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De Novo Design Workflow

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

Expand your compound design strategies with unbiased chemical space exploration for hit-to-lead and lead opt

Schrödinger’s De Novo Design Workflow is a fully-integrated, cloud-based design system for ultra-large scale chemical space exploration and refinement. Starting from a hit molecule or lead series, the technology identifies synthetically tractable molecules that meet key project criteria by combining multiple compound enumeration strategies with an advanced filtering cascade (AutoDesigner) and rigorous potency scoring with free energy calculations (Active Learning FEP+).

Key Capabilities

Dramatically improve synthetic tractability of the identified molecules

Through built-in reaction-based enumeration combined with advanced filtering to rule out undesired and unrealistic chemistry

Efficiently identify potent lead compounds in favorable physicochemical property space

By leveraging accurate potency predictions combined with active learning

Fast-track ligand optimization and program success

By efficiently evaluating up to billions of project-relevant virtual molecules

Accelerated, seamless exploration of large chemical space

The De Novo Design Workflow offers a cloud-deployable solution with the flexibility to customize settings and property space for the unique needs of your program.

Target Property Space
1. Control the chemical space to be explored with project-specific input parameters

Define the starting molecule, the portion of the molecule to explore, the desired physicochemical property space, and additional project-specific filters within LiveDesign, a web-based enterprise molecular design and collaboration platform.

Expand into synthetically-tractible space of interest to medicinal chemists
2. Expand into synthetically-tractible space of interest to medicinal chemists

Automatically carry out successive rounds of compound generation and filtering within desired chemical space using cloud-native, multi-stage enumeration strategies combined with an advanced filtering cascade based on physical properties, amenability to FEP+, IP, and docking.

Score idea molecules with a highly accurate in silico binding affinity assay
3. Score idea molecules with a highly accurate in silico binding affinity assay

Leverage a well-validated, automated workflow which trains a machine learning model on project-specific FEP+ data to allow processing of up to millions of compounds with highly accurate FEP+ calculations efficiently.

Analyze and prioritize output molecules with a collaborative design platform
4. Analyze and prioritize output molecules with a collaborative design platform

Review the top scoring compounds and use the FEP+-trained machine learning model in LiveDesign — allowing evaluation, interactive optimization, and prioritization by the project team.

Documentation & Tutorials

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

Materials Science Video

Getting Going with Materials Science Maestro Video Series

A free video series introducing the basics of using Materials Science Maestro.

Life Science Tutorial

Absolute Binding Free Energy Perturbation to Postprocess Docking Results

Use Absolute Binding Free Energy calculations to enrich virtual screening results.

Life Science Tutorial

Glide WS Evaluation of HSP90 Ligands

Build and use Glide WS models to evaluate Hsp90 ligands.

Life Science Tutorial

Evaluating Large Ligand Libraries with Active Learning Glide

Set up a virtual screen to analyze a 1M ligand library from using Active Learning Glide.

Life Science Tutorial

Defining QM and MM regions in QSite

Define regions to treat with QM and with MM for a QSite calculation.

Life Science Tutorial

pKa Predictions with Jaguar pKa

Predict the pKa of organic molecules with more than one acidic functional group.

Life Science Tutorial

Membrane-Bound FEP+ with A2A

Prepare, run, and analyze a free energy perturbation (FEP) simulation with a membrane-bound protein for a series of A2A inhibitors using FEP+.

Life Science Tutorial

Heteromultimer Homology Modeling with the Multiple Sequence Viewer/Editor

Build a heteromultimer homology model of human hemoglobin from a bar-head goose hemoglobin structure.

Life Science Tutorial

Training and Evaluating ADMET Models with DeepAutoQSAR

Build and test two models for predicting aqueous solubility using a large dataset.

Life Science Tutorial

Using IFD-MD on a Membrane-bound protein

Set up a membrane-bound protein for IFD-MD and visualize the results.

Publications

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

Life Science Webinar

Schrödinger デジタル創薬セミナー: Impacting drug discovery programs with large-scale de novo design

高品質な化学物質の創製をより包括的かつ効果的に可能にする技術の開発は、薬物探索の長年の目標でした。

Life Science Webinar

Impacting Drug Discovery Programs with Large-Scale De Novo Design

Developing technologies to more comprehensively and effectively enable de novo design of high-quality chemical matter has been a long-standing goal of drug discovery.

Life Science Webinar

In Silico Driven Drug Discovery of a Zwitterionic Integrin αvβ6 Development Candidate for Fibrosis

In this webinar, discover how in silico techniques combined with traditional medicinal chemistry approaches are applied in a structure-based drug discovery program.

Life Science Webinar

Japanese: Schrödinger デジタル創薬セミナー Into the Clinic ~計算化学がもたらす創薬プロセスの変貌~

Mucosa-associated Lymphoid Tissue Lymphoma Translocation Protein 1 (MALT1) is a genetically validated target for the treatment of diseases associated with lymphocyte regulation.

Life Science Case Study

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

Life Science Case Study

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

Life Science Webinar

Into the Clinic: Developing potent and selective kinase inhibitors using at-scale FEP and protein FEP: a Wee1 case study

In this webinar, we discuss the discovery of novel Wee1 kinase inhibitors using a strategy that couples ligand free energy calculations with protein free energy calculations to simultaneously find promising chemical matter and de-risk for off-target liabilities.

Life Science Webinar

Chinese: 2022薛定谔秋季中文生命科学网络讲座 | 基于物理理论的计算模拟 – 如何准确预测小分子晶体的结构和溶解度

对固态科学家来说,药物晶体形式的改变是药物研发后期甚至上市后是非常严重的,打击性极强的问题。

Life Science Webinar

Chinese: 2022薛定谔秋季中文生命科学网络讲座 | 薛定谔计算模拟技术助力新型 D-氨基酸氧化酶抑制剂的发现

D-Serine是N-甲基d-天冬氨酸 (NMDA) 受体的共激动剂,而NMDA受体是一种关键的兴奋性神经递质受体。

Life Science Webinar

Chinese: 2022薛定谔秋季中文生命科学网络讲座 | AutoDesigner,一种通过快速探索大型化学空间来优化先导化合物的从头设计算法

这算法值需要单个有活性数据和假想结合模式的小分子,非常适合早期数据贫乏的SBDD项目。

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

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

In a recent MALT1 drug discovery program led by Schrödinger’s Therapeutics Group, the De Novo Design Workflow amplified the team’s design efforts.

view case study

Training & Resources

Online certification courses

Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.

Tutorials

Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.