Protein assembly and crowding simulations

Proteins encounter frequent molecular interactions in biological environments. Computer simulations have become an increasingly important tool in providing mechanistic insights into how such interactions in vivo relate to their biological function. The review here focuses on simulations describing protein assembly and molecular crowding effects as two important aspects that are distinguished mainly by how specific and long-lived protein contacts are. On the topic of crowding, recent simulations have provided new insights into how crowding affects protein folding and stability, modulates enzyme activity, and affects diffusive properties. Recent studies of assembly processes focus on assembly pathways, especially for virus capsids, amyloid aggregation pathways, and the role of multivalent interactions leading to phase separation. Also, discussed are technical challenges in achieving increasingly realistic simulations of interactions in cellular environments.     

Studies of folding and misfolding using simplified models

Computer simulations are as vital to our studies of biological systems as experiments. They bridge and rationalize experimental observations, extend the experimental "field of view", which is often limited to a specific time or length scale, and, most importantly, provide novel insights into biological systems, offering hypotheses about yet-to-be uncovered phenomena. These hypotheses spur further experimental discoveries. Simplified molecular models have a special place in the field of computational biology. Branded as less accurate than all-atom protein models, they have offered what all-atom molecular dynamics simulations could not--the resolution of the length and time scales of biological phenomena. Not only have simplified models proven to be accurate in explaining or reproducing several biological phenomena, they have also offered a novel multiscale computational strategy for accessing a broad range of time and length scales upon integration with traditional all-atom simulations. Recent computer simulations of simplified models have shaken or advanced the established understanding of biological phenomena. It was demonstrated that simplified models can be as accurate as traditional molecular dynamics approaches in identifying native conformations of proteins. Their application to protein structure prediction yielded phenomenal accuracy in recapitulating native protein conformations. New studies that utilize the synergy of simplified protein models with all-atom models and experiments yielded novel insights into complex biological processes, such as protein folding, aggregation and the formation of large protein complexes.     

Review of stochastic hybrid systems with applications in biological systems modeling and analysis

Stochastic hybrid systems (SHS) have attracted a lot of research interests in recent years. In this paper, we review some of the recent applications of SHS to biological systems modeling and analysis. Due to the nature of molecular interactions, many biological processes can be conveniently described as a mixture of continuous and discrete phenomena employing SHS models. With the advancement of SHS theory, it is expected that insights can be obtained about biological processes such as drug effects on gene regulation. Furthermore, combining with advanced experimental methods, in silico simulations using SHS modeling techniques can be carried out for massive and rapid verification or falsification of biological hypotheses. The hope is to substitute costly and time-consuming in vitro or in vivo experiments or provide guidance for those experiments and generate better hypotheses.     

Molecular recognition of Cullin3 by KCTDs: Insights from experimental and computational investigations

Recent investigations have highlighted a key role of the proteins of the KCTD (K-potassium channel tetramerization domain containing proteins) family in several fundamental biological processes. Despite the growing importance of KCTDs, our current understanding of their biophysical and structural properties is very limited. Biochemical characterizations of these proteins have shown that most of them act as substrate adaptor in E3 ligases during protein ubiquitination. Here we present a characterization of the KCTD5-Cullin3 interactions which are mediated by the KCTD5 BTB domain. Isothermal titration calorimetry experiments reveal that KCTD5 avidly binds the Cullin3 (Cul3). The complex presents a 5:5 stoichiometry and a dissociation constant of 59 nM. Molecular modeling and molecular dynamics simulations clearly indicate that the two proteins form a stable (KCTD5–Cul3)₅ pinwheel-shaped heterodecamer in which two distinct KCTD5 subunits cooperate in the binding of each cullin chain. Molecular dynamics simulations indicate that different types of interactions contribute to the stability of the assembly. Interestingly, residues involved in Cul3 recognitions are conserved in the KCTD5 orthologs and paralogs implicated in important biological processes. These residues are also rather well preserved in most of the other KCTD proteins. By using molecular modeling techniques, the entire ubiquitination system including the E3 ligase, the E2 conjugating enzyme and ubiquitin was generated. The analysis of the molecular architecture of this complex machinery provides insights into the ubiquitination processes which involve E3 ligases with a high structural complexity.     

Uncovering new aspects of protein interactions through analysis of specificity landscapes in peptide recognition domains

Protein interactions underlie all biological processes. An important class of protein interactions, often observed in signaling pathways, consists of peptide recognition domains binding short protein segments on the surface of their target proteins. Recent developments in experimental techniques have uncovered many such interactions and shed new lights on their specificity. To analyze these data, novel computational methods have been introduced that can accurately describe the specificity landscape of peptide recognition domains and predict new interactions. Combining large-scale analysis of binding specificity data with structure-based modeling can further reveal new biological insights into the molecular recognition events underlying signaling pathways.     

Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport

Ion translocation across biological barriers is a fundamental requirement for life. In many cases, controlling this process—for example with neuroactive drugs—demands an understanding of rapid and reversible structural changes in membrane-embedded proteins, including ion channels and transporters. Classical approaches to electrophysiology and structural biology have provided valuable insights into several such proteins over macroscopic, often discontinuous scales of space and time. Integrating these observations into meaningful mechanistic models now relies increasingly on computational methods, particularly molecular dynamics simulations, while surfacing important challenges in data management and conceptual alignment. Here, we seek to provide contemporary context, concrete examples, and a look to the future for bridging disciplinary gaps in biological ion transport. This article is part of a Special Issue entitled: Beyond the Structure-Function Horizon of Membrane Proteins edited by Ute Hellmich, Rupak Doshi and Benjamin McIlwain.     

Extracting Curvature Preferences of Lipids Assembled in Flat Bilayers Shows Possible Kinetic Windows for Genesis of Bilayer Asymmetry and Domain Formation in Biological Membranes

Studies on the assembly of pure lipid components allow mechanistic insights toward understanding the structural and functional aspects of biological membranes. Molecular dynamic (MD) simulations on membrane systems provide molecular details on membrane dynamics that are difficult to obtain experimentally. A large number of MD studies have remained somewhat disconnected from a key concept of amphipathic assembly resulting in membrane structures—shape parameters of lipid molecules in those structures in aqueous environments. This is because most of the MD studies have been done on flat lipid membranes. With the above in view, we analyzed MD simulations of 26 pure lipid patches as a function of (1) lipid type(s) and (2) time of MD simulations along with 35–40 ns trajectories of five pure lipids. We report, for the first time, extraction of curvature preferences of lipids from MD simulations done on flat bilayers. Our results may lead to mechanistic insights into the possible origins of bilayer asymmetries and domain formation in biological membranes.     

Conformational flexibility of N-glycans in solution studied by REMD simulations

Protein–glycan recognition regulates a wide range of biological and pathogenic processes. Conformational diversity of glycans in solution is apparently incompatible with specific binding to their receptor proteins. One possibility is that among the different conformational states of a glycan, only one conformer is utilized for specific binding to a protein. However, the labile nature of glycans makes characterizing their conformational states a challenging issue. All-atom molecular dynamics (MD) simulations provide the atomic details of glycan structures in solution, but fairly extensive sampling is required for simulating the transitions between rotameric states. This difficulty limits application of conventional MD simulations to small fragments like di- and tri-saccharides. Replica-exchange molecular dynamics (REMD) simulation, with extensive sampling of structures in solution, provides a valuable way to identify a family of glycan conformers. This article reviews recent REMD simulations of glycans carried out by us or other research groups and provides new insights into the conformational equilibria of N-glycans and their alteration by chemical modification. We also emphasize the importance of statistical averaging over the multiple conformers of glycans for comparing simulation results with experimental observables. The results support the concept of “conformer selection” in protein–glycan recognition.     

Hybrid computational methods combining experimental information with molecular dynamics

A goal of structural biology is to understand how macromolecules carry out their biological roles by identifying their metastable states, mechanisms of action, pathways leading to conformational changes, and the thermodynamic and kinetic relationships between those states. Integrative modeling brings structural insights into systems where traditional structure determination approaches cannot help. We focus on the synergies and challenges of integrative modeling combining experimental data with molecular dynamics simulations.     

Molecular dynamics simulation of a phosphatidylglycerol membrane

Although molecular dynamics simulations are an important tool for studying membrane systems, relatively few simulations have used anionic lipids. This paper reports the first simulation of a pure phosphatidylglycerol (PG) bilayer. The properties of this equilibrated palmitoyloleoylphosphatidylglycerol membrane agree with experimental observations of PG membranes and with previous simulations of monolayers and mixed bilayers containing PG lipids. These simulations also provide interesting insights into hydrogen bonding interactions in PG membranes. This equilibrated membrane will be a useful starting point for simulations of membrane proteins interacting with PG lipids.     

Create and assess protein networks through molecular characteristics of individual proteins

MOTIVATION: The study of biological systems, pathways and processes relies increasingly on analyses of networks. Most often, such analyses focus on network topology, thereby treating all proteins or genes as identical, featureless nodes. Integrating molecular data and insights about the qualities of individual proteins into the analysis may enhance our ability to decipher biological pathways and processes. RESULTS: Here, we introduce a novel platform for data integration that generates networks on the macro system-level, analyzes the molecular characteristics of each protein on the micro level, and then combines the two levels by using the molecular characteristics to assess networks. It also annotates the function and subcellular localization of each protein and displays the process on an image of a cell, rendering each protein in its respective cellular compartment. By thus visualizing the network in a cellular context we are able to analyze pathways and processes in a novel way. As an example, we use the system to analyze proteins implicated with Alzheimers disease and show how the integrated view corroborates previous observations and how it helps in the formulation of new hypotheses regarding the molecular underpinnings of the disease. AVAILABILITY: http://www.rostlab.org/services/pinat.     

Combining experiment and simulation in protein folding: closing the gap for small model systems

All-atom molecular dynamics (MD) simulations on increasingly powerful computers have been combined with experiments to characterize protein folding in detail over wider time ranges. The folding of small ultrafast folding proteins is being simulated on micros timescales, leading to improved structural predictions and folding rates. To what extent is 'closing the gap' between simulation and experiment for such systems providing insights into general mechanisms of protein folding?     

Multiscale simulations of protein and membrane systems

Classical multiscale simulations are perfectly suited to investigate biological soft matter systems. Owing to the bridging between microscopically realistic and lower-resolution models or the integration of a hierarchy of subsystems, one gets access to biologically relevant system sizes and timescales. In recent years, increasingly complex systems and processes have come into focus such as multidomain proteins, phase separation processes in biopolymer solutions, multicomponent biomembranes, or multiprotein complexes up to entire viruses. The review shows factors that have contributed to this progress — from improved models to machine-learning-based analysis and scale-bridging methods.     

Molecular and genetic characterization of osmosensing and signal transduction in the nematode Caenorhabditis elegans

Osmotic homeostasis is a fundamental requirement for life. In general, the effector mechanisms that mediate cellular and extracellular osmoregulation in animals are reasonably well defined. However, at the molecular level, little is known about how animals detect osmotic and ionic perturbations and transduce them into regulatory responses. The nematode Caenorhabditis elegans provides numerous powerful experimental advantages for defining the genes and integrated gene networks that underlie basic biological processes. These advantages include a fully sequenced and well-annotated genome, forward and reverse genetic and molecular tractability, and a relatively simple anatomy. C. elegans normally inhabits soil environments where it is exposed to repeated osmotic stress. In the laboratory, nematodes readily acclimate to and recover from extremes of hypertonicity. We review recent progress in defining the molecular mechanisms that underlie osmosensing and associated signal transduction in C. elegans. Some of these mechanisms are now known to be highly conserved. Therefore, studies of osmosensing in nematodes have provided, and will undoubtedly continue to provide, new insights into similar processes in more complex organisms including mammals.     

Modifier genes in mice and humans

An emerging theme of studies with spontaneous, engineered and induced mutant mice is that phenotypes often depend on genetic background, implying that genetic modifiers have a role in guiding the functional consequences of genetic variation. Understanding the molecular and cellular basis by which modifier genes exert their influence will provide insights into developmental and physiological pathways that are critical to fundamental biological processes, as well as into novel targets for therapeutic interventions in human diseases.     

Polymyxin B1 within the E. coli cell envelope: insights from molecular dynamics simulations

Polymyxins are used as last-resort antibiotics, where other treatments have been ineffectual due to antibiotic resistance. However, resistance to polymyxins has also been now reported, therefore it is instructive to characterise at the molecular level, the mechanisms of action of polymyxins. Here we review insights into these mechanisms from molecular dynamics simulations and discuss the utility of simulations as a complementary technique to  experimental methodologies.     

On the validity of Shannon-information calculations for molecular biological sequences

The usefulness of information-theoretic measures of the Shannon-Weaver type, when applied to molecular biological systems such as DNA or protein sequences, has been critically evaluated. It is shown that entropy can be re-expressed in dimensionless terms, thereby making it commensurate with information. Further, we have identified processes in which entropy S and information H change in opposite directions. These processes of opposing signs for delta S and delta H demonstrate that while the Second Law of Thermodynamics mandates that entropy always increases, it places no such restrictions on changes in information. Additionally, we have developed equations permitting information calculations, incorporating conditional occurrence probabilities, on DNA and protein sequences. When the results of such calculations are compared for sequences of various general types, there are no informational content patterns. We conclude that information-theoretic calculations of the present level of sophistication do not provide any useful insights into molecular biological sequences.     

Technicolour transgenics: imaging tools for functional genomics in the mouse

Over the past decade, a battery of powerful tools that encompass forward and reverse genetic approaches have been developed to dissect the molecular and cellular processes that regulate development and disease. The advent of genetically-encoded fluorescent proteins that are expressed in wild type and mutant mice, together with advances in imaging technology, make it possible to study these biological processes in many dimensions. Importantly, these technologies allow direct visual access to complex events as they happen in their native environment, which provides greater insights into mammalian biology than ever before.     

Endothelial development taking shape

Blood vessel development is a vital process during embryonic development, during tissue growth, regeneration and disease processes in the adult. In the past decade researchers have begun to unravel basic molecular mechanisms that regulate the formation of vascular lumen, sprouting angiogenesis, fusion of vessels, and pruning of the vascular plexus. The understanding of the biology of these angiogenic processes is increasingly driven through studies on vascular development at the cellular resolution. Single cell analysis in vivo, advanced genetic tools and the widespread use of powerful animal models combined with improved imaging possibilities are delivering new insights into endothelial cell form, function and behavior angiogenesis. Moreover, the combination of in silico modeling and experimentation including dynamic imaging promotes insights into higher level cooperative behavior leading to functional patterning of vascular networks. Here we summarize recent concepts and advances in the field of vascular development, focusing in detail on the endothelial cell.