Our research

Our scientific approach

Extensive research in last a few decades provided huge suppository of collected heterogeneous data from animal and human studies related to myopathies. The data were collected at different length scales spanning genetics, protein interactions and structure, and cell, tissue, and organ function. Most of the findings at any scale were directly connected to particular diseases, neglecting processes at different scales that can significantly distort outcome at organ function which has led to expensive and frequently unsuccessful development of new drugs and therapies.

 

However, understanding human disease requires recognition that human biological systems are inherently complex and hierarchical. Inferring disease pathophysiology from genetic defects thus requires a method for translating structural and functional abnormalities at the molecular scale into pathophysiology at the scale of the whole organ.

To address this fundamental problem, we have constructed an approach based on two pillars:

The development of a computational platform MUSICO which integrates knowledge of muscle structure and function across all spatial scales and thus provides a framework to portray the complete array of myocyte behavior.

The assembly of a broad based self-consistent dataset from the same species, muscle type and under matched experimental conditions at each hierarchical level.

This makes a comprehensive modeling approach capable of predicting genotypic modulation of function in a physiological context enabling, for the first time, study of the relationship between genotype and the onset of disease phenotypes of the whole organs such as the heart, lungs, or skeletal muscles. The outcome of this system can provide essential information for decision support systems, more efficient and far less expensive new drug development, and help develop more effective new therapies and monitoring systems for evaluating progression or regression of disease for a prescribed therapy.

Our research interests

Our main research interest is developing a tool for the quantitative analysis of structure-function relationship in muscle over multiple length scales. Inferring disease pathophysiology from molecular dysfunction we have developed the computational platform MUSICO (Muscle Simulation Code), to enable translating structural or functional abnormalities at the nanoscale into abnormalities at the scale of the organ and organ systems.

Inspired by new discoveries and initiated development of multiscale muscle models we have included myofilament extensibility, crossbidge kinetics, thin and thick filament regulation, and mesoscale orientation muscle fibers from diffusion spectrum magnetic resonance imaging. The MUSICO platform provides opportunities for applications in drug testing, personalized evaluation of patient’s loss of performance in myopathies or with age.

The flow patterns in tubular organs are modulated by the mechanical forces acting on airway or vessel walls and causing change in their size. In order to predict realistic behavior of tubular organs under dynamic loading conditions and in the presence of active muscle force we have developed a molecular model of smooth muscle (SM) contraction including the SM regulation by calcium. As an application of this computational model we have developed a computational model of airway narrowing.  These models could lead to future development of virtual lungs or other virtual tubular organs containing smooth muscle.

Developing new drugs for muscular disorders is a long and expensive process, which could cost a lot of human and animal lives. That is why we are interested in using our innovative MUSICO platform as an in-silico clinical trials solution for the effective and low-cost drug design and monitoring of the effectiveness of pharmacological treatment, with the aim to reduce the animal studies and the human clinical trials.

We have been working on tracing the effects of sarcomeric protein mutations leading to familial cardiomyopathy by developing a computational platform for in-silico clinical trials of FCMs that will take into consideration comprehensive list of patient specific features (genetic, biological, pharmacologic, clinical, imaging and patient specific cellular aspects). The platform will be capable of optimizing and testing medical treatment strategy with the purpose of maximizing positive therapeutic outcome, avoiding adverse effects, avoiding drug interactions, preventing sudden cardiac death, shortening time between the drug treatment commencement and the desired result.

For monitoring health improvement or disease progression in patients with a variety of neuromuscular disorders, ranging from amyotrophic lateral sclerosis to muscular dystrophy, the development or refining muscle assessment tools is necessary. We are interested in connecting muscle impedance measurements and the pathological characteristics of tissue. For example non-invasive impedance data that can be used to characterize muscle histology; impedance-based imaging systems for the real-time evaluation of muscle contractile properties; and development of effective electrical muscle stimulation technology to serve as a useful means to improving muscle condition and health.

Small-angle X-ray diffraction is the only technique that can provide molecular level structural information from muscle tissue under hydrated, physiological conditions at the physiologically relevant millisecond time scale. The availability of spectacular quality diffraction data currently provides only limited amount of extracted information due to lack of suitable analysis and modeling tools. Newly developed tools using data from MUSICO simulations provide a novel way of extracting new information from monitoring interactions at molecular scale and muscle contractile response at macroscopic scale. For example, this approach provided, for the first time, measurement of forces acting on actin filaments in leaving cells. Continuous development of these tools is vital to allow extraction of maximum information from the X-ray data and provide the precise information about the changes in myofilament structure and function associated with myopathic diseases.

The contractility of striated muscle is regulated by calcium dependent azimuthal movements of tropomyosin-troponin complexes over the surface of the actin filament. On the other hand, our hypothesis that calcium regulates thick filaments has been recently experimentally confirmed. Calcium regulation of muscle contraction is essential for modulating impaired muscle function in most neuromuscular diseases. We have developed the most comprehensive models of calcium regulation that allow translation of data from the experiments in solution to contractility of muscle fibers and whole muscles.

Excitation–contraction coupling is a processes related to electrical excitation through force generation and contraction in muscles. It occurs at multiple levels from the whole organ to single myocytes and down to the sarcomere. This is an important process that affects Calcium concentration responsible for activation of the contractile proteins. In order to build the best true-to-life computational models of different muscles, we have been exploring the state-of-art excitation-contraction models and how to integrate them into our MUSICO platform.

Our projects

2020-2022

''Multiscale Modeling and X-ray Diffraction: A novel approach to understanding heart disease''

(19IPLOI34770173)
supported by American Heart Foundation, PI: Thomas C. Irving, IIT Chicago, USA
2018-2022

“SilicoFCM - In Silico trials for drug tracing the effects of sarcomeric protein mutations leading to familial cardiomyopathy”

(No 777204)
supported by the European Union’s Horizon 2020 research and innovation program, project coordinator: Nenad Filipovic, BioIRC, Serbia
2012-2014

“BioCAT”

(P41 GM103622)
supported by National Institutes of Health, PI: Thomas C. Irving, IIT Chicago, USA
2022-2026

“Analysis Tools for Fiber Diffraction of Muscle”

(R01GM144555)
supported by National Institute of General Medical Sciences of the National Institutes of Health, PI: Thomas C. Irving, IIT Chicago, USA