LM-VS™ Designed Scaffold Technology
LM-VS™ Designed Scaffold Technology
Translates
Molecular Dynamics
Into
Logical Hit Discovery
Translates
Molecular Dynamics
Into
Logical Hit Discovery
LM-VS™ understands molecular dynamics
discovering hits that stay stable, not just fit the pocket.
LM-VS™ understands molecular dynamics
discovering hits that stay stable, not just fit the pocket.
3 Target Verification
3 Target Verification
3 Target Verification
Challenges of Hit Discovery,
The Solutions Proposed by LM-VS™
Challenges of Hit Discovery,
The Solutions Proposed by LM-VS™
LM-VS™ has demonstrated stable and consistent binding with three challenging targets:
EGFR, MDM2, and CDK6.
LM-VS™ has demonstrated stable and consistent binding with three challenging targets: EGFR, MDM2, and CDK6.
Structural Variability of Membrane Proteins
EGFR (Transmembrane Receptor)
High structural variability during activation and mutation frequently reshapes the binding pocket. Under such dynamic conditions, small molecules struggle to maintain stable interactions.
Structural Variability of Membrane Proteins
EGFR (Transmembrane Receptor)
High structural variability during activation and mutation frequently reshapes the binding pocket. Under such dynamic conditions, small molecules struggle to maintain stable interactions.
Structural Variability of Membrane Proteins
EGFR (Transmembrane Receptor)
High structural variability during activation and mutation frequently reshapes the binding pocket. Under such dynamic conditions, small molecules struggle to maintain stable interactions.
Structural Variability of Membrane Proteins
EGFR (Transmembrane Receptor)
High structural variability during activation and mutation frequently reshapes the binding pocket. Under such dynamic conditions, small molecules struggle to maintain stable interactions.
Flat and Shallow Interaction Interfaces
MDM2 (Protein–Protein Interaction)
MDM2, which interacts with p53 on a broad and flat surface, offers little pocket depth for stable binding. Such a limited interface makes it difficult for typical small molecules to achieve sufficient affinity.
Flat and Shallow Interaction Interfaces
MDM2 (Protein–Protein Interaction)
MDM2, which interacts with p53 on a broad and flat surface, offers little pocket depth for stable binding. Such a limited interface makes it difficult for typical small molecules to achieve sufficient affinity.
Flat and Shallow Interaction Interfaces
MDM2 (Protein–Protein Interaction)
MDM2, which interacts with p53 on a broad and flat surface, offers little pocket depth for stable binding. Such a limited interface makes it difficult for typical small molecules to achieve sufficient affinity.
Flat and Shallow Interaction Interfaces
MDM2 (Protein–Protein Interaction)
MDM2, which interacts with p53 on a broad and flat surface, offers little pocket depth for stable binding. Such a limited interface makes it difficult for typical small molecules to achieve sufficient affinity.
Precision Control of Dual Binding Geometry
CDK6 (TPD Warhead Anchoring)
In TPD, the warhead must anchor precisely to control orientation and distance for forming ternary complexes with E3 ligases. But CDK6's deep, narrow pocket makes stable alignment nearly impossible.
Precision Control of Dual Binding Geometry
CDK6 (TPD Warhead Anchoring)
In TPD, the warhead must anchor precisely to control orientation and distance for forming ternary complexes with E3 ligases. But CDK6's deep, narrow pocket makes stable alignment nearly impossible.
Precision Control of Dual Binding Geometry
CDK6 (TPD Warhead Anchoring)
In TPD, the warhead must anchor precisely to control orientation and distance for forming ternary complexes with E3 ligases. But CDK6's deep, narrow pocket makes stable alignment nearly impossible.
Precision Control of Dual Binding Geometry
CDK6 (TPD Warhead Anchoring)
In TPD, the warhead must anchor precisely to control orientation and distance for forming ternary complexes with E3 ligases. But CDK6's deep, narrow pocket makes stable alignment nearly impossible.
Working on a challenging target?
LM-VS™ finds the logic behind binding — and helps you apply it to your own target.
LM-VS™ finds the logic behind binding —
and helps you apply it to your own target.
Transmembrane Receptor
Transmembrane Receptor
Case 1. EGFR —
Stable Binding in Dynamic Structures
Case 1. EGFR —
Stable Binding in Dynamic Structures
Problem
Why is it challenging?
EGFR undergoes significant conformational changes during activation and mutation, causing frequent reshaping of its binding pocket and charge distribution.
Conventional docking methods treat proteins as static structures, often failing to predict reliable binding modes.
IV (Input View)
How did LM-VS™ approach it?
By analyzing thousands of conformational frames, LM-VS™ identified anchor residues that remain stable across transitions and used them as the foundation for scaffold design.
Problem
Why is it challenging?
EGFR undergoes significant conformational changes during activation and mutation, causing frequent reshaping of its binding pocket and charge distribution.
Conventional docking methods treat proteins as static structures, often failing to predict reliable binding modes.
IV (Input View)
How did LM-VS™ approach it?
By analyzing thousands of conformational frames, LM-VS™ identified anchor residues that remain stable across transitions and used them as the foundation for scaffold design.
Problem
Why is it challenging?
EGFR undergoes significant conformational changes during activation and mutation, causing frequent reshaping of its binding pocket and charge distribution.
Conventional docking methods treat proteins as static structures, often failing to predict reliable binding modes.
IV (Input View)
How did LM-VS™ approach it?
By analyzing thousands of conformational frames, LM-VS™ identified anchor residues that remain stable across transitions and used them as the foundation for scaffold design.
Problem
Why is it challenging?
EGFR undergoes significant conformational changes during activation and mutation, causing frequent reshaping of its binding pocket and charge distribution.
Conventional docking methods treat proteins as static structures, often failing to predict reliable binding modes.
IV (Input View)
How did LM-VS™ approach it?
By analyzing thousands of conformational frames, LM-VS™ identified anchor residues that remain stable across transitions and used them as the foundation for scaffold design.
PAV (Post Analysis View)
Does it really work?
Incorporating full dynamic motion into the design preserved stable interactions throughout conformational shifts. Anchored scaffolds maintained contact even in regions where binding was expected to break.
Significance
A Shift in Design Philosophy
Instead of avoiding Molecular Dynamics, LM-VS™ integrates structural flexibility as a design variable — proving that motion-aware scaffolds can achieve stable binding on dynamic targets.
PAV (Post Analysis View)
Does it really work?
Incorporating full dynamic motion into the design preserved stable interactions throughout conformational shifts. Anchored scaffolds maintained contact even in regions where binding was expected to break.
Significance
A Shift in Design Philosophy
Instead of avoiding Molecular Dynamics, LM-VS™ integrates structural flexibility as a design variable — proving that motion-aware scaffolds can achieve stable binding on dynamic targets.
PAV (Post Analysis View)
Does it really work?
Incorporating full dynamic motion into the design preserved stable interactions throughout conformational shifts. Anchored scaffolds maintained contact even in regions where binding was expected to break.
Significance
A Shift in Design Philosophy
Instead of avoiding Molecular Dynamics, LM-VS™ integrates structural flexibility as a design variable — proving that motion-aware scaffolds can achieve stable binding on dynamic targets.
PAV (Post Analysis View)
Does it really work?
Incorporating full dynamic motion into the design preserved stable interactions throughout conformational shifts. Anchored scaffolds maintained contact even in regions where binding was expected to break.
Significance
A Shift in Design Philosophy
Instead of avoiding Molecular Dynamics, LM-VS™ integrates structural flexibility as a design variable — proving that motion-aware scaffolds can achieve stable binding on dynamic targets.
PPI Surface
PPI Surface
Case 2. MDM2 —
Shape Complementarity on Flat Surfaces
Case 2. MDM2 —
Shape Complementarity on Flat Surfaces
Problem
Why is it challenging?
MDM2 interacts with the tumor-suppressor protein p53 on a shallow and flat groove with little depth. Conventional inhibitors mimic the binding mode of p53, but lack sufficient surface complementarity to maintain stable adhesion — resulting in weak and transient binding on the flat interface.
IV (Input View)
How did LM-VS™ approach it?
Analyzed surface curvature to locate hydrophobic anchors and designed scaffolds that adhere to the contour rather than penetrating the plane.
Problem
Why is it challenging?
MDM2 interacts with the tumor-suppressor protein p53 on a shallow and flat groove with little depth. Conventional inhibitors mimic the binding mode of p53, but lack sufficient surface complementarity to maintain stable adhesion — resulting in weak and transient binding on the flat interface.
IV (Input View)
How did LM-VS™ approach it?
Analyzed surface curvature to locate hydrophobic anchors and designed scaffolds that adhere to the contour rather than penetrating the plane.
Problem
Why is it challenging?
MDM2 interacts with the tumor-suppressor protein p53 on a shallow and flat groove with little depth. Conventional inhibitors mimic the binding mode of p53, but lack sufficient surface complementarity to maintain stable adhesion — resulting in weak and transient binding on the flat interface.
IV (Input View)
How did LM-VS™ approach it?
Analyzed surface curvature to locate hydrophobic anchors and designed scaffolds that adhere to the contour rather than penetrating the plane.
Problem
Why is it challenging?
MDM2 interacts with the tumor-suppressor protein p53 on a shallow and flat groove with little depth. Conventional inhibitors mimic the binding mode of p53, but lack sufficient surface complementarity to maintain stable adhesion — resulting in weak and transient binding on the flat interface.
IV (Input View)
How did LM-VS™ approach it?
Analyzed surface curvature to locate hydrophobic anchors and designed scaffolds that adhere to the contour rather than penetrating the plane.
PAV (Post Analysis View)
Does it really work?
The LM-VS™ designed scaffold covered the interface snugly, showing improved persistence and complementarity compared to traditional inhibitors.
Significance
A Shift in Design Philosophy
A protein surface is not a limitation — it is a landscape to be engineered. By aligning electronic density instead of pursuing depth, LM-VS™ achieved structural persistence even on flat interfaces.
PAV (Post Analysis View)
Does it really work?
The LM-VS™ designed scaffold covered the interface snugly, showing improved persistence and complementarity compared to traditional inhibitors.
Significance
A Shift in Design Philosophy
A protein surface is not a limitation — it is a landscape to be engineered. By aligning electronic density instead of pursuing depth, LM-VS™ achieved structural persistence even on flat interfaces.
PAV (Post Analysis View)
Does it really work?
The LM-VS™ designed scaffold covered the interface snugly, showing improved persistence and complementarity compared to traditional inhibitors.
Significance
A Shift in Design Philosophy
A protein surface is not a limitation — it is a landscape to be engineered. By aligning electronic density instead of pursuing depth, LM-VS™ achieved structural persistence even on flat interfaces.
PAV (Post Analysis View)
Does it really work?
The LM-VS™ designed scaffold covered the interface snugly, showing improved persistence and complementarity compared to traditional inhibitors.
Significance
A Shift in Design Philosophy
A protein surface is not a limitation — it is a landscape to be engineered. By aligning electronic density instead of pursuing depth, LM-VS™ achieved structural persistence even on flat interfaces.
TPD Warhead Design
TPD Warhead Design
Case 3. CDK6 —
Precision Control in Dual Binding Geometry
Case 3. CDK6 —
Precision Control in Dual Binding Geometry
Problem
Why is it challenging?
CDK6, a cell-cycle regulatory kinase, features a deep, narrow ATP pocket.
Conventional inhibitors strengthen hinge binding but lose geometric balance when forming ternary complexes with E3 ligases.
IV (Input View)
How did LM-VS™ approach it?
Maintained the hinge axis while re-aligning local hydrophobic networks to fix the binding direction and spatial orientation.
Problem
Why is it challenging?
CDK6, a cell-cycle regulatory kinase, features a deep, narrow ATP pocket.
Conventional inhibitors strengthen hinge binding but lose geometric balance when forming ternary complexes with E3 ligases.
IV (Input View)
How did LM-VS™ approach it?
Maintained the hinge axis while re-aligning local hydrophobic networks to fix the binding direction and spatial orientation.
Problem
Why is it challenging?
CDK6, a cell-cycle regulatory kinase, features a deep, narrow ATP pocket.
Conventional inhibitors strengthen hinge binding but lose geometric balance when forming ternary complexes with E3 ligases.
IV (Input View)
How did LM-VS™ approach it?
Maintained the hinge axis while re-aligning local hydrophobic networks to fix the binding direction and spatial orientation.
Problem
Why is it challenging?
CDK6, a cell-cycle regulatory kinase, features a deep, narrow ATP pocket.
Conventional inhibitors strengthen hinge binding but lose geometric balance when forming ternary complexes with E3 ligases.
IV (Input View)
How did LM-VS™ approach it?
Maintained the hinge axis while re-aligning local hydrophobic networks to fix the binding direction and spatial orientation.
PAV (Post Analysis View)
Does it really work?
The designed warhead retained its orientation and balance, ensuring stable complex formation during E3 binding.
Significance
A Shift in Design Philosophy
Beyond simply improving potency, LM-VS™ proposes a structural buffering strategy — minimizing conformational distortion during degradation complex formation.
PAV (Post Analysis View)
Does it really work?
The designed warhead retained its orientation and balance, ensuring stable complex formation during E3 binding.
Significance
A Shift in Design Philosophy
Beyond simply improving potency, LM-VS™ proposes a structural buffering strategy — minimizing conformational distortion during degradation complex formation.
PAV (Post Analysis View)
Does it really work?
The designed warhead retained its orientation and balance, ensuring stable complex formation during E3 binding.
Significance
A Shift in Design Philosophy
Beyond simply improving potency, LM-VS™ proposes a structural buffering strategy — minimizing conformational distortion during degradation complex formation.
PAV (Post Analysis View)
Does it really work?
The designed warhead retained its orientation and balance, ensuring stable complex formation during E3 binding.
Significance
A Shift in Design Philosophy
Beyond simply improving potency, LM-VS™ proposes a structural buffering strategy — minimizing conformational distortion during degradation complex formation.
One Principle, Across All Targets
One Principle, Across All Targets
One Principle, Across All Targets
One Principle, Across All Targets
From Observation to Validation —
A Unified Logic for Molecular Design
From Observation to Validation — A Unified Logic
for Molecular Design
Designed Scaffold LM-VS™ observes protein dynamics, learns persistent binding patterns,
designs scaffolds based on these pattern, and validates their stability through AI-based simulation.
Designed Scaffold LM-VS™ observes protein dynamics, learns persistent binding patterns,
designs scaffolds based on these pattern, and validates their stability through AI-based simulation.
Observe
Tracking protein motion over time
Observe
Tracking protein motion over time
Observe
Tracking protein motion over time
Observe
Tracking protein motion over time
Learn
Learn persistent binding patterns
Learn
Learn persistent binding patterns
Learn
Learn persistent binding patterns
Learn
Learn persistent binding patterns
Design
Creating structures that fit the pattern
Design
Creating structures that fit the pattern
Design
Creating structures that fit the pattern
Design
Creating structures that fit the pattern
Validate
Testing stablity and performance
Validate
Testing stablity and performance
Validate
Testing stablity and performance
Validate
Testing stablity and performance
EGFR
MDM2
CDK6
Strategy
Controlling structural flexibility
Compensate for flat surface
Balance dual-site geometry
Issues
Active–inactive transition
Flat-surface instability
Narrow pocket restriction
Observation
Track motion dynamics
Map surface electrons
Map dual-site vectors
Learning
Find stable pivots
Identify planar anchors
Learn spatial correlation
Design (IV)
Hinge-pivot control
π–π / CH–π network
Fix warhead direction
Validation (PAV)
Maintain binding stability
Enhance surface adhesion
Verify alignment & balance
EGFR
MDM2
CDK6
Strategy
Controlling structural flexibility
Compensate for flat surface
Balance dual-site geometry
Issues
Active–inactive transition
Flat-surface instability
Narrow pocket restriction
Observation
Track motion dynamics
Map surface electrons
Map dual-site vectors
Learning
Find stable pivots
Identify planar anchors
Learn spatial correlation
Design (IV)
Hinge-pivot control
π–π / CH–π network
Fix warhead direction
Validation (PAV)
Maintain binding stability
Enhance surface adhesion
Verify alignment & balance
EGFR
MDM2
CDK6
Strategy
Controlling structural flexibility
Compensate for flat surface
Balance dual-site geometry
Issues
Active–inactive transition
Flat-surface instability
Narrow pocket restriction
Observation
Track motion dynamics
Map surface electrons
Map dual-site vectors
Learning
Find stable pivots
Identify planar anchors
Learn spatial correlation
Design (IV)
Hinge-pivot control
π–π / CH–π network
Fix warhead direction
Validation (PAV)
Maintain binding stability
Enhance surface adhesion
Verify alignment & balance
EGFR
MDM2
CDK6
Strategy
Controlling structural flexibility
Compensate for flat surface
Balance dual-site geometry
Issues
Active–inactive transition
Flat-surface instability
Narrow pocket restriction
Observation
Track motion dynamics
Map surface electrons
Map dual-site vectors
Learning
Find stable pivots
Identify planar anchors
Learn spatial correlation
Design (IV)
Hinge-pivot control
π–π / CH–π network
Fix warhead direction
Validation (PAV)
Maintain binding stability
Enhance surface adhesion
Verify alignment & balance
Now it's your turn to prove at your target
Now it's your turn to prove
at your target
Experience LM-VS™, which starts with logic and is completed with data,
from IV design to PAV validation.
Experience LM-VS™, which starts with logic
and is completed with data,
from IV design to PAV validation
Features
Features
Features
Features
Efficiency Maximized
by the Precision of Technology
Efficiency Maximized
by the Precision of Technology
LM-VS™ redefines Hit Discovery — delivering faster results, fewer failures, and lower costs.
LM-VS™ sets a new standard for Hit Discovery, not just in speed, but in accuracy
and validated data.
Accelerated Hit Discovery
Identify purchasable and synthesizable hit candidates within 2 weeks from a 10 billion-compound library.
Accelerated Hit Discovery
Identify purchasable and synthesizable hit candidates within 2 weeks from a 10 billion-compound library.
Accelerated Hit Discovery
Identify purchasable and synthesizable hit candidates within 2 weeks from a 10 billion-compound library.
Accelerated Hit Discovery
Identify purchasable and synthesizable hit candidates within 2 weeks from a 10 billion-compound library.
Reduced Trial & Error
Multiple rounds of AI learning refine prediction accuracy and increase confidence in hit validation.
Reduced Trial & Error
Multiple rounds of AI learning refine prediction accuracy and increase confidence in hit validation.
Reduced Trial & Error
Multiple rounds of AI learning refine prediction accuracy and increase confidence in hit validation.
Reduced Trial & Error
Multiple rounds of AI learning refine prediction accuracy and increase confidence in hit validation.
Cost-Efficient Research
AI-validated data and SAR-based insights streamline optimization and maximize research ROI.
Cost-Efficient Research
AI-validated data and SAR-based insights streamline optimization and maximize research ROI.
Cost-Efficient Research
AI-validated data and SAR-based insights streamline optimization and maximize research ROI.
Cost-Efficient Research
AI-validated data and SAR-based insights streamline optimization and maximize research ROI.
Process
Process
Process
Process
2-Week Completion Process
2-Week Completion Process
We share progress throughout the process and apply your feedback to accelerate successful Hit discovery.
We transparently share all stages from design to analysis and reporting based on target protein information, completing it together.
Deliverables
Deliverables
Deliverables
Deliverables
Comprehensive Hit Discovery Results Package
Comprehensive Hit Discovery Results Package
LM-VS™ delivers purchasable or synthesis-ready small-molecule candidates optimized for stable binding through AI,
reducing the time from Hit Discovery to lab validation.
LM-VS™ delivers purchasable or synthesis-ready small-molecule candidates optimized for stable binding through AI,
reducing the time from Hit Discovery to lab validation.
LM-VS™ delivers purchasable or synthesis-ready
small-molecule candidates optimized for stable binding through AI,
reducing the time from Hit Discovery to lab validation.
IV (Input View) Report
Visualization of scaffold design basis and structure
Protein–ligand interaction mapping
Key binding site analysis
PAV (Post Analysis View) Report
Visualization of Hit structures and interaction patterns
Protein–ligand binding mode interpretation
Hit summary and structural comparison
Final Report
Summary of key Hit candidates
Final Hit list with key metrics
3D Structures
Designed scaffold structures
Protein–ligand complex structures
Pricing
Pricing
Pricing
Pricing
Collaboration Models Tailored to
Research Stages and Goals
Collaboration Models Tailored to
Research Stages and Goals
Accelerate discovery, refine leads, and build lasting collaborations —
select the model that fits your research stage.
From early stages requiring rapid validation to strategic co-development, you can choose the most efficient collaboration method based on the speed and goals of your research.
Check out the optimal program for your research stage.
Standard
Popular
$20,000
/ Target Protein
Ideal for rapid Hit discovery and new target validation
AI-driven Hit design & screening
3rd-party app integrations
3rd-party app integrations
AI-driven Hit design & screening
Complete analysis package (IV+PAV+Reports)
Advanced analytics
Advanced analytics
Complete analysis package (IV+PAV+Reports)
Advanced
Guidance After Consultation
Ideal for expanding from Hit discovery to lead optimization
Follow-up lead design and optimization
Follow-up lead design and optimization
Follow-up lead design and optimization
Follow-up lead design and optimization
Customized analysis based on research goals
Customized analysis based on research goals
Customized analysis based on research goals
Customized analysis based on research goals
Partnership
Decision After Consultation
Design for strategic co-development and data collaboration
Joint research on custom AI algorithms and pipelines
Dedicated account & success manager
Dedicated account & success manager
Joint research on custom AI algorithms and pipelines
Long-term partnership with shared research goals
Custom dashboards & reports
Custom dashboards & reports
Long-term partnership with shared research goals
Support Center
Support Center
Support Center
Support Center
FAQ
FAQ
Is there any information or materials that the client needs to prepare for the consultation?
Are there minimum project size or conditions?
Is it possible to request intermediate reviews or modifications?
How are costs calculated?
Is it possible to issue proof documents such as invoices upon payment?
Is it possible to get a refund or cancellation?
Can the results be used for IP registration or patent strategies?
Can it be expanded into follow-up research or joint development?
How is data security and confidentiality ensured?
Is there any information or materials that the client needs to prepare for the consultation?
Are there minimum project size or conditions?
Is it possible to request intermediate reviews or modifications?
How are costs calculated?
Is it possible to issue proof documents such as invoices upon payment?
Is it possible to get a refund or cancellation?
Can the results be used for IP registration or patent strategies?
Can it be expanded into follow-up research or joint development?
How is data security and confidentiality ensured?
Is there any information or materials that the client needs to prepare for the consultation?
Are there minimum project size or conditions?
Is it possible to request intermediate reviews or modifications?
How are costs calculated?
Is it possible to issue proof documents such as invoices upon payment?
Is it possible to get a refund or cancellation?
Can the results be used for IP registration or patent strategies?
Can it be expanded into follow-up research or joint development?
How is data security and confidentiality ensured?
Is there any information or materials that the client needs to prepare for the consultation?
Are there minimum project size or conditions?
Is it possible to request intermediate reviews or modifications?
How are costs calculated?
Is it possible to issue proof documents such as invoices upon payment?
Is it possible to get a refund or cancellation?
Can the results be used for IP registration or patent strategies?
Can it be expanded into follow-up research or joint development?
How is data security and confidentiality ensured?
Let’s Connect
Let’s Connect
Let’s Connect
Let’s Connect
Ready to experience LM-VS™ —
start your hit discovery now
LM-VS™ simulates molecular dynamics to predict drug–target binding patterns and delivers hit candidates in just two weeks.
LM-VS™ simulates
molecular dynamics to predict drug-target
binding patterns and delivers
hit candidates in just two weeks.
From Data to Discovery.
Designed with Logic, Driven by Purpose.
Contact Us
Contact Us
© Syntekabio Co., Ltd. All rights reserved.
© Syntekabio Co., Ltd. All rights reserved.
© Syntekabio Co., Ltd. All rights reserved.
From Data to Discovery.
Designed with Logic, Driven by Purpose.
Contact Us
Contact Us
© Syntekabio Co., Ltd. All rights reserved.