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Company description

Receptor.AI is a TechBio company headquartered in the United States (with origins in Kyiv and a London office) that has built a multiplatform AI ecosystem for drug discovery. The company serves pharmaceutical and biotech organizations — from mid-sized companies to major Big Pharma partners — helping discovery teams navigate structural uncertainty, optimization trade-offs, and complex design challenges across the full spectrum from hit discovery to lead optimization. Receptor.AI's approach is modality-agnostic and biology-driven, deploying tailored Agentic AI to orchestrate modality-specific workflows and models that make the creation of new therapeutics faster, more rational, and transparently grounded in science.

Founded in 2021 with a team of 15 experts in medicinal chemistry and AI, Receptor.AI has grown to 40+ specialists across AI, molecular science, and operations. The company has initiated over 40 drug discovery projects and achieved an 86% success rate for completed projects. Key milestones include developing ArtiDock — a best-in-class AI docking model that outperforms conventional and AI docking techniques including AlphaFold — partnering with NVIDIA to enhance generative AI capabilities, establishing partnerships with major pharmaceutical companies, joining the Peptide Drug Hunting Consortium, and launching a joint program with Ono Pharmaceutical. Scientific leadership includes Nobel Laureate in Chemistry Dr. Morten P. Meldal as scientific advisor, alongside Dr. Rajiah Aldrin Denny as Chief Scientific Advisor and Dr. Tomi K. Sawyer as Scientific Advisor for peptide therapeutics.

Small Molecules Platform

• AI drug discovery workflows tailored for different target classes including kinases, GPCRs, ion channels, and enzymes.
• AI pocket identification and targeting covering allosteric, hidden, transient, and cryptic binding pockets.
• Automated SAR analysis using a hybrid intelligence approach, combined with AI-driven binding mode identification.
• Multiparametric virtual screening and lead optimization powered by the QuorumMap tool.
• Selectivity optimization against highly similar isoforms and mutants of target proteins.
• The largest set of ADMET endpoints for prediction and optimization, delivered through the ADMETiQ module — covering 80+ endpoints.
• Capabilities for the design of novel, IP-free compounds targeting cryptic and transient protein pockets.

Peptide Platform

• De novo binder design based on endogenous ligands, protein-protein interaction (PPI) partners, or display hits.
• Access to a library of 10,000+ non-canonical amino acids, non-peptide building blocks, and diverse linkage chemistry for unlimited structural diversity.
• Multiparametric optimization of peptide activity, membrane permeability, and oral bioavailability.
• A peptide-to-small-molecule workflow enabling the development of compounds with superior ADMET properties.
• A scaffold-agnostic system that supports peptides of any topology and secondary structure.
• Capabilities for targeting intracellular proteins and designing orally bioavailable peptides.

Biologics & Proximity Inducers Platform

• Design of proximity inducers including degraders, molecular glues, and PPI disruptors.
• Antibody-enabled therapeutics including bispecifics, immune cell engagers, and antibody-guided scaffolds.
• Prediction of PPI structures and ternary complexes without requiring known structures or homology templates, using a template-agnostic model.
• Targeting of both natural and induced PPIs, including transient and membrane-associated interactions.
• Support for diverse modality formats such as small molecules, peptides, antibody-derived formats, and drug conjugates.

Core Technology & Scientific Capabilities

• ArtiDock: a proprietary best-in-class AI docking model that outperforms all conventional and AI docking techniques, including AlphaFold-based approaches.
• ADMETiQ: a multitask ADMET prediction and optimization module covering the largest set of endpoints in the field.
• QuorumMap: a tool for multiparametric virtual screening and lead optimization.
• Physics-informed methods for assessing membrane permeability of challenging molecules, including conformationally flexible chameleonic macrocycles.
• Semi-ligand-based AI models and 3DProtDTA for binding affinity prediction and prioritization.
• Adaptive screening cascade orchestration and multiparameter optimization under biological assay constraints.

Leadership Team

• Dr. Alan Nafiev, CEO & Founder — PhD in Data Science with 15+ years at the intersection of data science, life sciences, and AI platforms, focused on decision-driven AI systems and adaptive screening cascade orchestration.
• Dr. Sergii Starosyla, CTO & Co-founder — PhD in Molecular Biology with 15+ years in drug discovery and scientific software development, building production-grade ML-based prioritization engines and multi-fidelity screening workflows.
• Dr. Semen Yesylevskyy, CSO & Co-founder — PhD in Biophysics with 25+ years of expertise in molecular modeling, membrane biophysics, and drug–membrane interaction simulation.
• Dr. Askar Kuchumov, Head of Business Development — PhD in Biochemistry and Molecular Biology with 15+ years of experience in biotech business development and venture capital.

Partnerships, Compliance & Notable Milestones

• Strategic partnership with NVIDIA to enhance generative AI capabilities for drug discovery.
• Joint program with Ono Pharmaceutical to design novel therapeutics, expanding reach in the Japanese pharma market.
• Established partnerships with major Big Pharma companies, including a key collaboration focused on membrane mitochondrial kinases.
• Member of the Peptide Drug Hunting Consortium (PDHC), contributing AI expertise and serving on advisory boards.
• Completed first IND-stage project focused on developing lipid formulations for TLR agonists.
• Demonstrated in vivo proof-of-concept for a membrane transporter inhibitor program.
• Case studies include targeting proteins from the integrin family, designing dual agonists to CD36/GPR120 for obesity and inflammation, addressing multidrug resistance in Acinetobacter baumannii via ATP synthase targeting, and developing selective inhibitors for one of six ion channel isoforms.

Receptor.AI combines deep scientific expertise with scalable AI infrastructure to address some of the most challenging problems in modern drug discovery — from undruggable targets and cryptic binding sites to complex multimodal therapeutics — making it a distinctive partner for organizations seeking to accelerate and de-risk their discovery programs.

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Software attributed to Receptor.AI

• PharmaSphereView
• PharmaSphereView
• REAXENSEView

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