5–20%
Virtual Screening Hit Rate
10M+
Screening Compounds Available
3
Complementary Strategies
CADD
Comprehensive Platform
AI
Deep Learning Integration
Service Overview
Identify Novel Leads from Millions of Molecules — In Silico
Virtual screening is a computational approach that selects promising compounds from large chemical databases by applying drug design theory, physics-based docking, and machine learning. iCDMO's comprehensive CADD platform enables customized in silico virtual screening services — from rapid pharmacophore filtering to multi-million compound docking campaigns — dramatically shortening the time and cost of early drug discovery.
By combining the results of virtual screening with experimental assays, the experimental effort becomes more targeted, the hit rate increases substantially, and the research cycle is shortened. Our positive hit rate typically reaches 5–20%, far exceeding conventional high-throughput screening approaches.
Suitable For
Drug targets with known 3D structure (crystal, cryo-EM, NMR)
Targets where only homologous structures are available
Projects with known active compounds for QSAR / pharmacophore
PPI (protein–protein interaction) hot-spot pocket inhibition
Fragment-to-lead expansion and scaffold hopping campaigns
Focused library design for a specific target class (kinase, GPCR, protease)
Repositioning studies: screening approved drug libraries against new targets
Projects requiring rapid, cost-effective hit identification before HTS
Service Workflow
From Target Information to Confirmed Hit Compounds
A systematic five-stage quality-controlled pipeline covering target investigation through final hit delivery and scientific report.
01
01
Target Investigation & Binding Site Analysis
Client provides target information: sequence, PDB ID, or homologous structure reference
Binding site identification: SiteMap, fpocket, or cavity detection algorithms
Target protein preparation: protonation, hydrogen addition, energy minimization
Druggability assessment and allosteric pocket characterization for novel targets
02
02
Compound Database Preparation & ADMET Pre-Filtering
Access to proprietary and public libraries: ZINC, ChemBridge, Enamine, Maybridge
Lipinski Rule-of-Five and ADMET property pre-filtering to reduce inactive compounds
Structure standardization: salt removal, tautomer enumeration, 3D conformer generation
Diversity-based subset selection; focused library curation around target class
03
03
Pharmacophore Modeling & QSAR Analysis
Structure-based pharmacophore generation from protein-ligand complex interactions
Ligand-based pharmacophore from known actives when no 3D structure is available
QSAR model development: physicochemical descriptors, 2D/3D fingerprints, ML models
Shape and electrostatic similarity screening (Phase, MOE, Pharmit) for rapid first-pass filtering
04
04
Molecular Docking & Scoring
Hierarchical docking: HTVS → Standard Precision (SP) → Extra Precision (XP)
Multiple docking engines: Glide, AutoDock Vina, GOLD — consensus scoring for confidence
Binding mode analysis: hydrogen bond, hydrophobic, halogen bond, pi-stacking interactions
Refinement with molecular dynamics (MD) and MM-GBSA free energy re-scoring
05
05
Hit Identification, Manual Selection & Delivery
Expert medicinal chemist review of top-scored compounds for synthetic accessibility
Cluster analysis to maximize structural diversity in final hit list
Predicted ADMET profiling: logP, solubility, CYP inhibition, hERG, BBB penetration
Delivery of shortlisted active compounds with full docking poses and scoring report
Why Choose iCDMO
Service Advantages
Advanced Target Structure Analysis
iCDMO uses cutting-edge binding site detection and structural analysis tools to characterize cryptic pockets and allosteric sites overlooked by conventional approaches, maximizing the chances of finding genuine binders.
Extensive Virtual Compound Database
Access to tens of millions of commercially available compounds spanning ZINC, Enamine REAL, ChemBridge, and our own curated focused libraries — covering a broad chemical space for any target class.
Comprehensive CADD Platform
Our integrated CADD platform combines molecular docking, pharmacophore modeling, QSAR, MD simulation, and free energy methods in a single quality-controlled pipeline, ensuring reproducible and scientifically rigorous outcomes.
Deep Learning Model Integration
iCDMO integrates graph neural networks and transformer-based scoring models alongside traditional docking, significantly improving hit rate and reducing false positives compared to classical virtual screening alone.
Flexible & Cost-Effective Solutions
We tailor every project to your specific needs and budget — whether a rapid pharmacophore filter on a focused library or a full multi-million compound docking campaign — delivering maximum value for your discovery investment.
Confidential Project Management
iCDMO adopts a strict private management and confidentiality policy for all project information and data. NDAs are standard, and your proprietary target data and hit lists remain fully protected throughout the engagement.
Case Studies
Representative Virtual Screening Projects
Services Included
Frequently Asked Questions
Note: Timelines are estimates for standard projects. Custom focused library design, large-scale multi-million compound campaigns, or projects requiring homology modeling and MD-based pocket sampling may require additional discussion. Contact our team for a project-specific timeline and proposal.
Free Feasibility Consultation
Describe your target and available information. Our scientists will recommend the optimal screening strategy and provide a project proposal — at no charge before commitment.
Contact Us Online ConsultationStandard Deliverables
✓Hit compound list (SDF / CSV with structures)
✓3D docking pose files (Maestro / MOL2 / PDB)
✓2D protein–ligand interaction diagrams
✓Predicted ADMET property table
✓MM-GBSA binding energy ranking
✓Pharmacophore hypothesis figure
✓Full written scientific report
✓Vendor ordering information for confirmed hits