Bunsen autonomously executes complex discovery workflows, allowing you to focus on the breakthroughs that matter. We’re launching an early-access version this summer.
Sign up to join the waitlist and be the first to bring agentic AI to your molecular discovery pipeline.
Bunsen strings together complex pipelines, submits and monitors jobs, and self-corrects in real time to keep your projects running
Pre-loaded with expert digital chemistry knowledge, Bunsen extends the reach of Schrödinger’s software suite directly your hands to truly scale your scientific impact.
Sign up to join the waitlist and be the first to bring agentic AI to your molecular discovery pipeline.
Bunsen is an AI co-scientist built directly on the Schrödinger platform. It lets you describe a scientific goal in natural language and translates it into a validated computational workflow
Bunsen spans the full range of Schrödinger workflows. You can prepare protein structures, run docking campaigns, set up FEP+ calculations, design novel molecules with AutoDesigner, run molecular dynamics simulations, predict ADMET properties, query scientific databases, and much more — all from a single conversational interface.
Yes. Bunsen includes curated skills, tools, and chemistry-specific context across small molecule drug discovery, biologics engineering, materials science, and enterprise informatics.
Bunsen is purpose-built for computational chemistry and executes real calculations using Schrödinger’s validated physics on your infrastructure.
Bunsen is deployed as a dedicated, single-tenant instance for your organization. Your structures, results, and session data remain entirely within your infrastructure, we never train on your data.
No. Bunsen works on top of your existing Schrödinger platform. It orchestrates the same tools you already use — FEP+, Glide, Jaguar, Desmond, AutoDesigner, and others — through a conversational interface.
Bunsen is currently in closed beta with select discovery teams. We are actively expanding access in the coming months. Contact your Schrödinger Account Manager to learn more about availability for your organization.
Reach out to your Schrödinger Account Manager to discuss early access. They can walk you through how Bunsen fits your team’s workflows and infrastructure.
Yes. New expert skills are being added continuously across all supported domains. The Bunsen team works closely with Schrödinger’s scientific development groups to expand coverage as new platform capabilities ship.
MS DeNovoML uses state-of-the-art generative AI to autonomously produce novel molecular structures optimized for specific performance criteria and material properties. The platform provides a streamlined graphical environment, enabling scientists to navigate complex chemical spaces and balance multiple design objectives, including incorporating predictive DeepAutoQSAR models and enforcing physical constraints such as molecular weight and chemical composition.
DeNovoML effectively bridges the gap between high-level generative modeling and practical materials science, delivering AI-driven property optimization and design exploration to users at all levels.
that transforms the REINVENT generative engine into an accessible, panel-based workflow for code-free molecular and materials design
to plug in custom-trained predictive models that provide real-time scoring of generated molecules against target properties
to enforce essential boundaries on molecular weight, molecular descriptors, and specific chemical features to ensure candidates meet project specifications
to explore vast chemical spaces and generate high-quality candidates that satisfy precise functional requirements
Automated, scalable solution for the training and application of predictive machine learning models
Automated machine learning tools for materials science applications
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Deploy digital materials discovery workflows with a comprehensive and user-friendly platform grounded in physics-based molecular modeling, machine learning, and team collaboration.
Leverage Schrödinger’s expert computational scientists to assist at key stages in your materials discovery and development process.
Access expert support, educational materials, and training resources designed for both novice and experienced users.
Point defects, such as vacancies, substitutions, interstitials, and antisites can – even at low concentrations – significantly impact the electronic, optical, structural, and mechanical properties of crystals. Therefore, predicting defect concentrations and understanding which defect types are predominant are crucial in solid state materials science. MS DefectPro provides a comprehensive platform for predicting defect formation energies and related properties.
In this tutorial, we will learn how to generate point defects and how to calculate their defect formation energy, which includes a correction term for charged defects. Additionally, we will have a brief look at the density of states and the projected density of states.
Integrated graphical user interface for nanoscale quantum mechanical simulations
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Deploy digital materials discovery workflows with a comprehensive and user-friendly platform grounded in physics-based molecular modeling, machine learning, and team collaboration.
Leverage Schrödinger’s expert computational scientists to assist at key stages in your materials discovery and development process.
Access expert support, educational materials, and training resources designed for both novice and experienced users.
Cost savings
Faster to fit into your DMTA cycles
In silico screening results
Move beyond pass/fail with actionable, comprehensive readouts in a single day to supercharge your design process in lead optimization
Rapidly dial out liabilities with atom-level toxicity attribution required to not just fix a compound, but to design the superior compound from the start
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Life Science
Learn more about how Predicitive Tox offers advanced solutions to your toxicity problems
Publication
Life Science
Capability |
Description |
Benefits |
|---|---|---|
Best-in-class predictive models (FEP+ and IFD-MD) |
Rationalize structure activity relationship (SAR) to effectively dial-out known liabilities |
Avoid de-railing, or worse, abandoning your programs with predictions you can trust |
Actionable, comprehensive readouts in 24hrs |
Atom-level attribution and affinity data to move beyond traditional binary reports |
Reduce evaluation time from weeks to a single day, while gaining guidance to address each liability |
No complex setup and deployment |
A credit-based SaaS cloud solution for immediate project impact |
Simply upload your ligands and click “submit” to screen virtual compounds |
Start screening off-targets with computational predictive models—contact us today to discuss how you can start using Schrödinger’s solutions on your programs.
Don’t see your off-target of interest in the current lists above? Reach out so we can help.
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Savings on synthesis cost
Faster synthesis turnaround time
Faster DMTA cycles
Tap into real-time building block intelligence delivering tractable routes based on the availability of internal and commercial precursors
Accurately generate and score thousands of optimal, plausible routes to deliver the most optimal synthetic routes directly to the bench
Eliminate the bottleneck of manual route planning and dramatically reduce project spend by minimizing the need for expensive, multi-stage custom synthesis
Only invest resources in compounds with the highest probability of successful synthesis by using AI-powered forward reaction verification
Capability |
Description |
Benefits |
|---|---|---|
Accurate route planning |
AI-powered forward reaction verification coupled with in-house custom scoring |
Ensures that every suggested route is plausible and bench-ready |
Real-time building block intelligence |
Query billions of building blocks in real-time |
Actionable routes based on the immediate availability of internal and commercial precursors |
Massive scale and performance |
Distributed cloud-native MCTS architecture and Kubernetes infrastructure allow you to complete 100,000+ ideas in 24 hours at a low compute cost |
Rapid exploration of ultra-large chemical spaces without sacrificing accuracy |
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.
*Data from active internal Schrödinger’s therapeutics group discovery programs
LiveDesign ML is your complete, centralized solution for deploying and maintaining advanced machine learning models to accelerate and guide drug discovery programs. Acting as your ML co-pilot, it democratizes AI/ML model generation with a fully automated, high-throughput workflow and provides a seamless and effortless way to build, validate, and deploy models for critical tasks. By integrating directly into your central design platform, LiveDesign ML ensures your team always has access to the most accurate, scalable predictions without the burden of complex model deployment or maintenance.
AI-driven tool that helps you move from complex chemical targets to actionable synthesis plans accurately and efficiently by performing highly exhaustive searches to predict and score optimal, scalable, and cost-efficient synthetic pathways.
ML-powered engine that helps you prioritize the most promising leads by training custom machine learning models on your chemical data to accurately forecast the physical and chemical profiles of novel molecular structures.
TuneLabTM is a collaborative platform created to offer access to AI/ML tools leveraging Lilly’s own drug discovery models.
Discover how Schrödinger technology is being used to solve real-world research challenges
Empowering scientists with integrated AI/ML modeling for rapid molecular property predictions
Benchmark study of DeepAutoQSAR, ChemProp, and DeepPurpose on the ADMET subset of the Therapeutic Data Commons
Automated, scalable solution for the training and application of predictive machine learning models
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.
Maestro+LiveDesign offers industry-leading computational modeling tools in a flexible, cloud-native working environment for your entire discovery team — spanning both small and large molecule research. Streamline workflows with centralized access to all project data (experiment and in silico predictions), cutting-edge computational modeling tools, and collaborative decision-making technology — all in a single interface.
Date & Time:
February 26th, 2026 | 11:00AM EST
Location:
Virtual 
Maestro is Schrödinger’s streamlined portal to access state-of-the-art predictive computational modeling and machine learning workflows for molecular discovery
AI-assisted, intuitive graphical interface to model and interpret molecular interactions Technology backed by 30+ years of scientific R&D and validated by thousands of customers Full stack of capabilities and workflows accessible for users of all experience levels 
LiveDesign is the digital platform for modern drug discovery teams – powering collaboration anytime, anywhere
Cloud-based enterprise informatics solution to connect all your project data, in silico and experimental, on a single platform Combine the powers of predictive modeling and real-time data management to drive fewer, faster design cycles Utilize live data systems to eliminate communication through spreadsheets – streamlining collaboration with colleagues and CRO partners 
Work with our team of solutions architects to customize your deployment
Cloud-based, SaaS solution built to handle any type of data integration (e.g. compound and assay registration systems) Multiple different access models (on-prem, virtual clusters) for your organizational needs
Snap-in your own corporate databases and workflows to create a true enterprise platform
Schrödinger provides expert support, educational materials, and training resources designed for both novice and experienced users
Access interactive consultations and ongoing support from our large teams of application scientists, solutions architects, and customer success managers Level up your skillset with hands-on, online molecular modeling training courses available on-demand 
“Our team was globally distributed across three different companies, and LiveDesign made it feel like we were all operating seamlessly in the same office.”
Empowering Collaborative Medicinal Chemistry with LiveDesign: The Takeda Success Story
Transform your drug discovery program with Maestro and LiveDesign – make industry-leading computational modeling tools available to your entire team.
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T-cell receptors (TCRs) are at the heart of the adaptive immune response, making them prime targets for developing powerful T-cell immunotherapies for cancer and other diseases. However, the intricate and diverse nature of TCRs presents significant challenges in drug discovery, including issues with target specificity, affinity, and off-target toxicity. Schrödinger’s TCR modeling solutions are designed to harness computational modeling to overcome the challenges of TCR variability, MHC restriction, and cross-reactivity from sequence to clinical candidate.
Identify better quality candidates through simultaneous optimization of multiple parameters to facilitate more rapid testing and triaging of ideas
Lower protein optimization costs compared to traditional directed evolution wet lab protocols by running fewer cycles and assaying fewer variants
Reduce time-to-results from months to weeks by discarding irrelevant mutations early, as well as quickly generating and iterating through new ideas and follow-up designs
Unlike antibodies, which target surface antigens, TCRs recognize short peptide fragments presented by major histocompatibility complex (MHC) molecules. This mechanism – the pMHC-TCR complex – introduces challenges in three key areas:
Modeling environment for biologics discovery
Collaborative digital biologics design and discovery lab
Enable your T-cell receptor program with structure-based computational methods — contact us today to discuss how you can start using Schrödinger’s solutions.
Thank you, we’ll be in touch soon.
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.
Protein degraders offer a novel mechanism for modulating protein function by leveraging the cell’s natural degradation pathways. The formation of the ternary complex between the protein of interest, the E3 ligase, and the degrader is essential for degradation of the target to occur, although it is not sufficient. Therefore, knowledge of the structure of the ternary complex is highly desirable for rational design of improved degraders. Schrödinger’s Bifunctional Degrader Solutions predict possible ternary complexes and accurately score them to narrow down the models to consider for linker design and degrader optimization.
Accurately score ternary complexes with state-of-the-art scoring functions to focus resources on a select few models
Design superior protein degraders by adopting in silico optimization to improve binding affinity and degrader potency
Enable structure-based rational design via predictive modeling with computational workflows to benefit from a hypothesis-driven design strategy from the outset
Schrödinger’s FEP+ can be used for target and E3 ligase warhead optimization, for maintaining potency while optimizing properties or exploring linker attachment points and possible exit vectors. Our MD workflow (Desmond) also explores the possible exit vectors of a degrader and allows for accurate sampling.
Streamline the discovery process and accelerate the design-predict-make-test-analyze cycle with LiveDesign:
• Real-time data sharing
• Project management
Enable your bifunctional degrader R&D with structure-based rational design — contact us today to discuss how you can start using Schrödinger’s solutions.
Thank you, we’ll be in touch soon.
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.
MS Complex Bilayer Builder streamlines system preparation and accelerates your research with automated workflows that build complex, biologically-realistic lipid bilayers with embedded proteins, ready for further molecular dynamics simulations.
Generate lipid bilayers with and without embedded proteins in biologically-realistic environments using automated protocols that minimize setup errors and significantly reduce preparation time
Support a wide range of lipid types, protein orientations, and membrane compositions to suit various biological scenarios and research needs
Seamlessly integrate with multiple simulation engines, ensuring adaptability and reproducibility across diverse computational setups
Get answers to common questions and learn best practices for using Schrödinger’s software.
High-performance molecular dynamics (MD) engine providing high scalability, throughput, and scientific accuracy
Efficient coarse-grained (CG) molecular dynamics (MD) simulations for large systems over long time scales
Advance your materials R&D with unrivaled technologies and expertise
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.
Improve the quality of your computational predictions with best-in-class, proprietary force fields — developed in-house and built for accuracy
Force fields are used in molecular simulations to describe the interactions between atoms in a system. Having an accurate force field is at the heart of obtaining useful molecular structures and predicting relative energies, and yet many in silico programs employ force fields that are years, if not decades, old and suffer from lack of sufficient coverage for many common molecular motifs.
We are witnessing a shift toward a computational “predict-first” approach to drug discovery and materials science research.
Generate precise binding free energy predictions with FEP+, enabling more reliable rank ordering within congeneric series.
Enhance and accelerate physics-based computational methods by integrating AI/ML into force fields and simulation engines.
Accurately predict binding modes of novel scaffolds using advanced induced fit docking methods in IFD-MD.
Reveal mechanisms of action and key interaction energies through high-fidelity molecular dynamics simulations with Desmond.
Achieve better conformational sampling and docking poses with improved torsional energy descriptions across Glide, ConfGen, MacroModel, and Prime.
Accurate ligand binding mode prediction for novel chemical matter, for on-targets and off-targets
High-performance molecular dynamics (MD) engine providing high scalability, throughput, and scientific accuracy
Efficient tool for optimizing custom torsion parameters in OPLS4
Cutting-edge force field technologies for accurate property predictions
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.
