Proof of Principle that Molecular Modeling Followed by a Biophysical Experiment Can Develop Small Molecules that Restore Function to the Cardiac Thin Filament in the Presence of Cardiomyopathic Mutations

Basic science methods for the characterization of variants of uncertain significance in hypertrophic cardiomyopathy

With the advent of next-generation whole genome sequencing, many variants of uncertain significance (VUS) have been identified in individuals suffering from inheritable hypertrophic cardiomyopathy (HCM). Unfortunately, this classification of a genetic variant results in ambiguity in interpretation, risk stratification, and clinical practice. Here, we aim to review some basic science methods to gain a more accurate characterization of VUS in HCM. Currently, many genomic data-based computational methods have been developed and validated against each other to provide a robust set of resources for researchers. With the continual improvement in computing speed and accuracy, in silico molecular dynamic simulations can also be applied in mutational studies and provide valuable mechanistic insights. In addition, high throughput in vitro screening can provide more biologically meaningful insights into the structural and functional effects of VUS. Lastly, multi-level mathematical modeling can predict how the mutations could cause clinically significant organ-level dysfunction. We discuss emerging technologies that will aid in better VUS characterization and offer a possible basic science workflow for exploring the pathogenicity of VUS in HCM. Although the focus of this mini review was on HCM, these basic science methods can be applied to research in dilated cardiomyopathy (DCM), restrictive cardiomyopathy (RCM), arrhythmogenic cardiomyopathy (ACM), or other genetic cardiomyopathies.

Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament

Point mutations within sarcomeric proteins have been associated with altered function and cardiomyopathy development. Difficulties remain, however, in establishing the pathogenic potential of individual mutations, often limiting the use of genotype in management of affected families. To directly address this challenge, we utilized our all-atom computational model of the human full cardiac thin filament (CTF) to predict how sequence substitutions in CTF proteins might affect structure and dynamics on an atomistic level. Utilizing molecular dynamics calculations, we simulated 21 well-defined genetic pathogenic cardiac troponin T and tropomyosin variants to establish a baseline of pathogenic changes induced in computational observables. Computational results were verified via differential scanning calorimetry on a subset of variants to develop an experimental correlation. Calculations were performed on 9 independent variants of unknown significance (VUS), and results were compared with pathogenic variants to identify high-resolution pathogenic signatures. Results for VUS were compared with the baseline set to determine induced structural and dynamic changes, and potential variant reclassifications were proposed. This unbiased, high-resolution computational methodology can provide unique structural and dynamic information that can be incorporated into existing analyses to facilitate classification both for de novo variants and those where established approaches have provided conflicting information.

Molecular dynamics provides new insights into the mechanism of calcium signal transduction and interdomain interactions in cardiac troponin

Understanding the regulation of cardiac muscle contraction at a molecular level is crucial for the development of therapeutics for heart conditions. Despite the availability of atomic structures of the protein components of cardiac muscle thin filaments, detailed insights into their dynamics and response to calcium are yet to be fully depicted. In this study, we used molecular dynamics simulations of the core domains of the cardiac muscle protein troponin to characterize the equilibrium dynamics of its calcium-bound and calcium-free forms, with a focus on elements of cardiac muscle contraction activation and deactivation, that is, calcium binding to the cardiac troponin Ca²⁺ -binding subunit (TnC) and the release of the switch region of the troponin inhibitory subunit (TnI) from TnC. The process of calcium binding to the TnC binding site is described as a three-step process commencing with calcium capture by the binding site residues, followed by cooperative residue interplay bringing the calcium ion to the binding site, and finally, calcium-water exchange. Furthermore, we uncovered a set of TnC-TnI interdomain interactions that are critical for TnC N-lobe hydrophobic pocket dynamics. Absence of these interactions allows the closure of the TnC N-lobe hydrophobic pocket while the TnI switch region remains expelled, whereas if the interactions are maintained, the hydrophobic pocket remains open. Modification of these interactions may fine-tune the ability of the TnC N-lobe hydrophobic pocket to close or remain open, modulate cardiac contractility and present potential therapy-relevant targets.

Strategies for targeting the cardiac sarcomere: avenues for novel drug discovery

Introduction: Heart failure remains one of the largest clinical challenges in the United States. Researchers have continually searched for more effective heart failure treatments that target the cardiac sarcomere but have found few successes despite numerous expensive cardiovascular clinical trials. Among many reasons, the high failure rate of cardiovascular clinical trials may be partly due to incomplete characterization of a drug candidate's complex interaction with cardiac physiology.Areas covered: In this review, the authors address the issue of preclinical cardiovascular studies of sarcomere-targeting heart failure therapies. The authors consider inherent tradeoffs made between mechanistic transparency and physiological fidelity for several relevant preclinical techniques at the atomic, molecular, heart muscle fiber, whole heart, and whole-organism levels. Thus, the authors suggest a comprehensive, bottom-up approach to preclinical cardiovascular studies that fosters scientific rigor and hypothesis-driven drug discovery.Expert opinion: In the authors' opinion, the implementation of hypothesis-driven drug discovery practices, such as the bottom-up approach to preclinical cardiovascular studies, will be imperative for the successful development of novel heart failure treatments. However, additional changes to clinical definitions of heart failure and current drug discovery culture must accompany the bottom-up approach to maximize the effectiveness of hypothesis-driven drug discovery.

Computational Studies of Cardiac and Skeletal Troponin

Troponin is a key regulatory protein in muscle contraction, consisting of three subunits troponin C (TnC), troponin I (TnI), and troponin T (TnT). Calcium association to TnC initiates contraction by causing a series of dynamic and conformational changes that allow the switch peptide of TnI to bind and subsequently cross bridges to form between the thin and thick filament of the sarcomere. Owing to its pivotal role in contraction regulation, troponin has been the focus of numerous computational studies over the last decade. These studies elegantly supplemented a large volume of experimental work and focused on the structure, dynamics and function of the whole troponin complex, individual subunits, and even on segments of the thin filament. Molecular dynamics, Brownian dynamics, and free energy simulations have been used to elucidate the conformational dynamics and underlying free energy landscape of troponin, calcium, and switch peptide binding, as well as the effect of disease mutations, small molecules and post-translational modifications such as phosphorylation. Frequently, simulations have been used to confirm or explain experimental observations. Computer-aided drug discovery tools have been employed to identify novel potential calcium sensitizing agents binding to the TnC-TnI interface. Finally, Markov modeling has contributed to simulating contraction within the sarcomere on the mesoscale. Here we are reviewing and classifying the existing computational work on troponin and its subunits, outline current gaps in simulations elucidating troponin's role in contraction and suggest potential future developments in the field.