Computational investigation of the Plasmodium falciparum fatty acid biosynthetic pathway toward the discovery of novel antimalarials

The structural peculiarities of a protein are related to its biological function. In the fatty acid elongation cycle, one small carrier protein shuttles and delivers the acyl intermediates from one enzyme to the other. The carrier has to recognize several enzymatic counterparts, specifically interact with each of them, and finally transiently deliver the carried substrate to the active site. Carry out such a complex game requires the players to be flexible and efficiently adapt their structure to the interacting protein or substrate. In a drug discovery effort, the structure-function relationships of a target system should be taken into account to optimistically interfere with its biological function. In this doctoral work, the essential role of structural plasticity in key steps of fatty acid biosynthesis in Plasmodium falciparum is investigated by means of molecular simulations. The key steps considered include the delivery of acyl substrates and the structural rearrangements of catalytic pockets upon ligand binding. The ground-level bases for carrier/enzyme recognition and interaction are also put forward. The structural features of the target have driven the selection of proper drug discovery tools, which captured the dynamics of biological processes and could allow the rational design of novel inhibitors. The model may be perspectively used for the identification of novel pathway-based antimalarial compounds.

Computational investigations of ion conduction mechanisms using enhanced sampling methods

Proper ion channels’ functioning is a prerequisite for a normal cell and disorders involving ion channels, or channelopathies, underlie many human diseases. Long QT syndromes (LQTS) for example may arise from the malfunctioning of hERG channel, caused either by the binding of drugs or mutations in HERG gene. In the first part of this thesis I present a framework to investigate the mechanism of ion conduction through hERG channel. The free energy profile governing the elementary steps of ion translocation in the pore was computed by means of umbrella sampling simulations. Compared to previous studies, we detected a different dynamic behavior: according to our data hERG is more likely to mediate a conduction mechanism which has been referred to as “single-vacancy-like” by Roux and coworkers (2001), rather then a “knock-on” mechanism. The same protocol was applied to a model of hERG presenting the Gly628Ser mutation, found to be cause of congenital LQTS. The results provided interesting insights about the reason of the malfunctioning of the mutant channel. Since they have critical functions in viruses’ life cycle, viral ion channels, such as M2 proton channel, are considered attractive targets for antiviral therapy. A deep knowledge of the mechanisms that the virus employs to survive in the host cell is of primary importance in the identification of new antiviral strategies. In the second part of this thesis I shed light on the role that M2 plays in the control of electrical potential inside the virus, being the charge equilibration a condition required to allow proton influx. The ion conduction through M2 was simulated using metadynamics technique. Based on our results we suggest that a potential anion-mediated cation-proton exchange, as well as a direct anion-proton exchange could both contribute to explain the activity of the M2 channel.

Computational modelling of human stem cell-derived cardiomyocytes - Texture descriptors for biological image processing

This thesis investigates two distinct research topics. The main topic (Part I) is the computational modelling of cardiomyocytes derived from human stem cells, both embryonic (hESC-CM) and induced-pluripotent (hiPSC-CM). The aim of this research line lies in developing models of the electrophysiology of hESC-CM and hiPSC-CM in order to integrate the available experimental data and getting in-silico models to be used for studying/making new hypotheses/planning experiments on aspects not fully understood yet, such as the maturation process, the functionality of the Ca2+ hangling or why the hESC-CM/hiPSC-CM action potentials (APs) show some differences with respect to APs from adult cardiomyocytes. Chapter I.1 introduces the main concepts about hESC-CMs/hiPSC-CMs, the cardiac AP, and computational modelling. Chapter I.2 presents the hESC-CM AP model, able to simulate the maturation process through two developmental stages, Early and Late, based on experimental and literature data. Chapter I.3 describes the hiPSC-CM AP model, able to simulate the ventricular-like and atrial-like phenotypes. This model was used to assess which currents are responsible for the differences between the ventricular-like AP and the adult ventricular AP. The secondary topic (Part II) consists in the study of texture descriptors for biological image processing. Chapter II.1 provides an overview on important texture descriptors such as Local Binary Pattern or Local Phase Quantization. Moreover the non-binary coding and the multi-threshold approach are here introduced. Chapter II.2 shows that the non-binary coding and the multi-threshold approach improve the classification performance of cellular/sub-cellular part images, taken from six datasets. Chapter II.3 describes the case study of the classification of indirect immunofluorescence images of HEp2 cells, used for the antinuclear antibody clinical test. Finally the general conclusions are reported.

Computational Modeling of Cardiac Excitation-Contraction Coupling in Physiological and Pathological Conditions

The cardiomyocyte is a complex biological system where many mechanisms interact non-linearly to regulate the coupling between electrical excitation and mechanical contraction. For this reason, the development of mathematical models is fundamental in the field of cardiac electrophysiology, where the use of computational tools has become complementary to the classical experimentation. My doctoral research has been focusing on the development of such models for investigating the regulation of ventricular excitation-contraction coupling at the single cell level. In particular, the following researches are presented in this thesis: 1) Study of the unexpected deleterious effect of a Na channel blocker on a long QT syndrome type 3 patient. Experimental results were used to tune a Na current model that recapitulates the effect of the mutation and the treatment, in order to investigate how these influence the human action potential. Our research suggested that the analysis of the clinical phenotype is not sufficient for recommending drugs to patients carrying mutations with undefined electrophysiological properties. 2) Development of a model of L-type Ca channel inactivation in rabbit myocytes to faithfully reproduce the relative roles of voltage- and Ca-dependent inactivation. The model was applied to the analysis of Ca current inactivation kinetics during normal and abnormal repolarization, and predicts arrhythmogenic activity when inhibiting Ca-dependent inactivation, which is the predominant mechanism in physiological conditions. 3) Analysis of the arrhythmogenic consequences of the crosstalk between β-adrenergic and Ca-calmodulin dependent protein kinase signaling pathways. The descriptions of the two regulatory mechanisms, both enhanced in heart failure, were integrated into a novel murine action potential model to investigate how they concur to the development of cardiac arrhythmias. These studies show how mathematical modeling is suitable to provide new insights into the mechanisms underlying cardiac excitation-contraction coupling and arrhythmogenesis.

Computational modeling of human atrial cardiomyocytes: integration of electro-mechanical & mechano-electric feedback pathways

The cardiomyocytes are very complex consisting of many interlinked non-linear regulatory mechanisms between electrical excitation and mechanical contraction. Thus given a integrated electromechanically coupled system it becomes hard to understand the individual contributor of cardiac electrics and mechanics under both physiological and pathological conditions. Hence, to identify the causal relationship or to predict the responses in a integrated system the use of computational modeling can be beneficial. Computational modeling is a powerful tool that provides complete control of parameters along with the visibility of all the individual components of the integrated system. The advancement of computational power has made it possible to simulate the models in a short timeframe, providing the possibility of increased predictive power of the integrated system. My doctoral thesis is focused on the development of electromechanically integrated human atrial cardiomyocyte model with proper consideration of feedforward and feedback pathways.