Hit-to-Lead & Lead Optimization

Design better quality drug candidates, faster

Hit-to-Lead & Lead Optimization

Explore and triage vast chemical space with high precision in silico tools

Identifying the best drug candidate — a novel molecule that optimizes key physicochemical properties while maintaining on-target potency and specificity — is the ultimate challenge of lead optimization programs.

Schrödinger’s platform for molecular design empowers project teams to deploy a ‘predict-first’ approach to lead optimization challenges, dramatically expanding the pool of molecules that can be explored through highly interactive, fully in silico design cycles. Teams can confidently spend time and energy exploring new, unknown, and often more complex designs while sending only the top performing molecules for synthesis.

Diverse solutions for chemical enumeration, property prediction, and team collaboration

Create and explore project-relevant chemical space to fast-track ligand design

Create and tailor your own chemical space using reaction or R-group based enumeration and advanced filtering capabilities
Combine accurate physics-based simulations with the power of machine learning to efficiently explore vast chemical space
Profile billions of virtual target-specific molecules with an intelligent, reaction-based enumeration, filtering and accurate FEP+ scoring workflow

Drive ligand design by leveraging the thermodynamics of water interactions in active sites 

Discover new potency drivers by predicting the location and thermodynamic potential of hydration sites in the binding site
Visualize hydration sites for an easy and intuitive method of interpreting SAR

Design and collaborate in real-time with your colleagues — anytime, anywhere

Share, revise, and test design ideas with team members using a single cloud-native platform, LiveDesign
Capture decisions and hypotheses to improve collective SAR understanding and accelerate compound progression
Build rich dashboards to analyze whole project data or individual molecules and quickly identify promising design opportunities in key property space

Predict key properties to accelerate ligand optimization

Free energy-based computational assay (FEP+):

• Potency
• Selectivity
• Solubility

Other physics-based predictions:

• Membrane permeability
• hERG inhibition
• CYP inhibition / TDI
• CYP induction (DDI)
• Site of metabolism
• Brain exposure

Case studies

Discover how Schrödinger technology is being used to solve real-world research challenges.

Life Science Case Study

Design of a highly selective, allosteric, picomolar TYK2 inhibitor using novel FEP+ strategies

Life Science Case Study

Design of a novel, potent CDC7 inhibitor development candidate with high ligand efficiency and optimized properties

Life Science Case Study

High precision, computationally-guided discovery of highly selective Wee1 inhibitors for the treatment of solid tumors

Life Science Case Study

Discovery of a novel, potent ACC inhibitor driven by computationally-guided design and assessment of water energetics in the binding site

Life Science Case Study

Hit to development candidate in 10 months: Rapid discovery of a novel, potent MALT1 inhibitor

Life Science Case Study

Indiana Biosciences Research Institute enables drug discovery using CDD Vault and Schrödinger LiveDesign

Life Science Case Study

Schrödinger solutions for small molecule protonation state enumeration and pKa prediction

Life Science Case Study

Morphic Therapeutic leverages digital chemistry strategy to design a novel small molecule inhibitor of α4β7 integrin

Life Science Case Study

Hit to lead design of novel d-amino-acid oxidase inhibitors using a comprehensive digital chemistry strategy

Life Science Case Study

Stories from drug discovery: Modeling strategies in the pursuit of development candidate in oncology program 1

  • Life Science
  • Webinar

Design of a highly selective, allosteric, picomolar TYK2 inhibitor in clinical development

In this webinar, we highlight key moments from the discovery of this potentially best-in-class selective, allosteric, picomolar inhibitor of TYK2.

Watch webinar
  • Life Science
  • Webinar

Impacting drug discovery programs with large-scale de novo design

In this webinar, scientists from Schrödinger’s therapeutics group describe several recent case studies where de novo design technologies have allowed teams to overcome critical design challenges and accelerate programs.

Watch webinar

Documentation & Tutorials

Get answers to common questions and learn best practices for using Schrödinger’s software.

Life Science Documentation

Learning Path: Oligonucleotide Modeling

A structured overview of tools and workflows for nucleic acids in drug discovery.

Life Science Tutorial

Predicting Drug Residence Times from Unbinding Kinetics Simulations

Run the unbinding kinetics workflow on a kinase system and analyze the results.

Life Science Tutorial

Forming RNA – Ligand Interactions with Ligand Designer

Modify ligand bound to RNA receptor to improve binding affinity using Ligand Designer.

Life Science Documentation

Membrane Permeability

Calculate the passive membrane permeability of a set of congeneric ligands.

Life Science Documentation

FEP+

Computational prediction of protein-ligand binding using physics-based free energy perturbation technology at an accuracy matching experimental methods.

Life Science Documentation

Ligand Designer

Interactively design a ligand in the context of a protein or DNA/RNA receptor to optimize its binding and properties.

Life Science Documentation

IFD-MD

GPU-accelerated prediction of receptor-ligand binding poses.

Life Science Documentation

Glide

Easy-to-use, reliable ligand-receptor docking.

Life Science Documentation

DeepAutoQSAR

Predict molecular properties based on chemical structure using machine learning (ML).

Life Science Documentation

ConfGen

ConfGen documentation including online help and user manual.

Key Products

Learn more about the key computational technologies available to progress your research projects.

Maestro

Complete modeling environment for your molecular discovery

FEP+

High-performance free energy calculations for drug discovery

Active Learning Applications

Accelerate discovery with machine learning

De Novo Design Workflow

Fully-integrated, cloud-based design system for ultra-large scale chemical space exploration and refinement

IFD-MD

Accurate ligand binding mode prediction for novel chemical matter, for on-targets and off-targets

WaterMap

State-of-the-art, structure-based method for assessing the energetics of water solvating ligand binding sites for ligand optimization

LiveDesign

Your complete digital molecular design lab

Publications

Browse the list of peer-reviewed publications using Schrödinger technology in related application areas.

Life Science Publication

Accelerated in silico discovery of SGR-1505: A potent MALT1 allosteric inhibitor for the treatment of mature B-cell malignancies

Life Science Publication

Discovery of highly potent noncovalent inhibitors of SARS-CoV-2 main protease through computer-aided drug design

Life Science Publication

Harnessing free energy calculations to achieve kinome-wide selectivity in drug discovery campaigns: Wee1 case study

Life Science Publication

Computational Hit Finding: An Industry Perspective

Life Science Publication

Active Learning FEP: Impact on Performance of AL Protocol and Chemical Diversity

Life Science Publication

Structure-based discovery and development of highly potent dihydroorotate dehydrogenase inhibitors for malaria chemoprevention

Life Science Publication

Leveraging the thermodynamics of protein conformations in drug discovery

Life Science Publication

In silico enabled discovery of KAI-11101, a preclinical DLK inhibitor for the treatment of neurodegenerative disease and neuronal injury

Life Science Publication

Discovery of a novel mutant-selective epidermal growth factor receptor inhibitor using an in silico enabled drug discovery platform

Life Science Publication

The Discovery of MORF-627, a Highly Selective Conformationally-Biased Zwitterionic Integrin αvβ6 Inhibitor for Fibrosis

Software and services to meet your organizational needs

Software Platform

Deploy digital materials discovery workflows with a comprehensive and user-friendly platform grounded in physics-based molecular modeling, machine learning, and team collaboration.

Research Services

Leverage Schrödinger’s expert computational scientists to assist at key stages in your materials discovery and development process.

Support & Training

Access expert support, educational materials, and training resources designed for both novice and experienced users.