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January 1st 2020
January 1st 2020
speaker: Alex Burgin
title: Overview of the Institute for Protein Innovation
abstract: An overview of the Institute, describing the mission, capabilities, and long-term vision and goals. IPI's 'Antibody Initiative' is a project to generate high-quality, well-validated, open source monoclonal antibodies against every extracellular protein in the human and mouse proteomes.
speaker: Frank Teets
title: How to design well interdigitated helical bundles de novo
abstract: Alpha-helical bundles combine ready amenability to de novo protein design with broad structural diversity. Here, I present an efficient protocol for the design of interdigitating residues onto arbitrarily oriented helical bundles, allowing for the stabilization of designs for which no native template exists.
February 5th 2020
February 5th 2020
speakers: Chris Sander, Frank Poelwijk, Mike Stiffler, Nick Gauthier
title: Protein Structure from Experimental Evolution
abstract: In this work we experimentally evolved two distinct antibiotic resistance proteins through cycles of mutation and selection. Statistical analysis of amino acid co-evolution patterns in our deep-sequenced mutant libraries revealed important amino acid interactions in each protein, which in turn allowed accurate computation of 3D structures. This work opens the door to a novel technology for 3D protein structure determination.
March 4th 2020
March 4th 2020
speaker: Cassie Bryan
title: Computational Design of a De Novo, Modular Miniprotein Targeting PD-1
abstract: Using a combination of computational design and experimental approaches, we have developed a de novo miniprotein that specifically binds the T cell receptor PD-1 at the ligand interface at a Kd of ~100 nM. The 5.6 kDa protein contains three disulfide bonds, making it highly stable to thermal and chemical denaturation, and the apo crystal structure shows that the binder folds as designed with a backbone RMSD of 1.3 Å to the design model. We have attached this protein to a designed icosahedral protein nanocage to demonstrate its use as a modular binding domain with ideal properties for application in a variety of targeted and cell-based immunotherapy platforms.
April 1st 2020
April 1st 2020
speaker: Eric Fischer
title: Primer to Targeted Protein Degradation and arising concepts from structure, design, and predictions
abstract: Small molecules that induce protein degradation through ligase-mediated ubiquitination, have shown considerable promise as a new pharmacological modality. Thalidomide and related IMiDs provided the clinical proof of concept, while significant progress has recently been made towards chemically induced targeted protein degradation using heterobifunctional small molecule ligands. Prospective development of degraders with drug-like properties, however, poses a significant challenge and requires new approaches to all aspects of drug discovery. I will present a primer to small molecule mediated protein degradation, highlights of recent work towards a better understanding of the molecular principles that govern neo-substrate recruitment, and concepts and ideas towards effective modelling in the discovery process.
May 6th 2020
May 6th 2020
speaker: Brahm Yachnin
title: Massively Parallel Protein Design to Develop Enzymes for Next-Generation Chemotherapy
abstract: Directed enzyme prodrug therapy (DEPT) is a chemotherapeutic strategy in which a non-toxic prodrug is activated to its toxic form at the tumour site by a tumour-directed enzyme, thereby reducing the systemic toxicity caused by the circulating drug. Unfortunately, the complexity of the dosing regimen, requiring precise timing of the administration of the enzyme and the prodrug, have precluded its mainstream adoption in the clinic. We have employed a massively parallel computation design and screening approach to develop a pro-enzyme that itself can be activated by proteases naturally produced by many tumour types. In this way, circulating enzyme will be dormant until it reaches the tumour site, mitigating off-target activation of the prodrug.
June 3rd 2020
June 3rd 2020
speaker: Una Nattermann
title: A hierarchical approach to protein crystal design
abstract: Controlling protein crystallization could increase our understanding of protein crystal nucleation and growth, aid in structure determination methods, and lead to a new field of biomaterials. During this seminar, I will talk about a top-down protein crystal design approach that yielded crystals, but highlighted specificity challenges in the design process. Then, I will talk about current efforts to pursue a bottom-up hierarchical approach that takes advantage of recent advances in RosettaDesign.
July 1st 2020
July 1st 2020
speaker: Jared Adolf-Bryfogle
title: De novo Glycan Modeling and Design
abstract: Carbohydrates and glycoproteins are critical in biological systems, but computational tools to aid in carbohydrate structure prediction, density fitting, and design are only just beginning to flourish. Here I present the GlycanTreeModeler, a new tool for robust glycan structure prediction within Rosetta, and an in-development application for automated epitope focusing and glycan masking of immunogens and protein therapeutics we call SugarCoat.
August 5th 2020
August 5th 2020
speaker: Sergey Ovchinnikov
title: Protein sequence design by explicit energy landscape optimization
abstract: https://colab.research.google.com/drive/1hMEZdT5z_1wzAvfrt5pYz1sYtkBGSZt6
September 2nd 2020
September 2nd 2020
speaker: Joe Cunningham
title: Biophysical prediction of protein–peptide interactions and signaling networks using machine learning
abstract: Much of signal transduction is mediated by weak protein-protein interactions between globular peptide-binding domains (PBDs; e.g. SH2) and unstructured peptidic motifs in partner proteins. The number and diversity of PBDs (> 1,800 known), relatively low binding affinity (micromolar range), and sensitivity of binding properties to sequence variation constitute substantial challenges to experimental and computational analyses of PBD specificity and their networks. Here, I will present a bespoke machine-learning approach, hierarchical statistical mechanical modeling (HSM), that accurately predicts PBD-peptide interactions across multiple protein (domain) families.
October 7th 2020
October 7th 2020
speaker: Gabe Rocklin
title: Why designs fail, and how they move
abstract: Our lab focuses on high-throughput technologies for protein design and biophysics. I will share two stories. First, we scanned >15,000 mutants of 20 failed protein designs, revealing the causes of failure and surprising directions for modeling improvement. Second, we developed a new experimental approach to characterize protein energy landscapes in parallel, which we are currently applying to understand how sequence and structure determine conformational dynamics.
November 4th 2020
November 4th 2020
speaker: Parisa Hosseinzadeh
title: A computational approach for designing structured peptides and predicting peptide behavior in solution
abstract: Despite their importance, our structural understanding of peptides and our ability to design those with predefined structures is limited due to practical difficulties in obtaining their experimental structure and limitations of generalizing protein structure prediction and design methods to peptide. We recently developed a computational pipeline that can accurately generate structured macrocycles. I will discuss the details of this method and our results, and then talk about how we can use this method to gain structural understanding of behavior of natural peptides in solution.
December 2nd 2020
December 2nd 2020
speaker: Sebastian Swanson
title: Tertiary motifs as building blocks for the design of protein binding peptides
abstract: Custom designed protein-binding peptides have the potential to advance research and medicine, but remain difficult to design de novo. This is due to the huge number of potential binding structures and difficulty of identifying structures that are realizable by amino acid sequence. To address these challenges we are developing a data-driven approach that leverages tertiary motifs mined from the PDB to sample and score peptide structures in the context of a binding site. I will show that many existing peptide structures can be sampled by our method and present preliminary design results.
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