All Molecular Modelling articles
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ArticleBeyond serendipity: rational design and AI’s expansion of the undruggable target landscape
For decades, drugging the ‘undruggable’ was thought to require luck rather than logic. Today, AI is transforming serendipity into strategy by enabling rational, data-driven approaches to previously inaccessible targets.
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NewsMolecular map reveals thromboxane receptor structure for new blood clotting drug development
International researchers have mapped the structure of the thromboxase A₂ receptor using cryo-electron microscopy, revealing some unexpected activation mechanisms.
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ArticleAI builds dual-action cancer drug targeting PKMYT1
Research published in Nature Communications shows how generative AI can be used to design complex dual-action cancer drug candidates. Insilico Medicine has developed a PKMYT1 degrader that both eliminates the target protein and blocks its activity, demonstrating the growing role of AI in advanced drug discovery.
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InterviewPhysics-based modelling offers a new way to study drug targets
Australian start-up OmnigeniQ has demonstrated what it describes as the first deterministic, physics-based computation of a human protein in its native state.
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NewsNew AI tool could accelerate drug discovery and cut lab costs
Scientists have developed a machine learning system that can predict how complex chemical reactions will produce the correct molecular form for medicines.
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NewsNew generative AI method could make drug discovery faster
A newly developed AI-driven technique could dramatically speed up the discovery of drugs and advanced materials, enabling scientists to design chemically valid, property-targeted molecules in minutes rather than years.
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Article2026: the year AI stops being optional in drug discovery
AI is moving from a supporting role into the core of drug discovery. By 2026, it is expected to shape how targets are chosen, how biology is analysed and how development decisions are made.
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NewsSchrödinger partners with Lilly TuneLab on AI drug discovery
Schrödinger has announced a collaboration with Eli Lilly’s TuneLab platform, integrating advanced AI-driven drug discovery workflows into its LiveDesign enterprise informatics system.
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NewsNew Type 2 diabetes drugs may improve insulin sensitivity
Scientists have used advanced computer modelling and lab techniques to design potential new diabetes drugs that improve insulin sensitivity.
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NewsControlling cellular noise may stop cancer and bacterial relapse
Scientists have developed a new mathematical ‘Noise Controller’ that can stabilise random cellular fluctuations, offering a potential breakthrough in preventing cancer recurrence and antibiotic resistance.
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ArticleThe data fragmentation problem holding drug discovery back
The DMTA cycle depends on clear data flow, yet most labs still work across disconnected systems. Sean McGee, Director of Product at Certara, explains how better infrastructure and AI can help teams work faster and make decisions with more confidence.
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NewsBits2Bonds: AI system accelerates discovery of RNA delivery polymers
Researchers at LMU Munich have developed Bits2Bonds, the first platform to fuse molecular simulations with machine learning – accelerating the discovery of polymer carriers for therapeutic RNA.
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NewsKinase inhibitors shown to accelerate protein breakdown
A new study has revealed that many kinase inhibitors – key drugs used in cancer and other diseases – also trigger the accelerated degradation of their target proteins, which could inform future therapies.
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ArticleFast, scalable free energy prediction with nonequilibrium switching
Nonequilibrium switching (NES) offers a faster, more scalable way to predict how strongly drugs bind to their targets. By replacing slow equilibrium simulations with rapid, parallel transitions, NES delivers accurate free energy predictions at speed.
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ArticleMapping lipid pockets to drug the undruggable proteome
Tasca Therapeutics is using chemical proteomics to map lipid-binding pockets on proteins. By targeting auto-palmitoylation, the company aims to turn previously undruggable cancer drivers into viable therapeutic targets.
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NewsRNA folding: new model could change future drug design
A Japanese research team has simulated how RNA molecules fold, using cutting-edge computational tools to model complex structures with accuracy – a breakthrough that could accelerate the development of RNA-based medicines and therapies.
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ArticleBeyond templates: advancing protein–protein interaction structure prediction with AI
Dr Alan Nafiiev evaluates template-based, docking and template-free approaches to PPI prediction, highlighting how AI can enhance structural accuracy.
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News
New class of chiral molecules offers strong stability for drug development
Scientists have created a new class of ultra-stable chiral molecules – a discovery that could lead to more precise drug design by preventing potentially harmful molecular “flipping” over time
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NewsBird flu is changing - AI might help us keep up
Researchers at the University of North Carolina at Charlotte have used artificial intelligence to look at how the H5N1 bird flu virus is evolving to evade the immune system - insights that could make way for development of effective future therapies.
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NewsNew nanoparticle enhances cancer drug penetration
Researchers at Southern Medical University have developed a self-propelled ferroptosis nanoinducer that penetrates deeper into tumour tissues - offering a new strategy for safer and more effective cancer treatment.