About

Harel Weinstein, D.Sc. is the Maxwell Upson Professor of Physiology and Biophysics and former Chairman of the Department of Physiology and Biophysics, and the Director of the Institute for Computational Biomedicine at Weill Cornell Medical College of Cornell University in New York City. As a Tri-Institutional Professor, he holds professorial appointments at Rockefeller University, Sloan-Kettering Institute and Cornell University. As the founding director of the Institute for Computational Biomedicine (ICB), he has developed it into an academic and research unit responsible for a novel approach to biomedicine that involves the mathematical, physical and computational sciences in combination with engineering and medical informatics. The ICB aims at fundamental study and practical use of the basic, quantitative understanding of physiological function and disease, in an integrative, multi-scale approach based on gene structure and defects responsible for properties and behaviors at all levels–from protein, to cell, tissue and organ. His lab is devoted to studies in molecular and computational biophysics that address complex systems in physiology, and to the development and application of bioinformatics and engineering approaches to systems biology. The Weinstein lab studies complex systems in physiology with methods of molecular and computational biophysics, bioinformatics and mathematical models. The work addresses structural and dynamic mechanisms in fundamental biological processes such as signal transduction, neuronal signaling and regulation of cell growth mechanisms, and the expression of these processes in the physiological functions of tissues and organs. Theoretical and computational methods of biophysics are combined with experimental designs to determine structural and dynamic properties at the molecular level. The processes emerging from the interaction of cellular components described at this molecular level are evaluated with computational simulations of cell function. A current theme centers on the mechanisms of molecular recognition and allostery of micromachines involved in signal transduction — specifically, how this explains macromolecular dynamics, oligomerization and encounter-complex formation in cellular signaling by G protein coupled receptors, neurotransmitter transporters and multidomain scaffolding proteins. The biomedical end points for these particular studies are neurotransmission in health and disease, drug abuse mechanisms and cancer.

Research topics

• Chemistry
• Internal medicine
• Biochemistry
• Virology
• Biology
• Medicine
• Biophysics
• Pharmacology

Selected publications

• ModeHunter: A Package for the Reductionist Analysis, Animation, and Application of Elastic Biomolecular Motion

  The Journal of Physical Chemistry B · 2025-01-10 · 1 citations

  articleOpen accessSenior author

  ModeHunter is a modular Python software package for the simulation of 3D biophysical motion across spatial resolution scales using modal analysis of elastic networks. It has been curated from our in-house Python scripts over the last 15 years, with a focus on detecting similarities of elastic motion between atomic structures, coarse-grained graphs, and volumetric data obtained from biophysical or biomedical imaging origins, such as electron microscopy or tomography. With ModeHunter, normal modes of biophysical motion can be analyzed with various static visualization techniques or brought to life by dynamics animation in terms of single or multimode trajectories or decoy ensembles. Atomic structures can also be refined against volumetric densities with flexible fitting strategies. The software consists of multiple stand-alone programs for the preparation, analysis, visualization, animation, and refinement of normal modes and 3D data sets. At its core, two spatially reductionist elastic motion engines are currently supported: elastic network models (typically for a Cα level of detail and rectangular meshes) and bend-twist stretch (for trigonal or tetrahedral meshes or trees resulting from spatial clustering). The programs have recently been modernized to Python 3, requiring only the common numpy and scipy external libraries for numerical support. The main advantage of our modular design is that the tools can be combined by the end users for specific modeling applications, either standalone or with complementary tools from our C/C++-based Situs modeling package. The modular design and consistent look and feel facilitate the maintenance of individual programs and the development of novel application workflows. Here, we provide the first complete overview of the ModeHunter package as it exists today, with an emphasis on functionality and workflows supported by version 1.4.

  PublisherOA PDFDOI

• BPS2025 - Decoding the address system for StarD4 shuttle transport of cholesterol in the cell

  Biophysical Journal · 2025-02-01

  article1st authorCorresponding
  PublisherDOI

• Recognition of Specific PIP2-subtype Composition Triggers the Allosteric Control Mechanism for Selective Membrane Targeting of Cargo Loading and Release Functions of the Intracellular Sterol Transporter StarD4

  Journal of Molecular Biology · 2025-04-15 · 2 citations

  articleOpen accessSenior authorCorresponding

  • StarD4 recognition of different PIP2-subtypes in organelle membranes selects its targets for CHL uptake vs release. • AI/ML analyses of MD simulations (totaling > 1.5 milliseconds/each) reveal mechanisms of StarD4 function and PIP2 recognition. • Specific allosteric networks connect either CHL-uptake or release to PIP2 recognition. • StarD4 mutation results are interpreted by the dynamic model of StarD4 function. • Discusses implications for CHL regulation and diseases associated with its dysfunction. We present a comprehensive, quantitative model of the allosteric molecular mechanisms of selective cholesterol (CHL) uptake and delivery by the StarD4 protein – an intracellular cholesterol trafficking protein that facilitates the crucial non-vesicular sterol transport between the plasma membrane and the endoplasmic reticulum. This sterol-specific transfer protein is essential for maintaining the healthy life of human cells. In its physiological function, StarD4 targets both sterol donor and acceptor membranes via interactions with anionic lipids. Experiments have illuminated the kinetics of this sterol transfer and shown it to be modulated by specific phosphatidylinositol phosphates (PIPs) on the target membrane, but the molecular mechanism of the recognition of the PIP2 subtype by StarD4, and how this affects the direction and kinetics of cholesterol transport remained unclear. By revealing a heretofore unrecognized allosteric mechanism that connects the sterol binding site to the part of the protein embedded in the membrane, we show here how StarD4 can respond with different actions to diverse organelle membranes based on their PIP2-subtype composition, in agreement with physiological and experimental evidence. The trajectories of extensive (millisecond range) molecular dynamics (MD) simulation of the StarD4-membrane interactions we calculated, were analyzed with advanced machine learning and information theory methods. Our findings outline how the specific molecular mechanism for recognizing PIP2-subtypes in membranes by StarD4 couples to the defined allosteric pathway that induces the CHL binding pocket to propagate the signal for either uptake or release of the sterol. The central role determined for allostery in these significant advances in the understanding of intracellular cholesterol trafficking by StarD4, aligns with experimentally determined properties of StarD4 function, and interprets them in experimentally testable atomistic terms that explain function-altering results of mutations.

  PublisherDOI

• Increasing the Efficiency of Ensemble Molecular Dynamics Simulations with Termination of Unproductive Trajectories Identified at Runtime

  The Journal of Physical Chemistry A · 2025-02-04 · 1 citations

  articleOpen access

  The application of molecular dynamics (MD) simulations to study increasingly larger and more complex systems is challenged by the required amounts of trajectory data needed to sample their conformational space appropriately. The analysis and interpretation phase of such massive data sets that have to be stored and fed to the various algorithms to reveal the dynamic behaviors of the systems and the underlying energetics in structural terms related to functional mechanisms are also a significant challenge. To develop computational means that can address these challenges, we are developing a software framework that can increase the efficiency of this process. We present one component of this framework that can reduce the size of the accumulating data set while maintaining the structural attributes, distribution, and relative probability ranking of the minima in the free energy map for the system. This framework component utilizes early termination of individual trajectories identified as unproductive in the sampling of conformational space. The criteria for termination are derived quantities such as collective variables (CVs) and secondary quantities calculated from the time series of CVs. They are computed and applied during the trajectory generation. The approach is illustrated with simulations of the FS peptide and evaluated from comparisons between the free energy surfaces calculated from ensembles of complete, unabridged simulations with those obtained from ensembles in which ∼5-50% of trajectories were terminated early. Our early termination approach can optimize computational efficiency while achieving a robust representation of conformational space.

  PublisherOA PDFDOI

• Exploring allosteric mechanisms in cholesterol transportation and PIP2 subtype recognition by StarD4

  Biophysical Journal · 2024-02-01

  articleOpen accessSenior author
  PublisherOA PDFDOI

• Recognition of specific PIP2-subtype composition triggers the allosteric control mechanism for selective membrane targeting of cargo loading and release functions of the intracellular sterol transporter StarD4

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-03-27 · 1 citations

  preprintOpen accessSenior authorCorresponding

  ABSTRACT StarD4 is an intracellular cholesterol trafficking protein that facilitates the crucial non-vesicular sterol transport between the plasma membrane and the endoplasmic reticulum. It targets both sterol donor and acceptor membranes via interactions with anionic lipids. Experiments have illuminated the kinetics of this sterol transfer and shown it to be modulated by specific phosphatidylinositol phosphates (PIPs) on the target membrane. The distinct subtype distribution of PIPs in the membranes of cellular organelles serves as a guide to direct StarD4 to recognized cell components. However, little is known about the molecular mechanism of the recognition of the PIP2 subtype by StarD4, and how this affects the direction and kinetics of cholesterol transport, as the reaction pathways of the cholesterol uptake and release processes in StarD4 have never been observed. Here, we investigated 1)-how StarD4 transports a cholesterol from/to membranes; 2)-how StarD4 recognizes PIP2-subtypes in membranes; and 3)-how the PIP2-subtype recognition impacts cholesterol transport kinetics, using extensive molecular dynamics (MD) sampling with advanced machine learning and information theory methods for trajectory analysis. The findings revealed function-related allosteric dynamics of StarD4, connecting the identified PIP2-subtype-specific conformational states to the cholesterol binding modes in the pocket, which steers the dynamics of the gates towards conformations that support either cholesterol release or uptake. This reveals the crucial role of PIP2 subtypes in shaping functional StarD4 motifs responsible for organelle selectivity of the cholesterol trafficking, providing fundamental insights into cellular cholesterol regulation.

  PublisherOA PDFDOI

• Recognition of Specific Pip2-Subtype Composition Triggers the Allosteric Control Mechanism for Selective Membrane Targeting of Cargo Loading and Release Functions of the Intracellular Sterol Transporter Stard4

  SSRN Electronic Journal · 2024-01-01

  preprintOpen accessSenior author
  PublisherDOI

• A Mechanistic Understanding of the Modes of Ca²⁺ Ion Binding to the SARS-CoV-1 Fusion Peptide and Their Role in the Dynamics of Host Membrane Penetration

  ACS Infectious Diseases · 2024-01-25 · 3 citations

  articleOpen accessCorresponding

  The SARS-CoV-1 spike glycoprotein contains a fusion peptide (FP) segment that mediates the fusion of the viral and host cell membranes. Calcium ions are thought to position the FP optimally for membrane insertion by interacting with negatively charged residues in this segment (E801, D802, D812, E821, D825, and D830); however, which residues bind to calcium and in what combinations supportive of membrane insertion are unknown. Using biological assays and molecular dynamics studies, we have determined the functional configurations of FP-Ca2+ binding that likely promote membrane insertion. We first individually mutated the negatively charged residues in the SARS CoV-1 FP to assay their roles in cell entry and syncytia formation, finding that charge loss in the D802A or D830A mutants greatly reduced syncytia formation and pseudoparticle transduction of VeroE6 cells. Interestingly, one mutation (D812A) led to a modest increase in cell transduction, further indicating that FP function likely depends on calcium binding at specific residues and in specific combinations. To interpret these results mechanistically and identify specific modes of FP-Ca2+ binding that modulate membrane insertion, we performed molecular dynamics simulations of the SARS-CoV-1 FP and Ca2+ions. The preferred residue pairs for Ca2+ binding we identified (E801/D802, E801/D830, and D812/E821) include the two residues found to be essential for S function in our biological studies (D802 and D830). The three preferred Ca2+ binding pairs were also predicted to promote FP membrane insertion. We also identified a Ca2+ binding pair (E821/D825) predicted to inhibit FP membrane insertion. We then carried out simulations in the presence of membranes and found that binding of Ca2+ to SARS-CoV-1 FP residue pairs E801/D802 and D812/E821 facilitates membrane insertion by enabling the peptide to adopt conformations that shield the negative charges of the FP to reduce repulsion by the membrane phospholipid headgroups. This calcium binding mode also optimally positions the hydrophobic LLF region of the FP for membrane penetration. Conversely, Ca2+ binding to the FP E801/D802 and D821/D825 pairs eliminates the negative charge screening and instead creates a repulsive negative charge that hinders membrane penetration of the LLF motif. These computational results, taken together with our biological studies, provide an improved and nuanced mechanistic understanding of the dymanics of SARS-CoV-1 calcium binding and their potential effects on host cell entry.

  PublisherOA PDFDOI

• Perspective from Effects of Tobacco Smoke on Gene Expression and Cellular Pathways in a Cellular Model of Oral Leukoplakia

  2023-04-03

  preprintOpen accessSenior author

  Perspective from Effects of Tobacco Smoke on Gene Expression and Cellular Pathways in a Cellular Model of Oral Leukoplakia

  PublisherDOI

• Revealing the allosteric mechanism of pH-dependence in the proton-activated chloride channel

  Biophysical Journal · 2023-02-01

  articleOpen accessSenior author
  PublisherOA PDFDOI

Recent grants

• NIH Grant R01DA006620

  NIH · $1.6M · 1996

• NIH Grant R01DA015170

  NIH · $2.8M · 2015

• BIGDATA: IA: Collaborative Research: In Situ Data Analytics for Next Generation Molecular Dynamics Workflows

  NSF · $547k · 2017–2023

• Ca2+-dependent lipid scrambling and ion transport by TMEM16 proteins

  NIH · $4.3M · 2014–2024

• NIH Grant P01DA012923

  NIH · $14.9M · 2013

Frequent coauthors

• George Khelashvili

  Cornell University

  141 shared

• Jonathan A. Javitch

  New York State Psychiatric Institute

  110 shared

• Roman Osman

  Icahn School of Medicine at Mount Sinai

  81 shared

• Lei Shi

  National Institutes of Health

  80 shared

• Jack Peter Green

  Icahn School of Medicine at Mount Sinai

  52 shared

• Saul Maayani

  City University of New York

  50 shared

• Matthias Quick

  Columbia University Irving Medical Center

  48 shared

• Michael V. Levine

  Cornell University

  46 shared

Awards & honors

• elected to the Executive Board of the International Society…
• President of the Biophysical Society in 2008
• President of the International Society for Quantum Biology a…