Structural Biology

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

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Unleash the Power of PPI3D: A Comprehensive Web Server to Explore, Analyze, and Model Protein-Protein, Protein-Peptide, and Protein-Nucleic Acid Interactions
ByDeotima Chakraborty April 18, 2024October 22, 2026
Understanding molecular mechanisms requires an understanding of protein interactions with nucleic acids. Researchers can query preprocessed and clustered structural data, analyze the data, and draw conclusions about protein interactions based on homology using the PPI3D web server. All interactions for proteins homologous to the query, interactions between two proteins or their homologs, and interactions within…
Read More Unleash the Power of PPI3D: A Comprehensive Web Server to Explore, Analyze, and Model Protein-Protein, Protein-Peptide, and Protein-Nucleic Acid Interactions
AI | Bioinformatics | Drug Discovery | Machine Learning | Neural Network | News | Paper Summary | Structural Biology | Trending
Smart Sampling for Smarter Drugs: How Active Learning Boosts Drug Discovery
ByDeotima Chakraborty April 16, 2024October 22, 2026
In computational drug discovery, active learning (AL) is a potent approach that makes it possible to identify the best binders from large chemical libraries. To get the best results, designing a strong AL methodology necessitates an understanding of AL parameters and data set properties. In order to systematically assess the efficacy of machine learning models…
Read More Smart Sampling for Smarter Drugs: How Active Learning Boosts Drug Discovery
Bioinformatics | Drug Discovery | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending
Meet PiMine: A Database-Driven Approach for Protein-Protein Interface Similarity Detection
ByAnshika Gupta March 30, 2024October 22, 2026
Researchers at Universität Hamburg introduced PiMine, an application that senses structurally related protein-protein interfaces while being driven by a database. PiMine analyzes these interfaces, which are sources of information about protein function and are also important in drug discovery. It distinguishes itself from other programs by the ability to scrutinize interfaces in terms of structural…
Read More Meet PiMine: A Database-Driven Approach for Protein-Protein Interface Similarity Detection
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Precision Medicine | Structural Biology | Tools | Trending
Brown University’s Subsampled AlphaFold2 Approach for Predicting Protein Dynamics: A Game-changer for Drug Discovery?
ByAnchal Negi March 30, 2024October 22, 2026
Proteins are life’s molecular workhorses and play crucial roles in every biological process. Understandably, their complex shapes, also known as conformations, are the key that unlocks their secrets to new drug development. Proteins are not still statues but rather change into different conformations like ninjas to play different functions. This movement of protein has been…
Read More Brown University’s Subsampled AlphaFold2 Approach for Predicting Protein Dynamics: A Game-changer for Drug Discovery?
Bioinformatics | Chemoinformatics | Computational Models | Drug Discovery | News | Paper Summary | Protein Design | Structural Biology | Tools | Trending
Unlocking New Drug Targets: Researchers Develop Computational Method to Target Proteins Inside Cell Membranes
ByAnchal Negi March 28, 2024October 22, 2026
Can you imagine that you can design proteins that have a particular function, and they are like small robots working inside our cells? This may be the reality pretty soon. Researchers from the University of California and Yale University came up with an innovative way of creating transmembrane proteins from scratch, thus leading to targeted…
Read More Unlocking New Drug Targets: Researchers Develop Computational Method to Target Proteins Inside Cell Membranes
Bioinformatics | Drug Discovery | News | Paper Summary | Proteomics | Structural Biology | Trending
A New Era in Enzyme Design: How NeuroFold Integrates Multimodal Data for Enzyme Variants Generation
ByDeotima Chakraborty March 23, 2024October 22, 2026
The main obstacle in protein engineering is the lack of diversity in training data, which makes it difficult to create high-performance enzyme variations with the desired characteristics and emphasizes the need for better techniques. Here, scientists present a cutting-edge method known as neurofold that overcomes these drawbacks and greatly increases the yield of functioning enzyme…
Read More A New Era in Enzyme Design: How NeuroFold Integrates Multimodal Data for Enzyme Variants Generation
AI | Bioinformatics | Covid-19 News | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending
Creating Antibodies from Scratch: Scientists Design Single-Domain Antibodies with Atomic Precision Using AI
ByDeotima Chakraborty March 21, 2024October 22, 2026
The inability to logically design new antibodies that bind a particular epitope on a target persists despite the crucial role that antibodies play in contemporary medicine. Instead, time-consuming animal immunization procedures or library screening techniques are currently used in antibody development. Here, scientists from the University of Washington show that user-specified epitopes can be bound…
Read More Creating Antibodies from Scratch: Scientists Design Single-Domain Antibodies with Atomic Precision Using AI
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending
Basecamp Research Introduces BaseFold: A New Deep Learning Approach to Protein Structure Prediction
ByDeotima Chakraborty March 17, 2024October 22, 2026
Scaling laws predict the presence of over a trillion species on our planet. However, only a small fraction of them have been studied. Deep learning models applied for work in life sciences generally depend on the size and quality of training or reference datasets. The study suggests a data-centric strategy to improve deep learning models…
Read More Basecamp Research Introduces BaseFold: A New Deep Learning Approach to Protein Structure Prediction
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Trending
Exploring the Boundless Frontiers of Biomolecular Modeling and Design with RoseTTAFold All-Atom
ByDeotima Chakraborty March 14, 2024October 22, 2026
Models like AlphaFold2 (AF2) and RoseTTAFold, a modified structural biology tool, have not been able to replicate well the interactions or covalent changes with tiny molecules that are essential to biological activity. Here, researchers from the University of Washington describe RoseTTAFold All-Atom (RFAA), a deep network that, given the sequences of the polymers and the…
Read More Exploring the Boundless Frontiers of Biomolecular Modeling and Design with RoseTTAFold All-Atom
AI | Bioinformatics | LLM | News | Paper Summary | Structural Biology | Trending
Unveiling the Potential of RiNALMo: Advancing RNA Structure Prediction with General-Purpose RNA Language Models
ByDeotima Chakraborty March 8, 2024October 22, 2026
Numerous fundamental functions of ribonucleic acid (RNA) are involved in basic biological processes. It is imperative that we deepen our comprehension of the structures and activities of RNA, as it has emerged as an intriguing target for pharmaceuticals in recent times. Sequencing technologies have yielded vast amounts of unlabeled RNA data throughout the years, concealing…
Read More Unveiling the Potential of RiNALMo: Advancing RNA Structure Prediction with General-Purpose RNA Language Models
AI | Bioinformatics | Chemoinformatics | Computational Models | Drug Discovery | News | Paper Summary | Structural Biology | Trending
Microsoft Reveals ViSNet: A Cutting-Edge Framework for Molecular Property Prediction and Simulating Molecular Dynamics
ByAnchal Negi March 7, 2024October 22, 2026
Molecular geometry modeling, which involves building models that show the spatial arrangement of atoms in a molecule, usually helps with this understanding. The field of molecular modeling has been transformed by geometric deep learning. However, due to molecules’ inherent 3D shape and the intricate interactions between their constituent atoms, standard deep learning algorithms need help…
Read More Microsoft Reveals ViSNet: A Cutting-Edge Framework for Molecular Property Prediction and Simulating Molecular Dynamics
AI | Bioinformatics | Computational Models | Neural Network | News | Paper Summary | Structural Biology | Trending
Revolutionizing Protein-Nucleic Acid Binding Prediction with PNAbind: A Graph Neural Network Approach
ByDeotima Chakraborty March 6, 2024October 22, 2026
The geometric characteristics of protein-nucleic acid complexes, which are explored using structural models, are crucial for proteins to recognize and bind nucleic acids. However, these features are limited when compared to unbound proteins. PNAbind is a deep learning method that the University of Southern California researchers have developed for predicting protein-nucleic acid (protein-NA) binding based…
Read More Revolutionizing Protein-Nucleic Acid Binding Prediction with PNAbind: A Graph Neural Network Approach
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Structural Biology | Trending
PocketGen: A Novel Deep Generative Model for Designing Protein Binding Sites
ByDr. Tamanna Anwar March 1, 2024October 22, 2026
The ability to accurately model and redesign ligand binding sites (pockets) on protein surfaces holds tremendous value across fields like drug discovery, enzyme engineering, and biosensing. However, effectively generating protein pockets tailored to recognize user-defined small molecules has remained challenging. Recent research from the University of Science and Technology of China details PocketGen – an…
Read More PocketGen: A Novel Deep Generative Model for Designing Protein Binding Sites
AI | Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending
AlphaFLOW and ESMFLOW: A New Approach to Modeling Protein Ensembles with Combined Power of AlphaFold and Flow Matching
ByDeotima Chakraborty February 28, 2024October 22, 2026
Dynamic structural ensembles play a major role in the biological functions of proteins. For the purpose of learning and sampling the conformational landscapes of proteins, researchers create a flow-based generative modeling technique in this work. Sequence-conditioned generative models of protein structure are produced by optimizing the highly accurate single-state predictor AlphaFold technique within a unique…
Read More AlphaFLOW and ESMFLOW: A New Approach to Modeling Protein Ensembles with Combined Power of AlphaFold and Flow Matching
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
Unlocking New Frontiers in Drug Design with PCMol: Integrating AlphaFold and De Novo Approaches
ByDeotima Chakraborty February 24, 2024October 22, 2026
Deep learning-based virtual screening provides a more effective way to find molecules that resemble drugs, and virtual sources give chemists useful information. Leiden University researchers present PCMol, a multi-target model that trains the de novo generative model on target proteins using the latent embeddings extracted from AlphaFold. Protein descriptors are a useful tactic for expanding…
Read More Unlocking New Frontiers in Drug Design with PCMol: Integrating AlphaFold and De Novo Approaches
AI | Bioinformatics | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending
AlphaFind: A New Frontier in Proteomic Exploration
ByDeotima Chakraborty February 22, 2024October 22, 2026
Effective structure-based search tools are necessary to efficiently organize the massive volume of data in the database. Novel tools like FoldSeek and 3D-surfer have been developed as a result of the inability of existing tools like PDBeFold to handle huge datasets. However, they are limited in their functionality by the fact that they can’t search…
Read More AlphaFind: A New Frontier in Proteomic Exploration
AI | Bioinformatics | Computational Models | News | Structural Biology | Tools | Trending
OpenFold Unveils SoloSeq and OpenFold-Multimer: Advancing AI in Protein Structure Analysis
ByDr. Tamanna Anwar February 20, 2024October 22, 2026
OpenFold, an artificial intelligence (AI) research consortium, has announced the release of two new tools that aim to improve protein structure prediction: SoloSeq and OpenFold-Multimer. These open-source tools represent important advances in integrating protein language models with structure prediction software, as well as modeling protein complexes more accurately. The SoloSeq model developed on Amazon Web…
Read More OpenFold Unveils SoloSeq and OpenFold-Multimer: Advancing AI in Protein Structure Analysis
Bioinformatics | Biotech | Drug Discovery | News | Structural Biology | Trending
University of Michigan Researchers Discover Novel Plant Protein Fold with Potential for Anti-Cancer Drugs
ByDr. Tamanna Anwar February 16, 2024October 22, 2026
Researchers from the University of Michigan have reported the discovery of a new plant protein fold that catalyzes the formation of macrocyclic peptides through a novel mechanism. Their findings provide insight into nature’s peptide cyclization strategies and expand the toolbox for bioengineering cyclic peptides as potential therapeutics. Introduction Cyclic peptides have gained increasing interest as…
Read More University of Michigan Researchers Discover Novel Plant Protein Fold with Potential for Anti-Cancer Drugs
AI | Bioinformatics | News | Proteomics | Structural Biology | Trending
Meet Proteus: Transforming the Landscape of Protein Design with Innovation and Efficiency
ByDr. Tamanna Anwar February 16, 2024October 22, 2026
Proteins perform essential functions in living organisms and adopt specific three-dimensional structures dictated by their amino acid sequences. The ability to accurately design novel protein structures from scratch could enable advances in areas like protein engineering and drug development. Recently, deep learning techniques like diffusion models have shown promise for generating designable protein structures without…
Read More Meet Proteus: Transforming the Landscape of Protein Design with Innovation and Efficiency
Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
DANCE Unveils Hidden Depths of Protein Movement, Paving the Way for Better Drug Design
ByAnchal Negi February 16, 2024October 22, 2026
One must understand proteins’ structural flexibility in-depth to comprehend their role in biological processes and functional systems. It is still challenging to predict various conformational states and motions of proteins despite the advances in high-throughput technologies that have increased our understanding of protein structures. For a methodical and thorough explanation of the conformational diversity of…
Read More DANCE Unveils Hidden Depths of Protein Movement, Paving the Way for Better Drug Design
AI | Bioinformatics | Drug Discovery | LLM | News | Structural Biology | Tools | Trending
tFold Unveiled: A Swift and Accurate Approach to Antibody-Antigen Complex Modeling and Design
ByAnchal Negi February 13, 2024October 22, 2026
The soldiers of our immune system, antibodies, bind to specific targets like viruses and toxins and neutralize them. Predicting antibody-antigen complex structures accurately has the potential to significantly advance both the creation of therapeutic antibodies and scientific research. Traditional approaches are costly and slow, but an emerging technique called tFold (tFold-Ab and tFold-Ag) is rewriting…
Read More tFold Unveiled: A Swift and Accurate Approach to Antibody-Antigen Complex Modeling and Design
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Trending
Unveiling the Power of Deep Learning: A Comprehensive Benchmark of Tertiary RNA Structure Prediction Methods
ByDeotima Chakraborty February 12, 2024October 22, 2026
Before understanding RNA biology, one must grasp the three-dimensional structure of RNA. Because experimental procedures require a lot of labor and money, computer approaches have emerged. With the use of machine learning and physics-based concepts, these techniques can quickly anticipate RNA structures. On the other hand, their accuracy is still not as high as that…
Read More Unveiling the Power of Deep Learning: A Comprehensive Benchmark of Tertiary RNA Structure Prediction Methods
AI | Bioinformatics | News | Structural Biology | Tools | Trending
Making AI-Driven Structural Biology Accessible with Foldy
ByDr. Tamanna Anwar February 11, 2024October 22, 2026
Recent breakthroughs in AI-based protein structure prediction have enormous potential to accelerate discoveries across the life sciences. However, major barriers persist in making these advanced tools accessible to non-experts without specialized computing resources. To address this gap, researchers from Joint BioEnergy Institute, US, have developed Foldy – an intuitive web application that puts powerful structural…
Read More Making AI-Driven Structural Biology Accessible with Foldy
AI | Algorithm | Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending
CombFold: Advancing Structure Prediction of Large Protein Assemblies with Combinatorial Algorithms and AlphaFold2
ByDeotima Chakraborty February 9, 2024October 22, 2026
Deep learning models like RosettaFold and AlphaFold2 can predict protein structure with high accuracy; however, they still have difficulties when it comes to intricate connections between large proteins. To combat this problem, scientists from The Hebrew University of Jerusalem introduced CombFold, a hierarchical and combinatorial assembly technique that uses pairwise interactions between subunits predicted by…
Read More CombFold: Advancing Structure Prediction of Large Protein Assemblies with Combinatorial Algorithms and AlphaFold2
Bioinformatics | News | Paper Summary | Structural Biology | Trending | Virus
UChicago Scientists Crack the Code of HIV Entry into the Nucleus of the Cell: Could it Lead to New Treatment Strategies?
ByDeotima Chakraborty February 8, 2024October 22, 2026
In a major scientific breakthrough, researchers at the University of Chicago have succeeded in creating a comprehensive model of the nuclear pore complex with the HIV-1 virus capsid. This sheds new light on the complex processes viruses like HIV use to enter host cell nuclei and replicate. HIV-1 transports genetic material into the nucleus through…
Read More UChicago Scientists Crack the Code of HIV Entry into the Nucleus of the Cell: Could it Lead to New Treatment Strategies?
AI | Bioinformatics | LLM | News | Paper Summary | Structural Biology | Trending
Has ESM-2 Truly Learned the Language of Protein Folding?
ByAnchal Negi February 6, 2024October 22, 2026
Protein structure prediction and design may be accomplished using protein language models (pLMs). They may not completely comprehend the biophysics of protein structures, though. The researchers from Harvard University provided an analysis of the structure prediction capabilities of the flagship pLM ESM-2. They developed an unsupervised method for comparing coevolutionary statistics to previous linear models…
Read More Has ESM-2 Truly Learned the Language of Protein Folding?
AI | Bioinformatics | Database | Deep Learning | News | Structural Biology | Trending
Revolutionize RNA Structure Prediction with RNA3DB: The Pinnacle Dataset for Training Deep Learning Models
ByDr. Tamanna Anwar February 6, 2024October 22, 2026
Harvard University researchers introduce RNA3DB, a dataset crafted from the Protein Data Bank (PDB), addressing challenges in RNA structure prediction. In response to limitations in existing literature and recent findings in CASP15, RNA3DB offers a non-redundant dataset for training and benchmarking deep learning models. With the success of deep learning in protein structure prediction, there…
Read More Revolutionize RNA Structure Prediction with RNA3DB: The Pinnacle Dataset for Training Deep Learning Models
AI | Bioinformatics | Deep Learning | Drug Discovery | LLM | News | Paper Summary | Structural Biology | Trending
Meet Lingo3DMol: A Pocket-based 3D Molecule Generation Method Leveraging Language Models and Geometric Deep Learning
ByAnchal Negi January 27, 2024October 22, 2026
The drug development process involves a winding trail across the enormous chemical wilderness, looking for compounds that interact ideally with their target proteins. Traditional approaches, while successful, frequently stumble in the dark, unable to capture the delicate 3D pattern of particles and their interactions. But do not worry; scientists from Beijing StoneWise Technology Co Ltd, …
Read More Meet Lingo3DMol: A Pocket-based 3D Molecule Generation Method Leveraging Language Models and Geometric Deep Learning
AI | Bioinformatics | Machine Learning | News | Paper Summary | Proteomics | Structural Biology | Tools | Trending
Unveiling the Future of Protein Design: RFdiffusion’s De Novo Revolution
ByDeotima Chakraborty January 26, 2024October 22, 2026
Protein design has seen significant progress, but a comprehensive deep-learning framework for protein design, including de novo binder design and higher-order symmetric architectures, remains unexplored. Diffusion models have shown success in image and language generative modeling but have limited success in protein modeling due to the complexity of protein backbone geometry and sequence-structure relationships. The…
Read More Unveiling the Future of Protein Design: RFdiffusion’s De Novo Revolution
AI | Bioinformatics | Cancer Research | News | Paper Summary | Structural Biology | Trending
Cleveland Clinic and IBM’s Blueprint for Discovering Novel Immunotherapy Targets Using Artificial Intelligence
ByAnchal Negi January 25, 2024October 22, 2026
Predicting the immunogenicity of peptide antigens attached to major histocompatibility complex (MHC) molecules is critical for developing new immunotherapies and better understanding human immune responses. While existing techniques rely on simple sequence representations, they neglect the complex chemical mechanisms that drive peptide recognition. Researchers from Cleveland Clinic and IBM collaborated to create supervised and unsupervised…
Read More Cleveland Clinic and IBM’s Blueprint for Discovering Novel Immunotherapy Targets Using Artificial Intelligence
AI | Bioinformatics | Computational Models | Drug Discovery | LLM | Machine Learning | News | Paper Summary | Structural Biology | Trending
Meet ChatDrug: A New ChatGPT-powered Conversational Drug Editing Framework
ByDeotima Chakraborty January 23, 2024October 22, 2026
Drug discovery is one of the many fields where recent developments in conversational large language models (LLMs), like ChatGPT, have shown incredible promise. However, the majority of the work that has already been done is on examining conversational LLMs’ skills with regard to chemical reactions and retrosynthesis. However, there is still much to learn about…
Read More Meet ChatDrug: A New ChatGPT-powered Conversational Drug Editing Framework
Bioinformatics | Cancer | Cancer Research | News | Paper Summary | Proteomics | Structural Biology | Trending
The Glue that Heals: St. Jude’s Researchers Unveil Molecular ‘Super-Glue’ Propelling Innovative Cancer Drug Development
ByAnchal Negi January 20, 2024January 21, 2024
Scientists at St. Jude Children’s Research Hospital have published their findings on SJ3149, a chemical with broad efficacy against various cancer types, particularly acute myeloid leukemia (AML). Scientists worked together to discover and improve a chemical molecule that functions as a molecular “super-glue” for a variety of tumors. SJ3149 binds to cancer-related protein casein kinase…
Read More The Glue that Heals: St. Jude’s Researchers Unveil Molecular ‘Super-Glue’ Propelling Innovative Cancer Drug Development
Bioinformatics | News | Paper Summary | Structural Biology | Trending
Illuminating AMBERff’s Potential: AMBER Force Fields Meet NAMD in Multimillion-Atom Simulations
ByDeotima Chakraborty January 14, 2024January 14, 2024
AMBERff with NAMD is implemented by researchers from the University of Delaware to enable simulations of large systems built upon existing software infrastructure. Increasingly used in multimillion-atom systems such as viruses and biological machinery, all-atom molecular dynamics (MD) simulations are a fundamental structural biology approach. The AMBER family of force fields (AMBERff) parameter sets are…
Read More Illuminating AMBERff’s Potential: AMBER Force Fields Meet NAMD in Multimillion-Atom Simulations
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Trending
High-throughput ADMET Properties Prediction Made Easy with ADMET-AI: A New Platform for Large-scale Chemical Libraries Evaluation
ByAnchal Negi January 13, 2024October 22, 2026
A vital step in drug discovery is accurately evaluating potential drug candidates’ Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET). Traditionally, this process has been time-consuming, expensive, and even limited to small compound libraries, making it difficult to test larger libraries. Recently, a group of researchers developed ADMET-AI, a simple, fast, and accurate platform for ADMET…
Read More High-throughput ADMET Properties Prediction Made Easy with ADMET-AI: A New Platform for Large-scale Chemical Libraries Evaluation
Bioinformatics | Drug Discovery | News | Paper Summary | Proteomics | Structural Biology | Trending
Scripps Scientists Develop High-Resolution Method to Uncover Druggable Sites on Proteins
BySonal Keni January 10, 2024October 22, 2026
The factors at play in the binding of proteins are intricate and hard to untangle – despite great advancements in recent years in humanity’s understanding of the proteome, conventional methods for determining binding sites and uncovering the mechanisms that influence small molecule-protein binding remain difficult, resource-intensive, and expensive. Computational biology may provide a more efficient…
Read More Scripps Scientists Develop High-Resolution Method to Uncover Druggable Sites on Proteins
Bioinformatics | News | Paper Summary | Structural Biology | Trending
Exploring the Diversity of Scavenger Receptor Class B Proteins Across Eukarya: An In-Depth Analysis through Phylogenetic and Protein Structure Analyses
ByDeotima Chakraborty January 6, 2024January 6, 2024
The class B scavenger receptor (SR-B) proteins, which are essential for innate immunity, pathogen identification, apoptotic cell clearance, and metabolic sensing, have an ectodomain called the CD36 domain. Previous research has suggested that SR-B proteins are old, although their diversity within Eukarya is yet unknown. The University of Miami researchers examined SR-B homologs found in…
Read More Exploring the Diversity of Scavenger Receptor Class B Proteins Across Eukarya: An In-Depth Analysis through Phylogenetic and Protein Structure Analyses
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Trending
AlphaFold’s Latest Strides: Improved Accuracy for Antibody-Antigen Complex Modeling
BySonal Keni January 5, 2024January 5, 2024
The launch of AlphaFold signaled a revolution in computational modeling: armed with new knowledge of protein structures and unencumbered by limitations on resources and time, scientists were able to use the tool to further their understanding of protein structure, functionality, and interactions. However, AlphaFold’s success in the realm of antibody-antigen modeling is limited. A new…
Read More AlphaFold’s Latest Strides: Improved Accuracy for Antibody-Antigen Complex Modeling
Bioinformatics | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending
Unleashing MACE-OFF23: Machine Learning Empowers Transferable Force Field for Organic Molecules
ByDeotima Chakraborty January 4, 2024October 22, 2026
For more than fifty years, biomolecular simulation has been dominated by classical empirical force fields. Despite being extensively employed in biomolecular dynamics, crystal structure prediction, and drug discovery, they typically lack the precision and transferability necessary for predictive modeling. In this paper, researchers from the University of Cambridge introduced MACE-OFF23. A high degree of quantum…
Read More Unleashing MACE-OFF23: Machine Learning Empowers Transferable Force Field for Organic Molecules
AI | Bioinformatics | Deep Learning | News | Paper Summary | Structural Biology | Tools | Trending
Meet LigandMPNN: A Deep Learning Model Redefining Protein Design with Precision for Small Molecules, Nucleotides, and Metals
BySonal Keni January 2, 2024January 2, 2024
Protein design is an upcoming niche with important implications for many fields in the realms of healthcare, genetic engineering, and drug creation, among others. However, current methods for sequence design have many disadvantages, including a lack of appropriate accuracy and efficiency. A new model, LigandMPNN, seeks to change this. The design of protein sequences is…
Read More Meet LigandMPNN: A Deep Learning Model Redefining Protein Design with Precision for Small Molecules, Nucleotides, and Metals
AI | Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
Designing Drug-like Molecules with DrugHIVE: A Deep Hierarchical Variational Autoencoder for the Structure-based Design
ByDeotima Chakraborty December 28, 2023January 4, 2024
Due to the rapid advancements in AI, structure-based medication design is now widely used as one of the most important methods in early drug development. AI’s deep generative modeling is expanding molecular design beyond classical methods by learning essential intra- and intermolecular interactions from available data, thanks to the increase of crystal structure data and…
Read More Designing Drug-like Molecules with DrugHIVE: A Deep Hierarchical Variational Autoencoder for the Structure-based Design
Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending
Revolutionizing Molecular Dynamics Analysis with VIAMD: A Unified Approach to Visualization, Property Calculation, and Synergistic Analysis
ByDeotima Chakraborty December 6, 2023December 6, 2023
Many different tools are needed for the standard molecular dynamics (MD) analysis workflow, which frequently leads to a lack of coordination and interaction between the various analysis steps. VIAMD is an application that combines adaptable analysis components with a 3D visualization of molecular trajectories to address this problem. VIAMD (Visual Interactive Analysis of Molecular Dynamics)…
Read More Revolutionizing Molecular Dynamics Analysis with VIAMD: A Unified Approach to Visualization, Property Calculation, and Synergistic Analysis
AI | Bioinformatics | Machine Learning | News | Paper Summary | Structural Biology | Tools | Trending
Decoding the Dance of Proteins and Nucleic Acids: Machine Learning Empowers Protein-Nucleic Acid Complexes Prediction with RoseTTAFoldNA
ByDeotima Chakraborty December 3, 2023January 26, 2024
Researchers at the University of Washington, USA, have developed a new AI system called RoseTTAFoldNA that can rapidly and accurately predict the 3D structures of proteins bound to DNA and RNA. The ability to model these protein-nucleic acid complexes has important implications across fields from biomedicine to biotechnology. RoseTTAFoldNA expands on the award-winning protein structure…
Read More Decoding the Dance of Proteins and Nucleic Acids: Machine Learning Empowers Protein-Nucleic Acid Complexes Prediction with RoseTTAFoldNA
AI | Bioinformatics | Drug Discovery | Machine Learning | News | Paper Summary | Structural Biology | Trending
Transforming Fragment-based Drug Design: Stanford’s FRAME Employs Machine Learning to Expand Fragments into Ideal Ligands
BySwasti Tyagi December 1, 2023October 22, 2026
Stanford University researchers developed FRAME (Fragment-Based Molecular Expansion), a machine learning framework that uses three-dimensional structures of interactions between proteins and ligands to facilitate drug design based on ‘fragments.’ Fragments are singular chemical groups that are added to ligands for the purpose of performing lead optimization tasks and improving their properties. Ligands are small molecules…
Read More Transforming Fragment-based Drug Design: Stanford’s FRAME Employs Machine Learning to Expand Fragments into Ideal Ligands
AI | Bioinformatics | Deep Learning | Drug Discovery | News | Paper Summary | Proteomics | Structural Biology | Trending
Decoding the Protein-Ligand Enigma: A Deep Dive into Deep Learning Approaches for Binding Affinity Prediction
ByDeotima Chakraborty November 30, 2023November 30, 2023
Researchers from the University of Edinburgh, UK, explore the impact of ligand and protein encodings on binding affinities prediction for different data sets, a crucial aspect of drug development and discovery. Sequence-based deep learning, convolutional neural network-based encodings, and graph neural network-based encodings were used to investigate protein roles. Graph-neural networks were used to construct…
Read More Decoding the Protein-Ligand Enigma: A Deep Dive into Deep Learning Approaches for Binding Affinity Prediction
AI | Bioinformatics | News | OMICS | Paper Summary | Proteomics | Structural Biology | Tools | Trending
Enlightening the Proteomic Space with Chroma: A Revolutionary Generative Model for Protein Design
ByDr. Tamanna Anwar November 21, 2023October 22, 2026
Proteins are incredible molecules that carry out nearly every function necessary for life. However, their staggering complexity has made designing new proteins an immensely difficult challenge. Now, AI is poised to change that. Scientists have developed Chroma, a groundbreaking AI system that can generate completely novel protein structures and sequences from scratch. This innovation could…
Read More Enlightening the Proteomic Space with Chroma: A Revolutionary Generative Model for Protein Design
Bioinformatics | News | Paper Summary | Phylogenetic Analysis | Proteomics | Structural Biology | Trending
Meet A3D-MODB: A New Database for Predicting Protein Aggregation in Model Organisms
BySonal Keni November 13, 2023October 22, 2026
The Protein Folding and Computational Diseases Group at IBB-UAB, in collaboration with researchers from the University of Warsaw, developed a new database, A3D-MOBD (A3D Model Organism Database), that collects information regarding proteomes from 12 of the key model organisms for biological research as well as protein structure predictions to form the most comprehensive resource on…
Read More Meet A3D-MODB: A New Database for Predicting Protein Aggregation in Model Organisms
AI | Bioinformatics | Chemoinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
DeepSA: A Cutting-edge Chemical Language Model for Compound Synthesis Accessibility Prediction
BySonal Keni November 10, 2023November 28, 2023
As computationally generated molecules become more popular in the fields of drug development and biotechnology, ease of synthesis becomes a common problem. Often, the molecules generated by machine learning models may be challenging to synthesize and may require many steps, making it too expensive for production. A new deep learning model DeepSA, developed by researchers…
Read More DeepSA: A Cutting-edge Chemical Language Model for Compound Synthesis Accessibility Prediction
Bioinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending
EasyDock: A Scalable and User-friendly Tool for High-throughput Molecular Docking
BySwasti Tyagi November 9, 2023November 9, 2023
Computational tools that are currently used for molecular docking are difficult to integrate into different computational distributions and interfaces; this becomes very inconvenient for users and researchers. EasyDock is a novel tool that can be applied to a network of computational nodes aided by the Dask Library and does not require scheduling for any specific clusters of…
Read More EasyDock: A Scalable and User-friendly Tool for High-throughput Molecular Docking
AI | Bioinformatics | News | Proteomics | Structural Biology | Tools | Trending
The AlphaFold Revolution Continues: Unraveling the Next-Gen Advancements
BySonal Keni November 6, 2023October 22, 2026
The introduction of AlphaFold 2 was a groundbreaking breakthrough in the field of predicting protein structures and interactions. Google’s DeepMind, was the driving force behind this tool, which used deep learning methods in order to successfully predict the structures of various proteins. Described by many experts in the field as one of the most transformational…
Read More The AlphaFold Revolution Continues: Unraveling the Next-Gen Advancements
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Demystifying the Genetic Architecture of Proteins through Experimental Models
BySwasti Tyagi November 3, 2023January 24, 2024
A collaborative effort between researchers from the UK, Spain, and Germany utilized experimental methods to explore amino acid sequence spaces and demonstrated that for a decent number of proteins, genetic architecture can be relatively simple. They also noted that models based on artificial intelligence that are conventionally used for biological prediction purposes can be much…
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