MoleculeOS by MoleculeX Achieves Breakthrough in AI-Driven Protein Dynamic Design with Quantum Chemistry Integration, Boosting Simulation Efficiency by 100 Billion Times

Source: Global Times

[Global Times Technology Comprehensive Report] The biopharmaceutical and biomanufacturing industries have long faced systemic bottlenecks such as long research and development cycles, high costs, and low success rates, which have become key factors restricting the efficiency improvement and original innovation capabilities of China's bio-industry. With the deep integration of artificial intelligence and life sciences, the industry urgently needs a fundamental technological force that can break through efficiency limits and truly deliver industrial value.

Recently, MoleculeMind, founded by Professor Jinbo Xu, the "pioneer of AI protein folding," announced a major generational upgrade to its AI protein optimization and design platform, MoleculeOS.

MoleculeOS is the "industry-level digital engine" developed by MoleculeMind based on over two decades of rare technical accumulation, aiming to solve the "bottleneck" problems in the development of the bioeconomy and provide self-controllable underlying technical support for China's biomanufacturing and pharmaceutical R&D.

In the just-passed 2025, MoleculeOS achieved breakthrough progress in specific industrial-grade application scenarios. The platform realized ultra-high-precision large molecule dynamic simulation and design, and reached industrial-grade accuracy capable of solving real industry challenges in key tasks such as antibody-antigen complex and protein-small molecule complex structure prediction. This means that in the two trillion-level markets of biomedicine and bio-manufacturing, MoleculeOS has demonstrated the ability to address complex scenarios that existing models like AlphaFold 3 have yet to fully conquer.

From "Predicting the Known" to "Creating the Unknown":AchieveProtein DevelopmentParadigmCrossing

The core value of MoleculeOS lies in driving a paradigm shift in biological R&D from "passive interpretation" to "active design." Traditional protein research is limited to "blindly panning for gold" in a vast sea of molecules, while MoleculeOS can "create" entirely new molecules from scratch based on specific needs. This transformation no longer relies on pure trial and error but significantly enhances the certainty and success rate of R&D through precise calculations, fundamentally reshaping the research process.

The platform is based on the NewOrigin (Darwin) large model. NewOrigin is a multi-modal AI protein foundational model independently developed by MoleculeMind, featuring a holistic "sequence, structure, function, evolution" four-in-one perspective. It can uniformly model protein sequences, 3D structures, functions, interactions, and evolutionary constraints. Trained for molecular design rather than single prediction tasks, it possesses cross-task and cross-industry reusability.

Based on an innovative technical approach, MoleculeMind continues to maintain accuracy and performance surpassing models like AlphaFold 3 in key technologies that are urgently needed by the industry, such as antibody-antigen complex structure prediction and protein-small molecule complex structure prediction.

At the same time, MoleculeMind, relying on the NewOrigin (Darwin) innovative algorithm, has solved industrial problems that models like AlphaFold 3 could not address. For example, regarding the challenges of predicting protein dynamic structures and designing protein dynamics, MoleculeMind integrated AI, molecular dynamics, and first-principles methods to establish a high-precision molecular modeling system. This system can efficiently simulate conformational changes and functional responses of proteins under different environmental conditions. While maintaining accuracy consistent with traditional quantum chemistry methods, its operational efficiency has improved by a factor of one trillion compared to them, reaching an "industrially usable" level.

Simulate the entire reaction process of an industrial enzyme and its substrate. Previously, there was no method to precisely observe the entire reaction process.

CrossingLandingChasm：BuildFrom Algorithm toApplicationTheEngineeringClosed-loop

To bridge the gap from laboratory conception to industrial implementation, MoleculeOS integratesMassive Data, dedicated algorithms and industry know-how have established a complete engineering closed-loop of "AI design - wet lab validation - result feedback - model iteration," ensuring not only accurate predictions but also that the designed molecules are "manufacturable and functionally effective."

MoleculeMind MoleculeOS Platform

Currently, MoleculeOS has validated its industrial value in the real pipelines of dozens of top pharmaceutical companies and leading synthetic biology firms:

Breakthrough in Production Rate Bottleneck: Collaboration with a leading biomanufacturing company in China to modify the structure of a key enzyme protein, increasing the strain's production rate by 5 times compared to the wild-type strain.

Reshaping Drug Developability: Increasing the expression level of a fusion protein drug, which was on the verge of being abandoned due to low expression, by over 400 times, with monomer content exceeding 90%, thereby reviving its development prospects;

Solving the hard problem that traditional methods couldn't: Delivering a solution to the pH-sensitive drug design challenge in 2 months, which was unsolvable by traditional high-throughput screening, achieving a 60-fold ultra-high affinity difference between pH 7.4 and pH 6.0 environments.

BreakTechnological "Dimension Wall": Making AIBiological Industry Worker"Super Tool"

As a typical representative of the "AI new infrastructure" and "new quality productivity" in the biotechnology industry, MoleculeOS is building a modern and intelligent "protein research and development operating system" to reconstruct the innovative infrastructure of the biotechnology industry through fundamental technological innovation.

Based on a comprehensive technology system and industry experience, MoleculeOS has developed a set of key general technology modules, including enzyme activity design, pH-sensitive protein design, peptide de novo design, and nanobody design. These capabilities are not only applicable to biomedicine but can also be widely used in synthetic biology, industrial enzyme design, agricultural functional proteins, biomaterials, and environmental governance.

To lower the usage threshold, the platform has developed a "one-click" automated workflow and a conversational interaction system, achieving a shift from "expert-exclusive" to "industry-wide accessibility." This allows small and medium-sized enterprises to quickly validate ideas without building expensive facilities, while large enterprises can focus on strategic decision-making, thereby stimulating industrial innovation vitality and promoting collaborative upgrades across the upstream and downstream of the industry chain.

MoleculeMind MoleculeOS Interface

"We are not trying to turn biologists into AI experts, but to make AI a super tool that every biologist can easily access." Professor Xu Jinbo, founder of MoleculeMind, hopes that AI will become a universal force driving the development of the bioeconomy. By breaking down the barriers between industry and laboratories, it will accelerate the delivery of affordable innovative therapies to patients, promote green and efficient biomanufacturing, and contribute systematic efforts toward achieving China's goals of universal healthcare, dual carbon targets, and high-quality development of the bioeconomy.