Zev Bryant

About

Zev Bryant is an Associate Professor of Bioengineering and, by courtesy, of Structural Biology at Stanford University. His laboratory focuses on understanding the physical mechanisms by which molecular motors convert chemical energy into mechanical work, which are essential to various biological processes such as DNA replication and vesicle transport. His research employs single molecule tracking and manipulation techniques to observe and perturb substeps in the mechanochemical cycles of individual motors, and utilizes protein engineering to explore the relationships between molecular structures and mechanical functions. His current research interests include torque generation by DNA-associated ATPases and mechanical adaptations of unconventional myosins. Bryant holds a B.Sc. in Biochemistry from the University of Washington (1998) and a Ph.D. in Molecular and Cell Biology from UC Berkeley (2003).

Research topics

• Computer Science
• Biophysics
• Biology
• Chemistry
• Biological system
• Physics
• Artificial Intelligence
• Genetics
• Materials science
• Engineering

Selected publications

• Spatiotemporal control of liquid crystal structure and dynamics through activity patterning

  Nature Materials · 2021 · 133 citations

  DOI

• Cas9 interrogates DNA in discrete steps modulated by mismatches and supercoiling

  Proceedings of the National Academy of Sciences · 2020 · 120 citations

  Senior authorCorresponding

  The CRISPR-Cas9 nuclease has been widely repurposed as a molecular and cell biology tool for its ability to programmably target and cleave DNA. Cas9 recognizes its target site by unwinding the DNA double helix and hybridizing a 20-nucleotide section of its associated guide RNA to one DNA strand, forming an R-loop structure. A dynamic and mechanical description of R-loop formation is needed to understand the biophysics of target searching and develop rational approaches for mitigating off-target…

  DOI

• Introduction: Molecular Motors

  Chemical Reviews · 2020 · 97 citations

  Senior authorCorresponding

  ADVERTISEMENT RETURN TO ISSUEEditorialNEXTIntroduction: Molecular MotorsRyota Iino*Ryota IinoInstitute for Molecular Science and The Graduate University for Advanced Studies (SOKENDAI)*E-mail: [email protected]More by Ryota IinoView Biographyhttp://orcid.org/0000-0003-0110-5704, Kazushi Kinbara*Kazushi KinbaraTokyo Institute of Technology*E-mail: [email protected]More by Kazushi KinbaraView Biography, and Zev Bryant*Zev BryantStanford University*E-mail: [email protected]More by Zev BryantView Bi…

  DOI

• Machine learning active-nematic hydrodynamics

  Proceedings of the National Academy of Sciences · 2021 · 88 citations

  Hydrodynamic theories effectively describe many-body systems out of equilibrium in terms of a few macroscopic parameters. However, such parameters are difficult to determine from microscopic information. Seldom is this challenge more apparent than in active matter, where the hydrodynamic parameters are in fact fields that encode the distribution of energy-injecting microscopic components. Here, we use active nematics to demonstrate that neural networks can map out the spatiotemporal variation of…

  PublisherOA PDFDOI

• Rapid two-step target capture ensures efficient CRISPR-Cas9-guided genome editing

  Molecular Cell · 2025-04-23 · 18 citations

  articleOpen access

  RNA-guided CRISPR-Cas enzymes initiate programmable genome editing by recognizing a ∼20-base-pair DNA sequence next to a short protospacer-adjacent motif (PAM). To uncover the molecular determinants of high-efficiency editing, we conducted biochemical, biophysical, and cell-based assays on Streptococcus pyogenes Cas9 (SpyCas9) variants with wide-ranging genome-editing efficiencies that differ in PAM-binding specificity. Our results show that reduced PAM specificity causes persistent non-selectiv…

  PublisherDOI

Recent grants

• Structural Dynamics and Mechanochemical Coupling in Nucleoprotein Machines

  NIH · $2.7M · 2014–2026

• NIH Grant DP2OD004690

  NIH · $2.4M · 2013

• Engineering Cytoskeletal Motors

  NIH · $1.3M · 2018–2023

Frequent coauthors

• Carlos Bustamante

  University of California, Berkeley

  49 shared

• Michael D. Stone

  Cardiff and Vale University Health Board

  45 shared

• Jeff Gore

  Massachusetts Institute of Technology

  36 shared

• Seok‐Cheol Hong

  Korea University

  30 shared

• Paul V. Ruijgrok

  Stanford University

  24 shared

• Nicholas R. Cozzarelli

  20 shared

• Nancy J. Crisona

  15 shared

• Steven B. Smith

  15 shared

Similar researchers at Stanford University

• Karl Deisserothh-218
• Michael Fischbachh-115
• Paul Yockh-79