May 01, 2018:
Welcome to Dr. Tuguldur Togo Odbadrakh joins our group after finishing his PhD at University of Pittsburgh.

Feb 13, 2018:
Dr. Shields is named as a 2018 Cottrell Scholar TREE Award recipient.

July 20-23, 2017:
Our group hosted the 16th MERCURY conference at Furman

June 26, 2017:
Skylight is in full production.

March 13, 2017:
Dr. Temelso is named as a 2017 Foresight Fellow in Computational Chemistry.

Feb 3, 2017:
Dr. Shields gave an invited talk at UVA.

Dec 15, 2016:
ArbAlign, our tool for aligning molecules is made publicly available here.

Sept 01, 2016:
MERCURY consortium was awarded an NSF-MRI grant to purchase a new computer cluster.

August 01, 2016:
After six wonderful years at Bucknell, our group has moved to Furman.

July 21-23, 2016:
Our group hosted the 15th MERCURY conference

March 18, 2016:
Our collaboration on tunneling in water hexamers was published in Science. See the paper, and perspective piece and video describing its significance.

March 24, 2015:
Dr. Shields received the ACS Award for Research at an Undergraduate Institution in Denver, CO.

June 18, 2013:
The new MERCURY machine, Marcy arrived. See its wiki for details.

May 18, 2012:
Our collaborative work on water hexamers got published in Science




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Growth of Water Clusters

Water Clusters Of the more than 50 water models developed over the last 75 years, none of them have been able to reproduce all the anomalous and complex properties of water across all size, temperature and other regimes. While many try to model water universally starting with its bulk properties, we take a more ground up approach. Using molecular dynamics sampling and highly accurate quantum mechanical models, we are studying the structure and energetics of water clusters of sizes ranging from 2 to 10 molecules.

The aim is to locate the global and all relevant low lying local minima for each cluster. Our molecular dynamics sampling ensures that we have searched the large configurational space of hydrogen bonding networks available to the water clusters and extracted the lowest energy configurations. Our quantum mechanical method of choice, MP2 is the most affordable yet very accurate method for studying non-covalently bonded systems like water clusters. The interplay between energy and entropy, the shapes and hydrogen bonding networks of the clusters are used to explain the growth patterns of water clusters. Furthermore, we calculate cluster populations and nucleation rates using quantum mechanical energies, enthalpies, entropies and free energies and compared them with those found from experiment and classical nucleation theory.

From Gas Phase Clusters to Atmospheric Aerosols

growth growth

The growth of gas phase clusters into aerosols and eventually cloud particles and droplets is an area of active research. In particular, their significant but poorly understood role in global warming ( radiative forcing) has sparked much interest.

The goal of our research is to determine the minimum energy structures and the thermodynamics for formation of small gas phase clusters that will serve as cloud condensation nuclei (CCN). We determine the structures of all relevant (H2SO4)n(H2O)m , (HSO4-)n(H2O)m , and (SO42-)n(H2O)m for n=1-2 and m=1-10.

We establish the thermodynamics of formation for these complexes, and for their incorporation into aerosols, based on state-of-the-art model chemistry methods. Also, we determine the relevant abundances of these complexes, allowing us to assess their atmospheric importance. Finally, we use the thermodynamic and abundance data to model the nucleation of small aerosols throughout the troposphere, connecting our results with available experimental data.


Computational Design of Peptides for Breast Cancer Inhibition


Breast cancer is the most common cancer among women and Tamoxifen is the preferred drug for estrogen receptor-positive (ER+) breast cancer treatment. Many of these cancers are intrinsically resistant to Tamoxifen or acquire resistance to it during treatment. Consequently, there is ongoing need for breast cancer drugs that have different molecular targets and/or mechanisms.

Alpha-fetoprotein (AFP) is a protein produced by the fetal yolk sac and is presumed to act as a growth regulator during gestation. It is 591 amino acids long. It was discovered that high levels of circulating AFP in maternal serum decrease a woman’s risk of developing estrogen receptor positive (ER+) breast cancer later in life. It has recently been discovered that the peptide can be shortened to peptides as small as 4 amino acids long and still retain active breast cancer inhibition qualities. We have applied and demonstrated for the first time that replica exchange molecular dynamics (REMD) simulations can be used as a novel lead compound design tool. We have shown that a common conformation that is shared between the active linear 8-mer and cyclic 9-mer peptides of AFP is a conserved reverse beta-turn, and the smaller peptide analogs TOVNO, TPVNP, TOVN, and TPVN. These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, through interaction with a yet to be discovered key receptor, and inhibit human breast cancer in a mouse xenograft. In addition these molecules reduce the prevalence of breast cancer in rats injected with the carcinogen methyl nitroso urea.