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Posts

Parametric disasters

3 minute read

Published:

I recently got a new computer and I have been (slowly) going through my old files to try to some order around here. So, while I was doing this kind of twenty-first century upkeep, I stumbled across a file called “nope_nope_nope.mov”. Here’s what was in that file…

Standing on the shoulders of giants

1 minute read

Published:

PreRosettaCon is a two-day meeting in which scientists from all over the world who are developing new methods in Rosetta or otherwise rely on it for their research come together, discuss issues, make plans to solve them.

portfolio

publications

Serverification of Molecular Modeling Applications: The Rosetta Online Server That Includes Everyone (ROSIE)

Lyskov S, Chou FC, et al.
PLOS ONE, 2013 : https://doi.org/10.1371/journal.pone.0063906

Here, we present a unified web framework for Rosetta applications called ROSIE that provides (a) a common user interface for Rosetta protocols, (b) a stable API for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance.

The origin of CDR H3 structural diversity

Weitzner BD, Dubrack RL Jr, Gray JJ
Structure, 2015 : https://doi.org/10.1016/j.str.2014.11.010

To determine why the majority of H3 loops are kinked, we searched a set of non-antibody structures for regions geometrically similar to the residues immediately surrounding the loop. We find that the kink is conserved in the immunoglobulin heavy chain fold because it disrupts β-strand pairing at the base of the loop. Thus, the kink is a critical driver of the observed structural diversity in CDR H3.

Rosetta Antibody Design (RAbD): A General Framework for Computational Antibody Design

Adolf-Bryfogle J, et al.
PLOS Computational Biology, 2018 : https://doi.org/10.1371/journal.pcbi.1006112

We present RAbD, which can be used to redesign a single CDR or multiple CDRs with loops of different length, conformation, and sequence. We rigorously benchmarked RAbD on a set of 60 diverse antibody–antigen complexes, using two design strategies—optimizing total Rosetta energy and optimizing interface energy alone. We tested RAbD experimentally demonstrating markedly improved binding affinities.

[PREPRINT] Designing Peptides on a Quantum Computer.

Mulligan VK, et al.
bioRxiv, 2019 : https://doi.org/10.1101/752485

We describe our mapping of the protein design problem to the D-Wave quantum annealer. We present a system whereby Rosetta, a state-of-the-art protein design software suite, interfaces with the D-Wave quantum processing unit to find amino acid side chain identities and conformations to stabilize a fixed protein backbone.

A computational method for design of connected catalytic networks in proteins.

Weitzner BD, Kipnis Y, Daniel AG, et al.
Protein Science, 2019 : https://doi.org/10.1002/pro.3757

Our new method starts from a ChemDraw‐like two‐dimensional representation of the transition state with hydrogen‐bond donors, acceptors, and covalent interaction sites indicated, and all placements of side‐chain functional groups that make the indicated interactions with the transition state, and are fully connected in a single hydrogen‐bond network are systematically enumerated. Used in conjunction with RosettaMatch, this method generates many fully‐connected active site solutions for a set of model reactions that are promising starting points for the design of fully‐preorganized enzyme catalysts.

Macromolecular modeling and design in Rosetta: recent methods and frameworks.

Koehler Leman J, Weitzner BD, Lewis SM, et al.
Nature Methods, 2020 : https://doi.org/10.1038/s41592-020-0848-2

We discuss the methods developed in the last five years, involving the latest protocols for structure prediction, protein–protein and protein–small molecule docking, protein structure and interface design, loop modeling, the incorporation of various types of experimental data, and modeling of peptides, antibodies and other proteins in the immune system, nucleic acids, non-standard amino acids, carbohydrates, and membrane proteins. We also briefly discuss improvements to the energy function, user interfaces, and usability of the ­­software.

The influence of proline isomerization on potency and stability of anti-HIV antibody 10E8.

Guttman M, et al.
Scientific Reports, 2020 : https://doi.org/10.1038/s41598-020-71184-7

We identify the source of the anti-HIV mAb 10E8’s heterogeneity being linked to cis/trans isomerization at two prolines within the YPP motif in the CRD3 loop that exists as two predominant conformers that interconvert on a slow timescale. The YtransP conformation conformer can bind the HIV gp41 epitope, while the YcisP is not binding competent and shows a higher aggregation propensity. This study highlights how proline isomerization should be considered a critical quality attribute for biotherapeutics with paratopes containing potential cis proline amide bonds.

Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites.

Hosseinzadeh P, et al.
Nature Communications, 2021 : https://doi.org/10.1038/s41467-021-23609-8

We developed a computational “anchor extension” methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor to design function cyclic peptide binders that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor.

talks

PyMOL–PyRosetta Integration

Published:

In this talk I present a new tool to enable real-time visualization in PyMOL of macromolecular simulations performed in Rosetta or PyRosetta.

Using PyRosetta for research

Published:

Andrew Leaver-Fay, Dan Kulp, and Sergey Lyskov, and I led a workshop that went over first time use of PyRosetta, using interactive sessions to get things done quickly, and basic usage patterns.

PyRosetta 2.0: I can make a new score term in 6 lines!

Published:

Along with Sergey Lyskov, I discuss the new developments in the python-accessible distribution of Rosetta, PyRosetta. Of particular note is that every component of Rosetta is now available in PyRosetta and key Rosetta data structures can be created in python and passed back into the system, enabling rapid prototyping of new score function terms and sampling strategies.

Antibodies are proteins too!

Published:

The third complementarity-determining region loop on the IgG heavy chain (CDR H3) is the focal point of the gene recombination that gives rise to the immense diversity of antibodies. A consequence of this diversity is observed in the variability in length, sequence and structure of the H3 loop. Because of the circumstances that give rise to the H3 loop, it is unclear if the conformations they adopt are unique to antibodies. We set out to determine what it means for a loop to have an H3-like conformation and whether or not these conformations are commonplace in other proteins. To that end, we searched a set of high-quality non-antibody structures for regions with 1) 3D transformations matching the conserved transformation of the H3 loop and 2) a C-terminal “kink”/“bulge”. We found these criteria were enough to identify a set of loops with similar DSSP code distributions and RMSDs within 2.0 Å of nearly all H3 loops of length 15 or shorter. We believe this set can be used to find starting structures for H3 loop modeling and that this result is powerful evidence suggesting that CDR H3 is just another loop.

Kinked CDR H3-like loops are common

Published:

The difficulty of de novo CDR H3 loop modeling is surprising in many cases because of the modest loop lengths at which they occur. One possible explanation is that V(D)J recombination can produce loops that access conformations that are extremely rare in existing protein structural databases. An alternate hypothesis is that the environment formed by the VH and VL domains stabilizes CDR H3 loop conformations that existing methods do not detect as favorable. We identified a diverse set of loops across a wide range of lengths that adopt H3-like conformations. These loops show that the kinked conformation of CDR H3 loops is common.

Benchmarking RosettaAntibody: Antibody Modeling Assessment II

Published:

Antibody Modeling Assessment II (AMA-II) presented an opportunity to test the RosettaAntibody structure prediction tool on 11 benchmark antibody FV regions whose structures were determined, but not yet deposited in the Protein Data Bank. Along with groups from Accelrys Software, Inc, Chemical Computing Group, Inc, Astellas Pharma, Macromoltek, and Schrödinger, we discussed the strengths, weaknesses, and future plans for each of the methods employed.

Computational structure prediction, docking and design of antibodies

Published:

I discussed the latest developments in Rosetta-based approaches for antibody structure prediction and docking, with a focus on new loop prediction methods, (specifically for CDR H3 loops), and using homology models to design for binding desired target epitopes.

The origin of CDR H3 structural diversity

Published:

The third complementarity determing region loop on the heavy chain (CDR H3) of antibodies is the most diverse of the CDR loops in terms of length, sequence and structure. This loop also provides a plurality of interatomic contacts and binding energy in antibody–antigen complexes. In light of this, I disucss the factors that contribute to the observed structural diversity of CDR H3 in order to provide a starting point for improved strucutre prediction methods.

Next-generation antibody modeling

Published:

Developments in high-throughput sequencing technologies have made it possible to sequence 105 B cells in a single experiment, renewing the need for accurate structural modeling methodologies. I discuss the process by which we identify weaknesses in current approaches and how we go about filling in the gaps.

Next-generation antibody modeling

Published:

Developments in high-throughput sequencing technologies have made it possible to sequence 105 B cells in a single experiment, renewing the need for accurate structural modeling methodologies. I discuss the process by which we identify weaknesses in current approaches and how we go about filling in the gaps.

teaching

Teaching Assistant, ChemE 1120

Introduction to Chemical Engineering, Cornell University, Department of Chemical and Biomolecular Engineering, 2008

This course introduces freshman undergraduate students to design strategies for contemporary chemical and biomolecular engineering. Methods for analyzing designs, mathematical modeling, empirical analysis by graphics, and dynamic scaling through dimensional analysis are also covered in the context of assessing product quality, economics, safety, and environmental issues. My role in this course was grading assignments and presenting problems along with solutions in weekly recitation sessions.

Teaching Assistant, ChemE 3900

Chemical Kinetics and Reactor Design, Cornell University, Department of Chemical and Biomolecular Engineering, 2009

This course is aimed at junior-level undergraduates to introduce the study of chemical reaction kinetics and principles of reactor design for chemical processes. The students develop a molecular-level understanding of chemical reaction kinetics, practical approaches to modeling complex reactions, and the ability to construct mathematical models to predict system behavior from first principles. With these tools in hand, the students learn to optimize reactor design with regard to multiple performance criteria. My role in this course was presenting problems along with solutions in weekly recitation sessions.

Teaching Assistant, ChemBE 414/614

Computational Protein Structure Prediction and Design, Johns Hopkins University, Department of Chemical and Biomolecular Engineering, 2010

This course is aimed at introducing the fundamental concepts in protein structure, biophysics, optimization and informatics that have enabled the breakthroughs in computational structure prediction and design to advanced seniors and interested graduate students. My role in this course was running the weekly laboratory sessions as well as grading homework assignments.

Teaching Assistant, ChemBE 409

Modeling, Dynamics and Control of Chemical and Biological Systems, Johns Hopkins University, Department of Chemical and Biomolecular Engineering, 2010

This course introduces the modeling, dynamics, and control concepts necessary for the unsteady state analysis of biomolecular and chemical processes to seniors in the Chemical & Biomolecular Engineering program. Model construction for biomolecular and cellular systems including pharmacokinetic model- ing, biomolecular modeling using the central dogma of biology/control of gene expression, large scale biosimulation. I held office hours, proctored exams, ran a lab assignment and assisted students with model analysis using Matlab.

Co-Instructor, ChemBE 418

Projects in the Design of a Chemical Car, Johns Hopkins University, Department of Chemical and Biomolecular Engineering, 2011

This coursUndergraduate students work in small groups over the course of the semester to design and build a chemically powered vehicle that will compete with other college teams at the American Institute of Chemical Engineers (AIChE) Regional Conference. The students must design and construct the chassis as well as chemically powered propulsion and break mechanisms within the constraints of the competition. In addition, students will give oral presentation, write reports, and do thorough safety analysis of their prototypes. My role as a co-instructor was to challenge the students’ designs, assist them in organizing their experiments and keep- ing on schedule to successfully construct their car.

Co-Instructor, Rosetta Boot Camp

An intense week-long crash course to developing in Rosetta, University of North Carolina, 2013

This course is aimed at introducing the computer science concepts and architecture of Rosetta to graduate students and postdocs who have recently joined labs that develop Rosetta. After this week-long course, students should be able to use Rosetta to solve specific structure prediction and design problems as well as develop new methods tailored to a specific problem. I delivered three lectures and guided lab sessions. All course lectures are available on YouTube.

Guest Lecturer, ChemBE 414/614

Computational Protein Structure Prediction and Design, Johns Hopkins University, Department of Chemical and Biomolecular Engineering, 2014

This course is aimed at introducing the fundamental concepts in protein structure, biophysics, optimization and informatics that have enabled the breakthroughs in computational structure prediction and design to advanced seniors and interested graduate students. My role in this course was delivering a lecture on side-chain conformations, optimization and libraries. All course lectures are available on YouTube.

Guest Lecturer, Engl 182

Multimodal Composition, University of Washington, Department of English, 2017

This course introduces the study and practice of strategies and skills for effective writing and argument in various situations, disciplines, and genres with an explicit focus on how multimodal elements of writing work together to produce meaning. My lecture focused on how rhetorical appeals are used in various scientific disciplines, ways in which the scientific record incorporates subjectivity, and how to critique scientific writing.

Co-Instructor, Rosetta Boot Camp

An intense week-long crash course to developing in Rosetta, Rosetta Commons, 2017

This course is aimed at introducing the computer science concepts and architecture of Rosetta to graduate students and postdocs who have recently joined labs that develop Rosetta. After this week-long course, students should be able to use Rosetta to solve specific structure prediction and design problems as well as develop new methods tailored to a specific problem. I delivered six lectures and guided lab sessions.