Predicting material properties with the help of machine learning A central goal of computational physics and chemistry is to predict material properties using first-principles methods based on the fundamental laws of quantum mechanics. However, the high computational costs of these methods typically prevent rigorous predictions of macroscopic quantities at finite temperatures, such as chemical potential, […]
Molecules in quantum motion In order to fully understand the nature of chemical reactions and molecular properties, we need to simulate both the electronic and vibrational motion quantum mechanically. However, simulations of quantum many body systems, such as molecules, scale exponentially with system size. I will explain how to tame this ‘curse of dimensionality’ by […]
“ Exploring Metalloenzymes for Therapeutics and Sustainable Catalysis” Abstract: Metalloenzymes are at the heart of numerous biological processes ranging from respiration and photosynthesis to natural product biosynthesis. Research in the Bhagi-Damodaran lab focuses on investigating structure, function and reaction mechanisms of metalloenzymes, and developing rational approaches to modulate their biological activities. Drawing from the core […]
Abstract: Primary and secondary mutations in anaplastic lymphoma kinase (ALK) are oncogenic. Insights into ALK acquired resistance were used to define a drug design strategy that led to the discovery of lorlatinib (Lorbrena; PF-06463922), a novel ATP-competitive macrocyclic inhibitor of ALK and ROS1 kinases. Structure based drug design, lipophilic efficiency and physicochemical property-based optimization provided […]
"Switches, sensors, and new shapes: from design of new functions to cellular consequences of allostery"
“Multidisciplinary (mission directed) research in nanotechnology at the University of Sydney”
"Structural Evidence for Dynamic Nitrogenase Metalloclusters" Abstract: Nitrogenase catalyzes dinitrogen reduction to ammonia and is the only enzyme capable of supplying the world with a reduced form of ‘N’ that can be directly incorporated into biomolecules such as DNA and proteins. The most well-studied nitrogenase, molybdenum nitrogenase, consists of two component proteins, the Fe protein […]
Abstract: SARS-CoV2, the causative agent of the COVID-19 pandemic, is an RNA virus that has efficient human to human transmission and carries significant morbidity and mortality for vulnerable patient populations. Remdesivir (Veklury®) is a broad-spectrum inhibitor of RNA viruses and the first agent to be approved for the treatment of COVID-19. The seminar will introduce […]
"Metabolic control of post-translational modifications"
First-Principles Materials Prediction: From Sustainability to the Quantum Information Age Theory-guided materials design is vital to the advancement of sustainability and quantum information science. First-principles theory entirely based on quantum mechanics without prior input parameters is the perfect tool. In order to reliably predict exotic quantum materials and out-of-equilibrium processes, many-body physics and quantum kinetic […]
The NSF Center for Integrated Catalysis is delighted to announce that it will be hosting a monthly webinar series. The next webinar of this series will be held on Tuesday, February 9th, 2021 at 1:00 PM. We are pleased to invite all students, postdocs, faculty, and staff.
