Paul Robustelli

Academic Appointments
  • Assistant Professor of Chemistry

  • Neukom Cluster of Computational Science

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The Robustelli group develops and applies computational methods to obtain atomic-level descriptions of the functional motions of biomolecules, with a particular interest in intrinsically disordered proteins. 

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Burke 203
HB 6128


  • B.A. Pomona College 2002-2006
  • Ph.D. University of Cambridge (with Michele Vendruscolo) 2006-2010
  • NSF Postdoctoral Fellow, Columbia University (with Arthur G. Palmer III) 2010-2013
  • Scientist, D.E. Shaw Research 2013-2019

Selected Publications

  • Robustelli P, Piana S, Shaw DE. "The mechanism of coupled folding-upon-binding of an intrinsically disordered protein" Journal of the American Chemical Society (2020)

    Piana S*, Robustelli P*, Tan D,  Chen S, Shaw DE. "Development of a force field for the simulation of single-chain proteins and protein-protein complexes" Journal of Chemical Theory and Computation (2020)

    Robustelli P, Piana S, Shaw DE "Developing a molecular dynamics force field for both folded and disordered protein states." Proceedings of the National Academy of Sciences (2018) 115(21):E4758-E4766

    Piana S, Donchev AG, Robustelli P, Shaw DE. Water dispersion interactions strongly influence simulated structural properties of disordered protein states. The Journal of Physical Chemistry B. (2015) 119(16):5113-23

    Robustelli P, Stafford KA, Palmer III AG. Interpreting protein structural dynamics from NMR chemical shifts. Journal of the American Chemical Society. (2012), 134(14):6365-74 

    Neudecker P, Robustelli P, Cavalli A, Walsh P, Lundström P, Zarrine-Afsar A, Sharpe S, Vendruscolo M, Kay LE. "Structure of an intermediate state in protein folding and aggregation. Science. (2012) 336(6079):362-366

    C Camilloni, P Robustelli, AD Simone, A Cavalli, M Vendruscolo "Characterization of the conformational equilibrium between the two major substates of RNase A using NMR chemical shifts"  Journal of the American Chemical Society (2012) 134 (9), 3968-3971

    Robustelli P, Kohlhoff K, Cavalli A, Vendruscolo M. Using NMR chemical shifts as structural restraints in molecular dynamics simulations of proteins. Structure. (2010) 18(8):923-33 

Postdoctoral Research Fellow Position

The Robustelli Laboratory in the Dartmouth Department of Chemistry is searching for its first postdoctoral fellow.  As a charter member of the laboratory, this position will provide opportunities to make foundational contributions to our research directions, build a diverse and inclusive lab culture, and play an active role in the research mentorship of graduate students and undergraduate researchers.   

The Robustelli Laboratory is broadly interested in using atomistic molecular simulations to model the conformational dynamics and molecular recognition mechanisms of intrinsically disordered proteins.  We aim to use insights from simulations to understand, predict and ultimately design new dynamic and heterogeneous IDP binding interactions.  Current focuses of the laboratory include understanding the molecular mechanisms and diving forces of small molecules binding to IDPs, dissecting the intermolecular interactions that drive IDP phase separation and aggregation, and rationally designing small molecule and biologic IDP binders that modulate these processes.

We are seeking a candidate with experience developing and applying advanced molecular simulation techniques which may include, but are not limited to, one or more of the following areas: enhanced sampling algorithms, maximum-entropy methods, adaptive sampling strategies, markov-state models, dimensionality reduction, clustering methods, protein or small molecule force field parameterization, alchemical free-energy calculations, de novo protein/biologics design, de novo small molecule drug design. 

The ideal candidate has a fascination with intrinsically disordered protein biophysics, experience integrating molecular simulations and biophysical experiments, feels comfortable in high-dimensional spaces, and is interested in rational drug design.  Protein NMR experience (experimental or computational) is a plus. 

The computational methods of our group are tightly integrated with biophysical experiments, particularly from NMR spectroscopy, and opportunities exist to collaborate with experimental groups and/or conduct biophysical experiments in-house.  Our laboratory has access to excellent NMR facilities with high-throughput screening capabilities.

As initial funding for this position is coming from laboratory start-up funds, there is substantial freedom to develop projects of mutual interest spanning a broad range of research areas related to IDP simulations, IDP molecular recognition, IDP NMR, and IDP drug design.  Potential projects may include any combination of the following:

Enhanced Sampling Method Development

MD Analysis Methods (MSMs, Clustering, Dimensionality Reduction, Machine Learning)

Small Molecule/Biologic Inhibitor Design

Ensemble Based De Novo Design Algorithms

NMR Spectroscopy

Protein aggregation inhibition

Drugging biological condensates

Interested candidates should send an inquiry to, including a CV, a brief description of your research experience, interests and aspirations, and a note about the potential project/area that you find most interesting.  Examples of code you have written or a link to a GitHub page are encouraged.   There is substantial flexibility in potential start-dates and the length of the appointment.

About Dartmouth: Dartmouth College is private Ivy League Research University in Hanover, New Hampshire. The Dartmouth Department of Chemistry is a highly collaborative department which, in addition to traditional focus areas in biophysical chemistry, organic synthesis, materials chemistry, and inorganic chemistry, is currently establishing a growing community of computational chemistry scholars.  Dartmouth Chemistry is part of a broader biomedical research community at Dartmouth made up of labs across the Dartmouth Geisel School of Medicine, Institute for Biomolecular Targeting,  Molecular & Cellular Biology program and the Norris Cotton Cancer Center.

Hanover, New Hampshire is located along the Connecticut River on the border of New Hampshire and Vermont in the idyllic Upper Valley Region.  The Upper Valley is known for its scenic mountains, lakes, and rivers and its network of charming small towns.  The Upper Valley has a vibrant outdoor culture with extensive hiking, biking, and cross-country skiing trails, canoeing and kayaking, and proximity to a number of downhill skiing mountains.  Hanover is located 2-hours from Boston, MA, 1.5 hours from Burlington, VT, 2.5 hours from Portland Maine, and 3 hours from Montreal, Quebec.