125 papers
The intersection of quantum physics and biology is a frontier where the strange rules of the microscopic world begin to explain life itself. In this emerging field, researchers explore how quantum effects like coherence and tunneling might drive essential processes in living organisms, from how birds navigate using the Earth's magnetic field to the incredible efficiency of photosynthesis. These studies challenge our traditional understanding of biology, suggesting that quantum mechanics plays a more active role in nature than previously imagined.
At Gist.Science, we track every new preprint appearing in the Q-Bio — Bm category on arXiv to bring these complex discoveries to a broader audience. As soon as a paper is posted, our system processes it to generate both a clear, plain-language explanation and a detailed technical summary, ensuring that whether you are a student or a specialist, you can grasp the significance of these findings without getting lost in dense jargon.
Below are the latest papers in this category, freshly processed and ready for you to explore the quantum side of biology.
This paper presents a master equation framework based on a force-dependent nucleation-zipper pathway that accurately models the shear-induced rupture of short double-stranded DNA, successfully reproducing experimental data and providing a unified kinetic description essential for interpreting force-rupture experiments and designing DNA nanostructures.
The paper introduces AMix-1, a 1.7-billion parameter protein foundation model based on Bayesian Flow Networks that leverages systematic training scaling laws, MSA-based in-context learning, and evolutionary test-time scaling to achieve robust protein design, demonstrated by generating an AmeR variant with up to 50-fold activity improvement over its wild type.
The paper introduces Montparnasse, a Monte Carlo search framework that outperforms existing state-of-the-art methods like DesiRNA and LinearDesign in RNA design by solving the Eterna100 benchmark faster and identifying superior sequences for messenger RNA optimization.
SurfDesign is a novel protein design framework that integrates continuous molecular surface representations with pretrained language models to outperform existing methods in functional protein and enzyme design by explicitly modeling surface geometry and physicochemical complementarity.
This paper introduces ShallowBench, a curated benchmark of 5,780 shallow-pocket targets, to evaluate and expose the limitations of current generative AI models in designing ligands for historically "undruggable" low-concavity interfaces like KRAS and MYC.
This study utilizes long molecular dynamics simulations to demonstrate that the A31P mutation destabilizes the native Rop protein structure by causing turn region unfolding, thereby explaining its experimental topology switch to a 'bisecting U' fold despite predictions from standard energy minimization methods suggesting the mutation should be benign.
This study analyzes atomic density distributions across 21,255 non-redundant protein structures to reveal statistically significant, systematic variations linked to specific structural motifs, functional families, and protein size, while also exploring the relationship between packing density and structural stability indicators.
This paper introduces a memory-efficient, linear-scaling variant of the Good-Turing algorithm that enables the reliable estimation of uncertainty in extremely long molecular dynamics simulations, overcoming previous limitations while maintaining accuracy on datasets containing up to 22 million structures.
The paper introduces Igloo, a multimodal antibody loop tokenizer that encodes backbone dihedral angles and sequence to overcome the coverage limitations of canonical clusters, thereby enhancing protein foundation models for improved antibody loop retrieval, binding affinity prediction, and structural design.
The paper introduces PROBE, a probing-guided framework for LLM agents in structure-based drug design that decomposes ligands into editable sites to create a site map and EditManual, thereby enabling iterative multi-agent optimization that effectively balances binding affinity and druggability while mitigating the failure modes of existing methods.