Order-disorder transition of intrinsically disordered kinase inducible transactivation domain of CREB

Intrinsically Disordered Proteins: Perspective on COVID-19 Infection and Drug Discovery

Since the beginning of the COVID-19 pandemic caused by SARS-CoV-2, millions of patients have been diagnosed and many of them have died from the disease worldwide. The identification of novel therapeutic targets are of utmost significance for prevention and treatment of COVID-19. SARS-CoV-2 is a single-stranded RNA virus with a 30 kb genome packaged into a membrane-enveloped virion, transcribing several tens of proteins. The belief that the amino acid sequence of proteins determines their 3D structure which, in turn, determines their function has been a central principle of molecular biology for a long time. Recently, it has been increasingly realized, however, that there is a large group of proteins that lack a fixed or ordered 3D structure, yet they exhibit important biological activities─so-called intrinsically disordered proteins and protein regions (IDPs/IDRs). Disordered regions in viral proteins are generally associated with viral infectivity and pathogenicity because they endow the viral proteins the ability to easily and promiscuously bind to host proteins; therefore, the proteome of SARS-CoV-2 has been thoroughly examined for intrinsic disorder. It has been recognized that, in fact, the SARS-CoV-2 proteome exhibits significant levels of structural order, with only the nucleocapsid (N) structural protein and two of the nonstructural proteins being highly disordered. The spike (S) protein of SARS-CoV-2 exhibits significant levels of structural order, yet its predicted percentage of intrinsic disorder is still higher than that of the spike protein of SARS-CoV. Noteworthy, however, even though IDPs/IDRs are not common in the SARS-CoV-2 proteome, the existing ones play major roles in the functioning and virulence of the virus and are thus promising drug targets for rational antiviral drug design. Presented here is a COVID-19 perspective on the intrinsically disordered proteins, summarizing recent results on the SARS-CoV-2 proteome disorder features, their physiological and pathological relevance, and their prominence as prospective drug target sites.

Disorder-to-order transition of the amyloid-β peptide upon lipid binding

There is mounting evidence that Alzheimer's disease progression and severity are linked to neuronal membrane damage caused by aggregates of the amyloid-β (Aβ) peptide. However, the detailed mechanism behind the membrane damage is not well understood yet. Recently, the lipid-chaperone hypothesis has been put forward, based on which the formation of complexes between Aβ and free lipids enables an easy insertion of Aβ into membranes. In order to test this hypothesis, we performed numerous all-atom molecular dynamics simulations. We studied the complex formation between individual lipids, considering both POPC and DPPC, and Aβ and examined whether the resulting complexes would be able to insert into lipid membranes. Complex formation at a one-to-one ratio was readily observed, yet with minimal effects on Aβ's characteristics. Most importantly, the peptide remains largely disordered in 1:1 complexes, and the complex does not insert into the membrane; instead, it is adsorbed to the membrane surface. The results change considerably once Aβ forms a complex with a POPC cluster composed of three lipid molecules. The hydrophobic interactions between Aβ and the lipid tails cause the peptide to fold into either a helical or a β-sheet structure. These observations provide atomic insight into the disorder-to-order transition that is needed for membrane insertion or amyloid aggregation to proceed.

Energy landscapes of protein aggregation and conformation switching in intrinsically disordered proteins

The protein folding problem was apparently solved recently by the advent of a deep learning method for protein structure prediction called AlphaFold. However, this program is not able to make predictions about the protein folding pathways. Moreover, it only treats about half of the human proteome, as the remaining proteins are intrinsically disordered or contain disordered regions. By definition these proteins differ from natively folded proteins and do not adopt a properly folded structure in solution. However these intrinsically disordered proteins (IDPs) also systematically differ in amino acid composition and uniquely often become folded upon binding to an interaction partner. These factors preclude solving IDP structures by current machine-learning methods like AlphaFold, which also cannot solve the protein aggregation problem, since this meta-folding process can give rise to different aggregate sizes and structures. An alternative computational method is provided by molecular dynamics simulations that already successfully explored the energy landscapes of IDP conformational switching and protein aggregation in multiple cases. These energy landscapes are very different from those of 'simple' protein folding, where one energy funnel leads to a unique protein structure. Instead, the energy landscapes of IDP conformational switching and protein aggregation feature a number of minima for different competing low-energy structures. In this review, I discuss the characteristics of these multifunneled energy landscapes in detail, illustrated by molecular dynamics simulations that elucidated the underlying conformational transitions and aggregation processes.

Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.

Optimization of Molecular Dynamics Simulations of c-MYC1-88-An Intrinsically Disordered System

Many of the proteins involved in key cellular regulatory events contain extensive intrinsically disordered regions that are not readily amenable to conventional structure/function dissection. The oncoprotein c-MYC plays a key role in controlling cell proliferation and apoptosis and more than 70% of the primary sequence is disordered. Computational approaches that shed light on the range of secondary and tertiary structural conformations therefore provide the only realistic chance to study such proteins. Here, we describe the results of several tests of force fields and water models employed in molecular dynamics simulations for the N-terminal 88 amino acids of c-MYC. Comparisons of the simulation data with experimental secondary structure assignments obtained by NMR establish a particular implicit solvation approach as highly congruent. The results provide insights into the structural dynamics of c-MYC^1-88, which will be useful for guiding future experimental approaches. The protocols for trajectory analysis described here will be applicable for the analysis of a variety of computational simulations of intrinsically disordered proteins.