# Revilico

## Docs

- [Revilico Platform](https://docs.revilico.bio/index.md): Revilico is digitizing pharmaceutical R&D, empowering every chemist and biologist with unified virtual simulations and closed loop experimentation to develop better medicines faster, and with greater precision.
- [RevSingleCell](https://docs.revilico.bio/docs/revsinglecell.md): Prioritizing Therapeutic Candidates Using Revilico's scRNA Seq Engine: DEG Analysis, Automated Target ID, and Temporal Omics
- [RevMethyl](https://docs.revilico.bio/docs/revmethyl.md): Epigenetic Biological Age Estimation from DNA Methylation Using Validated Epigenetic Clocks
- [RevRisk](https://docs.revilico.bio/docs/revrisk.md): Polygenic Risk Scoring Across 36 Disease Panels and the Full PGS Catalog from Whole-Genome VCF
- [AlphaFold and OpenFold](https://docs.revilico.bio/docs/alphafold-openfold.md): Protein Structural Prediction with Alphafold & OpenFold
- [RevPocket](https://docs.revilico.bio/docs/revpocket.md)
- [RevPhospho](https://docs.revilico.bio/docs/revphospho.md): Kinase Activity Inference and Drug Target Prioritization from Phosphoproteomics Data
- [RevScreen](https://docs.revilico.bio/docs/revscreen.md): Optimizing Ligand Binding Predictions with Revilico's Docking Engines: Static, Flexible, and Ensemble Methods
- [Boltz2](https://docs.revilico.bio/docs/boltz2.md): Understanding Structure-Binding Dynamics using Revilico’s Boltz Co-Folding Engine
- [BoltzGen](https://docs.revilico.bio/docs/boltzgen.md): Understanding Joint Folding and Binding Dynamics using Revilico’s BoltzGen Co-Folding Engine
- [RevQSAR](https://docs.revilico.bio/docs/revqsar.md): Utilizing Revilico’s Quantitative Structure Activity Relationship (QSAR) Model for Understanding Chemical Spaces
- [RevPhore](https://docs.revilico.bio/docs/revphore.md): Understanding Interaction Dynamics using Revilico’s Pharmacophore Analysis Engine
- [RevBench](https://docs.revilico.bio/docs/revbench.md): Benchmarking Docking and Co-Folding Predictions Against Experimental Bioactivity Data
- [RevDenovo](https://docs.revilico.bio/docs/revdenovo.md): Generating a Compound Library Using Revilico’s De Novo Library Generator
- [RevOptimization](https://docs.revilico.bio/docs/revoptimization.md): Utilizing Revilico’s Molecular Optimization Engine to Transform Lead Compounds to Optimized Candidates
- [RevTrain](https://docs.revilico.bio/docs/revtrain.md): Model Training for Generative Chemistry Campaign with Revilico’s Custom Model Training Engine
- [RevMD-Aqua](https://docs.revilico.bio/docs/revmd-aqua.md): Protein-Water Molecular Dynamics for Conformational Sampling and Binding Site Analysis
- [RevMD-Bind](https://docs.revilico.bio/docs/revmd-bind.md): Understanding Drug-Target Dynamics with Revilico's MD Simulation Suite: Protein, Ligand, and Membrane Systems
- [RevMD-Mem](https://docs.revilico.bio/docs/revmd-mem.md): Ligand-Membrane Molecular Dynamics for Permeability and Drug-Lipid Interaction Analysis
- [RevFEP](https://docs.revilico.bio/docs/revfep.md): Cloud-Native Free Energy Perturbation for Binding Affinity Prediction Powered by OpenFE, OpenMM, and AWS Batch
- [RevMut-PMX](https://docs.revilico.bio/docs/revmut-pmx.md): Alchemical Free Energy Calculations for Protein Mutation Binding Affinity Prediction
- [RevGeometry](https://docs.revilico.bio/docs/revgeometry.md): Understanding Interaction Dynamics using Revilico’s Pharmacophore Analysis Engine
- [RevOrbitals](https://docs.revilico.bio/docs/revorbitals.md): A Crash Course on Revilico’s Molecular Orbital Analysis Engine
- [RevSol](https://docs.revilico.bio/docs/revsol.md): A Crash Course on Revilico’s Compound Solubility Engine
- [RevADMET](https://docs.revilico.bio/docs/revadmet.md): Assessing Compound Developmentality Risk with Revilico’s ADMET AI Engine
- [RevConformer](https://docs.revilico.bio/docs/revconformer.md): Running a Conformer Search Screening for a High Throughput Set of Molecules
- [RevRetro](https://docs.revilico.bio/docs/revretro.md): Analyzing Synthesizability of Target Molecule Using Revilico’s Retrosynthesis Engine
- [RevQS](https://docs.revilico.bio/docs/revqs.md): DFT-Based Quantum Mechanical Scoring of Protein-Ligand Binding Interactions
- [RevTS](https://docs.revilico.bio/docs/revts.md): DFT Transition State Search, Optimization, and Reaction Barrier Characterization
- [RevViability](https://docs.revilico.bio/docs/revviability.md): In Silico Drug Sensitivity and Cell Viability Prediction Across Cancer Cell Lines
- [RevGRN](https://docs.revilico.bio/docs/revgrn.md): Gene Regulatory Network Inference and Boolean Attractor Simulation from Expression Data
- [Cell Death](https://docs.revilico.bio/docs/revcell-death.md): Apoptosis and Necrosis Prediction Across Cancer Cell Lines from Drug-Induced Stress
- [Cytokine Release](https://docs.revilico.bio/docs/revcytokine-release.md): Drug-Induced Cytokine Release and Cytokine Storm Risk Prediction Across Cell Lines
- [Pathway Activation](https://docs.revilico.bio/docs/revpathway-activation.md): Signaling Pathway Activity Scoring and Fold-Change Prediction from Drug-Induced Transcriptional Stress
- [Migration / Invasion](https://docs.revilico.bio/docs/revmigration-invasion.md): Cancer Cell Motility and Invasive Capacity Prediction Under Drug Treatment
- [Proliferation (GR)](https://docs.revilico.bio/docs/revproliferation-gr.md): Growth Rate-Corrected Proliferation Analysis Separating Cytostasis from Cytotoxicity
- [RevAgent](https://docs.revilico.bio/docs/revagent.md): Your AI Science Partner — An Intelligent Agent That Understands Your Science, Orchestrates Your Workflows, and Accelerates Discovery Through Natural Conversation
- [3D Visualization](https://docs.revilico.bio/docs/rev3d-viz.md): Interactive 3D Molecular and Structural Visualization with Mol* for Proteins, Ligands, Densities, and Trajectories
- [Compound Design](https://docs.revilico.bio/docs/revcompound-design.md): Interactive 2D Molecular Structure Drawing and Editing with Direct Export to Revilico Engines
- [Compound Review](https://docs.revilico.bio/docs/revcompound-review.md): Collaborative Compound Review Sessions for Molecular Libraries with SMILES-Based Annotation and Shared Analysis
- [RevScan](https://docs.revilico.bio/docs/revscan.md): Optical Chemical Structure Recognition — Convert Chemical Structure Images to SMILES Notation
- [RevDrive](https://docs.revilico.bio/docs/revdrive.md): Centralized File Storage, Organization, and Sharing for All Revilico Research Assets
- [RevEdit](https://docs.revilico.bio/docs/revedit.md): Quick Edit — Spreadsheet Editor and Molecular Viewer for Research Data Files
- [RevNotes](https://docs.revilico.bio/docs/revnotes.md): Structured Research Note-Taking, Knowledge Capture, and Shared Scientific Documentation
- [Bioinformatic Analyses](https://docs.revilico.bio/solutions/target-identification/Conducting-Multiomics-Analysis-on-Revilico-OS.md): Conducting Multiomics Analysis on Revilico OS
- [Disease Bio and Mechanisms](https://docs.revilico.bio/solutions/target-identification/Understanding Disease-Biology-and-Mechanisms-on-Revilico-OS.md): Understanding Disease Biology and Mechanisms on Revilico OS
- [Target Identification](https://docs.revilico.bio/solutions/target-identification/IdentifyPrimary-Molecular-Target-for-Phenotypic.md): Identify Primary Molecular Target for Phenotypic Hit via Reverse Docking
- [Generating 3D Structures](https://docs.revilico.bio/solutions/target-identification/Generate-a-3D-Structural-Hypothesis-for-a-Molecular-Target.md): Generate a 3D Structural Hypothesis for a Molecular Target
- [Deciding Therapeutic Strategy](https://docs.revilico.bio/solutions/target-identification/Determining-Optimal-Therapeutic-Strategy.md): Determining Optimal Therapeutic Strategy for Drugging a Molecular Target
- [Druggable Binding Site ID](https://docs.revilico.bio/solutions/target-identification/Identifying-Druggable-Binding-Sites.md): Identifying Druggable Binding Sites on Challenging “Undruggable” Targets
- [Cell Line Identification](https://docs.revilico.bio/solutions/target-identification/Identifying-the-Best-Therapeutic-Cell-Line.md): Identifying the Best Therapeutic Cell Line for a Drug-Target Complex
- [Ligand Protein Multi-Plexing](https://docs.revilico.bio/solutions/target-identification/Compound-Protein-Interaction-Discovery-at-Scale.md): Compound–Protein Interaction Discovery at Scale
- [Protein Variant / Mutagenesis Validation at Scale](https://docs.revilico.bio/solutions/target-identification/Protein-Variant-Mutagenesis-Validation-at-Scale.md)
- [Elucidating Binding Mechanisms](https://docs.revilico.bio/solutions/hit-identification/Resolve-Binding-Mechanisms-and-Molecular-Interactions.md): Resolve Binding Mechanisms and Molecular Interactions from Experimental Activity Data
- [Therapeutic Strategy and Hit Matching](https://docs.revilico.bio/solutions/hit-identification/Identify-Hits-That-Match-a-Specific-Binding-Modality.md): Identify Hits That Match a Specific Binding Modality or Mechanism
- [Screening Compound Libraries](https://docs.revilico.bio/solutions/hit-identification/Prioritize-a-Compound-Library.md): Prioritize a Compound Library Against a Target Using Virtual Screening
- [Expand Chemical Libraries](https://docs.revilico.bio/solutions/hit-to-lead/Generate-an-Expanded-Small-Molecule-Library.md): Generate an Expanded Small-Molecule Library From Hit Compounds
- [Optimizing Molecular Properties](https://docs.revilico.bio/solutions/hit-to-lead/Optimize-a-Moderately-Active-Molecule.md): Optimize a Moderately Active Molecule for Potency, Selectivity, and Developability
- [Gaining Confidence in Your Hits](https://docs.revilico.bio/solutions/hit-to-lead/Refine-an-Initial-Hit-Set.md): Refine an Initial Hit Set into a High-Confidence Subset
- [Multi-Parameter Lead Optimization](https://docs.revilico.bio/solutions/hit-to-lead/Multi-Parameter-Optimize-a-Moderately-Active-Molecule.md): Multi-Parameter Optimize a Moderately Active Molecule via Scaffold Decoration and Scaffold Hopping
- [Design Allosteric Modulators](https://docs.revilico.bio/solutions/hit-to-lead/Metabolite-Inspired-Drug-Development.md): Metabolite-Inspired Drug Development & Allosteric Optimization
- [Quantum Chemistry Characterization](https://docs.revilico.bio/solutions/lead-optimization/Deeply-Characterize-Lead-Molecules.md): Deeply Characterize Lead Molecules Using Quantum Chemistry and Property Analysis
- [Multi-Plex Tox Screens](https://docs.revilico.bio/solutions/lead-optimization/Assess-Lead-Toxicity-Risk.md): Assess Lead Toxicity Risk via Target-Based Computational Screening
- [On and Off Target Effects](https://docs.revilico.bio/solutions/lead-optimization/Understand-On-Target-and-Off-Target.md): Understand On-Target and Off-Target Biological Pathway Engagement for Lead Compounds
- [ADME Multi-Parameter Optimization](https://docs.revilico.bio/solutions/lead-optimization/Multi-Parameter-Optimization-for-Developability.md): Multi-Parameter Optimization for Developability: Solubility, ADME, and Toxicity
- [Planning Retrosynthesis](https://docs.revilico.bio/solutions/lead-optimization/Plan-Synthetic-Routes-and-Pathways-for-Lead-Compounds.md): Plan Synthetic Routes and Pathways for Lead Compounds
- [Design Around Patents](https://docs.revilico.bio/solutions/lead-optimization/Non-Infringing-Chemical-Matter-with-Comparable-Performance.md): Design Novel, Non-Infringing Chemical Matter with Comparable Performance
- [Cross Team Collaborations](https://docs.revilico.bio/solutions/operational-efficiency/Cross-Team-Collaboration-Without-File-Chaos.md): Cross-Team Collaboration Without File Chaos
- [Reproducibility, Traceability, Version Controls](https://docs.revilico.bio/solutions/operational-efficiency/Reproducibility-Version-Control.md): Reproducibility & Version Control
- [Structured Knowledge Transfer](https://docs.revilico.bio/solutions/operational-efficiency/Structured-Knowledge-Transfer.md)
- [Pipeline Transparency & Execution Oversight](https://docs.revilico.bio/solutions/operational-efficiency/Pipeline-Transparency-Execution-Oversight.md)
- [Centralized Experimental + Computational Data Management](https://docs.revilico.bio/solutions/operational-efficiency/Centralized-Experimental-Computational-Data-Management.md)
- [Revilico product changelog and release notes](https://docs.revilico.bio/changelog.md): Weekly release notes for the Revilico drug discovery platform: new engines, workflow improvements, billing changes, and bug fixes.
- [High Throughput Screening](https://docs.revilico.bio/high-throughput-screening.md): A complete walkthrough of structure-based drug design and computational HTS on the Revilico platform — from target identification to a confirmed lead set.
- [Filtering Molecules for your Virtual Screen](https://docs.revilico.bio/guides/filtering-molecules-virtual-screen.md): A complete, engine-by-engine protocol for filtering mega chemical spaces into experimental-ready compound sets using static docking, flexible docking, ensemble docking, Boltz2, and diversity-driven selection.
- [RevScreen - Static & Flexible Docking](https://docs.revilico.bio/tutorials/rev-bind/static-flexible-docking.md): A step-by-step walkthrough of Rigid Receptor and Flexible Docking in the RevBind Virtual Screening Engine
- [RevScreen - Ensemble Docking](https://docs.revilico.bio/tutorials/rev-bind/ensemble-docking.md): A step-by-step walkthrough of Ensemble Docking in Rev-Bind — using molecular dynamics-sampled protein conformations for high-accuracy virtual screening
- [Boltz2 Cofolding](https://docs.revilico.bio/tutorials/rev-bind/boltz2-cofolding.md): Predict binding poses and activity metrics from a protein sequence and SMILES string using Boltz2's AI co-folding engine
- [Production VS with 2M+ Compounds](https://docs.revilico.bio/tutorials/rev-bind/production-vs.md): A step-by-step walkthrough of production-scale high-throughput virtual screening using RevDock and RevScreen — from batch configuration to parallel pipeline execution
- [AlphaFold](https://docs.revilico.bio/tutorials/rev-target/alphafold.md): Predict the 3D structure of a protein from its amino acid sequence using Revilico's AlphaFold engine
- [RevPocket](https://docs.revilico.bio/tutorials/rev-target/revpocket.md): Identify and characterize druggable binding sites on protein structures using Revilico's pocket search engine
- [2D Structure MedChem Review](https://docs.revilico.bio/tutorials/medchem-review/2d-structure-medchem-review.md): Export RevBind screening results and triage them into a collaborative RevStudio Compound Review session for medicinal chemistry sign-off
- [2D/3D Structure MedChem Review with Poses](https://docs.revilico.bio/tutorials/medchem-review/2d-3d-structure-medchem-review-with-poses.md): Downselect compounds from a high throughput screen and triage them — poses and all — into a collaborative RevStudio Compound Review session
- [Managing Pipeline Projects Effectively](https://docs.revilico.bio/tutorials/medchem-review/managing-pipeline-projects-effectively.md): Organize pipelines, notes, and files by target using Revilico OS Projects, and track campaign status on a shared Kanban board with timeline view

## OpenAPI Specs

- [openapi](https://docs.revilico.bio/api-reference/openapi.json)