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X-WR-CALNAME:Computational Biology Seminar - Dr. Peng Tao
X-WR-TIMEZONE:Central Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260816T130020Z
UID:tag:localist.com\,2008:EventInstance_47871306065136
DTSTART:20241104T170000Z
DTEND:20241104T180000Z
DESCRIPTION:Talk title: Interrogating proteins as molecular machines aided 
 by machine learning\n\n \n\nSpeaker: Peng Tao\, PhD\nAssociate Professor\n
 Southern Methodist University\n\n \n\nAbstract: \n\nProtein molecules are 
 in constant motion yet perform their functions with remarkable specificity
  and accuracy. Computational modeling and simulation\, alongside experimen
 tal studies\, provide critical insights into the structure\, dynamics\, an
 d function of proteins. Recently\, machine learning has emerged as a power
 ful tool to advance biomolecular modeling and simulations. Our research ap
 plies these techniques to investigate two fundamental aspects of protein d
 ynamics and function. 1) One area of focus is allosteric proteins\, which 
 undergo shape and activity changes in response to molecule binding at allo
 steric sites\, transmitting structural changes across the protein to regul
 ate function through subtle conformational shifts. Using molecular dynamic
 s (MD) simulations\, we have developed computational methods to capture th
 e underlying mechanisms of protein allostery at an atomic level\, providin
 g a deeper understanding of this dynamic regulation. 2) Additionally\, we 
 explore enzyme catalysis\, where enzymes serve as molecular machines drivi
 ng essential biochemical reactions. Traditionally studied with quantum mec
 hanical/molecular mechanical (QM/MM) methods\, our work now uses machine l
 earning to investigate diverse enzyme-catalyst reaction landscapes. Recent
  efforts include machine learning models that predict acylation mechanisms
  for β-lactamase TEM-1 with benzylpenicillin and employ explainable AI (X
 AI) to gain mechanistic insights into Toho-1 β-lactamases with substrates
  like ampicillin and cefalexin. By integrating protein dynamics\, these mo
 dels uncover relationships between enzyme dynamics\, catalytic activity\, 
 and evolutionary traits through MD simulations. These two research avenues
  converge in our goal to create a unified framework that characterizes pro
 teins as dynamic molecular machines\, offering new insights into their fun
 ctional mechanisms.\n\n \n\nSpeaker Bio:\n\nDr. Peng Tao is an Associate P
 rofessor in the Department of Chemistry at Southern Methodist University (
 SMU)\, where he has been a faculty member since 2013. He earned his B.S. i
 n Chemistry (1998) and M.S. in Physical Chemistry (2001) from Peking Unive
 rsity\, China\, followed by a Ph.D. in Computational Chemistry from Ohio S
 tate University in 2007. Dr. Tao’s research focuses on developing comput
 ational methods to explore protein allostery and the evolution of protein 
 catalytic mechanisms. He also applies machine learning techniques to enhan
 ce the depth and efficiency of computational tools in studying biomolecule
 s as molecular machines. His work has attracted multiple federal research 
 grants\, including an NSF CAREER award to create a machine learning-based 
 theoretical framework for enzyme catalytic mechanism evolution. Dr. Tao is
  a recipient of the American Chemical Society OpenEye Junior Faculty Award
  and the Ralph E. Powe Junior Faculty Enhancement Award. He has authored 7
 8 peer-reviewed publications.\n\n \n\nHost:\nLauren McCormick\, PhD
GEO:32.820521;-96.842748
LOCATION:T. Boone Pickens Biomedical Building (ND)\, ND11.218
SUMMARY:Computational Biology Seminar - Dr. Peng Tao
URL;VALUE=URI:https://events.utsouthwestern.edu/event/computational-biology
 -seminar-dr-peng-tao
CATEGORIES:Academics & Co-Curricular
CATEGORIES:Research
CATEGORIES:Science & Technology
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