Answers about NCMNtech, the NCMN System, native-state membrane protein structural biology, and what it looks like to work with the team.
NCMNtech Inc. is a biotech company and an enabling technology platform for structure-based drug discovery, built on the NCMN System, a detergent-free method that resolves membrane protein structures in their native cell membrane lipid environment. The platform supports cryo-EM structure determination, polymer-based membrane protein stabilization, and collaborations with pharmaceutical partners for drug-target studies, giving programs an accurate structural starting point for challenging membrane targets.
Most membrane proteins are studied only after standard preparation methods have altered them. Detergents strip away native lipids and stabilizing mutations shift the very conformations a drug needs to target, so the structure that gets solved may not match the protein a drug actually encounters. NCMNtech's native-state approach removes that distortion, giving programs an accurate starting point from the first data point onward.
The NCMN System is NCMNtech's detergent-free technology for membrane protein structure determination. It extracts a membrane protein together with its associated native lipids as a single stable nanoparticle, with no detergents and no engineered mutations, truncations, or fusions. What goes onto the cryo-EM grid is the protein in its real membrane environment, ready to be resolved at high resolution.
Native-state means the membrane protein is kept in its natural cell membrane lipid environment rather than stripped into detergent. It matters because removing native lipids changes the protein's shape, creating false binding pockets and hiding real allosteric sites. A native-state structure reflects the protein as it actually exists in the cell, so a program is built on accurate biology from the first data point.
Membrane proteins are a fraction of the proteome but the majority of where drugs act. They make up about 22% of all human proteins and represent more than 60% of approved drug targets. They are also among the hardest targets to resolve accurately, which is the gap the NCMN System addresses.
Standard methods use detergents to extract membrane proteins, which strips the native lipids and can distort conformations, create false binding pockets, and hide real allosteric sites. The NCMN System keeps the native lipids retained and requires no protein engineering, producing homogeneous, reproducible nanoparticles with full functional activity preserved, resolved at sub-3Å cryo-EM resolution.
AI structure-prediction tools like AlphaFold capture sequence-based folding, but they cannot model the native lipid environment, membrane dynamics, or the lipid-dependent conformations a drug actually encounters. For membrane proteins, an experimental structure in a native membrane is still required, which is what the NCMN System provides.
The platform produces native-state cryo-EM structures at sub-3Å resolution, with PDB-ready coordinates and mapped lipid sites, and NCMN particles for functional characterization. Structures are delivered ready for computational chemistry and AI-enabled drug-discovery workflows.
The NCMN System can resolve a membrane protein drug target across multiple states, both static and dynamic, including ligand-free or ligand binding states, all in a physiologically relevant membrane context. This provides a basis for allosteric and structure-based drug discovery.
Yes. NCMNtech has resolved real drug targets in their native state, with results independently verified through peer-reviewed publication in PNAS and Nature Communications. Published examples include the bacterial AcrB transporter (PNAS, 2018), the human mitochondrial TSPO (PNAS, 2025), and human integrin αIIbβ3 (Nature Communications, 2024).
The NCMN System is built for the decisions where membrane-protein programs usually stall: solving a target that will not survive detergents, telling real binding pockets from lipid-filled ones, capturing the functional state a drug needs to target, and confirming that the solved structure behaves like the real, functional protein. It offers broad target coverage and works across a range of membrane proteins, with each collaboration shaped around the specific target.
Yes. The NCMN System produces structures ready for computational chemistry and AI-enabled design workflows, with coordinates processed for docking, MD simulation, and pharmacophore modeling, and lipid occupancy annotated to reduce false-positive screening hits. It is designed to be compatible with external third-party platforms such as AIDDISON™ and SYNTHIA®. Integration with such tools would be subject to separate licensing, subscription agreements, or future collaboration.
NCMNtech works as a direct partner to drug discovery teams. Every collaboration is shaped around your target, your timeline, and your program stage, through co-discovery and long-term collaboration models. To begin, tell NCMNtech about your target and the team will share what native-state characterization can reveal for your program. You can start a collaboration through the site or reach the team directly at info@ncmntech.com.