BOSTON PROTEIN DESIGN AND MODELING CLUB
2023 seminars
January 11th 2023
speaker: Nick Polizzi
location: Cannon Room, Building C, Harvard Medical School
title: Designing ligand-binding proteins from scratch
February 8th 2023
speaker: Bruno Correia
location: Room B101, Northwest Building, Harvard University
title: Expanding the Universe of Functional Proteins by Computational Design
March 8th 2023
speaker: Gabriele Corso, Hannes Stärk, Bowen Jing
location: Cannon Room, Building C, Harvard Medical School
title: DiffDock: Diffusion Steps, Twists and Turns for Molecular Docking and Beyond!
April 12th 2023
speaker: Hannah Wayment-Steele
location: Room B101, Northwest Building, Harvard University
title: Understanding and discovering fold-switching proteins by combining AlphaFold2 and sequence clustering
May 10th 2023
speaker: Philipp Lorenz
location: Cannon Room, Building C, Harvard Medical School
title: Building a global data supply chain to improve protein design and protect biodiversity
June 14th 2023
speaker: Sebastian Swanson
location: Room B101, Northwest Building, Harvard University
title: Fragment-based backbone sampling and neural network-derived scoring potentials for the design of protein-binding peptides
July 12th 2023
speaker: Nick Gauthier
location: Cannon Room, Building C, Harvard Medical School
title: Exploration of novel functional sequence space using evolution-informed design
August 2nd 2023
speaker: Alissa Hummer
location: Cannon Room, Building C, Harvard Medical School
title: Investigating the volume and diversity of data needed for generalizable antibody-antigen ∆∆G prediction
September 13th 2023
speaker: Odessa Goudy
location: Room B101, Northwest Building, Harvard University
title: Computational design of autoinhibitory domains for a protease-activated PD-L1 antagonist
October 25th 2023
speaker: Joey Davis
location: Room B103, Northwest Building, Harvard University
title: Exploring structural heterogeneity through cryoEM, cryoET, and deep learning
November 15th 2023
speaker: Ava Amini
location: Cannon Room, Building C, Harvard Medical School
title: Bridging Biophysics and AI to Optimize Protein Design
December 13th 2023
speaker: Soojung Yang
location: Room B101, Northwest Building, Harvard University
title: Generating all-atom ensembles from C-alpha traces: Learning transferable protein backmapping from conformational ensembles
2022 seminars
February 2nd 2022
speaker: Sergey Ovchinnikov
title: Tutorial on using structure prediction methods for protein design
abstract: For this tutorial, I'll discuss the pros/cons of inverting structure prediction models for protein design. I'll walkthrough recent colab notebooks for designing proteins with TrRosetta and/or AlphaFold.
March 2nd 2022
speaker: Jeff Ruffolo
title: Learning from natural antibodies for sequence generation and fast structure prediction
abstract: Billions of natural antibody sequences have been identified through immune repertoire sequencing studies. Using this data, we developed a novel infilling language model for antibody sequence generation and targeted diversification. Pairing this data with structural information, we trained an end-to-end model for antibody structure prediction, which enables accurate structural modeling at scale.
April 13th 2022
speakers: Nasos Dousis and Andrew Giessel
title: Therapeutic enzyme engineering using a generative neural network
abstract: We present a novel, broadly applicable engineering method that combines deep latent variable modelling of sequence co-evolution with automated protein library design and construction to rapidly identify metabolic enzyme variants that are both more thermally stable and more catalytically active. We apply this approach to improve the potency of ornithine transcarbamylase (OTC), a urea cycle enzyme for which loss of catalytic activity causes a rare but serious metabolic disease.
May 11th 2022
speaker: Eva-Maria Strauch
title: From large to small, protein design for stability and de novo interfaces
abstract: I will talk about how we are stabilizing viral surface proteins, developed new small proteins of different folds and diverse shapes and turning them into de novo binding proteins. For the latter we develop deep learning algorithms for backbone and sequence design.
2021 seminars
January 6th 2021
speakers: Mohammed AlQuraishi & Sergey Ovchinnikov
title: CASP14 summary
abstract: A group discussion about the results from CASP14 - similar to what we did two years ago for CASP13. We will unpack the dramatic results from AlphaFold2 and help us to understand their implications for the field of protein structure prediction.
February 3rd 2021
speaker: Chris Ing
title: The 7 Habits of Highly Successful Protein Therapeutics
abstract: A holistic, integrated, and principle-centered approach is necessary for any protein facing translational challenges in drug discovery. In the style of a self-help seminar for proteins, I reveal a step-by-step guide for becoming an effective and developable protein on the path to the clinic through penetrating insights and pointed anecdotes across academic and industry settings. Specifically, we'll cover the core design strategies (i.e. habits) necessary to adapt to change, attain therapeutic goals, and thrive as a protein therapeutic in the modern world.
March 3rd 2021
speaker: Ben Meinen
title: Rational de novo design of disulfide-rich miniprotein agonists and antagonists for family B G-protein coupled receptors
abstract: The family of B1 (secretin) GPCRs control physiological responses like glucose metabolism, cardiovascular and gastrointestinal development as well as immune response. Approaches to convert the intrinsically disordered endogenous peptide hormones into agonist and especially antagonist have been largely unsuccessful. Miniproteins are small 3-12 kDa proteins that have great promise for therapeutic applications, because they allow for the combination of the binding specificity of antibodies, the stability of small molecules, and a low molecular weight that improves tissue penetrance. We are using de novo protein design to engineer disulfide-rich miniproteins that act as agonist and antagonist for family B GPCRs.
April 4th 2021
speaker: Dylan Marshall
title: A view of the structure-fitness landscape from an unsupervised vantage
abstract: Inferring the structure and mutational fitness of a given protein from sequence patterns alone are two tasks commonly addressed with generative sequence models. Here, we pedantically highlight a dearth of consistency in mutational fitness assays and introduce pairwise-saliency, a novel method for revealing the structural information learned by a given model. We also compare and contrast the capacity of a suite of progressively complex models towards these two tasks, thus allowing a view of the structure-fitness landscape to come into focus.
speaker: Frances Chu
title: Designing c-KIT Receptor Inhibitors to Clear Hematopoietic Stem Cells Prior to Bone Marrow Transplants
abstract: Current methods to clear hematopoietic stem cells (HSCs) from the bone marrow prior to bone marrow transplants have adverse, off-target effects on patients. A preferable method is to inhibit the c-KIT receptor, a receptor tyrosine kinase responsible for HSC survival, proliferation, and differentiation. By creating a protocol to dissemble protein quaternary structure, an inhibitor of c-KIT is obtained from its natural ligand.
May 5th 2021
speaker: Jack Maguire
title: Autocomplete for Protein Design
abstract: Rosetta's "FastDesign" protein design meta-protocol is constructed as a linear series of rotamer substitution rounds. The field of machine learning has made strong developments recently in the area of natural language processing, which considers linear series of data. Let's merge these together! This project attempts to use introspective machine learning techniques to guide Rosetta design simulations to the finish line.
June 2nd 2021
speaker: Andrea Garavito
title: De novo design of mini-proteins to inhibit bacterial biofilm formation
abstract: Biofilms are a prominent health and economical threat to society because they can be found in almost every environment, including water supplies, air condition vents, oil pipelines, or even medical devices such as a prosthetic heart valve. The formation of the biofilms in many Gram-negative bacteria is mediated in the periplasm by the Lap system. We are using a novel computational approach to design de-novo mini-protein from a single hotspot residue to inhibit a protein-protein interaction critical to the Lap system. Here, I will discuss the computational approach and the experimental screening of the de-novo designs. This work will facilitate investigation of the mechanisms controlling biofilm formation, and will provide a demonstration that the Lap system is a viable target for biofilm inhibition.
July 7th 2021
speaker: Pallav Kosuri
title: New tools for studying the mechanics of single proteins
abstract: I will present my research into fundamental principles of protein disulfide bond formation, and tell you how disulfide chemistry may influence the mechanics of your muscles. I will then discuss my recent invention of DNA devices that can be used to amplify protein movements and visualize protein-DNA interactions. Finally I will share our future plans to develop mechanical toolkits for all sorts of molecules at my newly opened lab at the Salk Institute.
August 4th 2021
speaker: Sergey Ovchinnikov
title: ColabFold - Making Protein folding accessible to all via Google Colab!
abstract: We will walk through a series of notebooks designed to run RoseTTAFold and AlphaFold for protein structure and protein-protein-complex prediction.
September 1st 2021
speaker: Nazim Bouatta
title: Predicting protein structures from single sequences
abstract: Despite the outstanding performance of AlphaFold2 and RoseTTAFold in protein structure prediction, many challenges remain, including (i) prediction of orphan proteins for which multiple sequence alignments (MSAs) cannot be generated and (ii) understanding the physical principles encoding the rules of protein folding. In this talk, I will first provide a brief survey of the available deep learning methods for protein structure prediction and then describe our end-to-end differentiable model (RGN2) able to predict structures starting from single sequences and without MSAs.
October 6th 2021
speaker: Brian Coventry
title: Learning to design mini-proteins that bind to specific protein targets
abstract: Antibodies have no trouble binding specifically to nearly any protein, but how do they do it? We set out to discover the principle necessary to design mini-proteins that bind to arbitrary protein targets using only the target apo-crystal-structure as our guide. While we certainly can't match the broad spectrum binding of antibodies, for a certain class of protein targets (those with rigid, exposed hydrophobics), we've learned quite a bit and have found binders to 30+ targets so far.
November 3rd 2021
speaker: Anum Glasgow
title: How local changes in secondary structure flexibility can drive protein function
abstract: Transcription factors regulate genes in response to environmental signals. Evolution took 4 billion years to make hundreds of transcription factors that all have the same fold, but which respond to many different signals, posing the question of how ligand specificity is achieved. We determined the mechanism of specificity for one transcription factor using biophysical measurements and computational modeling. Learning how the conformational ensemble of the protein changes upon binding partners that drive different functional responses can help us to determine how it evolved and how we can re-engineer it for new genetic circuits.
2020 seminars
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
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
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
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
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
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
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
speaker: Sergey Ovchinnikov
title: Protein sequence design by explicit energy landscape optimization
abstract: https://colab.research.google.com/drive/1hMEZdT5z_1wzAvfrt5pYz1sYtkBGSZt6
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
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
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
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.
2019 seminars
January 9th 2019
speaker: Krishna Praneeth Kilambi
title: Integrating structural data with the human interactome to support target discovery and characterization
abstract: Talk overview:
Introduce the human protein–protein interaction (PPI) network as a framework to better understand therapeutic targets
Combine structural information with the human interactome to enhance the network
Interpret the effects of disease-associated mutations on PPI to allow comparison of normal and disease states
speaker: Andreas Lehmann
title: Model of a solubilizing GDF11 prodomain peptide as an example for protein modeling & design at Biogen
abstract: Growth differentiation factor 11 (GDF11) is a member of the transforming growth factor β (TGF-β) family. Members of this protein family play very diverse roles in mammalian development and homeostasis, and have tremendous therapeutic potential. I will discuss a semi-artisanal model (borrowing Chris’ poetic description of this) I made to illustrate the potential conformation of a peptide that can be proteolytically cleaved from GDF11’s prodomain. This prodomain peptide keeps the otherwise insoluble homodimeric GDF11 soluble and does not interfere with its activity. Using this example, I aim to illustrate the use of protein modeling & design as an embedded function of biologics drug discovery R&D at Biogen, the oldest independent biotech company in the world.
February 6th 2019
speaker: Samaneh Mesbahi-Vasey
title: how to build entirely novel, functional proteins de novo with SEWING
abstract: De novo protein design traditionally has begun with the researchers specifying a protein structure to be created and then using molecular modeling to identify amino acid sequences that will adopt that fold. However, when designing for protein function, we no longer need structure-driven design. I will present a method called SEWING which allows design for protein function without the need to know/predict the desired protein’s structure a priori
speaker: Chris Bahl
title: the beast is slain; LayerDesign is dead but not gone (yet)
abstract: I'll review LayerDesign, why and where it's useful when performing design in Rosetta. Then, I'll walk through how to do LayerDesign without using LayerDesign; this relies on several different residue selectors and the new DesignRestrictions task operation. Finally, I'll discuss the new recommended changes to default LayerDesign behavior.
March 6th 2019
speaker: Shourya Sonkar Roy Burman
title: Modeling Interactions of Flexible Proteins
abstract: A story of two related methods:
RosettaDock 4.0: a heterodimer docking protocol that incorporates flexibility by efficiently simulating conformational selection from hundreds of pre-generated backbone conformations and identifies the near-native models with a novel coarse-grained score function called Motif Dock Score (MDS)
Rosetta SymDock2: a symmetric protein assembly method that leverages MDS in the coarse-grained phase and simulates subunit flexibility through induced fit by all-atom flexible-backbone refinement
April 3rd 2019
speaker: Surge Biswas
title: Unified rational protein engineering using sequence-only deep representation learning
abstract: We use deep representation learning to learn a semantically rich basis in which we can quantitatively compare proteins given only their amino acid sequences. This paradigm enables stability and quantitative function prediction and shows promise for protein engineering. I’ll talk about these results, and will discuss future directions related to structure prediction, data efficient protein design, and specific applications thereof that we’re exploring in the lab.
May 1st 2019
speaker: Sergey Ovchinnikov
title: A workshop on using sequence models for protein design (pssm, gremlin/mrf, vae, seq2seq autoencoders etc)
abstract: topics:
1) intro to google colab
2) intro to tensorflow and optimization
3) PSSM (simple one-body model)
4) Markov Random Fields (one-body, two-body model)
5) Autoencoders (simple mixture one-body model)
6) Variational Autoencoders
7) Sequence models
June 5th 2019
speaker: AJ Vincelli
title: Optimizing Rosetta’s Relax Algorithm to Prepare Published Protein X-Ray Structures
abstract: This project aims to improve the quality of X-ray crystal structures published in the PDB as an essential preparatory first step of biomedical and drug discovery initiatives. We have developed and calculated a six-factor aggregate “Quality Score” for 428 published X-ray structures, both before and after refinement with Rosetta's Relax algorithm, and found that the scores of low-quality structures improved significantly after Relaxation. Our next steps include expanding the dataset to protein:ligand complexes, and optimizing the refinement protocol for general use on protein X-ray structures found in the PDB.
speaker: Firas Khatib
title: Building Denovo Cryo-EM Structures Collaboratively with Video Gamers
abstract: With the rapid improvement of cryo-electron microscopy (Cryo-EM) resolution, new computational tools are needed to assist and improve upon atomic model building and refinement options. Microscopists can now collaborate with the players of the protein folding game Foldit to generate thorough high quality de novo structural models. This development could greatly speed the generation of excellent Cryo-EM structures when used in addition to current methods.
July 10th 2019
speaker: Per Greisen
title: Computational design of biosensors for small molecules
abstract: The ability to detect and respond to small molecules has great applications ranging from biotechnology to the pharmaceutical industry. Many natural biosensors are made from proteins and can function both inside cells/bacteria as well as outside of cell/bacteria. Unfortunately, there are not preexisting for all small molecules of interest but still a great need to generate biosensors. Computational protein design has shown its ability to generate new protein folds as well as create new functions in proteins. One way to generate new biosensors is to use computational protein design which in principle can design proteins binders with high affinity and specificity. Here, we will go through the successes and failures of computational protein design for small molecules with emphasis on Rosetta showing results from different small molecules (e.g. fentanyl, vitamin D/THC). Lastly, we will briefly discuss endeavours to solve and improve the protocols for computational design of small molecules.
August 14th 2019
speaker: Shourya Sonkar Roy Burman
title: Using Movers in PyRosetta
abstract: This will be a tutorial on how to use PyRosetta to write protocols. As an example, we will use PyRosetta to write code with basic movers. Next, we will explore the PyRosetta documentation to see what functions are available for given movers and write a more complicated protocol.
September 4th 2019
speaker: Nasos Dousis
title: Can we incorporate dynamics into routine enzyme design?
abstract: I will share some highlights from the Fall 2019 ACS meeting, and then guide a discussion on how we might incorporate dynamics to engineer catalytic rate in enzymes.
September 1st 2019
speaker: Alex Garruss
title: Deep Mutational Learning
abstract: I’ll present some machine learning approaches we are developing in the Church Lab to understand large-scale, deep mutational scanning experiments of protein function. We will discuss three areas of approach: sequence-only modeling (using embedding layers, local convolutional and graph convolutional neural networks), evolution-guided modeling (using latent variable models built from related sequences), and structural modeling (3D convolutions of all-atom structures) to predict the functional effect of varying a given protein’s sequence. Such approaches enable new understanding of function and are useful for objectives in protein engineering.
October 2nd 2019
speaker: Sergey Ovchinnikov
title: Improved protein structure prediction using predicted inter-residue orientations
abstract: I'll describe some improvements to our structure prediction protocol, more specifically using residual blocks to generate better restraints for rosetta modeling. (Aka, what we did to catch up to alphafold)
November 6th 2019
speaker: Victor Ovchinnikov
title: An Atomic Structure of the EmrE Multidrug Transporter for the Design of Inhibitor Peptides
abstract: Atomic-resolution structures of the EmrE multidrug transporter in ligand-free form, as well as bound to the ligands tetraphenylphosphonium+ (TPP) and ethidium+ are refined using multi-microsecond molecular dynamics simulations, using restraints to a low-resolution electron density map. We designed proteolysis-resistant stapled peptides with the aim of inhibiting the drug-resistance activity of EmrE by interfering with dimerization.
December 4th 2019
speaker: Frank Teets
title: Advances in Requirement-Driven Protein Design
abstract: Requirement-driven protein design is a historically underdeveloped approach to de novo design, relying on functional rather than structural constraints to guide the design process. Here, I present a series of computational improvements to the requirement-driven protein design algorithms in Rosetta that dramatically improve the flexibility and performance of the design pipeline.
2018 seminars
May 2nd 2018
speaker: Sergey Ovchinnikov
title: a workshop on protein structure prediction with Rosetta
June 6th 2018
speaker: Mohammed AlQuraishi
title: End-to-end differentiable learning of protein structure
abstract: https://www.biorxiv.org/content/early/2018/02/14/265231
speaker: Julian Mintseris
title: High-density chemical cross-linking for modeling protein interactions
abstract: Here we report advances in method development, combining orthogonal cross-linking chemistries as well as improvements in search algorithms, statistical analysis and computational cost to achieve coverage of one unique cross-linked position pair for every 7-8 amino acids at 3% false discovery rate. We demonstrate that this level of cross-linking density is sufficient to reconstruct subunit architecture without any additional structural information for the subunits.
August 1st 2018
speaker: Radek Nowak
title: Plasticity in binding confers selectivity in ligand-induced protein degradation
abstract: We utilize a comprehensive characterization of the ligand-dependent CRBN–BRD4 interaction to demonstrate that binding between proteins that have not evolved to interact is plastic. Our findings that plastic interprotein contacts confer selectivity for ligand-induced protein dimerization provide a conceptual framework for the development of heterobifunctional ligands.
speaker: Victor Ovchinnikov
title: Biomolecular simulations using a flexible-boundary solvation model
abstract: Development of a flexible solvent boundary model, which combines fine granularity near solute interfaces and coarse granularity (continuum) in the bulk solvent
September 5th 2018
speakers: Kelly Brock, Nathan Rollins
title: Using natural and synthetic sequences to identify protein structure and function
abstract: We will talk about several projects using evolutionary couplings and expand to using mutational scans to predict folding.
October 3rd 2018
speaker: Dylan Marshall
title: Manipulating and Visualizing Data with Python - a 20 minute tutorial that will blow your mind
abstract: Big data this, data science that - if you've been seeking to hop aboard the "data (insert buzzword here)" hype train, I invite you to come get up to speed with the latest and greatest in python-based data manipulation and visualization tools. I kid you not, all you need is a Google Drive account - and a laptop of course. Using the medium of Google CoLab (how we will be coding Python), you will be introduced to Pandas (tool for data manipulation) and Seaborn (tool for data visualization) in the most succinct way possible. Any remaining advocates for Excel will be vigorously debated with, and definitively vanquished, over beers afterwards.
speaker: Sergey Ovchinnikov
title: a quick intro to Rosetta and how to modify it to work with cryo-em density
November 7th 2018
speaker: David Nannemann
title: Capturing Diversity to Improve Affinity
abstract: Hit antibodies often require affinity maturation or other optimization to tune the therapeutic properties or manufacturability of the molecule. Next Generation Sequencing of the full antibody repertoire in the sample can guide affinity maturation and/or optimization processes. I will discuss two methods which leverage NGS data and sparse screening of clonal families to identify high affinity antibodies.
speaker: Mohammed AlQuraishi
title: a tutorial on deep learning
December 5th 2018
speaker: Chris Bahl
title: Discovery and engineering of enhanced SUMO protease enzymes
abstract: https://doi.org/10.1074/jbc.RA118.004146