BioLuminate

BioLuminate is Schrödinger's comprehensive modeling platform designed to streamline computationally-guided biologics drug discovery. Built on the Maestro interface, it leverages industry-leading molecular simulations and logically organized workflows to provide predictive methods that optimize the properties of biomolecules from sequence to structure. The platform is intended for researchers and scientists working across protein-based therapeutics, including antibody engineering, peptide discovery, and enzyme engineering.

By combining advanced physics-based computational methods with a user-friendly interface, BioLuminate enables teams to rationally design potent, safe, and developable biologics. The platform supports a broad range of biological modalities and provides access to cutting-edge workflows within a single, streamlined portal.

Build & Model

• Easily build accurate structural models that serve as key starting points for the rational design of biologics.
• Model antibody structures using a fully guided, specialized workflow incorporating de novo CDR loop sampling.
• Leverage advanced protein sequence analysis tools, including annotation capabilities.

Predict & Analyze

• Access cutting-edge, predictive computational modeling workflows for biologics discovery within a streamlined portal.
• Predict and analyze protein–protein or protein–nucleic acid interactions at the atomic level using computational workflows.
• Calculate descriptors for characterizing and triaging antibodies and proteins, including protein surface properties and aggregation propensity.

Design & Engineer

• Enumerate potential amino acid substitutions and design focused libraries.
• Perform in silico mutagenesis to engineer novel variants with superior binding affinity, selectivity, and thermostability.
• Design flexible and rigid linkers to generate multi-functional fusion proteins.

Application Areas Across Protein-Based Therapeutics

• Antibody Design: Rationally design potent, safe, and developable monoclonal antibodies, including homology modeling, humanization via CDR grafting and residue mutation, antigen–antibody docking, liability prediction, and in silico mutations.
• Peptide Discovery: Design peptidic drugs using in silico structure-based methods.
• Enzyme Engineering: Efficiently optimize enzymes using structure-based design methods, including investigation of the effects of mutations on enzyme stability and ligand binding.

Key Workflows and Tutorials

• Antibody structure prediction, visualization, and quality refinement.
• Antibody humanization through CDR grafting and residue mutation.
• Antibody–antigen docking using PIPER to generate complex structures.
• MM-GBSA residue scanning to improve antibody stability and affinity.
• FEP+ residue scanning to identify the impact of mutations on stability and affinity of protein–protein systems.
• Disulfide bond engineering via cysteine scanning to improve thermal stability and facilitate crystallization.
• T cell receptor (TCR) modeling, including structure preparation, visualization, and analysis of key interactions in the TCR–peptide–MHC complex.
• Building and analyzing complex lipid bilayers and embedding membrane proteins.

Training and Learning Resources

• Hands-on online certification courses, including an Introduction to Computational Antibody Engineering course for leveling up computational modeling skills.
• Self-paced online molecular modeling courses covering a range of scientific topics, with access to Schrödinger software and support.
• Tutorials, quick start guides, videos, and documentation covering best practices for deploying BioLuminate technology.
• A library of case studies, webinars, and peer-reviewed publications demonstrating real-world applications of the platform.

BioLuminate is supported by extensive documentation, regular software updates, and dedicated support resources. The platform's workflows span aggregation scoring, liability prediction, viscosity modeling, and QSPR descriptor generation for biologics, making it a broad-based solution for teams engaged in computationally guided biologics drug discovery.