Biochemistry Seminar: Lieyang (Eric) Chen, and Silas Hartley
https://zoom.us/j/4165865928
***The seminar originally scheduled for this date -- Harel Weinstein, Professor and Chairman, Physiology & Biophysics, Director, Institute for Computational Biomedicine, Weill Cornell Medical College of Cornell University, NY -- has been postponed and will be rescheduled for the 2020-2021 academic year.***
The following seminars will only be available remotely.
VIEW THIS SEMINAR LIVE VIA THE WEB AT:
https://zoom.us/j/4165865928
Lieyang (Eric) Chen, Ph.D. Student, Thomas Kurtzman group, Lehman College, will give a talk on "Advanced Computational Methodologies to Study Binding Free Eneregies of Protein-Ligand Complexes"
ABSTRACT: Machine learning has recently been applied to computational drug discovery after achieving remarkable success in image/voice recognition. However, the complexity of the protein-ligand binding interaction combined with issues inherent to current binding affinity databases make it a challenging task to develop reliable machine learning methods to predict ligand binding affinity. Here we will show how scientists are tricked by the machine-learning black box when developing such methods.
Silas Hartley, Ph.D. student, David Jeruzalmi group, City College, will give a talk on "DNA Damage Recognition and UvrB Loading by UvrA within the Nucleotide Excision Repair Pathway"
ABSTRACT: Nucleotide excision repair (NER) is a DNA damage repair pathway vital for cell survival. As part of the NER pathway, UvrA searches DNA until damages are found. Despite extensive research into the NER pathway, it remains unclear how UvrA recognizes damaged DNA. Our research presented an image of the UvrA-DNA complex post-damage recognition; an important step in understanding the UvrA-DNA damage recognition mechanism. Additionally, a UvrA-UvrB complex can search for damages. Our findings in the UvrA-UvrB damaged DNA search mechanism provide details into previous research that suggested the complex has an alternate DNA search mechanism then UvrA alone.