Investigating cellular pathways as druggable targets
Research in Dr. Caulfield's lab cuts across all areas of investigation at Mayo Clinic. Primarily through using in silico technologies, the lab employs techniques that aid with structural biology, cell biology, enzymology, protein engineering and nanodesign implementation.
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Novel quantum docking technology for drug design
Molecular positioning of a lead molecule for inhibition of the cancer target DNA methyltransferase 3 beta (DNMT3B) enzyme is shown as a result from quantum mechanics-based scoring while under the Maxwell's demon molecular dynamics (MdMD) algorithm called qDockMdMD. The lab's MdMD program is derived from a thought experiment proposed by James Clerk Maxwell, a 19th century physicist.
Insulin-degrading enzyme capture and release of insulin
Using the MdMD algorithm to complete simulations that rapidly sample dynamic conformational changes in the protein, we are able to determine how insulin-degrading enzyme (IDE) can degrade insulin and develop IDE inhibitors to alter insulin pathways.
Mayo Clinic's Drug Discovery, Design and Optimization for Novel Therapeutics Laboratory is led by Thomas Caulfield, Ph.D., and focuses on the molecular interactions and driving forces that enable biomolecular activities to be studied at the atomic level. This atomic-level knowledge guides interrogations of these interactions to alter cellular pathways.
A crucial step in druggability and drug engineering is understanding the cellular target's behavior. Typically, our cellular targets are proteins comprised of folded amino acid chains in complexes, which can be elucidated from multiple data sources, such as cryogenic electron microscopy (cryo-EM), X-ray crystallography and kinetics studies, that then enable us to dynamically model processes underlying change over time. This time factor is crucial to capturing the inherent behavior of the biomolecules. The lab also studies ribonucleic complexes and nanoparticle constructs.
Drug engineering aims to accelerate the benchtop phase of drug development, since our lab can rapidly test tens of 1000s to many millions of combinations of potential drug molecules rapidly and save our collaborators time and money, allowing us to propose intelligent hypotheses underlying the structure-function behavior we observe. The lab primarily applies our in silico approaches toward neurodegeneration, cancer biology and metabolic disorders. The Caulfield lab engages in collaborative endeavors with many departments, including neuroscience, cancer biology, neurosurgery, quantitative health sciences, clinical genomics, biochemistry and molecular biology, hematology-oncology, gastroenterology, infectious disease, and cardiology.
In some disease processes, the delicate balance between production, activation and inhibition of the proteins, enzymes, ribonucleic acids and other biomolecules are often disturbed, leading to disease progression. These various biomolecules then become our lab's targets for dissecting biomolecular behavior using simulations and in silico methods coupled with experimental feedback.
Related to this, the Drug Discovery, Design and Optimization for Novel Therapeutics Lab works with the Center for Individualized Medicine to aid in dissection of variants in disease related to genomics and personalized medicine. Dr. Caulfield works with the Precision Cancer Therapeutics (PCT) unit within the Center for Individualized Medicine to make novel anti-cancer agents in conjunction with participating laboratories.
The lab studies these targets for changes in functional behavior that comes as a consequence of structural changes in their 3D shape that occur over a 4D set of properties. This time propagation effect is observed in proteins when introducing mutagenic amino acids that deviate from the wild-type sequence. The outcome of the genetic variation (called a variant) can be an overactive or underactive enzyme or protein. This protein is part of a cellular pathway that can cause large changes to the system (organs, tissues and pathologies) resulting in cancers, for example. Part of the lab's mission is to find agents or compounds that can have a restorative effect on the pathway by either blocking or accelerating the protein or enzyme behavior to counter the effect from the variant.
Identification of altered interactions provides us with potentially useful therapeutic intervention gateways to probe, which may allow us to search for new candidate drugs suitable for preclinical studies. Ultimately, this may result in clinically relevant drugs for trials.
By studying the interactions between these targets and inhibitors or activators, our lab aspires to continue to design better de novo designed agents for use in a wide range of medicinal research areas, which includes neurodegeneration diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis (ALS) and others.
Research focus areas (at large)
Major goals of Mayo Clinic's Drug Discovery, Design and Optimization for Novel Therapeutics Lab led by Thomas Caulfield, Ph.D., are:
- Structurally determining the mechanistic drivers underlying diseases
- Investigating the pathogenicity or protective effects of genetic variants with the Center for Individualized Medicine for structural basis of missense mutation effect on translated protein products (protein informatics platform)
- Developing novel small-molecule, peptide-based or biologics therapeutics
Individual focus areas
- Ribosomopathies, frameshifting and ribosomal quality control mechanisms
- Variants of uncertain significance categorizations — pathogenicity versus benign
- SARS-CoV-2 (COVID-19) multidrug high-throughput screening in collaboration with Harvard University and the University of California (see related publication)
- Methods development — quantum-based adaptive docking using Maxwell's demon molecular dynamics (MdMD)
To accomplish these goals, Dr. Caulfield's research team brings together multidisciplinary and translational approaches. Through combining structural, molecular, cellular and biochemical outputs from various laboratories, complex decisions are driven by context integrated from multiple data sources, such as high-content imaging to X-ray crystallography, to cryo-EM data, to dose response curves (DRCs) and kill assays for EC50s/IC50s. The resulting data fusion assimilates all of these data into various adaptive learning algorithms.
The lab's multiomics approach brings aboard organ-on-a-chip and animal modeling through collaborations that feed back into both ligand-based and structure-based drug design.
Functional studies with collaborators allow us to do virtual-to-actual screening in rapid rotation for delivery of customizable high-confidence libraries for testing hypotheses and mechanistic validation. Our 3D quantitative structure-activity relationship (3D-QSAR) methodology when combined with our machine learning and data layering allows for transformative de novo drug generation that takes labs from hits to leads and leads through optimization. Further progress continues before and during preclinical stages by the formation of early-stage companies (series A-C) and continues with the drug development of pharmacokinetic-pharmacodynamic (Pk-Pd) models, ADMET (absorption, distribution, metabolism and excretion toxicity) testing and more.
Dr. Caulfield and his team strive to contribute to improving the druggability of novel targets and obtaining de novo drug treatments for people with neurodegenerative diseases, metabolic diseases and cancers.
About Dr. Caulfield
Thomas Caulfield, Ph.D., is an associate professor of neuroscience at Mayo Clinic College of Medicine and Science in Jacksonville, Florida. Dr. Caulfield also holds appointments in the cancer biology, neurologic surgery, quantitative health sciences (computational biology), clinical genomics, and biochemistry and molecular biology departments. With a research background in biophysics, biochemistry, medicinal chemistry, structural biology and computational sciences, Dr. Caulfield's long-term focus is on generating novel therapeutics for metabolic, cancer and neurological disease targets and improving the potency and specificity of therapeutics.