Molecular Dynamics

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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 | 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
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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
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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
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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 | 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
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?
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Streamlining Drug Discovery with Automated Binding Free Energy Calculations
ByNeermita Bhattacharya July 20, 2024October 22, 2026

In the world of drug discovery, predicting how well a drug molecule will bind to its target is like figuring out the best path on a treasure map when you’re lost. Scientists use complex calculations to predict this binding affinity. One powerful method is called “Absolute Binding Free Energy” (ABFE) calculations. These calculations help scientists…

Read More Streamlining Drug Discovery with Automated Binding Free Energy Calculations
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Predicting Multiple Conformations and Ensembles with AFsample2: An AlphaFold2 Extension
ByAnshika Gupta June 6, 2024October 22, 2026

Acting as enzymes, structural elements, and molecular motors, proteins represent the molecular drive of biological systems, the elucidation of which relies on the explication of conformational transitions. In a recent study by Linköping University, Sweden, researchers got into the issue of protein conformational sampling, stating that there are limitations to current methods and that AFsample2…

Read More Predicting Multiple Conformations and Ensembles with AFsample2: An AlphaFold2 Extension
Bioinformatics | News | Paper Summary | Structural Biology | Tools | Trending

Unraveling the Mysteries of Molecular Dynamics: MDverse Sheds Light on Dark Matter
ByDeotima Chakraborty May 13, 2024October 22, 2026

Molecular dynamics (MD) files have accumulated in generalist data repositories due to the rise of open science and the lack of a worldwide repository specifically for MD simulations. This data is known as the “dark matter” of MD, which is technically accessible but not indexed, curated, or readily searchable. Researchers discovered and indexed over 250,000…

Read More Unraveling the Mysteries of Molecular Dynamics: MDverse Sheds Light on Dark Matter
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 | 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 | 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
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
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
Bioengineering | Bioinformatics | News | Proteomics | Structural Biology | Tools | Trending

Illuminating the Complexity of Interactions within and between Proteins and Ligands with Surfaces
ByDr. Tamanna Anwar November 2, 2023October 22, 2026

Computational methods have revolutionized our understanding of molecular interactions and their pivotal role in the stability of biomolecular structures and complexes. These insights are crucial for modulating, engineering, and comprehending biological processes. Scientists from the Université de Montréal, Canada, introduce Surfaces, a groundbreaking software that offers a seamless, fast, and highly customizable approach to quantify…

Read More Illuminating the Complexity of Interactions within and between Proteins and Ligands with Surfaces
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Brock Researchers Develop AI-Powered Tool ‘DAPTEV’ to Design New Aptamer Drugs for COVID-19
ByNeegar Naushaba Iqbal August 5, 2023October 22, 2026

Traditional drug discovery and development methods are quite expensive, cumbersome, and prone to the biases of experts. A revolution in the field of drug development has emerged in the form of aptamers. Aptamers are single-stranded oligonucleotides (DNA/RNA) capable of binding to biomolecules with high affinity as well as specificity. However, the conventional process of aptamer…

Read More Brock Researchers Develop AI-Powered Tool ‘DAPTEV’ to Design New Aptamer Drugs for COVID-19
Bioinformatics | Cancer Research | Chemoinformatics | Machine Learning | News | Structural Biology

A New Computer Simulation Coupled with Machine Learning Cracked the Mechanism of Cancer Drug Resistance
ByDr. Tamanna Anwar June 5, 2022June 18, 2022

A team led by the University of Maryland utilizes machine learning to explain why a “wonder drug” may not work in all patients. Understanding how mutations cause a medicine to become ineffective is a huge issue. The mechanism by which mutations produce drug resistance is frequently discussed solely in terms of thermodynamics. The case where…

Read More A New Computer Simulation Coupled with Machine Learning Cracked the Mechanism of Cancer Drug Resistance

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Molecular Dynamics

Predicting Multiple Conformations and Ensembles with AFsample2: An AlphaFold2 Extension

A New Computer Simulation Coupled with Machine Learning Cracked the Mechanism of Cancer Drug Resistance

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