A vast chemical repository optimized for hit identification, lead optimization, and high-throughput screening.

Seamlessly integrated with Receptor.AI, ChemoVista enables AI-powered virtual screening, SAR modeling, and data-driven compound selection. The space is curated for:

Plated compounds, custom assay plates, and bulk supply options ready for immediate worldwide shipment.

Every compound undergoes HPLC, NMR, MS, and stability testing, ensuring reproducibility and high-quality data. Purity: min 90%, max 99%.

Compounds provided in standardized formats (SDF, SMILES, InChI, etc.), ensuring compatibility with computational pipelines and AI-driven screening.

Single-package shipments, temperature-controlled handling for DMSO solutions, and free customs clearance for US & EU customers.

VirtuSynthium provides access to a virtual library of 10¹⁶ synthetically accessible molecules—the largest AI-navigable chemical space available — constructed through the combinatorial application of over 1,000,000 validated reagents and building blocks using diverse, reaction-aware design protocols for dynamic and scalable molecular generation.

Advanced machine learning, predictive ADMET modeling, and AI-guided virtual screening enable precise compound selection for high-impact drug discovery.

Unlike static enumerated libraries, VirtuSynthium incorporates real-time synthetic feasibility assessment using over 1,000 validated reaction pathways and qualified building blocks, ensuring that each proposed compound is practically accessible and can be synthesized and delivered within industry-standard lead times, starting from as little as 4 weeks.

SAS < 7 ensures that AI-generated molecules are not only innovative but also synthetically actionable, streamlining the path from design to synthesis and ultimately, to clinical relevance.

Directly embedded in the REAXENSE platform, facilitating hit identification, lead optimization, and structure-based drug design with IP-free exploration.

Balances Rule of Five (Ro5) and Beyond Ro5 (bRo5) compounds, including macrocycles, peptidomimetics, and PROTAC-like structures, for tackling previously undruggable targets.

VirtuSynthium streamlines hit-to-lead workflows by integrating AI-driven compound prioritization with synthetic feasibility modeling, significantly reducing development timelines, cost burdens, and attrition rates — thereby enabling researchers to efficiently navigate and exploit untapped regions of chemical space.

Use Receptor.AI’s ensemble-based conformational analysis to model dynamic peptide structures. Integrate real-time 3D visualization and AI-guided SAR tools for affinity, selectivity, and stability optimization.

Predict and rank peptide-target interactions using Receptor.AI’s proprietary deep learning models for binding affinity, ADMET, and immunogenicity. Map interactions with protein–protein interfaces and allosteric sites.

Enhance pharmacokinetics via AI-driven prediction of cyclization, PEGylation, lipidation, or D-amino acid substitutions—guided by Receptor.AI’s molecular dynamics and de novo design engines.

Transition from design to synthesis using automated planning and virtual reagent matching within the REAXENSE ecosystem. Deliver peptides at scale, from research-grade to GMP-compliant formats.

Ideal for oncology, infectious diseases, immunotherapy, and targeting “undruggable” PPIs. OmniPeptide Nexus empowers faster, smarter peptide drug discovery—fully embedded in Receptor.AI’s discovery pipeline.

Utilizes transformer-based models and generative algorithms (e.g., ProtGPT, LSTM, GANs) to design chemically and structurally diverse macrocycles—including cyclic peptides, bridged scaffolds, and peptidomimetics—optimized for target engagement, stability, and synthesis.

MacroCyclePro leverages a multi-tiered DOS strategy to construct structurally diverse, stereochemically rich macrocyclic libraries. The platform implements both algorithmic assembly routes and ring distortion tactics to expand scaffold complexity and chemical space coverage:

Integrated with Receptor.AI, the platform enables real-time binding affinity prediction, conformational scoring, and ADMET profiling. Structural optimization workflows refine hits into high-quality leads with enhanced pharmacological properties.

MacroCyclePro is purpose-built to tackle flat, groove-shaped, and tunnel-like protein interfaces—such as protein–protein interactions—through preorganized, conformationally restricted scaffolds capable of chameleonic behavior and ternary complex formation.

Focuses on chemically privileged macrocyclic space with rich stereochemistry, increased polar surface area, and high molecular weight—balancing permeability, solubility, and bioavailability via intra-molecular hydrogen bonding and scaffold engineering.

Every AI-designed macrocycle is paired with a validated, cost-effective synthetic route. MacroCyclePro supports parallel solid-phase peptide synthesis, native ligation, and custom modifications with up to 99% purity in both research and GMP-grade formats.

Predictive AI tools guide PEGylation, lipidation, and encapsulation into nanoparticles or microneedles to engineer orally bioavailable and injectable macrocyclic drugs with sustained release and improved pharmacokinetics.