Your browser is unsupported

We recommend using the latest version of IE11, Edge, Chrome, Firefox or Safari.

Nov 13 2023

11/13 – David Minh, Illinois Institute of Technology

CBQB Seminar (in-person event)

November 13, 2023

12:00 PM - 1:00 PM


CBQB Seminar in COMRB 8175


909 S Wolcott Ave, Chicago, IL 60612

This is an in-person event in room COMRB 8175 on west campus (directions).  You can also watch seminar live here>>


David Minh, PhD
Robert E. Frey, Jr. Endowed Chair in Chemistry
Associate Professor, Department of Chemistry
Associate Director, Center for Interdisciplinary Scientific Computation
Illinois Institute of Technology


Topic 1: Energy-Preserving Auto-Encoding and Decoding of Atomistic Protein Structure


Auto-Encoding and Decoding Neural Networks (AE) have the potential to be applied to ensembles of molecular structures to compress data and to enhance sampling. We constructed AE with various numbers of latent dimensions to encode protein structures into a low dimensional space and subsequently decode to a varied protein structure output. The AE was trained to minimize the structural (root mean square deviation) and potential energy differences between the given input and the resultant varied output. The number of latent dimensions necessary to accurately reconstruct the ensemble observed in MD simulations of deca-alanine and crambin was analyzed. While small numbers of latent dimension lead to a decoded ensemble with low variance, increasing the latent dimension leads to progressively more accurate ensemble reconstruction. A Gaussian mixture model was fit to the latent space. Remarkably, decoded structures from the Gaussian mixture model had similar energies to the original Boltzmann distribution.

Topic 2: Enzyme kinetic model for the coronavirus main protease including dimerization and ligand binding

The coronavirus main protease (MPro) is an essential enzyme in the viral life cycle and the target of antivirals recently developed against SARS-CoV-2. Across coronavirus family members, MPro is an obligate dimer. However, compared to MPro from other coronaviruses such as SARS CoV, Middle Easterrn Respiratory Syndrome (MERS) CoV MPro has a weaker dimerization affinity and is often monomeric under biochemical assay conditions (which are not likely representative of the conditions relevant to antiviral therapy in infected cells). Because ligand binding increases dimerization, addition of ligands appears to enhance enzyme activity at low concentrations before reducing it at higher concentrations. This behavior has been observed not only in biochemical assays for MERS MPro (1), but also for SARS-CoV-2 MPro with weakened dimerization (2). Unfortunately, there are no published biochemical models that quantitatively fit to these non-monotonic concentration response curves. In the recent scientific literature, these data have been presented without a model fit (1,2). Without such fitting, it is impossible to use biochemical assays to predict the behavior of the compounds in cellular models and in the clinic. Thus, we have developed an enzyme kinetic model that incorporates dimerization and ligand binding. Bayesian regression was used to perform a global fit of the model to all the published data in Nashed et al (2). We also performed a sensitivity analysis to determine conditions under which concentration response exhibit apparent cooperative behavior, as has been observed in several published studies.


UIC Biomedical Engineering

Date posted

Oct 20, 2023

Date updated

Jan 2, 2024