Challenges at the frontiers of structural biology

Knowledge of the three-dimensional structures of proteins is the key to unlocking the full potential of genomic information. There are two distinct directions along which cutting-edge research in structural biology is currently moving towards this goal. On the one hand, tightly focused long-term research in individual laboratories is leading to the determination of the structures of macromolecular assemblies of ever-increasing size and complexity. On the other hand, large consortia of structural biologists, inspired by the pace of genome sequencing, are developing strategies to determine new protein structures rapidly, so that it will soon be possible to predict reasonably accurate structures for most protein domains. We anticipate that a small number of complex systems, studied in depth, will provide insights across the field of biology with the aid of genome-based comparative structural analysis.     

Challenges at the frontiers of structural biology

Knowledge of the three-dimensional structures of proteins is the key to unlocking the full potential of genomic information. There are two distinct directions along which cutting-edge research in structural biology is currently moving towards this goal. On the one hand, tightly focused long-term research in individual laboratories is leading to the determination of the structures of macromolecular assemblies of ever-increasing size and complexity. On the other hand, large consortia of structural biologists, inspired by the pace of genome sequencing, are developing strategies to determine new protein structures rapidly, so that it will soon be possible to predict reasonably accurate structures for most protein domains. We anticipate that a small number of complex systems, studied in depth, will provide insights across the field of biology with the aid of genome-based comparative structural analysis.     

蛋白质结构的分形及其与进化关系的研究

本文在应用分形理论对蛋白质分子结构的分形进行研究的基础上,从非线性角度,就蛋白质多肽链的结构与形以及球蛋白三维结构的分形与进化的关系问题,进行了理论探讨和分析。     

Overcoming the challenges of membrane protein crystallography

Membrane protein structural biology is still a largely unconquered area, given that approximately 25% of all proteins are membrane proteins and yet less than 150 unique structures are available. Membrane proteins have proven to be difficult to study owing to their partially hydrophobic surfaces, flexibility and lack of stability. The field is now taking advantage of the high-throughput revolution in structural biology and methods are emerging for effective expression, solubilisation, purification and crystallisation of membrane proteins. These technical advances will lead to a rapid increase in the rate at which membrane protein structures are solved in the near future.     

Adaptability in protein structures: structural dynamics and implications in ligand design

The basic framework of understanding the mechanisms of protein functions is achieved from the knowledge of their structures which can model the molecular recognition. Recent advancement in the structural biology has revealed that in spite of the availability of the structural data, it is nontrivial to predict the mechanism of the molecular recognition which progresses via situation-dependent structural adaptation. The mutual selectivity of protein–protein and protein–ligand interactions often depends on the modulations of conformations empowered by their inherent flexibility, which in turn regulates the function. The mechanism of a protein’s function, which used to be explained by the ideas of ‘lock and key’ has evolved today as the concept of ‘induced fit’ as well as the ‘population shift’ models. It is felt that the ‘dynamics’ is an essential feature to take into account for understanding the mechanism of protein’s function. The design principles of therapeutic molecules suffer from the problems of plasticity of the receptors whose binding conformations are accurately not predictable from the prior knowledge of a template structure. On the other hand, flexibility of the receptors provides the opportunity to improve the binding affinity of a ligand by suitable substitution that will maximize the binding by modulating the receptors surface. In this paper, we discuss with example how the protein’s flexibility is correlated with its functions in various systems, revealing the importance of its understanding and for making applications. We also highlight the methodological challenges to investigate it computationally and to account for the flexible nature of the molecules in drug design.     

Structural genomics: opportunities and challenges

Following the complete genome sequencing of an increasing number of organisms, structural biology is engaging in a systematic approach of high-throughput structure determination called structural genomics to create a complete inventory of protein folds/structures that will help predict functions for all proteins. First results show that structural genomics will be highly effective in finding functional annotations for proteins of unknown function.     

蛋白质结构预测进展

蛋白质的序列决定结构,结构决定功能。新一代准确的蛋白质结构预测工具为结构生物学、结构生物信息学、药物研发和生命科学等许多领域带来了全新的机遇与挑战,单链蛋白质结构预测的准确率达到与试验方法相媲美的水平。本综述概述了蛋白质结构预测领域的理论基础、发展历程与最新进展,讨论了大量预测的蛋白质结构和基于人工智能的方法如何影响实验结构生物学,最后,分析了当前蛋白质结构预测领域仍未解决的问题以及未来的研究方向。     

Coverage of whole proteome by structural genomics observed through protein homology modeling database

We have been developing FAMSBASE, a protein homology-modeling database of whole ORFs predicted from genome sequences. The latest update of FAMSBASE (), which is based on the protein three-dimensional (3D) structures released by November 2003, contains modeled 3D structures for 368,724 open reading frames (ORFs) derived from genomes of 276 species, namely 17 archaebacterial, 130 eubacterial, 18 eukaryotic and 111 phage genomes. Those 276 genomes are predicted to have 734,193 ORFs in total and the current FAMSBASE contains protein 3D structure of approximately 50% of the ORF products. However, cases that a modeled 3D structure covers the whole part of an ORF product are rare. When portion of an ORF with 3D structure is compared in three kingdoms of life, in archaebacteria and eubacteria, approximately 60% of the ORFs have modeled 3D structures covering almost the entire amino acid sequences, however, the percentage falls to about 30% in eukaryotes. When annual differences in the number of ORFs with modeled 3D structure are calculated, the fraction of modeled 3D structures of soluble protein for archaebacteria is increased by 5%, and that for eubacteria by 7% in the last 3 years. Assuming that this rate would be maintained and that determination of 3D structures for predicted disordered regions is unattainable, whole soluble protein model structures of prokaryotes without the putative disordered regions will be in hand within 15 years. For eukaryotic proteins, they will be in hand within 25 years. The 3D structures we will have at those times are not the 3D structure of the entire proteins encoded in single ORFs, but the 3D structures of separate structural domains. Measuring or predicting spatial arrangements of structural domains in an ORF will then be a coming issue of structural genomics.     

Integrative Structural Biology in the Era of Accurate Structure Prediction

Characterizing the three-dimensional structure of macromolecules is central to understanding their function. Traditionally, structures of proteins and their complexes have been determined using experimental techniques such as X-ray crystallography, NMR, or cryo-electron microscopy—applied individually or in an integrative manner. Meanwhile, however, computational methods for protein structure prediction have been improving their accuracy, gradually, then suddenly, with the breakthrough advance by AlphaFold2, whose models of monomeric proteins are often as accurate as experimental structures. This breakthrough foreshadows a new era of computational methods that can build accurate models for most monomeric proteins. Here, we envision how such accurate modeling methods can combine with experimental structural biology techniques, enhancing integrative structural biology. We highlight the challenges that arise when considering multiple structural conformations, protein complexes, and polymorphic assemblies. These challenges will motivate further developments, both in modeling programs and in methods to solve experimental structures, towards better and quicker investigation of structure–function relationships.     

Protein structuromics: A new method for protein structure–function crosstalk in glioma

Glioma is a type of tumor that starts in the glial cells of the brain or spine. Since the 1800s, when the disease was first named, its survival rates have always been unsatisfactory. Despite great advances in molecular biology and traditional treatment methods, many questions regarding cancer occurrence and the underlying mechanism remain to be answered. In this study, we assessed the protein structural features of 20 oncogenes and 20 anti-oncogenes via protein structure and dynamic analysis methods and 3D structural and systematic analyses of the structure–function relationships of proteins. All of these results directly indicate that unfavorable group proteins show more complex structures than favorable group proteins. As the tumor cell microenvironment changes, the balance of oncogene-related and anti-oncogene-related proteins is disrupted, and most of the structures of the two groups of proteins will be disrupted. However, more unfavorable group proteins will maintain and refold to achieve their correct shape faster and perform their functions more quickly than favorable group proteins, and the former thus support cancer development. We hope that these analyses will help promote mechanistic research and the development of new treatments for glioma.     

The long coming of computational structural biology

Fifty years ago, the structures of the alpha-helix, the beta-sheet, the alpha-helical coiled coil and the collagen triple helix raised the expectation that protein structure could be understood computationally, using a combination of geometric considerations, model-building and parametric equations. The first crystal structures dispelled this hope, revealing a disconcerting lack of regularity in the folding patterns of proteins. Gradually it became clear that the protein folding problem-namely deducing the structure of a protein from its amino acid sequence-was of exceptional difficulty. Its solution has remained outside our reach to this day and, arguably, it represents the most important unsolved problem in molecular biology. Nevertheless, our ability to understand and predict molecular structure by computational means has made steady progress, suggesting that we will eventually conquer the problem, not by a few heroic insights, but by steady advances in biophysical knowledge, biological databases, software applications and raw computer power. Computational structural biology, whose influence is already pervasive, will come to dominate structural approaches in the next decades.     

Bridging from molecular simulation to biochemical networks

How can we make the connection between the three-dimensional structures of individual proteins and understanding how complex biological systems involving many proteins work? The modelling and simulation of protein structures can help to answer this question for systems ranging from multimacromolecular complexes to organelles and cells. On one hand, multiscale modelling and simulation techniques are advancing to permit the spatial and temporal properties of large systems to be simulated using atomic-detail structures. On the other hand, the estimation of kinetic parameters for the mathematical modelling of biochemical pathways using protein structure information provides a basis for iterative manipulation of biochemical pathways guided by protein structure. Recent advances include the structural modelling of protein complexes on the genomic level, novel coarse-graining strategies to increase the size of the system and the time span that can be simulated, and comparative molecular field analyses to estimate enzyme kinetic parameters.     

Membrane transporter research in times of countless structures

Structural biology has advanced our understanding of membrane proteins like no other scientific discipline in the past two decades and the number of high resolution membrane transporter structures solved by X-ray crystallography has increased exponentially over this time period. Currently, single particle cryo-EM is in full swing due to a recent resolution revolution and permits for structural insights of proteins that were refractory to crystallization. It is foreseeable that multiple structures of many human transporters will be solved in the coming five years. Nevertheless, many scientifically important questions remain unanswered despite of available structures, as is illustrated in this article at the example of multidrug efflux pumps and ABC transporters. Structure-function studies likely continue to be a supporting pillar of membrane transporter research. However, there is a trend towards the “integrated structural biologist”, whose research focusses on a biological question and who closely collaborates with other research groups specialized in spectroscopy techniques or molecular dynamics simulation. Future membrane protein research requires joint efforts from specialists of various disciplines to finally work towards a molecular understanding of membrane transport in the context of the living cell. 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     

Native ion mobility-mass spectrometry and related methods in structural biology

Mass spectrometry-based methods have become increasingly important in structural biology — in particular for large and dynamic, even heterogeneous assemblies of biomolecules. Native electrospray ionization coupled to ion mobility-mass spectrometry provides access to stoichiometry, size and architecture of noncovalent assemblies; while non-native approaches such as covalent labeling and H/D exchange can highlight dynamic details of protein structures and capture intermediate states. In this overview article we will describe these methods and highlight some recent applications for proteins and protein complexes, with particular emphasis on native MS analysis. This article is part of a Special Issue entitled: Mass spectrometry in structural biology.     

Lipidic cubic phase technologies for membrane protein structural studies

Lipidic cubic phase (LCP) is a membrane-mimetic matrix suitable for stabilization and crystallization of membrane proteins in lipidic environment. LCP technologies, however, have not been fully embraced by the membrane protein structural biology community, primarily because of the difficulties associated with handling viscous materials. Recent developments of pre-crystallization assays and improvements in crystal imaging, successes in obtaining high resolution structures of G protein-coupled receptors (GPCRs), and commercial availability of LCP tools and instruments are beginning to attract structural biologists to integrate LCP technologies in their research. This wider acceptance should translate to an increased number of otherwise difficult-to-crystallize membrane protein structures, shedding light on their functional mechanisms and on structural details of lipid-protein interactions.     

Circularly permuted dihydrofolate reductase possesses all the properties of the molten globule state, but can resume functional tertiary structure by interaction with its ligands.

It is obvious that functional activity of a protein molecule is closely related to its structure. On the other hand, the understanding of structure-function relationship still remains one of the intriguing problems of molecular biology. There is widespread belief that mutagenesis presents a real way to solve this problem. Following this assumption, we have investigated the effect of circular permutation in dihydrofolate reductase from E. coli on protein structure and functioning. It has been shown that in the absence of ligands two circularly permuted variants of dihydrofolate reductase possess all the properties of the molten globule state. However, after addition of ligands they gain the native-like structural properties and specific activity. This means that the in vitro folding of permuted dihydrofolate reductase is terminated at the stage of the molten globule formation. Interaction of permuted protein with ligands leads to the structural adjustment and formation of active protein molecules.     

Two mechanisms of protein folding: A theoretical analysis

In the current paper, two presumable mechanisms of protein folding are discussed; one of them, the “nucleation mechanism”, is exemplified by 3β-corner domains containing proteins, while the other, “structural units mechanism”, is exemplified by serine proteases. The analysis of the spatial structure of 3β-corners and of the common features of the amino acid sequences encoding them made it possible to conclude, that 3β-corners are capable of assuming their unique structures on their own and can serve as the nuclei or preformed structural units in the process of protein folding. The high order protein structures may be obtained by the further successive addition of β strands to a 3β-corner acting as a nucleus, according to certain rules and restrictions. On the other hand, 3β-corner may serve as a preformed structural unit, and the association of two 3β-corners may result in the formation of such 3D structures, which can be found in the domains of serine proteases and similar proteins.     

Identification of homology in protein structure classification.

Structural biology and structural genomics are expected to produce many three-dimensional protein structures in the near future. Each new structure raises questions about its function and evolution. Correct functional and evolutionary classification of a new structure is difficult for distantly related proteins and error-prone using simple statistical scores based on sequence or structure similarity. Here we present an accurate numerical method for the identification of evolutionary relationships (homology). The method is based on the principle that natural selection maintains structural and functional continuity within a diverging protein family. The problem of different rates of structural divergence between different families is solved by first using structural similarities to produce a global map of folds in protein space and then further subdividing fold neighborhoods into superfamilies based on functional similarities. In a validation test against a classification by human experts (SCOP), 77% of homologous pairs were identified with 92% reliability. The method is fully automated, allowing fast, self-consistent and complete classification of large numbers of protein structures. In particular, the discrimination between analogy and homology of close structural neighbors will lead to functional predictions while avoiding overprediction.     

结构生物学研究在中国

1970年代初期,中国科学工作者测定了亚洲地区第一个蛋白质晶体结构——猪胰岛素三方二锌晶体结构,成为中国结构生物学历史发展的起点.进入新世纪,该学科领域已进入国际前沿,展现出快速发展态势,正在迎来发展新时期.本篇评述包含"历史发展","现代化实验设施建设"和"深入生命世界,走进国际前沿——近年代表性研究成果集萃"三个主题节段,以较全视野反映结构生物学研究在中国的发展历程.