Navigating BioLuminate for PyMOL Users: A Practical Approach. 2nd European Life Science Bootcamp Ana Negri, PhD

Transcription

1 Navigating BioLuminate for PyMOL Users: A Practical Approach 2nd European Life Science Bootcamp Ana Negri, PhD

2 Agenda Introduction to BioLuminate PyMOL-like features in the BioLuminate interface: Basic rendering and visualization using BioLuminate Beyond visualization: Antibody Modeling and Protein-Protein Docking Residue Mutation and Affinity Maturation Hands-on tutorial: Visualization, Sequence Analysis, and Modeling with BioLuminate: A case Study with Neuraminidase Questions

3 Introduction to BioLuminate BioLuminate is the Schrödinger biologics software platform A suitably low learning curve for new users, non expert users Focused on workflows and tasks, with multiple modeling features GUI modeled on PyMOL Antibody Antigen

4 Functionality groups in BioLuminate Antibody design Structure prediction from sequence, humanization Protein design Residue scanning (affinity / stability); Cysteine scanning; Protein crosslinking; In silico affinity maturation; Non-standard amino acids; Protein FEP Protein liability ID Aggregation propensity ID; Reactive residue ID (glycosylation, proteolysis, oxidation, deamination); Peptide QSAR; Titration curve / Isoelectric point; Solubility Protein modeling Homology modeling Protein-protein docking; Prime de novo loop modeling Protein interaction analysis; Chimeric model generation; Automated peptide docking Advanced sequence viewer (MSV); Automated protein quality report Molecular Dynamics, minimization, quantum mechanics, etc

5 Agenda Introduction to BioLuminate PyMOL-like features in the BioLuminate interface: Basic rendering and visualization using BioLuminate Beyond visualization: Antibody Modeling and Protein-Protein Docking Residue Mutation and Affinity Maturation Hands-on tutorial: Visualization, Sequence Analysis, and Modeling with BioLuminate: A case Study with Neuraminidase Questions

6 PyMOL-like features in the BioLuminate interface

7 PyMOL-like features in the BioLuminate interface

8 Agenda Introduction to BioLuminate PyMOL-like features in the BioLuminate interface: Basic rendering and visualization using BioLuminate Beyond visualization: Antibody Modeling and Protein-Protein Docking Residue Mutation and Affinity Maturation Hands-on tutorial: Visualization, Sequence Analysis, and Modeling with BioLuminate: A case Study with Neuraminidase Questions

9 Antibody Modeling and Protein-Protein Docking (1A43) HIV-1 Capsid Protein (P24) FAB13B5 Green=xray Blue/Maroon=predict Piper/Cluspro (in BioLuminate) CAPRI rankings (Nir London, Rosetta Design Group, 2010) Orange=xray (1E6J) Blue/Green/Red=predict Third ranked complex shown

10 Antibody Modeling CDR Prediction: Input & Framework Antibody-specific workflow Search public or in-house structures for templates Framework selection: Separate control over L/H chain framework templates Control over framework used to align chains

11 Antibody Modeling CDR Prediction: Loop Grafting Start with fast loop lookup: Find largest cluster with maximum sequence similarity Minimize grafted loop Optionally perform advanced loop prediction using Prime

12 Antibody Modeling Database Management Multiple databases can be created and later selected New structures can be added to existing or new DB

13 Protein-Protein Docking Licensed from Vajda group at Boston University Kozakov et al. (2006) Proteins: Struct, Funct, Bioinf #1 server in most recent CAPRI competition Competitive with human groups CAPRI rankings (Nir London, Rosetta Design Group, 2010) Piper/Cluspro: #1 group #1 server

14 Protein-Protein Docking is Easy to Run

15 Antibody/Antigen Complex: Predicted Versus Experiment Modeled FAB13B5 CDR docked with crystal structure of unbound antigen P24 (orange) versus x-ray complex 1E6J. 3 rd ranked complex shown.

16 Residue Scanning: ID mutations for improved affinity / stability Residue scanning is a technique used to determine the contribution of a specific residue to the stability, binding or function of a given protein Walk mutation R Ala along sequence Measure Δ Affinity Δ Stability Tells us what mutations may be beneficial, and what may be harmful Can be a very laborious and difficult task to do in the lab.

17 MM-GBSA residue mutation calculations Prime energy function Select residues to mutate Calculate relevant energies Apply equations from statistical mechanics Implicit solvent (Generalized Born) Rigorous all atom force field model Extensively validated for protein structure prediction Collaborative effort: Schrödinger, Rich Friesner (Columbia) and Matt Jacobson (UCSF) (Output) Free energies from mutation

18 From Residue Scanning to Affinity Maturation Residue Scanning (single mutations): Protein 1 Protein 1 Protein 2 Protein 2 Affinity Maturation/Protein Design (multiple simultaneous mutations): Protein 1 Protein 1 Protein 2 Protein 2

19 Affinity Maturation in BioLuminate

20 Affinity Maturation in BioLuminate Search multiple residue positions simultaneously for changes Implicit solvent MM-GBSA model Uses Monte Carlo sampling due to combinatorial explosion Use to suggest new sequences, or to influence random library design Reveals positions and types of beneficial mutations

21 Agenda Introduction to BioLuminate PyMOL-like features in the BioLuminate interface: Basic rendering and visualization using BioLuminate Beyond visualization: Antibody Modeling and Protein-Protein Docking Residue Mutation and Affinity Maturation Hands-on tutorial: Visualization, Sequence Analysis, and Modeling with BioLuminate: A case Study with Neuraminidase Questions

22 Useful Video Links Related to Today s Webinar Biologics modeling tutorial series: Intro to BioLuminate Homology Modeling (Antibody modeling) Residue Scanning Protein-Protein Docking, etc

23 Other Useful Resources Schrödinger support: Knowledge Base: Support Center and Training Videos: Schrödinger Seminar Series: Script Center:

24 Questions? Thanks for Joining Us!