Oligonucleotide Design
Smarter, Faster, More Reliable Oligonucleotide Design
Advanced force fields and molecular dynamics simulations ensure realistic modeling of modified nucleotides—delivering sequences optimized for stability, affinity, and selectivity before you hit the bench.
Establish design purpose and functionality
The specific therapeutic or biotechnological application is clarified, and the type of oligonucleotide to be designed or optimized (e.g., ASO, siRNA, aptamer) is identified. This step focuses on understanding the required molecular function and target interactions.
Propose trial compounds and exploring key conformations
Initial three-dimensional models of oligonucleotides are constructed using validated force field models and molecular dynamics simulations, followed by preliminary conformational sampling. This includes considering the impact of potential chemical modifications on the structure.
Simulating dynamics to predict properties
Extensive molecular dynamics (MD) simulations are performed to study the oligonucleotide's structural stability, conformational dynamics, and electrostatic properties. Key metrics like binding affinity and melting temperature are predicted.
Assess impact of modification on structure/property
The effects of chemical modifications on the oligonucleotide's structure, dynamics, and interactions with target molecules are analyzed. For chemically modified nucleic acids, our nucleic acid force fields offer accurate predictions.
Guide design for efficient therapeutic development
Insights derived from simulations guide the selection and optimization of lead compounds, reducing the number of experimental iterations. This accelerates the development of effective nucleic acid therapeutics.
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Compare our plans
Depending on system size, compute usage & level of support.
Project Scope | 1–2 systems, low–medium complexity | Multiple systems, high complexity | Long-term support, flexible tasks |
Methods | Basic/diverse docking; short–mid MD; µs-level MD; preliminary ML | Extended MD; FEP/TI; DFT; custom ML/workflows | Priority resources; advisory analysis; ad-hoc studies |
Deliverables | Full report + reproducible workflow (includes quick results + summary) | Complete technical dossier + reusable pipeline | Continuous deliverables with monthly milestones |
Use Cases | Feasibility, lead triage, publication-ready prep | Lead optimization, regulatory/Review-ready submissions | Ongoing R&D and parallel projects |
Customizable Report | Fixed Templates |
FAQ
Expert Insights. Scaled to Your Needs
How does the consulting process work?
Our process follows six steps: Scope Determination → Solution Proposal → Pilot Study → Result Presentation → Evaluation → Finalization & Execution. This ensures transparency and alignment at each stage.
What engagement models do you offer?
We offer fixed-price, milestone-based, time-and-materials, and retainer models, depending on project needs and level of support required.
How long does a typical project take?
Timelines depend on complexity, but small pilot studies can be completed in 2–4 weeks, while full-scale projects usually take 2–3 months or more.
Who owns the results and intellectual property?
Clients retain full ownership of results and foreground intellectual property. We work under NDA and provide clear IP agreements.
What types of systems do you work on?
We work across nucleic acids (natural and chemically modified), proteins, small molecules, polymers, and aqueous or complex chemical systems. Our workflows are adaptable to diverse research questions in biology, chemistry, and materials science.
Can you integrate experimental data into the modeling workflow?
Absolutely. Experimental observations such as binding assays, thermodynamic measurements, or structural data can be used to calibrate, benchmark, and validate our computational results.
How reliable are the predictions?
Our results are supported by validation against reference data, convergence diagnostics, and explicit reporting of uncertainties. We emphasize reproducibility and clearly state limitations alongside predictions.
Can you customize workflows for specific problems?
Yes. Every project is tailored to the client’s system, objectives, and available data. We design flexible workflows that balance accuracy, scalability, and cost.
What deliverables will I receive at the end of a project?
Deliverables typically include a detailed report with figures and tables, curated datasets, and reproducible workflows or scripts. All results are prepared to be publication- or presentation-ready.
Do you work with both academic and industry groups?
Yes. We collaborate with academic labs, biotech startups, and established companies worldwide.
Can you support grant or funding applications?
Yes. We provide preliminary computational results, methods descriptions, and figures that can strengthen the technical case of grant or funding proposals.
Can you scale computations using cloud resources if needed?
Yes. We routinely deploy workflows on cloud platforms for large-scale simulations, ensuring cost-efficiency, scalability, and secure data management.
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