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OpenEye Outstanding Junior Faculty Awards at ACS Fall Conference

OpenEye Outstanding Junior Faculty Awards at ACS Fall Conference

OpenEye Scientific is proud to grant four Outstanding Junior Faculty Awards at the Fall 2022 American Chemical Society (ACS) National Meeting, at the McCormick Place Convention Center in Chicago, Ill., August 21-25, 2022. In addition to the awards ceremony, OpenEye will give four presentations. Times and dates for the award ceremony and presentations are listed below. 


Outstanding Junior Faculty Award Details

OpenEye would like to congratulate the following winners of the ACS's Fall 2022 Outstanding Junior Faculty Award and the research they're presenting at the Fall ACS 2022 National Meeting: 

  • Kateri DuBayUniversity of Virginia, Department of Chemistry
    Modeling the self-templating and seeding of homopolymer blocks within a one-pot A,Bcopolymerization
  • Justin A. LemkulVirginia Tech, Department of Biochemistry 
    Electric Field Effects in DNA G-Quadruplexes Drive Ion Binding
  • Bryan Richard Goldsmith,University of Michigan, Department of Chemical Engineering
    Interpretable machine learning to elucidate structure-property relationships of catalysts and materials
  • Connor W. Coley, Massachusetts Institute of Technology, Department of Chemical Engineering
    Molecular Design from Virtual Screening to De Novo Generation with Models of Chemical Reactivity 

Sponsored by OpenEye, ACS's OpenEye Outstanding Junior Faculty Award is designed to recognize the work of excellent researchers and assist those newer faculty members in gaining visibility within the computational chemistry community.

The Fall 2022 Outstanding Junior Faculty award ceremony will occur on August 23, 2022, at the Comp Chemistry Poster session from 7 - 9 p.m. Central Daylight Time (CDT) in Hall F2 at the McCormick Place Convention Center. 

The awards will be presented by Caitlin Bannan, PhD, Scientific Software Developer II at OpenEye.

To find out more about the awards and how to apply, visit the OpenEye Outstanding Junior Faculty Award page on the ACS website.



Presentation Details

The OpenEye presentation titles, speakers, dates, locations, and abstracts are listed below.


Conformer generation for multi-component crystal structure prediction

Authors: Caitlin C. Bannan, Varsha Jain, Hari Muddana, Geoff Skillman

Date: Sunday, August 21, 2022, from 4:15 - 4:45 p.m.

Place: S401a - McCormick Place Convention Center 

Abstract: Understanding polymorph risk is an important part of the drug development process. Physical properties, including solubility, bioavailability, and hygroscopicity, can vary significantly with the solid form of the drug. OpenEye has previously presented our automated protocols for predicting small molecule crystal structures beginning with any representation of the molecule (e.g. SMILES string).  This process has four steps (1) generate a 3D conformer ensemble, (2) randomly pack conformers into crystal structures and optimize them with a force field, (3) QM optimize crystal structures and rank structures based on DFT enthalpy, and (4) calculate entropy and re-rank structures based on free energy. In this presentation, we will focus on steps 1 and 2 for multi-component crystal structures. Generating conformers for multi-component crystals requires sampling positions of two or more small molecules together. We generate possible multi-component conformations according to trends in experimental crystal structure databases and use physics-based methods to rank those conformers before packing. We show how this process can be used as an extension of step 1 to fit easily into our automated workflows for crystal structure prediction. These workflows will allow for polymorph risk assessment to include the formation of hydrates, salts, or co-crystals.


Crystal Structure Prediction: A Few Cases on Drug-Like Molecules

Speaker: Varsha Jain, PhD, Application Scientist, OpenEye 

Date: Sunday, August 21, 2022, from 4:15 - 4:30 p.m.

Place: S403a - McCormick Place Convention Center

Abstract: Crystal structure prediction (CSP) has become a powerful tool in the pharmaceutical industry to assess the crystal form landscape of drug molecules, and to assess the risk of polymorph discovery in formulation. Despite many successes in CSP, crystal structures of some small molecules remain challenging due to high strain of the conformer and poor accuracy of quantum methods for ranking relative stability of polymorphs. Usually, molecules in the crystalline state adopt low-strain conformers with a strain energy of <=3 kcal/mol. However, there is a small fraction of drug-like molecules which crystalize with higher torsional strain energy due to steric hinderance and intramolecular hydrogen bonding. On the other hand, DFT functionals that accurately rank many small molecule crystal structures, can perform poorly in some cases due to poor intramolecular conformational energies. The present study examines a few such challenging cases to demonstrate conformational preference and energetics of these drug-like molecules using dimer-expansion approach and possible ways to overcome through these challenges.


Exploring a Hyperparameter Optimization Strategy for Weighted Ensemble Molecular Dynamics in the Cloud

Authors: Daniel Zuckerman, David LeBard, Won Hee Ryu, John Russo, Jeff Thompson
Date: Sunday, August 21, 2022, from 9:20 - 9:40 a.m.
Place: S401bc - McCormick Place Convention Center
Abstract: Efficient sampling of the conformational space of biomolecular systems is a challenging problem with direct relevance to drug discovery research. Among the numerous enhanced sampling techniques that seek to address this challenge, the weighted ensemble (WE) method is attractive insofar as it is unbiased regardless of the chosen hyperparameters. The variance versus cost of WE-based estimates, however, depends strongly on the choices of hyperparameters. These choices include the way in which the conformational space is subdivided into “bins” and the allocation of trajectory walkers across these bins. Aristoff and Zuckerman recently proposed techniques for optimizing the choices of binning and walker allocation, given an observable whose steady-state average is to be computed. Here we describe our efforts to automate their hyperparameter optimization strategy within a workflow for performing weighted ensemble molecular dynamics simulations on the Orion cloud computing platform. We discuss preliminary applications of the optimized WE approach to estimate reaction rates in molecular systems of varying complexity. By developing a better understanding of how to apply the optimized WE approach to different pharmaceutically relevant systems, we hope to reduce the guesswork required to achieve efficient sampling in our large-scale WE simulations.

More details are available for ACS members at


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