AI-Powered Drug Discovery Services

Protein Modeling.
Molecular Docking.
Structure to Drug Lead.

Molecular Docking is ushering in a new era in precision drug development for the pharmaceutical industry, and Genix.ai is your partner to lead pharma in that direction.

Start Your Project → View All Services

$500

Per Target
Starting

3–14d

Turnaround
Time

AF3

AlphaFold3
Integrated

NDA

Full IP
Protection

End-to-End Workflow

From Sequence to Drug Candidate

Each step in the CADD pipeline, handled by our team. Pick individual services or commission the full pipeline.

Target Identification

Protein target selection from literature, genomics, or client specification

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Structure Prediction

AlphaFold3 / Rosetta / homology modeling + validation (Ramachandran, MolProbity)

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Molecular Docking

Virtual screening of ligand libraries, binding affinity scoring, pose analysis

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MD Simulation

Stability validation, RMSD/RMSF, binding free energy (MM-GBSA/PBSA), trajectory analysis

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ADMET & Reporting

Drug-likeness, toxicity prediction, Lipinski's rules, lead compound ranking + full report

Service Catalogue

Six Core Services

Commission individually or as a full CADD campaign. Every deliverable PhD-reviewed.

Foundation

Protein Structure Prediction

$500–1,500/target

3D structure from sequence using AI and physics-based methods. AlphaFold3 for monomers and complexes, RoseTTAFold for multi-chain, traditional homology modeling when templates exist. Every model validated with Ramachandran, MolProbity, and ProSA-web.

PDB structure file

Confidence scores (pLDDT)

Ramachandran validation

MolProbity quality report

PyMOL visualization images

Comparison with known structures

AlphaFold3 RoseTTAFold SWISS-MODEL Modeller

TAT: 3–5 days

Most Requested

Molecular Docking & Virtual Screening

$1,000–3,000

Dock your compounds against target proteins. From single-target docking to high-throughput virtual screening of thousands of ligands. Active site identification, grid preparation, flexible/rigid docking, binding mode analysis, and interaction visualization.

Binding affinity scores

Top-ranked ligand poses

2D interaction diagrams

3D binding site visualization

Hydrogen bond / hydrophobic maps

Ranked compound report

AutoDock Vina GOLD Glide HADDOCK

TAT: 5–10 days

Molecular Dynamics Simulation

$2,000–5,000/run

Validate docking results and study protein-ligand stability over time. 50–500 ns simulations using GROMACS or NAMD. RMSD, RMSF, radius of gyration, hydrogen bond analysis, binding free energy calculations (MM-GBSA / MM-PBSA).

RMSD / RMSF plots

Radius of gyration

H-bond occupancy analysis

Binding free energy (MM-GBSA)

Trajectory snapshots

Principal component analysis

GROMACS NAMD AMBER VMD

TAT: 7–14 days

ADMET & Drug-Likeness Prediction

$500–1,500/set

Absorption, Distribution, Metabolism, Excretion, and Toxicity profiling for your compound library. Lipinski's Rule of Five, Veber's rules, BBB permeability, CYP inhibition, hERG toxicity, AMES mutagenicity — all computationally predicted and report-ready.

Lipinski / Veber / Ghose filters

ADMET property table

Bioavailability radar charts

Toxicity risk assessment

CYP inhibition prediction

Lead compound ranking

SwissADME pkCSM ADMETlab RDKit

TAT: 3–5 days

Network Pharmacology

$2,000–8,000

Multi-target mechanism analysis for herbal formulations and complex drugs. Compound-target-pathway networks, PPI networks, hub gene identification, GO/KEGG enrichment. Perfect for AYUSH regulatory submissions and traditional medicine validation publications.

Compound-target network

PPI network (STRING)

Hub gene identification

GO & KEGG enrichment

Cytoscape visualizations

Publication-ready figures

Cytoscape STRING DAVID SwissTargetPrediction

TAT: 5–10 days

Full Pipeline

End-to-End CADD Campaign

$10K–50K

The complete computational drug discovery pipeline in one engagement: target identification → structure prediction → library preparation → docking → MD validation → ADMET → lead compound report. For pharma R&D and funded biotech companies.

All services above, integrated

Compound library curation

Multi-target screening

Ranked lead compound shortlist

SAR analysis

Executive summary report

Milestone-based delivery

Dedicated project manager

All tools from above TAT: 4–8 weeks

Who Uses This Service

Four distinct buyer segments — each with tailored deliverables.

💊

Pharma R&D

Outsourced CADD campaigns for drug pipeline targets. Virtual screening of proprietary compound libraries. NDA-protected, milestone-based delivery.

$10K–$50K/campaign

🧪

Biotech Startups

Structure prediction and docking for pitch deck data packages. Validate target-compound interactions before wet lab investment. Fast, affordable, investor-ready.

$2K–$15K/project

🌿

AYUSH / Herbal Pharma

Molecular docking of phytochemicals, network pharmacology, ADMET profiling for regulatory submissions. Publication-ready figures for evidence-based validation.

₹1.5L–₹6L/study

🎓

Academic Researchers

Structure prediction, docking, MD simulation for PhD thesis or journal publication. Methods section included. Academic pricing available.

$500–$5K/project

Pricing

Clear, Competitive Pricing

All prices in USD. AYUSH pricing also available in INR. Custom quotes for multi-target campaigns.

Service	Starting At	Typical Range	Turnaround	Input Required
Protein Structure Prediction	$500	$500–$1,500	3–5 days	Amino acid sequence (FASTA)
Homology Modeling + Validation	$500	$500–$1,200	3–5 days	Sequence + template PDB (optional)
Molecular Docking (single target)	$1,000	$1,000–$2,000	5–7 days	PDB + ligand structures (SDF/MOL2)
Virtual Screening (library)	$2,000	$2,000–$5,000	7–14 days	PDB + compound library (SMILES/SDF)
MD Simulation (100 ns)	$2,000	$2,000–$5,000	7–14 days	PDB complex or docking output
ADMET Profiling	$500	$500–$1,500	3–5 days	Compound list (SMILES)
Network Pharmacology	$2,000	$2,000–$8,000	5–10 days	Compound names or SMILES + disease
Full CADD Campaign	$10,000	$10K–$50K	4–8 weeks	Target + compound library

FAQ

Common Questions

I only have a protein sequence — can you still do docking?

Yes — we predict the 3D structure from your sequence first (using AlphaFold3 or homology modeling), validate it, and then proceed with docking. This is actually our most common workflow. You don't need an experimental crystal structure.

Can you dock herbal/phytochemical compounds for AYUSH submissions?

Absolutely — this is one of our specialties. We source phytochemical structures from PubChem/IMPPAT, dock them against your disease targets, run network pharmacology analysis, and deliver publication-ready figures. We understand AYUSH regulatory requirements and format deliverables accordingly. Pricing in INR available.

How long does an MD simulation take?

For a standard 100 ns simulation: 7–14 days including system setup, equilibration, production run, and analysis. Longer simulations (200–500 ns) take proportionally more time. We run on GPU-accelerated servers for maximum speed. Rush delivery available for time-sensitive projects.

What if I have thousands of compounds to screen?

We handle high-throughput virtual screening — from hundreds to hundreds of thousands of compounds. We use a funnel approach: initial fast docking to filter top 1–5% hits, followed by refined docking and optionally MD simulation on the top candidates. This keeps costs manageable while ensuring thoroughness. Contact us for volume pricing.

Do you use commercial software (Schrödinger, MOE)?

Our standard toolchain uses industry-standard open-source tools (AutoDock Vina, GROMACS, AlphaFold3, RDKit) which are widely accepted in peer-reviewed journals and by regulatory bodies. If your project specifically requires commercial tools (Schrödinger Glide, MOE, etc.), we can accommodate this — contact us for availability and pricing adjustments.

Will my compound structures and targets be kept confidential?

Yes — we sign an NDA before any data exchange. Your proprietary compound structures, targets, and results are never shared, published, or used for any other purpose. All data is stored on encrypted servers and deleted after project completion unless you request retention. Full IP ownership stays with you.

Get Started

Describe Your Target.
We'll Design the Campaign.

Free consultation — we assess feasibility, recommend the right approach, and deliver a clear proposal within 24 hours.

Email

biocompute@genix.ai

Response Time

Within 24 hours

🌿 AYUSH / Herbal Drug Companies

Looking for computational validation of your Ayurvedic, Unani, or Siddha formulations? We specialize in molecular docking and network pharmacology for traditional medicines. INR pricing available. Email us directly →

Request Docking / Modeling Quote

Name *

Email *

Organization *

Service Needed

Target Protein

Number of Compounds

Project Details

Quote within 24 hours. NDA available upon request.

Frequently Ask Questions

1. What is Molecular Docking?

Molecular docking is a computational technique that predicts the preferred orientation and binding affinity of a small molecule (ligand) to a target protein or receptor. By modeling how potential drug candidates interact at the atomic level with biological targets, docking provides researchers with a high-resolution view of molecular behavior before a single compound is synthesized in the lab.

2. Why Molecular Docking Matters for Pharma Companies?

The benefits of molecular docking extend across the entire drug development pipeline:

Reduced Time and Cost: Genix.ai delivers the holistic metrics in molecular docking for pharma. Thereby cutting down laboratory expenses and reduces the time required to develop new drugs. We virtually screen thousands to millions of compounds against a target, and eliminate the need for exhaustive physical high-throughput screening.
Higher Hit Rates: Docking prioritizes compounds with the strongest predicted binding affinity, meaning that only the most promising candidates advance to in vitro and in vivo testing. This improves the overall success rate of downstream experiments.
Precision Drug Design: Molecular docking enables structure-based drug design, a cornerstone of precision medicine. By analyzing the unique structural features of a patient-specific protein target, researchers can design molecules tailored to bind selectively, minimizing off-target effects and adverse reactions.
Optimization of Lead Compounds: Docking allows medicinal chemists to iteratively refine molecular structures, fine-tuning interactions such as hydrogen bonding, hydrophobic contacts, and electrostatic forces to maximize potency and selectivity.
Repurposing Existing Drugs: Docking can rapidly evaluate approved drugs against novel targets, opening viable pathways for drug repurposing — a strategy that significantly de-risks development.

3. Why Should Pharma Companies Partner with Genix.ai?

Genix.ai bridges the gap between IT infrastructure and biological research. As a reputable pharma company in the world, you are faced with the continuous task of discovering new drugs to cure major diseases.
Our biocompute environments are pre-configured for pharmaceutical workflows, reducing setup time from months to days and ensuring your computational foundation never becomes a bottleneck to scientific innovation.
With the help of artificial intelligence, Genix.ai will accelerate your efforts in drug research and development, ushering in a new era of collective ascendancy in medical science.

Protein Modeling. Molecular Docking. Structure to Drug Lead.