind’s AI Revolution in Protein Design
AI | Bioinformatics | Computational Models | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Tools | Trending
Breakthrough in Virtual Screening: OpenVS a Game-Changer for AI-Powered Drug Discovery
ByAnchal Negi September 9, 2024October 22, 2026
In a recent study published in Nature Communications, researchers at the University of Washington, University of California, San Francisco, and University of Michigan, along with others, revisited the concept of drug discovery by using an innovative AI-augmented virtual screening tool. Named RosettaVS, this technology merges machine learning approaches with a physical model to provide excellent…
Read More Breakthrough in Virtual Screening: OpenVS a Game-Changer for AI-Powered Drug Discovery
AI | Bioinformatics | Machine Learning | News | Paper Summary | Structural Biology | Tools | Trending
Are We Closer to Mapping the Full Conformational Landscape of Proteins?
ByAnchal Negi September 5, 2024October 22, 2026
Proteins perform enormous tasks in our cells as molecular machines. These functions rely on the structural plasticity or the ability to adopt multiple shapes of the corresponding molecules. This is why knowledge of the conformational flexibility of proteins is very important in their function. A new tool, called Cfold, has been developed by scientists from…
Read More Are We Closer to Mapping the Full Conformational Landscape of Proteins?
AI | Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending
Unlocking Protein Secrets: AlphaFold-SFA’s Breakthrough in Cryptic Pocket Discovery
ByDeotima Chakraborty September 4, 2024October 22, 2026
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 dynamics. The high free energy barrier separating metastable states is the cause of this comprehension gap in these processes. In this work, a novel unsupervised learning technique called slow feature analysis…
Read More Unlocking Protein Secrets: AlphaFold-SFA’s Breakthrough in Cryptic Pocket Discovery
AI | Bioinformatics | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending
Navigating the AlphaFold Universe with DPCstruct’s Domain-Level Classification
ByNeermita Bhattacharya August 30, 2024October 22, 2026
AlphaFold is a database of protein structures and predictions. It contains predictions for ~214 million proteins. AlphaFold2, developed by DeepMind, has dramatically scaled our capability to predict protein structures in silico. The extent of this data is overwhelming, and there are challenges regarding protein annotation, which practically applies to the information. Hence, researchers from the…
Read More Navigating the AlphaFold Universe with DPCstruct’s Domain-Level Classification
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
Revolutionary One-Step Approach: Predicting and Screening Protein-Ligand Complexes with Geometric Deep Learning
ByDeotima Chakraborty August 29, 2024October 22, 2026
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 structure measurement that combines docking and deep learning despite limitations in accuracy and efficiency. Here, researchers demonstrate that a single multi-task geometric deep learning model, LigPose, can accurately handle these two…
Read More Revolutionary One-Step Approach: Predicting and Screening Protein-Ligand Complexes with Geometric Deep Learning
AI | Bioinformatics | LLM | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending
ProteinGPT: Streamlining Complex Protein Analysis Through Conversational AI
ByAnchal Negi August 29, 2024October 22, 2026
ProteinGPT was developed jointly by specialists from the University of California in Los Angeles and the Georgia Institute of Technology and Meta AI. The model is performed on the transformer framework, which has been proven to work on numerous natural language processing applications. As the information revolution progressed within the past few decades, the focus…
Read More ProteinGPT: Streamlining Complex Protein Analysis Through Conversational AI
AI | Bioinformatics | Drug Discovery | LLM | News | Paper Summary | Structural Biology | Trending
Revolutionizing Molecular Representation: A Deep Dive into Fragment and Geometry-Aware Tokenization
ByDeotima Chakraborty August 25, 2024October 22, 2026
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 vast chemical space and complex protein-ligand interactions. The progress of language models (LMs) in NLP is commendable; still, there is much to learn about how LMs can be utilized in SBDD….
Read More Revolutionizing Molecular Representation: A Deep Dive into Fragment and Geometry-Aware Tokenization
Bioinformatics | Biotech | News | Paper Summary | Structural Biology | Trending
A DNA Damage Repair Superhero ‘DdrC’
ByAnchal Negi August 24, 2024October 22, 2026
A recent study published in Nucleic Acids Research has unveiled a critical role played by DdrC. The researchers found out that it can work as a repairer of damages and also a preventer of the same. It acts like a sentry patrolling DNA for damage signs. Researchers have been fascinated by Deinococcus radiodurans for some…
Read More A DNA Damage Repair Superhero ‘DdrC’
AI | Machine Learning | News | Paper Summary | Protein Design | Structural Biology | Tools | Trending
Breaking New Ground in Protein Engineering: Riff-Diff and the Creation of High-Performance Enzymes
ByDeotima Chakraborty August 11, 2024October 22, 2026
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 century. The rotamer inverted fragment finder–diffusion (Riff-Diff) approach, which scaffolds catalytic arrays in de novo protein backbones with customized substrate pockets, is a hybrid machine learning and atomistic modeling technique presented…
Read More Breaking New Ground in Protein Engineering: Riff-Diff and the Creation of High-Performance Enzymes
AI | Bioinformatics | Drug Discovery | News | Paper Summary | PLM | Protein Design | Structural Biology | Tools | Trending
ProseLM’s Novel Approach to Transform Protein Language Models into Powerful Design Tools
ByNeermita Bhattacharya August 9, 2024October 22, 2026
Protein design is important for personalized medicine and drug discovery. Generative models for protein structures prove to be especially useful in these areas. Traditional methods of protein design- for example, Rosetta- do this by solving optimization problems for the sequence that minimizes energy functions. Such methods are often effective but can frequently be very computationally…
Read More ProseLM’s Novel Approach to Transform Protein Language Models into Powerful Design Tools
AI | Bioinformatics | Drug Discovery | News | Paper Summary | PLM | Protein Design | Structural Biology | Tools | Trending
Redefining Protein Engineering: The Role of Natural Language Processing in De Novo Protein Design
ByDeotima Chakraborty August 8, 2024October 22, 2026
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 learning-based DNPD methods are sometimes constrained by their concentration on particular or poorly defined protein designs, which prevents more extensive investigation and the identification of a wide range of useful proteins….
Read More Redefining Protein Engineering: The Role of Natural Language Processing in De Novo Protein Design
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
FeatureDock: Revolutionizing Protein-Ligand Docking with Transformer-Based Local Environment Learning
ByDeotima Chakraborty August 3, 2024October 22, 2026
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 techniques such as DiffDock have demonstrated improved performance in binding pose prediction. Unfortunately, the lack of a clear scoring mechanism in these methods can make it difficult to distinguish between strong…
Read More FeatureDock: Revolutionizing Protein-Ligand Docking with Transformer-Based Local Environment Learning
Bioinformatics | Chromatin | Molecular Dynamics | News | Paper Summary | Structural Biology | Tools | Trending
Exploring Chromatin: How MultiMM Transforms Multiscale Molecular Modeling from Nucleosomes to Genomes
ByNeermita Bhattacharya August 3, 2024October 22, 2026
DNA, the blueprint of life, spans about 2 meters in length. This complexity is similar to stuffing an entire library into a shoebox without crumpling a single page. The complexity of this folding is a subject of immense scientific interest. Modeling this complexity is crucial for understanding gene expression, cellular function, and numerous other biological…
Read More Exploring Chromatin: How MultiMM Transforms Multiscale Molecular Modeling from Nucleosomes to Genomes
Bioinformatics | Drug Discovery | Molecular Dynamics | News | Paper Summary | Structural Biology | Tools | Trending
The Future of Pharma: How Quantum Computing Could Revolutionize Drug Discovery
ByAnchal Negi August 2, 2024October 22, 2026
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 drug discovery. This new approach is expected to transform the pharmaceutical industry by reducing the time to develop drugs and enhancing therapeutic success. The need to create up-to-date medications for intricate…
Read More The Future of Pharma: How Quantum Computing Could Revolutionize Drug Discovery
Bioinformatics | Infectious Diseases | News | Paper Summary | Structural Biology | Trending | Virus
Avian Flu’s Shifting Landscape: What 65 Years of H5 Data Tell Us
ByAnchal Negi July 31, 2024October 22, 2026
Scientists from the University of North Carolina at Charlotte (UNC Charlotte) recently employed an advanced computational technique on the H5N1 virus and its interaction with existing antibodies to analyze 65 years of H5 data. Avian influenza, or H5N1 influenza as often called, has long been a concern for poultry farmers and public health officials. H5N1…
Read More Avian Flu’s Shifting Landscape: What 65 Years of H5 Data Tell Us
AI | Bioinformatics | News | Paper Summary | Structural Biology | Trending
Optimizing Diffusion Models for Biological Applications: A Deep Dive into Reinforcement Learning-based Fine-Tuning
ByNeermita Bhattacharya July 29, 2024October 22, 2026
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 to provide excellent generative modeling capability, but practical applications require generating samples that maximize some desired metric (such as docking score in molecules and stability in proteins). Researchers from Genentech, Princeton…
Read More Optimizing Diffusion Models for Biological Applications: A Deep Dive into Reinforcement Learning-based Fine-Tuning
Bioinformatics | Cancer | Drug Discovery | News | Structural Biology | Trending
Harnessing the Body’s Natural Marijuana: Stony Brook’s New Drug for Pain and Cancer Treatment Gets FDA Clearance
ByDeotima Chakraborty July 28, 2024October 22, 2026
The Stony Brook University scientists tied to the Institute of Chemical Biology and Drug Discovery (ICB & DD) discovered that Fatty Acid Binding Proteins (FABPs) are pharmacological targets of the body’s endocannabinoid system licensed to Artelo Biosciences, Inc. Fatty Acid Binding Proteins (FABPs) were identified as potential pharmacological targets for the treatment of cancer, inflammation,…
Read More Harnessing the Body’s Natural Marijuana: Stony Brook’s New Drug for Pain and Cancer Treatment Gets FDA Clearance
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Protein Design | Structural Biology | Trending
DrugDiff: Harnessing Diffusion Models for Smarter Drug Design
ByAnchal Negi July 27, 2024October 22, 2026
A team of scientists from the German Center for Neurodegenerative Diseases (DZNE) and Helmholtz AI have conducted an innovative study that presents DrugDiff — a unique tool to generate new compounds with different desired molecular properties. This tool will change the face of the early stages of drug development by generating fresh small molecules possessing…
Read More DrugDiff: Harnessing Diffusion Models for Smarter Drug Design

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

Streamlining High-Throughput Protein Complex Modeling with AlphaPulldown2

The Protein Revolution: 2024 Nobel Prize in Chemistry Pioneers Protein Design and AI-Powered Predictions

Training

Services

Resources

Company