On Protein Structure Function And Modularity From An Evolutionary Perspective
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On protein structure, function and modularity from an evolutionary perspective
Author: Robert Pilstål
language: en
Publisher: Linköping University Electronic Press
Release Date: 2018-05-23
We are compounded entities, given life by a complex molecular machinery. When studying these molecules we have to make sense of a diverse set of dynamical nanostructures with wast and intricate patterns of interactions. Protein polymers is one of the major groups of building blocks of such nanostructures which fold up into more or less distinct three dimensional structures. Due to their shape, dynamics and chemical properties proteins are able to perform a plethora of specific functions essential to all known cellular lifeforms. The connection between protein sequence, translated into protein structure and in the continuation into protein function is well accepted but poorly understood. Malfunction in the process of protein folding is known to be implicated in natural aging, cancer and degenerative diseases such as Alzheimer's. Protein folds are described hierarchically by structural ontologies such as SCOP, CATH and Pfam all which has yet to succeed in deciphering the natural language of protein function. These paradigmatic views centered on protein structure fail to describe more mutable entities, such as intrinsically disordered proteins (IDPs) which lack a clear defined structure. As of 2012, about two thirds of cancer patients was predicted to survive past 5 years of diagnosis. Despite this, about a third do not survive and numerous of successfully treated patients suffer from secondary conditions due to chemotherapy, surgery and the like. In order to handle cancer more efficiently we have to better understand the underlying molecular mechanisms. Elusive to standard methods of investigation, IDPs have a central role in pathology; dysfunction in IDPs are key factors in cellular system failures such as cancer, as many IDPs are hub regulators for major cell functions. These IDPs carry short conserved functional boxes, that are not described by known ontologies, which suggests the existence of a smaller entity. In an investigation of a pair of such boxes of c-MYC, a plausible structural model of its interacting with Pin1 emerged, but such a model still leaves the observer with a puzzle of understanding the actual function of that interaction. If the protein is represented as a graph and modeled as the interaction patterns instead of as a structural entity, another picture emerges. As a graph, there is a parable from that of the boxes of IDPs, to that of sectors of allosterically connected residues and the theory of foldons and folding units. Such a description is also useful in deciphering the implications of specific mutations. In order to render a functional description feasible for both structured and disordered proteins, there is a need of a model separate from form and structure. Realized as protein primes, patterns of interaction, which has a specific function that can be defined as prime interactions and context. With function defined as interactions, it might be possible that the discussion of proteins and their mechanisms is thereby simplified to the point rendering protein structural determination merely supplementary to understanding protein function. Människan byggs upp av celler, de i sin tur består av än mindre beståndsdelar; livets molekyler. Dessa fungerar som mekaniska byggstenar, likt maskiner och robotar som sliter vid fabrikens band; envar utförandes en absolut nödvändig funktion för cellens, och hela kroppens, fortsatta överlevnad. De av livets molekyler som beskrivs centralt i den här avhandling är proteiner, vilka i sin tur består utav en lång kedja, med olika typer av länkar, som likt garn lindar upp sig i ett nystan av en (mer eller mindre...) bestämd struktur som avgör dess roll och funktion i cellen. Intrinsiellt oordnade proteiner (IDP) går emot denna enkla åskådning; de är proteiner som saknar struktur och beter sig mer likt spaghetti i vatten än en maskin. IDP är ändå funktionella och bär på centrala roller i cellens maskineri; exempel är oncoproteinet c-Myc som agerar "gaspedal" för cellen - fel i c-Myc's funktion leder till att cellerna löper amok, delar sig hejdlöst och vi får cancer. Man har upptäckt att c-Myc har en ombytlig struktur vi inte kan se; studier av punktvisa förändringar, mutationer, i kedjan av byggstenar hos c-Myc visar att många länkar har viktiga roller i funktionen. Detta ger oss bättre förståelse om cancer men samtidigt är laboratoriearbetet både komplicerat och dyrt; här kan evolutionen vägleda oss och avslöja hemligheterna snabbare. Molekylär evolution studeras genom att beräkna variation i proteinkedjan mellan besläktade arter som finns lagrade i databaser; detta visar snabbt, via nätverksanalys och grafteori, vilka delar av proteinet som är centrala och kopplade till varandra av nödvändighet för artens fortlevnad. På så vis hjälper evolutionen oss att förstå proteinfunktioner via modeller baserade på proteinernas interaktioner snarare än deras struktur. Samma modeller kan nyttjas för att förstå dynamiska förlopp och skillnader mellan normala och patologiska varianter av proteiner; mutationer kan uppstå i vår arvsmassa som kan leda till sjukdom. Genom analys av proteinernas kopplingsnätverk i grafmodellerna kan man bättre förutsäga vilka mutationer som är farligare än andra. Dessutom har det visat sig att en sådan representation kan ge bättre förståelse för den normala funktionen hos ett protein än vad en proteinstruktur kan. Här introduceras även konceptet proteinprimärer, vilket är en abstrakt representation av proteiner centrerad på deras interaktiva mönster, snarare än på partikulär form och struktur. Det är en förhoppning att en sådan representation skall förenkla diskussionen anbelangande proteinfunktion så till den grad att strukturbestämmelse av proteiner, som är en mycket kostsam och tidskrävande process, till viss mån kan anses vara sekundär i betydelse jämfört med funktionellt modellerande baserat på evolutionära data extraherade ur våra sekvensdatabaser.
Insights in Systems Biology Research
Summary of Topic: This collection represents an interdisciplinary exploration of systems biology and systems medicine, integrating advanced methodologies from computational modeling, deep neural networks, and multiomics to improve understanding and treatment of human diseases and biological mechanisms. Emphasis is placed on cutting-edge technologies, including deep learning for statistical inference from gene expression data and noncoding genetic variants, quantitative systems pharmacology for virtual patient generation, and semi-mechanistic modeling applied to novel therapies such as CAR T-cell interventions. The articles further highlight disease modeling across various scales, exemplified through multi-scale simulation frameworks applied to complex conditions such as COVID-19 long-term sequelae, rheumatoid arthritis, epilepsy, and tuberculosis. Additionally, the importance of modularity in biological networks, developments in functional annotation of microbial transporters, and new approaches towards bioengineered bacterial consortia through molecular communication are discussed. This collection informs us of the ongoing efforts to harness computational power and biological insights to advance personalized medicine, improve therapeutic strategies, and deepen our understanding of complex biological phenomena. ----- Systems Biology has undergone significant transformations due to the pioneering efforts of researchers worldwide. The discipline now spans several subfields, such as Neuroscience, Genetics and Genomics, Medicine, among others, each advancing the field in unique ways through innovative technologies and insightful discoveries. This evolution is celebrated in a curated collection by Frontiers in Systems Biology, which aims to highlight the state-of-the-art developments and set the stage for future inquiries and applications in the field. This collection actively showcases the overlap of technology with theoretical advancements, creating a broad framework from which new methodologies and strategies are born. This Research Topic aims to provide an overview of the most recent progress in Systems Biology. It seeks to outline the impacts that the integration of disparate biological research areas can have in solving complex biological problems and advancing human health. Without losing sight of the past achievements, the goal is to explore the potential of future advancements, addressing the challenges that remain at the forefront of this vibrant field. The scope of this Research Topic is broadly defined yet focused on areas where significant innovative strides have been made. We welcome contributions that emphasize: - Integrative approaches in Systems Neuroscience - Contemporary breakthroughs in Genetics and Genomics - The use of Multiscale Mechanistic Modelling to represent biological interfaces - Bridging gaps between experimental and computational biology in Translational Systems Biology - Enhancing methodologies in Data and Model Integration This collection welcomes contributions from Editorial Board Members or those referred by a board member, reflecting on current developments and plotting pathways for upcoming research endeavors. Authors are encouraged to engage critically with their fields, identifying current challenges and proposing novel solutions to advance the understanding of complex systems within biology.