Drug Discovery Workflows

Revolutionize drug discovery by immersing teams in a collaborative digital ecosystem integrated with industry-leading scientific workflows

Discovery Teams

Build the foundation for digital transformation through an integrated ecosystem for discovery.

Empower multi-disciplinary teams with self-service, predictive models for experts and non-experts alike.

Enable hypothesis-driven design with centralized data and automated workflows accessible to the entire team.

Rationalize and expedite the design-make-test-analyze cycle to explore broader chemical space and make fewer, better quality compounds.

Allied drug discovery solutions

Securely integrate all project data, design in real-time, and analyze multiple parameters side-by-side to optimize molecules quickly and efficiently. LiveDesign centralizes drug discovery data and provides scalable workflows and expert computational predictions in a single web-based interface accessible to the entire project team.

Unify Discovery Workflows
Centralize & Integrate Diverse Data
Collaborate & Communicate Seamlessly

Integrated Modeling Environment

Easily access state-of-the-art molecular design tools using intuitive workflows in order to achieve program objectives for early candidate molecules faster. Maestro offers a streamlined portal to industry-leading predictive models and machine learning workflows and integrates with LiveDesign to allow iterative data retrieval and transfer.

Designed for Novice and Experts Users
Access Diverse Computational Solutions
Access & Scale Execution with LiveDesign

Discovery workflows

Schrödinger’s drug discovery workflows enable teams to identify better drug candidates faster by digitally transforming the entire system with well-proven world-class computational solutions delivered in a centralized platform. This collaborative platform reconciled across an entire organization delivers cutting-edge solutions for:


Perform comprehensive protein target assessment to ensure allocation of finite project resources to programs with the highest probability of success, and build accurate structural models for downstream molecular design work.


Unlock structural insights by predicting and refining protein complexes to enable structure-based drug design, high-quality computational assessment, and discovery of novel drug-like molecules.

Predict Novel Protein-Ligand Complexes

Quickly obtain protein structures conformationally optimized to novel ligand scaffolds using a highly accurate next-generation induced-fit docking workflow.

Learn more about IFD-MD >
Correct & Assess Structure to Create Reliable Models

Correct common structural problems and create reliable, all-atom protein models with an easy-to-use tool that improves the accuracy of subsequent computational applications.

Learn more about Protein Preparation Wizard >
Create Homology Models for Structure-Based Design

Harness the power of genomic data to create homology models of pharmaceutically relevant targets.

Learn more about Prime >
Perform Structure Refinement by Coupling PHENIX with an Advanced Force Field

Refine your structures with the accuracy of the OPLS4 force field employing the industry-accepted structural biology determination and refinement package PHENIX.

Read more >
Refine Ligand Poses in Cryo-EM Structures

Improve ligand placement for cryoEM structures with the application of Glide to cryoEM potential maps.

Read more >

Binding site & structure analysis

Explore binding site druggability and exploit potential interactions that reveal new avenues for ligand optimization through careful binding site analysis.

Identify Binding Pockets

Identify and assess the druggability and properties of a target’s probable binding sites.

Learn more about SiteMap >
Understand Molecular Motions

Predict dynamic phenomena and study molecular motions with a high-performance molecular dynamics engine.

Learn more about Desmond >
Perform Hydration Site Analysis

Discover new possibilities for ligand optimization by predicting the location and thermodynamic potential of hydration sites in the binding site.

Learn more about WaterMap >
Discover Cryptic Binding Sites

Elucidate cryptic binding pockets and reveal binding hot spots using metadynamics accelerated sampling workflow for mixed solvent simulations.

Learn more about Desmond >


Identify chemically diverse, high-quality initial screening hits that provide the first indication of biological impact using comprehensive and scalable solutions capable of assessing several hundred or several billion compounds.


Rapidly generate bioactive ligand structures with accurate ionization and tautomeric states to assure error-free hit identification.

Perform Ligand Preparation

Easily translate molecular structures from 1D, 2D to 3D while carefully enumerating structural and chemical possibilities to ensure the accuracy of subsequent modeling predictions.

Learn more about LigPrep >
Screen Prepared Compound Libraries

Access prepared compound libraries from 10 million to >1 billion compounds from Enamine, MolPort, Sigma Aldrich, WuXi, and Mcule to easily purchase virtual hits and progress programs quickly.

Predict pKa using a Knowledge-based System

Predict pKa using a rapid and robust knowledge-base algorithm.

Learn more about Epik >
Predict pKa using Quantum Mechanics

Predict pKa of molecules in novel chemical space using a highly accurate quantum mechanics approach.

Learn more about Jaguar >

Hit Discovery

Leverage rapid orthogonal virtual screening technologies to accurately screen billions of compounds, with or without target information.

ligand-based virtual screening
Screen using Pharmacophores

Rapidly screen compounds based on the steric and electronic features of molecules known to have biological activity, optionally including receptor information.

Learn more about Phase >
Screen using 3D Ligand Shape

Screen billions of compounds quickly by optimizing the 3D shape overlap between known active ligand conformations and library molecules.

Learn more about Shape Screening >
structure-based virtual screening
Dock Novel Ligands

Screen compounds accurately with a well-validated, grid-based ligand-receptor docking algorithm.

Learn more about Glide >
Virtually Screen Billion+ Libraries with Docking and Machine Learning

Rapidly, accurately, and cost-effectively screen billions of purchasable compounds by combining Glide docking and scoring with the power of machine learning models.

Learn more Active Learning Glide >
Enrich Hits from Screens

Use advanced techniques to improve the enrichment of virtual screens and find the most promising hits.

Learn more about ABFEP >


Design thoughtfully crafted ligands with optimal drug-like profiles by rapidly enumerating and evaluating multiple properties simultaneously through robust predictive modeling.


Precisely predict the binding affinity of novel compounds using free energy perturbation methods coupled with a fully integrated and scientifically validated force field to triage more design ideas faster.

Learn more about FEP+ >


Quickly enumerate hit-to-lead and lead optimization libraries to improve initial hit properties and transition to lead-like molecules.

Enumerate Broad Chemical Space

Take advantage of comprehensive enumeration techniques that exploit project chemistry, explore SAR, and discover biosimilars to find best-in-class molecules faster.

Learn more about Core Hopping >
Interactively Design and Enumerate

Design in 2D or 3D interactively or via intuitive guided workflows that rapidly generate ideas to satisfy common design objectives.

Learn more about Ligand Designer >

Property Predictions

Predict and evaluate properties of new molecular designs to quickly and inexpensively prioritize molecules, achieving program objectives for candidate molecules faster.

Rapidly Build MPOs for Data-Driven Compound Progression

Drive towards project goals with customizable and dynamic Multiple Parameter Optimization capabilities.

Learn more about LiveDesign >
Predict Affinity, Selectivity, & Solubility

Rigorously predict ligand affinity, selectivity, and solubility using free energy perturbation techniques that improve drug-like properties of lead molecules.

Learn more about FEP+ >
Create and Apply Expert-level QSAR & QSPR Models

Automatically create and apply predictive QSAR & QSPR models that use comprehensive data modeling techniques including machine-learning following best practices.

Learn more about AutoQSAR >
Predict Membrane Permeability

Predict passive membrane permeability using an accurate, physics-based approach.

Learn more about Membrane Permeability >
Predict ADME Properties

Rapidly predict ADME properties of ligands.

Learn more about QikProp >


Learn more about Schrödinger's Drug Discovery Solutions


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