Lecturers

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Organizers
Stochastic Gene Regulation

Lecturers teaching this course include:

Cell Signaling

Lecturers teaching this course include:

Cancer Dynamics

Lecturers teaching this course include:

Computational Synthetic Biology: Cells, Communities and Living Matter

Lecturers teaching this course include:

Example of Past Lectures

2015

2016

Braun.

Brian Munsky

 

 

 

About Rosemary Braun 

About Rosemary Braun 

Rosemary Braun is a computational biologist with an interest in the development of methods for integrative, systems-level analysis of high-dimensional ("big") *omic data. These methods incorporate bioinformatic information with experimental data to characterize the networks of interactions that lead to the emergence of complex phenotypes, particularly cancers.  Dr. Braun is an Assistant Professor of Biostatistics (Feinberg School of Medicine) and Engineering Sciences & Applied Mathematics at Northwestern University.

Hlavacek.

Brian Munsky

 

 

 

About William S. Hlavacek  

About William S. Hlavacek  

Marek Kimmel.

Brian Munsky

 

 

 

About Marek Kimmel 

About Marek Kimmel 

Brian Munsky.

Brian Munsky

 

 

 

About Brian Munsky Abstract

About Brian Munsky

Dr. Munsky joined the Department of Chemical and Biological Engineering and the School of Biomedical Engineering as an assistant professor in January of 2014. He received B.S. and M.S. degrees in Aerospace Engineering from the Pennsylvania State University in 2000 and 2002, respectively, and his Ph.D. in Mechanical Engineering from the University of California at Santa Barbara in 2008. Following his graduate studies, Dr. Munsky worked at the Los Alamos National Laboratory — as a Director’s Postdoctoral Fellow (2008-2010), as a Richard P. Feynman Distinguished Postdoctoral Fellow in Theory and Computing (2010-2013), and as a Staff Scientist (2013). Dr. Munsky is best known for his discovery of Finite State Projection algorithm, which has enabled the efficient study of probability distribution dynamics for stochastic gene regulatory networks. Dr. Munsky’s research interests at CSU are in the integration of stochastic models with single-cell experiments to identify predictive models of gene regulatory systems. He was the recipient of the 2008 UCSB Department of Mechanical Engineering best Ph.D. Dissertation award, the 2010 Leon Heller Postdoctoral Publication Prize and the 2012 LANL Postdoc Distinguished Performance Award for his work in this topic. Dr. Munsky is the contact organizer of the internationally recognized, NIH-funded q-bio summer school, where he runs single-cell stochastic gene regulation (q-bio.org). Dr. Munsky is very excited about the future of quantitative biology, and he would love to talk about this with you!

Abstract

Stochastic fluctuations can cause identical cells or individual molecules to exhibit wildly different behaviors. Often labeled "noise," these fluctuations are frequently considered a nuisance that compromises cellular responses, complicates modeling, makes predictive understanding and control all but impossible. However, if we examine fluctuations more closely and match them to discrete stochastic analyses, we discover virtually untapped, yet powerful sources of information and opportunities. In this talk, I will present our collaborative endeavors to integrate single-cell and single-molecule experiments with precise stochastic analyses to gain new insight and quantitatively predictive understanding for signal-activated gene regulation. I will explain how we experimentally quantify transcription dynamics at high temporal and spatial resolutions; how we use precise computational analyses to model this data and efficiently infer biological mechanisms and parameters; how we predict and evaluate the extent to which model constraints (i.e., data) and uncertainty (i.e., model complexity) contribute to our understanding. I will finish with the discussion of new opportunities in which noise analysis not only helps us to better understand gene regulation phenomena, but where it actually introduces new opportunities to precisely control these phenomena.

Ashok Prasad.

Brian Munsky

 

 

 

About Ashok Prasad 

About Ashok Prasad 

Ashok Prasad is an Associate Professor in the Department of Chemical and Biological Engineering at Colorado State University in Fort Collins.  Dr. Prasad has had a somewhat unusual career path. After initially doing physics, he moved to Economics and graduated with an MA in 1987 after which he spent the next 14 years teaching economics in an undergraduate college of Delhi University in India. However his childhood dream of becoming a scientist never quite left him, and he finally decided to go back to it. In 2001 he left his tenured job and came to Brandeis University to do a PhD in physics at the age of 37. He did a  PhD, with Jane'  Kondev as adviser, in soft matter theory in 2006. While at Brandeis he fell in love with Biology, and after his PhD he joined the lab of Arup Chakraborty at MIT as a postdoc from 2006-08, where he worked on modeling the activation of T cells. He joined Colorado State University as an Assistant Professor in the Chemical and Biological Engineering department in 2009. His research interests are diverse, and his group currently studies the determination of cell shape, the theoretical properties of signaling and gene transcription networks, helps develop plant synthetic biology, looks for signatures of drug susceptibility in gene expression of cancer cells using big data and artificial intelligence approaches and does genome scale metabolic modeling of cyanobacteria.  

Douglas Shepherd.

Brian Munsky

 

 

 

About Douglas Shepherd 

About Douglas Shepherd 

Dr. Shepherd is an Assistant Professor in the Departments of Physics and Pediatrics at the University of Colorado Denver. He received his B.S. in Physics from University of California Santa Barbara in 2003 and his Ph.D. in Physics from Colorado State University in 2011. He was a postdoctoral scholar at Los Alamos National Laboratory from 2011-2013 in the Center for Integrated Nanotechnologies and Center for Nonlinear Studies. His interests are in developing and applying new fluorescent microscopy techniques, data processing algorithms, and statistical modeling tools to study single-cell heterogeneity in cellular decision-making processes. He has been involved in the q-Bio Summer School since 2011, including starting the Membrane Dynamics track and serving as co-organizer for the Single Cell Gene Regulation track.

Patrick Shipman.

Brian Munsky

 

 

 

About Patrick Shipman 

About Patrick Shipman 

Patrick Shipman is an Associate Professor of Mathematics at Colorado State University. He earned his PhD in Mathematics at The University of Arizona in 2008, applying the modern theory of pattern formation and ideas from number theory to understand how biochemical and biomechanical mechanisms interact to form patterns, such as Fibonacci spirals, on plants. He was an NSF postdoc at the Max-Planck Institute for Mathematics in the Sciences, in Leipzig, Germany and at the University of Maryland-College Park. His current research interests include nanoscale pattern formation, topological data analysis, and models of nucleation and growth.

Sabrina Spencer.

Brian Munsky

 

 

 

About Sabrina Spencer 

About Sabrina Spencer 

Research in my lab is focused on understanding how signaling events control cell fate. Studying these processes in single cells reveals remarkable cell-to-cell variability in response to stimuli, even among genetically identical cells in a uniform environment. We seek to understand the sources and consequences of this heterogeneity in the cellular response to stimuli. The stimuli we study include growth factors, cell stress, and targeted cancer therapeutics. To do this, we develop genetically encoded fluorescent sensors for signaling events of interest. We then use long-term live-cell microscopy and cell tracking to quantify the dynamics of upstream signals and link them to cell fate (proliferation, quiescence, apoptosis, differentiation). Our long-term goal is to understand the normal mechanistic functioning of signaling pathways that control proliferation, to understand how these signals go awry in cancer, and eventually to alter the fate of individual cells.

Lev Tsimring.

Brian Munsky

 

 

 

About Lev Tsimring 

About Lev Tsimring 

Lev Tsimring is a theoretical and computational physicist who has worked in a number of fields including nonlinear dynamics, chaos, synchronization, pattern formation, granular physics, and in the last 10 years, biological physics and quantitative systems biology. He started his scientific career at the Institute of Applied Physics of the Russian Academy of Sciences, and moved to the University of California, San Diego, in 1992 where he remained ever since. His main focus currently is developing and validating quantitative dynamical models of gene regulatory networks, signaling pathways, and multicellular communities. Lev Tsimring is an Associate Director of the BioCircuits Institute at UCSD. He is a Fellow of American Physical Society.

Matthew Bennett.

Brian Munsky

 

 

 

About Matthew Bennett 

About Matthew Bennett 

Matthew R. Bennett is an associate professor in the Departments of Biosciences and Bioengineering at Rice University. He received is PhD in physics at Georgia Tech, where he studied nonlinear dynamics and non-equilibrium statistical physics. He began working in synthetic biology as a postdoctoral fellow in the Department of Bioengineering at the UC San Diego. Dr. Bennett’s current research spans the boundary between experimental and theoretical synthetic biology. He is particularly interested in the dynamics of gene regulation – from small-scale interactions such as transcription and translation, to the large-scale dynamics of gene networks and synthetic microbial consortia. His lab uses an interdisciplinary approach to 1) uncover the underlying design principles governing gene networks and microbial consortia, 2) engineer novel synthetic gene circuits for practical applications, and 3) develop new mathematical tools to better describe gene networks. The ultimate goal of his research is to develop synthetic multicellular systems for biomedical and environmental applications.

Meredith Betterton.

Brian Munsky

 

 

 

About Meredith Betterton 

About Meredith Betterton 

Moumita Das.

Brian Munsky

 

 

 

About Moumita Das 

About Moumita Das 

Dr. Moumita Das is a theoretical soft condensed matter matter and biological physicist, and an Assistant Professor of Physics at RIT. She obtained her PhD degree in Physics from the Indian Institute of Science Bangalore, and did postdocs at Harvard University, University of California Los Angeles, and Vrije Universiteit Universiteit, Amsterdam, The Netherlands. Her current research focuses on mechanobiology of biological cells and tissues, including how mechanical information is transmitted from molecular to cellular to tissue scales. Her research group uses a combination of analytical theory and computer simulations to investigate, understand, and predict emergent behavior in cells and tissues based on the interplay of structure, mechanics, and statistical physics of underlying components. She is a Fellow of the Scialog: Molecules Come to Life program, and her ongoing research is funded by the Research Corporation, Moore Foundation, and National Science Foundation.

Jame R. Faeder.

Brian Munsky

 

 

 

About James R. Faeder 

About James R. Faeder 

James R. Faeder is Associate Professor of Computational and Systems Biology at the University of Pittsburgh School of Medicine. He is also Co-Director of the Joint Carnegie Mellon--University of Pittsburgh PhD Program in Computational Biology and Department Vice Chair for Educational Programs. His research focuses on computational modeling of cell regulatory networks. His research combines development of novel methodologies with applications to specific systems of biological and biomedical relevance, including the immune system and cancer. He collaborates actively with experimental scientists both within the University of Pittsburgh as well as nationally and internationally. His work has been published in many high-profile journals including Science Signaling, Nature Methods, PLOS Computational Biology, and Bioinformatics. Dr. Faeder was a founding organizer of the well-known q-bio Conference on Cellular Information Processing, is a member of the Board of Reviewing Editors of Science Signaling, and has served as ad hoc member of numerous NIH study sections. For more see https://www.csb.pitt.edu/Faculty/Faeder/

Ryan N. Gutenkunst.

Brian Munsky

 

 

 

About Ryan N. Gutenkunst 

About Ryan N. Gutenkunst 

Prof. Ryan Gutenkunst studies the evolution of protein networks by integrating computational systems biology, population genetics, and molecular evolution. He received his Ph.D. in physics from Cornell University, where he worked with Jim Sethna on unveiling universal “sloppy” parameter sensitivities in systems biology models and on modeling their evolutionary implications. He then did a postdoc with Carlos Bustamante, where he developed ∂a∂i, a powerful method for inferring population histories from genomic data. His second postdoc was with Byron Goldstein at Los Alamos National Lab, where Ryan modeled aspects of immune signaling in mast cells. He is now faculty in the Department of Molecular and Cellular Biology at the University of Arizona. There his group has recently integrated systems biology models with comparative genomic data to reveal purifying selection on network dynamics and developed novel methods for inferring selection from population genomic data. Outside of research, Ryan’s interests include hiking, skiing, and photography.

Steve Haase.

Brian Munsky

 

 

 

About Steve Haase 

About Steve Haase 

Steve Haase did his graduate work in Genetics at Stanford University and his postdoc at The Scripps Research Institute. He is currently an Associate Professor of Biology and the Director of the Program in Genetics and Genomics at Duke University. He was one of the original members of the Duke Center for Systems Biology and served as the Director of Graduate Studies for the Computational Biology and Bioinformatics graduate program. His research is focused on understanding the structure and function of gene regulatory networks that drive large periodic gene expression programs during cell division and development. He studies organisms ranging from budding yeast and humans, to the Plasmodium species that cause malaria.

Srividya Iyer-Biswas.

Brian Munsky

 

 

 

About Srividya Iyer-Biswas 

About Srividya Iyer-Biswas 

After obtaining a PhD in theoretical physics, Sri Iyer-Biswas transitioned to doing biophysics experiments and theory during her postdoc years. Currently, she is a member of faculty at the Department of Physics, Purdue University. Her lab uses experiments and theory to elucidate the physics of stochastic single-cell dynamics.

Katherine King.

Brian Munsky

 

 

 

About Katherine King 

About Katherine King 

Katherine Y. King MD PhD is an Assistant Professor of Pediatric Infectious Diseases at Baylor College of Medicine, where she is also part of the faculty for the Stem Cells and Regenerative Medicine Center and the Center for Cell and Gene Therapy. She received her MD and PhD degrees from Washington University in St. Louis in 2003 before completing her residency and fellowship training at Baylor College of Medicine where she has been on faculty since 2012. Dr. King has been the recipient of the March of Dimes Basil O’Connor Starter Scholar Award and the Aplastic Anemia and MDS International Foundation Liviya Anderson Award. In her mission to alleviate deaths from infectious diseases, her current research focuses on the molecular mechanisms by which inflammation damages blood and immune cell production by hematopoietic stem cells in the bone marrow. When she is not seeing patients at Texas Children’s Hospital or conducting research in the lab, Dr. King enjoys running, yoga, and volunteering her time for health care advocacy through the group Doctors for Change.

Natalia Komarova.

Brian Munsky

 

 

 

About Natalia Komarova 

About Natalia Komarova 

Diego Krapf.

Brian Munsky

 

 

 

About Diego Krapf  Abstract

About Diego Krapf 

Prof. Krapf has a BS in Physics and MS and PhD in Applied Physics from the Hebrew University of Jerusalem. During his Ph.D. research he worked on infrared optics on nanostructured materials. Then, Dr. Krapf joined the research group of Prof. Cees Dekker in Delft University of Technology in the Netherlands where he focused on single-molecule biophysics using solid-state nanopores. Since August 2007, he serves as a faculty member in the Electrical and Computer Engineering Department at Colorado State University. Dr. Krapf is also associate professor in the School of Biomedical Engineering. His current research interests include cellular biophysics at the single-molecule level, with particular emphasis on membrane and cytoskeleton dynamics.

Abstract

DYNAMIC ORGANIZATION OF THE PLASMA MEMBRANE IN MAMMALIAN CELLS

Diego Krapf

Department of Electrical and Computer Engineering and School of Biomedical Engineering, Colorado State University

Tracking individual proteins on the surface of live mammalian cells reveals complex dynamics involving anomalous diffusion and clustering into nanoscale domains. Theoretical models show that anomalous subdiffusion can be caused by different processes. By performing time series and ensemble analysis of extensive single-molecule tracking we show that two anomalous subdiffusion processes simultaneously coexist and only one of them is ergodic. Weak ergodicity breaking is found to be maintained by immobilization events that take place when the proteins are captured within clathrin-coated pits. Furthermore, using a combination of dynamic super-resolution imaging and single-particle tracking, we observe that the actin cytoskeleton introduces barriers leading to the compartmentalization of the plasma membrane and that proteins are transiently confined within actin domains. Our results show that the actin-induced compartments are scale free and that the actin cortex forms a self-similar fractal structure.

 

 

 

Herbie Levine.

Brian Munsky

 

 

 

About Herbie Levine 

About Herbie Levine 

Francis Motta.

Brian Munsky

 

 

 

About Francis Motta 

About Francis Motta 

Francis C. Motta received his Ph.D. from Colorado State University in 2014.  He now lives with his wife, Jordan, and mini Dachshund, Einstein, in Durham, NC where he is a visiting assistant professor at Duke University.  His research interests include computational biology, pattern formation, and applications of computational topology to the study of dynamical systems.

Gerry Ostheimer.

Brian Munsky

 

 

 

About Gerry Ostheimer  Abstract

About Gerry Ostheimer 

Sustainable Energy for All is a global initiative that works to achieve universal access to sustainable energy, as a means to a cleaner, more just, and more prosperous world for all.

Dr. Ostheimer supports the Sustainable Energy for All Initiative by serving as the Global Lead for the Sustainable Bioenergy.

Working with diverse international partners, like the UN Food and Agriculture Organization and the International Renewable Energy Agency, he promotes the development and deployment of sustainable bioenergy solutions thru

  • Knowledge Sharing;
  • Policy Support; and
  • Deployment Support.

In collaboration with the World Business Council for Sustainable Development Dr. Ostheimer co-founded below50, which works to deploy the world’s most sustainable Low Carbon Fuels.

Previously, Dr. Ostheimer served as a Science Advisor for the U.S. Department of Agriculture during which time he contributed to finalizing the Global Bioenergy Partnership Indicators of Sustainable Bioenergy Production and Use.

Dr. Ostheimer has a Ph.D. in Molecular Biology from the University of Oregon and did postdoctoral work in Cancer Systems Biology at MIT.

Abstract

Re-Enlightenment: Corrosive trends at the messy intersection of Science, Civics and Society - and what Scientists can do to strengthen the foundations of modernity.

Truthiness . . .  Alternative Facts . . .  Climate Change . . .  Vaccines . . . The War on Science . . .  March for Science . . .  March for Climate . . .

Science and Facts have been politicized and selectively used by politicians for decades, but recent proposals by the Trump Administration threaten to erode the bedrock of modernity, including the role of impartial evidence-based policy and the future ability of Science to benefit society.

To explore and address these challenges, I will

  • Introduce the history and state of Science Policy in the United States; including both, Policy for Science and Science for Policy;
  • Explore the War on Science being waged by actors across the political spectrum;
  • Explain why Citizens and Scientists need to engage the public andto educate policy makers on the proper role of science in creating a healthy and prosperous future; and

Show ways that advocacy-minded young scientists and enthusiastic citizens can take useful action NOW without morphing into science policy lobbyists

Steve Presse.

Brian Munsky

 

 

 

About Steve Presse 

About Steve Presse 

Steve went to McGill as an undergrad in Chemistry (2000-2003). He did his graduate work under the guidance of Bob Silbey at MIT in the area of Chemical Physics (2003-2008). He later turned to Biophysics for his postdoc with Ken Dill at UCSF (2008-2013). Steve’s research as Assistant Professor of Physics at IUPUI focused on statistical mechanical models of biological systems in addition to questions of inference and data analysis (2013-2016). Most recently, as Associate Professor of Physics and Chemistry at ASU (2017-), Steve is working in methods of nonparametric Bayesian analysis and has continued fluorescence experiments begun at IUPUI aimed at understanding bacterial predator-prey dynamics.

Michael Savageau.

Brian Munsky

 

 

 

About Michael Savageau 

About Michael Savageau 

Michael Savageau is a Distinguished Professor in the Departments of Microbiology & Molecular Genetics and Biomedical Engineering at The University of California Davis. He earned his Ph.D. from Stanford University (Ph.D.), and was a postdoctoral fellow at both UCLA and Stanford University prior to joining the faculty at The University of Michigan. Dr. Savageau initiated Michigan’s interdisciplinary training program in Cellular Biotechnology and its interdisciplinary Bioinformatics Program. He also chaired the Department of Microbiology & Immunology from 1992-2002 and was named the Nicolas Rashevsky Distinguished University Professor in 2002. After moving to the University of California Davis in 2003 he chaired the Department of Biomedical Engineering from 2003 to 2005. His honors include Guggenheim Fellow, Fulbright Senior Research Fellow, American Association for the Advancement of Science Fellow, American Institute for Medical and Biological Engineering Fellow, Institute of Electrical and Electronic Engineers Fellow, Moore Distinguished Scholar at the California Institute of Technology, Invited Scholar at the Institut des Hautes Études Scientifiques, 79th Josiah Willard Gibbs Lecturer for the American Mathematical Society, Stanislaw Ulam Distinguished Scholar Award from the Center for Non-Linear Studies, Los Alamos National Laboratory, Member of the US National Academy of Medicine, Honorary Doctor of Science, Universitat de Lleida, Spain, and The Michael A. Savageau Collegiate Professorship in Computational Medicine and Bioinformatics permanently endowed by the University of Michigan. He was Editor-in-Chief of Mathematical Biosciences from 1995 to 2005, and serves on advisory panels for the National Institutes of Health, the National Science Foundation, the Howard Hughes Medical Institute, the Keck Foundation, and the National Academies of Science. He lectures extensively in the US and abroad on his research, which is focused on biochemical systems theory with an emphasis on function, design and evolution of metabolic networks, signaling cascades, and gene circuitry.

Tim Stasevich.

Brian Munsky

 

 

 

About Tim Stasevich  Abstract

About Tim Stasevich 

Timothy J. Stasevich is an Assistant Professor in the Department of Biochemistry at Colorado State University (CSU). His lab uses a combination of advanced fluorescence microscopy, genetic engineering, and computational modeling to study the dynamics of gene regulation in living mammalian cells. Most recently, his lab has pioneered the imaging of real-time single mRNA translation dynamics in living cells1. Dr. Stasevich received his B.S. in Physics and Mathematics from the University of Michigan, Dearborn, and his Ph. D. in Physics from the University of Maryland, College Park. He transitioned into experimental biophysics as a post-doctoral research fellow in the laboratory of Dr. James G. McNally at the National Cancer Institute. During this time, he developed technology based on fluorescence microscopy to help establish gold-standard measurements of live-cell protein dynamics. Dr. Stasevich next moved to Osaka University, where he worked with Dr. Hiroshi Kimura as a Japan Society for the Promotion of Science Foreign Postdoctoral Research Fellow. While there, he helped create technology to image endogenous proteins and their post-translation modifications in vivo. This allowed him to image the live-cell dynamics of epigenetic histone modifications during gene activation for the first time2. Before joining the faculty at CSU, Dr. Stasevich took a one year hiatus at the HHMI Janelia Research Campus, where he further improved the spatio-temporal resolution of endogenous protein imaging in live-cells.

 

  1. Morisaki, T. et al. Real-time quantification of single RNA translation dynamics in living cells. Science 352, 1425–1429 (2016).
  2. Stasevich, T. J. et al. Regulation of RNA polymerase II activation by histone acetylation in single living cells. Nature 516, 272–275 (2014).

Abstract

We are developing technology to image single RNA translation dynamics in living cells. Using high-affinity antibody-based probes, multimerized epitope tags, and single molecule microscopy, we are able to visualize and quantify the emergence of nascent protein chains from single pre-marked RNA1. Here, I’ll describe this technology as well as a two color extension useful for comparing translation rates between two different parts of a single open reading frame (ORF) or two different ORFs. Using information from the correlations of fluorescence fluctuations, we can accurately quantify single mRNA translation elongation rates in both tagged and untagged portions of ORFs. By transiently loading probes and reporter DNA into cells in a combinatorial fashion, multiplexed imaging of gene expression is possible. Preliminary application of this technology to the study of viral frameshifting will be discussed.

  1. Morisaki, T. et al. Real-time quantification of single RNA translation dynamics in living cells. Science 352, 1425–1429 (2016).

Whelton Miller.

Brian Munsky

 

 

 

About Whelton Miller    Abstract Current Research

About Whelton Miller   

Whelton received a B.S. in Biochemistry from University of Delaware in 2001 where he worked under the supervision of Dr. Douglass F. Taber. After graduation, he took a job working in industry as a synthetic organic chemist for a pharmaceutical company. After over 3 years of industrial experience, he returned to school to complete a Ph.D. in Theoretical/Computational Chemistry from the University of the Sciences in Philadelphia in 2012. After graduate school, he was given a unique opportunity through the University of Pennsylvania's (Penn) - Postdoctoral Opportunities in Research and Teaching (PENN-PORT) program, an NIH sponsored, Institutional Research and Academic Career Development Award (IRACDA) postdoctoral fellowship 1. In addition to Whelton’s responsibilities through the Penn-PORT program, he served on the Biomedical Postdoctoral Council (BPC), as well as chair of the Engineering PostDoc Association (EpoD). He has worked closely with the Physician Scientist Training Program (PSTP) 2 as a mentor to a high school student, as well as a program guest speaker. This allowed Whelton to be a Postdoctoral Research Fellow in the Department of Bioengineering at Penn, as well as serve as a Visiting Professor in the Department of Chemistry at Lincoln University. After accepting a position at Lincoln University as an Assistant Professor, Whelton continues to work on collaborative research projects and include colleagues at, Los Alamos National Laboratory, Instituto Tecnológico de Santo Domingo, University of Pennsylvania, and University of the Sciences.

Abstract

Introduction to Biomolecular Simulations and Molecular Docking

Whelton Miller, Ph.D.

Molecular Modeling encompasses a wide collection of computational techniques, including visualization, transition state modeling, ab inito (Quantum Mechanics), and Molecular Dynamics (MD). These methods are now standard tools use by theoretical/computational chemists and biologists for predicting chemical structural properties of biomolecules. In this workshop, we will focus on medicinal chemistry, in particular rational drug design. One technique, molecular docking, is a computational procedure that attempts to predict non-covalent binding of small “drug-like” molecules (ligands) to larger macromolecules (receptors) – proteins in this case. The goal of molecular docking is to start with the unbound structures (ligands and receptors) and efficiently “dock” the ligand into the binding pocket of the receptor. This allows for the calculation of binding affinity, which is a measure of the ligand’s ability to non-covalently attach itself to a particular receptor. An underlying principle of molecular docking is that ligands with similar properties, such as lipophilicity or electrostatic potential via chemical similarity (e.g., shape), should have similar chemical or physical behavior with the same receptors. Therefore, the identification of compounds expected to be active against a given target can be justified.

Current Research

Whelton’s current research involves using computational chemistry techniques for theoretical design and study of organometallic and inorganic compounds, protein ligand interactions, and structural electronic effects. These calculations are used to identify and predict electronic-structural properties and interactions for molecular design.