Natural Product Drug Discovery — AI Platform

Nature encoded
medicine.
We decode it.

Bionics AI is the world's most advanced AI platform for natural product drug discovery — from plant compound to engineered clinical candidate, orchestrated by proprietary AI in a single session.

Open Platform See the science

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SIRT1 — NAD-dependent deacetylase

PDB: 5BTR · Resveratrol binding complex · Natural product target

Docking

PDB: 1HSG

HIV-1 Protease with inhibitor

NP target

PDB: 5BTR

SIRT1 — resveratrol complex

Target

PDB: 6LU7

SARS-CoV-2 Main protease

Anti-inflammatory

PDB: 1PXX

COX-2 with ligand

Molecular docking

Where a molecule fits determines what it cures.

Bionics AI computes high-precision molecular docking at the binding pocket level. Given a protein structure and a natural compound SMILES, the platform identifies optimal binding poses, scores free energy of binding, and ranks candidates by estimated affinity — with full residue-level interaction maps.

Structures are energy-minimized via molecular dynamics before docking, ensuring pocket geometry reflects biologically realistic conditions, not idealized templates.

P2Rank

Binding pocket detection

Vina

AutoDock scoring engine

OpenMM

MD energy minimization

< 3 min

Fold → dock pipeline

Natural intelligence

Millions of plant compounds.
Nature's undiscovered drug library.

Bionics AI integrates PubChem, ChEMBL, and COCONUT to screen natural product space against defined targets — with full 3D structure retrieval, ADMET profiling, and analog generation from each hit.

CID 445154

Resveratrol

Vitis vinifera — red grape skin & seeds

StilbeneSIRT1 agonistAntioxidant

CID 5280343

Quercetin

Quercus robur — oak bark & leaves

FlavonoidPI3K inhibitorAnti-inflammatory

CID 969516

Curcumin

Curcuma longa — turmeric rhizome

CurcuminoidNF-κB inhibitorPleiotropic

CID 5281672

Apigenin

Apium graveolens — parsley & celery

FlavoneCDK2 inhibitorAnxiolytic

CID 73659

Berberine

Berberis vulgaris — barberry root

IsoquinolineAMPK activatorAntimicrobial

CID 2723872

EGCG

Camellia sinensis — green tea leaves

CatechinEGFR inhibitorAntitumor

Protein structures

Every target is a three-dimensional problem.

Bionics AI folds, analyzes, and docks against any human protein — from UniProt accession to energy-minimized structure with annotated binding pockets, membrane topology, and interaction network.

PDB: 3HTB · GPCR

β2 Adrenergic Receptor

G-protein coupled receptor — transmembrane target for cardiovascular and pulmonary drug design.

PDB: 4RLU · Kinase

EGFR Kinase Domain

Epidermal growth factor receptor — primary target in NSCLC, breast cancer, and head/neck cancer research.

PDB: 2HHB · Transport

Hemoglobin

Classic allosteric protein — used as structural benchmark for fold quality and binding site annotation.

Our premise

Nature has already solved most of what medicine needs to find.

Millions of bioactive molecules exist across plant, fungal, and marine sources. The bottleneck is not biology — it is the ability to read, interpret, and translate molecular information at scale.

Bionics AI was built to eliminate that bottleneck: every pipeline produces real, traceable scientific output — not summaries, not approximations.

Every molecule is a message. We decode it — and improve on it.

Natural compounds are starting points. Bionics AI generates optimized analogs, designs protein-drug conjugates, predicts ADMET profiles, and scores binding affinity against validated targets — producing new molecules that nature never made.

Pipeline catalog

15 end-to-end research workflows

Pipeline ID	Name	Description	Mode
natural_to_drug	Natural to Drug	Natural compound → analogs → ADMET → docking → ranked candidates	GPU
admet_full_screen	ADMET Screen	Full PK/safety — BBB, hERG, CYP450, solubility, bioavailability, toxicity	CPU
medchem_optimization	MedChem Opt.	SMILES + objective → scaffold mutation → QED-ranked analog series	CPU
structure_to_function	Structure to Function	Sequence → fold → pocket detection → druggability score	GPU
genomic_target_discovery	Genomic Targets	Variant → VEP → Open Targets → PPI network → compound shortlist	API
clinical_landscape	Clinical Landscape	Indication → ClinicalTrials.gov → competitive intelligence report	API
drug_repurposing	Drug Repurposing	SMILES + target → approved drugs → ADMET comparison → clinical evidence	Hybrid
cellular_3d_modeling	Cellular 3D Model	Gene → fold → membrane analysis → PPI → energy minimization → report	GPU
synergistic_therapies	Synergistic Therapies	Two compounds → pathway overlap → mechanistic synergy + toxicity profile	Hybrid
protein_chimera_design	Protein Chimera	Two sequences → domain analysis → chimera design → fold + docking	GPU
multi_omics_integration	Multi-Omics	Proteomics + transcriptomics + metabolomics → AI reasoning → target ranking	GPU
antibiotic_discovery	Antibiotic Discovery	Organism target → mechanism → analog generation → membrane permeability	GPU
natural_product_screening	NP Screening	Natural product library → ADMET filter → target docking → ranked hits	CPU
protein_drug_conjugate	PDC Design	Carrier + warhead → complex folding → conjugate scoring → alternate carriers	GPU
peptide_linker_design	Peptide Linker	Target + compound → linker design → stability + affinity estimate	GPU

Proprietary engines

Built for drug discovery.
Not assembled from parts.

Every computational engine is purpose-built and owned by Bionics-AI, LLC. No licensing dependencies. No third-party scientific computation APIs.

Structure

Bionics Fold

Single-sequence protein folding. pLDDT-scored, energy-minimized. Up to 1,024 residues.

Complex

Bionics Complex

Protein-ligand and protein-protein complex folding for docking and conjugate design.

Reasoning

Bionics Reason

Biomedical reasoning engine for mechanism inference, synergy prediction, and multi-omics synthesis.

Generation

Bionics Mol

De novo molecule generation from learned chemical space — structurally coherent, drug-like analogs.

Protein design

Bionics Design

4.5B-parameter protein design engine for carrier design, chimera generation, and linker prediction.

Embeddings

Bionics Embed

Evolutionary-scale protein embeddings for similarity search and functional annotation.

Orchestration

Bionics AI

LLM coordinator that routes queries, dispatches specialized engines, synthesizes scientific output.

Cheminformatics

Bionics Chem

ADMET, docking, energy minimization, descriptor computation. Sub-100ms single-molecule queries.

Real scientific output

Traceable data.
Not summaries.

Every pipeline step returns structured scientific data — pChEMBL affinity values, pLDDT confidence scores, endpoint-specific ADMET thresholds, and residue-level docking interactions.

Live integration with ChEMBL, UniProt, ClinicalTrials.gov, STRING, KEGG, Open Targets, and Ensembl — always current, always traceable to source.

// drug_repurposing — candidate output
{
  "name": "Celecoxib",
  "smiles": "CC1=CC=C(C=C1)C1=CC(=NN1...",
  "target": "PTGS2 (COX-2)",
  "target_chembl_id": "CHEMBL230",
  "max_phase": 4,
  "pchembl_value": 7.4,
  "docking_score_kcal": -8.4,
  "admet": {
    "bbb_penetrant": false,
    "herg_risk": "low",
    "bioavailability": 0.74,
    "cyp3a4_inhibitor": false
  },
  "clinical_trials": 12,
  "repurposing_score": 0.83
}

Nature encodedmedicine.We decode it.

Where a molecule fits determines what it cures.

Millions of plant compounds.Nature's undiscovered drug library.

Every target is a three-dimensional problem.

Nature has already solved most of what medicine needs to find.

Every molecule is a message. We decode it — and improve on it.

15 end-to-end research workflows

Built for drug discovery.Not assembled from parts.

Traceable data.Not summaries.

Begin wherenature left off.

Nature encoded
medicine.
We decode it.

Millions of plant compounds.
Nature's undiscovered drug library.

Built for drug discovery.
Not assembled from parts.

Traceable data.
Not summaries.

Begin where
nature left off.