Laboratory for Pharmacological Innovation

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isom lab @ the university of miami

 

pH regulation of cell signaling systems

 

structural and chemical informatics

 

computational drug discovery

 

cell-based drug discovery

 

synthetic biology

 

cell stress

 

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OUR RESEARCH FOCUS

PH REGULATION OF CELL SURFACE RECEPTORS

PH REGULATION OF G PROTEIN-COUPLED RECEPTORS

G protein-coupled receptors (GPCRs) are both the largest class of cell surface receptors in humans, and the receptor family most targeted by therapeutic drugs. Major efforts in the lab are focused on understanding  how  acidic pH changes regulate GPCR-drug interactions and signaling. Our objective is to identify GPCR-drug interactions (in)capable of endomembrane signaling, and (in)sensitive to disease-related acidosis.

PH REGULATION OF CELL SURFACE RECEPTORS

Our lab studies  proteins and cell-surface receptors that detect and transduce cellular signals. In certain biological scenarios—cancer, hypoxia, nutrient stress, inflammation, endocytosis—these signaling proteins encounter acidic conditions. Our lab uses experimental and computational approaches to understand how signaling proteins and their constituent networks are regulated by such  pH changes.

INFORMATICS & DRUG DISCOVERY

PROTEIN ELECTROINFORMATICS

The need for pH regulation of molecular, cellular, and physiological processes is wide-ranging, as it exists in all domains of life and viruses.  At the molecular level, pH changes act to regulate the structure, function, and interaction of proteins, RNA, DNA, lipids, metabolites, and drugs.      pH effects in  proteins, which are mediated by ionizable side chains and electrostatic forces, are difficult to predict from sequence and structure.  In the lab we develop informatics algorithms to address this challenge, and validate our findings at the lab bench using a variety of approaches.

STRUCTURAL AND CHEMICAL INFORMATICS

The discovery of new molecular therapeutics begins by searching for novel lead compounds. Building on the success of our algorithms for identifying pH sensitivities in proteins, we are developing new structure- and shape-based approaches for exploring new and unexpected areas of chemical space to predict new drug-like compounds. In the lab we test our predictions using cell-based (DCyFIRplex) and protein-based (fQCR) methods developed in our lab. Our unique ability to iteratively predict, validate, and refine our findings greatly expedites the discovery cycle.

CELL STRESS RESPONSES

PH REGULATION OF STRESS-RESPONSE SIGNALING NETWORKS

A surprising variety of conditions cause a significant drop in cellular pH, such as nutrient limitation, oxidative stress, and ischemia. Recent studies indicate that these acidic pH signals serve a cytoprotective function by mediating unexpected changes in cellular biochemistry and signaling. Examples include changes in the material properties of cytoplasm, and assembly of proteins into phase-separated macromolecular structures. We aim to identify the signaling cascades that regulate these processes.

PHASE-SEPARATED MACROMOLECULAR STRUCTURES

We are also interested in identifying proteins that are predisposed to assemble into phase-separated structures in response to pH changes.  This interest is an extension of our studies on protein electroinformatics. Our objective is to identify topological patterns of ionizable side chains that are characteristic of higher-order structures stimulated by pH stress. In the longer term, our goal is to use these insights to develop predictive approaches that assess the scope of assembly formation in proteomes.

Our major computational efforts in the lab are focused on mining protein structural information for actionable intelligence. We use computational geometry as our primary conceptual framework for identifying residue topologies that are predictive of protein function. We develop our own algorithms, primarily in Python, and use the incredible high performance computing infrastructure in place at the University of Miami to routinely undertake millions of calculations on thousands of protein structures.

Our major experimental efforts are organized to broadly support our computational research. We have a variety of protein- and cell-based assays in place for rapidly quantifying biochemical parameters such as protein stability, ligand and drug affinity, receptor-drug interactions, and changes in cellular pH. Our core experimental infrastructure comprises technologies that include a liquid handling robotic screening platform, highly sensitive microplate readers, and novel cell-based model systems.

COMPUTATIONAL OVERVIEW

EXPERIMENTAL OVERVIEW

OUR APPROACH COMBINES COMPUTATION & EXPERIMENT

RESEARCH TEAM

DAN ISOM, PH.D.

PRINCIPAL INVESTIGATOR

GRADUATE STUDENT

NICK KAPOLKA

DISOM at MIAMI.EDU

GRADUATE STUDENT

GEOFF TAGHON

GRADUATE STUDENT

JACOB ROWE

SENIOR RESEARCH ASSOCIATE

SANTIAGO VILAR, PH.D.

Dan began his undergraduate education pursuing a degree in fine art as a painting and sculpture major at the Cleveland Institute of Art, near where he was born and raised. After two years at CIA, Dan transitioned to a career in science, majoring in both Biochemistry and Chemistry at Case Western Reserve University, and earning his doctorate in Molecular Biophysics from Johns Hopkins University. Dan is currently a practicing molecular pharmacologist and biophysicist, systems and synthetic biologist, technologist, heavy CRISPR user, protein sequence- and structure-based informaticist, computational geometer, virtual screener, and python, medical, and graduate educator leading at talented and multidisciplinary research team at the University of Miami.

isom lab

ACTIONABLE INTELLIGENCE THRU INFORMATICS AND SCALABLE FUNCTIONAL ASSAYS