Conference 2024

The 2024 annual MERCURY Conference for undergraduate computational chemistry will be held the week of July 15, 2024. MERCURY is delighted to have Hrant Hratchian, Dean for Graduate Education at the University of California at Merced hosting the meeting on the campus of UC Merced in Merced, California. As usual, we will have six outstanding speakers, an undergraduate poster session and evening social networking events. The conference will be preceded by a MOLSSI workshop. The conference is an excellent forum for undergraduates to present their work and to learn from experts in the field, allowing them to put their own research into perspective. It is equally valuable as a networking event for faculty working with undergraduates. Undergraduates from all types of institutions are invited to come present their work.

Speakers

Caitlin Bannan, OpenEye Scientific Software

Modeling small drug molecules and the winding career path that got me here


Daniel Crawford, Virginia Tech

The Mysteries of Chirality, Solvation, and Optical Activity.

The determination of the “handedness’” of chiral compounds remains a fascinating and critical challenge in which theory and computation play a vital role.  In the effort to assign the absolute stereochemical configurations of chiral isolates, quantum chemical models have the potential to provide experimentalists with robust predictions of the requisite spectroscopic signatures, such as specific rotation, circular dichroism rotatory strengths, Raman scattering circular intensity differences, and more. 

However, such properties are among the most challenging to simulate because of their delicate dependence on a variety of intrinsic and extrinsic factors.  Solvent effects, for example, not only dramatically expand the complexity of the simulation, but can sometimes even alter the sign of the chiral response.  In this lecture, I will discuss recent efforts in my group toward the goal of developing reliable theoretical predictions of chiroptical properties, including the exploration of reduced-scaling methods, a variety of implicit and explicit solvation models, and even explicitly time-dependent quantum dynamics.


Giulia Palermo, UC Riverside 


Aurora Pribam-Jones, UC Merced

Stretching, Squeezing, Heating, Cooling: Using the Adiabatic Connection to Learn About Electronic Interaction

In this talk, I will provide a brief overview of thermal and ensemble density functional theories, starting from the ground-state version of DFT and noting how the theories are similar and where they must be different. I will then focus on the interplay between ensemble weightings, interaction strength, and density dependence in density functional theories, particularly in how they influence the adiabatic connection and its connection to fundamental properties of matter and their limits. I’ll close with some stories about how we use these tools to analyze the way electrons interact in different situations and tie these ideas back to the pursuit of fusion as an energy source and how to flip DFT on its head for a new perspective.

Introductory/pedagogical: DFT, Thermal DFT, Ensemble DFT

More recent work: DFT and Hartree-Fock, Thermal DFT, Ensemble DFT.


Dean Tantillo, UC Davis

Dynamic Effects on Organic Reactivity – Pathways to and from Discomfort

Computational studies highlighting the importance of accounting for dynamic effects on organic reactivity will be discussed, along with descriptions of the factors that led me – as an organic chemist – to pursue these projects.


Florentina Tofoleanu, Treeline Biosciences 

Computational approaches in early drug discovery: hit identification, hit-to-lead, and lead optimization

The development of new medicines starts when we learn of a biological target implicated in diseases and search for ways in which we can modulate its function. When the program focuses on small molecules as potential drug candidates, the process involves identifying chemical matter that has confirmed activity against the biological target (hits). We further investigate the hits to confirm that they are indeed active (hit-to-lead). The leads are then optimized for physico-chemical properties (solubility, permeability etc) and characterized (metabolism, toxicity) to be declared preclinical candidates. I will discuss how computational methods streamline each of these processes, such that the program can reach a preclinical candidate more efficiently.