In animations developed by Mayo Clinic's Drug Discovery, Design and Optimization for Novel Therapeutics Laboratory, Dr. Caulfield's lab demonstrates algorithms used for structural biology, drug design and large conformational changes needed to understand biological processes that are important for probing behavior.

Protein behavior

  1. Uses simulations that include both long-standard runs and algorithms with enhanced sampling.
  2. Generates conformations of the enzyme, protein or complex that may not be available from static X-ray structure or other data sources, such as nuclear magnetic resonance (NMR) and cryogenic electron microscopy (cryo-EM).
  3. Visualizes dynamics changes of structures to reveal insights into protein function and behavior. Can newly identified structures be targeted using above methods?
  4. Leads, potentially, to new ideas on how to modulate the protein or enzyme behavior. For example, can we determine the genetic variant's intrinsic function as benign or pathogenic? Can we target this variant using above methods?
  5. Allows Maxwell's demon molecular dynamics (MdMD) algorithm to capture rare and hard-to-reach states for studying.

Cryo-EM Fitting

During cryo-EM fitting of crystal structure for tRNA into cryogenic-EM map for alternative conformation, MdMD is used for adaptive fitting into the new shape.

Shape Change Searchers

Apolipoprotein AI (Apo-AI) is a lipoprotein that forms a discoidal shape during lipid transport. The model hypothesis for the double belt structure needs advanced simulations to explain the Paris and Milano mutations. MdMD is used to accelerate the transition.

Small molecule therapeutics program (virtual to actual screening)

  1. Discovery Phase 1; Hit Identification Phase 2; Hit Validation to establish structure-activity relationships.
  2. Design Implementation (parallel to sister analogs), such as scanning around chem-space for 3D quantitative structure-activity relationship (3D-QSAR) and potential pharmacophores for new classes of lead compounds.
  3. Analyze the generated de novo drugs and continue to optimize these candidate drugs, which generates intellectual property when the results have high potency and efficacy.
  4. Quantum docking allows us to focus in on top leads for final modifications. See Quantum Docking animation.

Quantum Docking

qDockMdMD is shown for a new lead compound bound in DNMT3B, which can be probed using this method to get highly accurate binding modes suitable for lead optimization of new drugs.

Protein-protein modeling (biologics)

  1. Categorized as a kind of docking technique, which we can use MdMD for as well.
  2. Useful for determining protein-protein interfaces, such as ubiquitin (UB) ligase Parkin or PTEN-induced putative kinase protein 1 (PINK1). See Parkin MdMD animation.
  3. Can help generate mutagenesis predictions for actual bench-top testing thereby reducing cost and amount of required bench tests needed to get same or better result. Speed is key!
  4. This can be a precursor to a small molecule screening campaign or to a biologics approach or to better understand protein engineering. See Mesotrypsin-APPI Dynamics animation.

Parkin MdMD

Multiple parallel simulations using MdMD for the release of Parkin's ubiquitin-like (UBL) domain into the unrepressed (or active) state allows ubiquitin-conjugating (E2) enzyme to bind and catalyze transfer of ubiquitin to Parkin's catalytic cysteine residue (Cys431) via a thioester bond. This opening allows probing essential conformation of Parkin for druggability and launching a virtual-to-actual drug screening agenda.

Mesotrypsin-APPI Dynamics

Staged-biasing movement of mesotrypsin between crystallized conformation is shown with amyloid precursor protein inhibitor (APPI) bound and a predicted conformation from amyloid precursor-like protein 2 (APLP2).