Point mutations and sequence variability in proteins: redistributions of preexisting populations

Mass spectrometry-complemented molecular modeling predicts the interaction interface for a camelid single-domain antibody targeting the Plasmodium falciparum circumsporozoite protein's C-terminal domain

Background

Bioanalytical methods that enable rapid and high-detail characterization of binding specificities and strengths of protein complexes with low sample consumption are highly desired. The interaction between a camelid single domain antibody (sdAbCSP1) and its target antigen (PfCSP-Cext) was selected as a model system to provide proof-of-principle for the here described methodology.

Research design and methods

The structure of the sdAbCSP1 - PfCSP-Cext complex was modeled using AlphaFold2. The recombinantly expressed proteins, sdAbCSP1, PfCSP-Cext, and the sdAbCSP1 - PfCSP-Cext complex, were subjected to limited proteolysis and mass spectrometric peptide analysis. ITEM MS (Intact Transition Epitope Mapping Mass Spectrometry) and ITC (Isothermal Titration Calorimetry) were applied to determine stoichiometry and binding strength.

Results

The paratope of sdAbCSP1 mainly consists of its CDR3 (aa100-118). PfCSP-Cext's epitope is assembled from its α-helix (aa40-52) and opposing loop (aa83-90). PfCSP-Cext's GluC cleavage sites E46 and E58 were shielded by complex formation, confirming the predicted epitope. Likewise, sdAbCSP1's tryptic cleavage sites R105 and R108 were shielded by complex formation, confirming the predicted paratope. ITEM MS determined the 1:1 stoichiometry and the high complex binding strength, exemplified by the gas phase dissociation reaction enthalpy of 50.2 kJ/mol. The in-solution complex dissociation constant is 5 × 10-10 M.

Conclusions

Combining AlphaFold2 modeling with mass spectrometry/limited proteolysis generated a trustworthy model for the sdAbCSP1 - PfCSP-Cext complex interaction interface.

Non-active Site Residue in Loop L4 Alters Substrate Capture and Product Release in d-Arginine Dehydrogenase

Numerous studies demonstrate that enzymes undergo multiple conformational changes during catalysis. The malleability of enzymes forms the basis for allosteric regulation: residues located far from the active site can exert long-range dynamical effects on the active site residues to modulate catalysis. The structure of Pseudomonas aeruginosa d-arginine dehydrogenase (PaDADH) shows four loops (L1, L2, L3, and L4) that span the substrate and the FAD-binding domains. Loop L4 comprises residues 329-336, spanning over the flavin cofactor. The I335 residue on loop L4 is ∼10 Å away from the active site and ∼3.8 Å from N(1)-C(2)═O atoms of the flavin. In this study, we used molecular dynamics and biochemical techniques to investigate the effect of the mutation of I335 to histidine on the catalytic function of PaDADH. Molecular dynamics showed that the conformational dynamics of PaDADH are shifted to a more closed conformation in the I335H variant. In agreement with an enzyme that samples more in a closed conformation, the kinetic data of the I335H variant showed a 40-fold decrease in the rate constant of substrate association (k₁), a 340-fold reduction in the rate constant of substrate dissociation from the enzyme-substrate complex (k₂), and a 24-fold decrease in the rate constant of product release (k₅), compared to that of the wild-type. Surprisingly, the kinetic data are consistent with the mutation having a negligible effect on the reactivity of the flavin. Altogether, the data indicate that the residue at position 335 has a long-range dynamical effect on the catalytic function in PaDADH.

Enzyme activity engineering based on sequence co-evolution analysis

The utility of engineering enzyme activity is expanding with the development of biotechnology. Conventional methods have limited applicability as they require high-throughput screening or three-dimensional structures to direct target residues of activity control. An alternative method uses sequence evolution of natural selection. A repertoire of mutations was selected for fine-tuning enzyme activities to adapt to varying environments during the evolution. Here, we devised a strategy called sequence co-evolutionary analysis to control the efficiency of enzyme reactions (SCANEER), which scans the evolution of protein sequences and direct mutation strategy to improve enzyme activity. We hypothesized that amino acid pairs for various enzyme activity were encoded in the evolutionary history of protein sequences, whereas loss-of-function mutations were avoided since those are depleted during the evolution. SCANEER successfully predicted the enzyme activities of beta-lactamase and aminoglycoside 3'-phosphotransferase. SCANEER was further experimentally validated to control the activities of three different enzymes of great interest in chemical production: cis-aconitate decarboxylase, α-ketoglutaric semialdehyde dehydrogenase, and inositol oxygenase. Activity-enhancing mutations that improve substrate-binding affinity or turnover rate were found at sites distal from known active sites or ligand-binding pockets. We provide SCANEER to control desired enzyme activity through a user-friendly webserver.

Investigation of Interferon Gamma Activity Using Bioinformatics Methods

Breast cancer grows from the breast tissue and is a severe health problem worldwide. Genetics is believed to be the primary cause of all cases of breast cancer via gene mutation. Bioinformatics methodology has been used to determine the sequences and structures of bioactive substances. This study aimed to analyze the function and structure of the Interferon Gamma (IFNγ) in healthy controls and patients with breast cancer using bioinformatics methods. Blood samples were collected from 75 patients with breast cancer and 25 healthy subjects as control samples. The results showed transition mutation (30%) and transversion mutation (70%) in patients with breast cancer. Moreover, missense mutations (84%) and silent mutations (16%) were detected by BLAST. In addition, the amino acid of the IFNγ protein consisting of alpha-helical, β-sheet, and coil of secondary structure was determined in this study using BioEdit. The results of the physicochemical properties of the IFNγ protein reflect the function, stability, molecular weight, isoelectric point, and instability index of the IFNγ protein using ProtParam. Moreover, the results of mutation affected the percentage of alpha-helix, β-turns, and coil in breast cancer patients compared to healthy groups with reference of NCBI using PSIpred program. Additionally, the PHYRE2 server and RasMol program showed a tertiary structure of the IFNγ protein in breast cancer patients. Furthermore, the STRING program revealed the poly IFNγ protein interacted with other proteins to perform its functions normally. From the recorded data in the current study, it was concluded that IFNγ is considered a marker for patients with breast cancer.

Hinge-shift mechanism as a protein design principle for the evolution of β-lactamases from substrate promiscuity to specificity

TEM-1 β-lactamase degrades β-lactam antibiotics with a strong preference for penicillins. Sequence reconstruction studies indicate that it evolved from ancestral enzymes that degraded a variety of β-lactam antibiotics with moderate efficiency. This generalist to specialist conversion involved more than 100 mutational changes, but conserved fold and catalytic residues, suggesting a role for dynamics in enzyme evolution. Here, we develop a conformational dynamics computational approach to rationally mold a protein flexibility profile on the basis of a hinge-shift mechanism. By deliberately weighting and altering the conformational dynamics of a putative Precambrian β-lactamase, we engineer enzyme specificity that mimics the modern TEM-1 β-lactamase with only 21 amino acid replacements. Our conformational dynamics design thus re-enacts the evolutionary process and provides a rational allosteric approach for manipulating function while conserving the enzyme active site.

A multidimensional computational exploration of congenital myasthenic syndrome causing mutations in human choline acetyltransferase

Missense mutations of human choline acetyltransferase (CHAT) are mainly associated with congenital myasthenic syndrome (CMS). To date, several pathogenic mutations have been reported, but due to the rarity and genetic complexity of CMS and difficult genotype-phenotype correlations, the CHAT mutations, and their consequences are underexplored. In this study, we systematically sift through the available genetic data in search of previously unreported pathogenic mutations and use a dynamic in silico model to provide structural explanations for the pathogenicity of the reported deleterious and undetermined variants. Through rigorous multiparameter analyses, we conclude that mutations can affect CHAT through a variety of different mechanisms: by disrupting the secondary structure, by perturbing the P-loop through long-range allosteric interactions, by disrupting the domain connecting loop, and by affecting the phosphorylation process. This study provides the first dynamic look at how mutations affect the structure and catalytic activity in CHAT and highlights the need for further genomic research to better understand the pathology of CHAT.

Physical Constraints on Epistasis

Living systems evolve one mutation at a time, but a single mutation can alter the effect of subsequent mutations. The underlying mechanistic determinants of such epistasis are unclear. Here, we demonstrate that the physical dynamics of a biological system can generically constrain epistasis. We analyze models and experimental data on proteins and regulatory networks. In each, we find that if the long-time physical dynamics is dominated by a slow, collective mode, then the dimensionality of mutational effects is reduced. Consequently, epistatic coefficients for different combinations of mutations are no longer independent, even if individually strong. Such epistasis can be summarized as resulting from a global nonlinearity applied to an underlying linear trait, that is, as global epistasis. This constraint, in turn, reduces the ruggedness of the sequence-to-function map. By providing a generic mechanistic origin for experimentally observed global epistasis, our work suggests that slow collective physical modes can make biological systems evolvable.

Mapping allosteric communications within individual proteins

Allostery in proteins influences various biological processes such as regulation of gene transcription and activities of enzymes and cell signaling. Computational approaches for analysis of allosteric coupling provide inexpensive opportunities to predict mutations and to design small-molecule agents to control protein function and cellular activity. We develop a computationally efficient network-based method, Ohm, to identify and characterize allosteric communication networks within proteins. Unlike previously developed simulation-based approaches, Ohm relies solely on the structure of the protein of interest. We use Ohm to map allosteric networks in a dataset composed of 20 proteins experimentally identified to be allosterically regulated. Further, the Ohm allostery prediction for the protein CheY correlates well with NMR CHESCA studies. Our webserver, Ohm.dokhlab.org, automatically determines allosteric network architecture and identifies critical coupled residues within this network.

Effect of Correlated Pair Mutations in Protein Misfolding

A Monte Carlo simulation based sequence design method is proposed to explore the effect of correlated pair mutations in proteins. In the designed sequences, the most correlated residue pairs are identified and mutated with all possible amino acid pairs except those already present. The cumulative correlated pair mutations generated an array of mutated sequences. Results show a significant increase in the probability of misfolding for correlated pair mutations as compared to that of the random pair mutations. The pair mutations of correlated residues that are in contact record a higher probability of misfolding as compared to the correlated residues that are not in contact. The probability of misfolding increases on pair mutation of nonlocally correlated residue pairs as compared to that of the locally correlated residue pairs. The choice of a compact or expanded conformation does not depend on the type of correlated pair mutations. Pair mutation of the most correlated residue pairs at the surface with hydrophobic amino acids results in higher misfolding probability as compared to that in the core. An exactly opposite behavior is observed on pair mutation with hydrophilic and charged amino acid pairs. The neutral amino acid pairs do not differentiate between core and surface sites. This study may be used for targeted mutation experiments to predict complex mutation patterns, reengineer the existing proteins, and design new proteins with reduced misfolding propensity.

RaaMLab: A MATLAB toolbox that generates amino acid groups and reduced amino acid modes

Amino acid (AA) classification and its different biophysical and chemical characteristics have been widely applied to analyze and predict the structural, functional, expression and interaction profiles of proteins and peptides. We present RaaMLab, a free and open-source MATLAB toolbox, to facilitate studies on proteins and peptides, to generate AA groups and to extract the structural and physicochemical features of reduced AAs (RedAA). This toolbox offers 4 kinds of databases, including the physicochemical properties of AAs and their groupings, 49 AA classification methods and 5 types of biophysicochemical features of RedAAs. These factors can be easily computed based on user-defined alphabet size and AA properties of AA groupings. RaaMLab is an open source freely available at https://github.com/bioinfo0706/RaaMLab. This website also contains a tutorial, extensive documentation and examples.

Effect of site-directed point mutations on protein misfolding: A simulation study

A Monte Carlo simulation based sequence design method is proposed to investigate the role of site-directed point mutations in protein misfolding. Site-directed point mutations are incorporated in the designed sequences of selected proteins. While most mutated sequences correctly fold to their native conformation, some of them stabilize in other nonnative conformations and thus misfold/unfold. The results suggest that a critical number of hydrophobic amino acid residues must be present in the core of the correctly folded proteins, whereas proteins misfold/unfold if this number of hydrophobic residues falls below the critical limit. A protein can accommodate only a particular number of hydrophobic residues at the surface, provided a large number of hydrophilic residues are present at the surface and critical hydrophobicity of the core is preserved. Some surface sites are observed to be equally sensitive toward site-directed point mutations as the core sites. Point mutations with highly polar and charged amino acids increases the misfold/unfold propensity of proteins. Substitution of natural amino acids at sites with different number of nonbonded contacts suggests that both amino acid identity and its respective site-specificity determine the stability of a protein. A clash-match method is developed to calculate the number of matching and clashing interactions in the mutated protein sequences. While misfolded/unfolded sequences have a higher number of clashing and a lower number of matching interactions, the correctly folded sequences have a lower number of clashing and a higher number of matching interactions. These results are valid for different SCOP classes of proteins.

Labeling for Quantitative Comparison of Imaging Measurements in Vitro and in Cells

Qualitative imaging of biomolecular localization and distribution inside cells has revolutionized cell biology. Most of these powerful techniques require modifications to the target biomolecule. Over the past 10 years, these techniques have been extended to quantitative measurements, from in-cell protein folding rates to complex dissociation constants to RNA lifetimes. Such measurements can be affected even when a target molecule is just mildly perturbed by its labels. Here, the impact of labeling on protein (and RNA) structure, stability, and function in cells is discussed via practical examples from the recent literature. General guidelines for selecting and validating modification sites are provided to bring the best from cell biology and imaging to quantitative biophysical experiments inside cells.

Evolution of intrinsic disorder in eukaryotic proteins

Conformational flexibility conferred though regions of intrinsic structural disorder allows proteins to behave as dynamic molecules. While it is well-known that intrinsically disordered regions can undergo disorder-to-order transitions in real-time as part of their function, we also are beginning to learn more about the dynamics of disorder-to-order transitions along evolutionary time-scales. Intrinsically disordered regions endow proteins with functional promiscuity, which is further enhanced by the ability of some of these regions to undergo real-time disorder-to-order transitions. Disorder content affects gene retention after whole genome duplication, but it is not necessarily conserved. Altered patterns of disorder resulting from evolutionary disorder-to-order transitions indicate that disorder evolves to modify function through refining stability, regulation, and interactions. Here, we review the evolution of intrinsically disordered regions in eukaryotic proteins. We discuss the interplay between secondary structure and disorder on evolutionary time-scales, the importance of disorder for eukaryotic proteome expansion and functional divergence, and the evolutionary dynamics of disorder.

The thermodynamics of protein aggregation reactions may underpin the enhanced metabolic efficiency associated with heterosis, some balancing selection, and the evolution of ploidy levels

Identifying the physical basis of heterosis (or "hybrid vigor") has remained elusive despite over a hundred years of research on the subject. The three main theories of heterosis are dominance theory, overdominance theory, and epistasis theory. Kacser and Burns (1981) identified the molecular basis of dominance, which has greatly enhanced our understanding of its importance to heterosis. This paper aims to explain how overdominance, and some features of epistasis, can similarly emerge from the molecular dynamics of proteins. Possessing multiple alleles at a gene locus results in the synthesis of different allozymes at reduced concentrations. This in turn reduces the rate at which each allozyme forms soluble oligomers, which are toxic and must be degraded, because allozymes co-aggregate at low efficiencies. The model developed in this paper can explain how heterozygosity impacts the metabolic efficiency of an organism. It can also explain why the viabilities of some inbred lines seem to decline rapidly at high inbreeding coefficients (F > 0.5), which may provide a physical basis for truncation selection for heterozygosity. Finally, the model has implications for the ploidy level of organisms. It can explain why polyploids are frequently found in environments where severe physical stresses promote the formation of soluble oligomers. The model can also explain why complex organisms, which need to synthesize aggregation-prone proteins that contain intrinsically unstructured regions (IURs) and multiple domains because they facilitate complex protein interaction networks (PINs), tend to be diploid while haploidy tends to be restricted to relatively simple organisms.

Computational Tools for Allosteric Drug Discovery: Site Identification and Focus Library Design

Allostery is an intrinsic phenomenon of biological macromolecules involving regulation and/or signal transduction induced by a ligand binding to an allosteric site distinct from a molecule's active site. Allosteric drugs are currently receiving increased attention in drug discovery because drugs that target allosteric sites can provide important advantages over the corresponding orthosteric drugs including specific subtype selectivity within receptor families. Consequently, targeting allosteric sites, instead of orthosteric sites, can reduce drug-related side effects and toxicity. On the down side, allosteric drug discovery can be more challenging than traditional orthosteric drug discovery due to difficulties associated with determining the locations of allosteric sites and designing drugs based on these sites and the need for the allosteric effects to propagate through the structure, reach the ligand binding site and elicit a conformational change. In this study, we present computational tools ranging from the identification of potential allosteric sites to the design of "allosteric-like" modulator libraries. These tools may be particularly useful for allosteric drug discovery.

5-Aryl-2-(naphtha-1-yl)sulfonamido-thiazol-4(5H)-ones as clathrin inhibitors

The development of a (Z)-5-((6,8-dichloro-4-oxo-4H-chromen-3-yl)methylene)-2-thioxothiazolidin-4-one (2), rhodanine-based lead that led to the Pitstop® 2 family of clathrin inhibitors is described herein. Head group substitution and bioisosteric replacement of the rhodanine core with a 2-aminothiazol-4(5H)-one scaffold eliminated off target dynamin activity. A series of N-substituents gave first phenylglycine (20, IC₅₀ ∼ 20 μM) then phenyl (25, IC₅₀ ∼ 7.1 μM) and 1-napthyl sulfonamide (26, Pitstop® 2 compound, IC₅₀ ∼ 1.9 μM) analogues with good activity, validating this approach. A final library exploring the head group resulted in three analogues displaying either slight improvements or comparable activity (33, 38, and 29 with IC₅₀ ∼ 1.4, 1.6 and 1.8 μM respectively) and nine others with IC₅₀ < 10 μM. These results were rationalized using in silico docking studies. Docking studies predicted enhanced Pitstop® 2 family binding, not a loss of binding, within the Pistop® groove of the reported clathrin mutant invalidating recent assumptions of poor selectivity for this family of clathrin inhibitors.

Multiple Conformations of Gal3 Protein Drive the Galactose-Induced Allosteric Activation of the GAL Genetic Switch of Saccharomyces cerevisiae

Gal3p is an allosteric monomeric protein that activates the GAL genetic switch of Saccharomyces cerevisiae in response to galactose. Expression of constitutive mutant of Gal3p or overexpression of wild-type Gal3p activates the GAL switch in the absence of galactose. These data suggest that Gal3p exists as an ensemble of active and inactive conformations. Structural data have indicated that Gal3p exists in open (inactive) and closed (active) conformations. However, a mutant of Gal3p that predominantly exists in inactive conformation and is yet capable of responding to galactose has not been isolated. To understand the mechanism of allosteric transition, we have isolated a triple mutant of Gal3p with V273I, T404A, and N450D substitutions, which, upon overexpression, fails to activate the GAL switch on its own but activates the switch in response to galactose. Overexpression of Gal3p mutants with single or double mutations in any of the three combinations failed to exhibit the behavior of the triple mutant. Molecular dynamics analysis of the wild-type and the triple mutant along with two previously reported constitutive mutants suggests that the wild-type Gal3p may also exist in super-open conformation. Furthermore, our results suggest that the dynamics of residue F237 situated in the hydrophobic pocket located in the hinge region drives the transition between different conformations. Based on this study, we suggest that conformational selection mechanism is the driving force in the allosteric transition of Gal3p, which may have implications in other signaling pathways involving monomeric proteins.

The cytochrome b Zn binding amino acid residue histidine 291 is essential for ubihydroquinone oxidation at the Qo site of bacterial cytochrome bc1

The ubiquinol:cytochrome (cyt) c oxidoreductase (or cyt bc₁) is an important membrane protein complex in photosynthetic and respiratory energy transduction. In bacteria such as Rhodobacter capsulatus it is constituted of three subunits: the iron-sulfur protein, cyt b and cyt c₁, which form two catalytic domains, the Q_o (hydroquinone (QH₂) oxidation) and Q_i (quinone (Q) reduction) sites. At the Q_o site, the pathways of bifurcated electron transfers emanating from QH₂ oxidation are known, but the associated proton release routes are not well defined. In energy transducing complexes, Zn²⁺ binding amino acid residues often correlate with proton uptake or release pathways. Earlier, using combined EXAFS and structural studies, we identified Zn coordinating residues of mitochondrial and bacterial cyt bc₁. In this work, using the genetically tractable bacterial cyt bc₁, we substituted each of the proposed Zn binding residues with non-protonatable side chains. Among these mutants, only the His291Leu substitution destroyed almost completely the Q_o site catalysis without perturbing significantly the redox properties of the cofactors or the assembly of the complex. In this mutant, which is unable to support photosynthetic growth, the bifurcated electron transfer reactions that result from QH₂ oxidation at the Q_o site, as well as the associated proton(s) release, were dramatically impaired. Based on these findings, on the putative role of His291 in liganding Zn, and on its solvent exposed and highly conserved position, we propose that His291 of cyt b is critical for proton release associated to QH₂ oxidation at the Q_o site of cyt bc₁.

Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell

All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.

Allosteric sites can be identified based on the residue-residue interaction energy difference

Allosteric drugs act at a distance to regulate protein functions. They have several advantages over conventional orthosteric drugs, including diverse regulation types and fewer side effects. However, the rational design of allosteric ligands remains a challenge, especially when it comes to the identification allosteric binding sites. As the binding of allosteric ligands may induce changes in the pattern of residue-residue interactions, we calculated the residue-residue interaction energies within the allosteric site based on the molecular mechanics generalized Born surface area energy decomposition scheme. Using a dataset of 17 allosteric proteins with structural data for both the apo and the ligand-bound state available, we used conformational ensembles generated by molecular dynamics simulations to compute the differences in the residue-residue interaction energies in known allosteric sites from both states. For all the known sites, distinct interaction energy differences (>25%) were observed. We then used CAVITY, a binding site detection program to identify novel putative allosteric sites in the same proteins. This yielded a total of 31 "druggable binding sites," of which 21 exhibited >25% difference in residue interaction energies, and were hence predicted as novel allosteric sites. Three of the predicted allosteric sites were supported by recent experimental studies. All the predicted sites may serve as novel allosteric sites for allosteric ligand design. Our study provides a computational method for identifying novel allosteric sites for allosteric drug design.

Allosterism in human complement component 5a ((h)C5a): a damper of C5a receptor (C5aR) signaling

The phenomena of allosterism continues to advance the field of drug discovery, by illuminating gainful insights for many key processes, related to the structure-function relationships in proteins and enzymes, including the transmembrane G-protein coupled receptors (GPCRs), both in normal as well as in the disease states. However, allosterism is completely unexplored in the native protein ligands, especially when a small covalent change significantly modulates the pharmacology of the protein ligands toward the signaling axes of the GPCRs. One such example is the human C5a ((h)C5a), the potent cationic anaphylatoxin that engages C5aR and C5L2 to elicit numerous immunological and non-immunological responses in humans. From the recently available structure-function data, it is clear that unlike the mouse C5a ((m)C5a), the (h)C5a displays conformational heterogeneity. However, the molecular basis of such conformational heterogeneity, otherwise allosterism in (h)C5a and its precise contribution toward the overall C5aR signaling is not known. This study attempts to decipher the functional role of allosterism in (h)C5a, by exploring the inherent conformational dynamics in (m)C5a, (h)C5a and in its point mutants, including the proteolytic mutant des-Arg(74)-(h)C5a. Prima facie, the comparative molecular dynamics study, over total 500 ns, identifies Arg(74)-Tyr(23) and Arg(37)-Phe(51) "cation-π" pairs as the molecular "allosteric switches" on (h)C5a that potentially functions as a damper of C5aR signaling.

The origins of mutational robustness

Biological systems are resistant to genetic changes; a property known as mutational robustness, the origin of which remains an open question. In recent years, researchers have explored emergent properties of biological systems and mechanisms of genetic redundancy to reveal how mutational robustness emerges and persists. Several mechanisms have been proposed to explain the origin of mutational robustness, including molecular chaperones and gene duplication. The latter has received much attention, but its role in robustness remains controversial. Here, I examine recent findings linking genetic redundancy through gene duplication and mutational robustness. Experimental evolution and genome resequencing have made it possible to test the role of gene duplication in tolerating mutations at both the coding and regulatory levels. This evidence as well as previous findings on regulatory reprogramming of duplicates support the role of gene duplication in the origin of robustness.

Harnessing proteasome dynamics and allostery in drug design

SIGNIFICANCE

The proteasome is the essential protease that is responsible for regulated cleavage of the bulk of intracellular proteins. Its central role in cellular physiology has been exploited in therapies against aggressive cancers where proteasome-specific competitive inhibitors that block proteasome active centers are very effectively used. However, drugs regulating this essential protease are likely to have broader clinical usefulness. The non-catalytic sites of the proteasome emerge as an attractive alternative target in search of highly specific and diverse proteasome regulators.

RECENT ADVANCES

Crystallographic models of the proteasome leave the false impression of fixed structures with minimal molecular dynamics lacking long-distance allosteric signaling. However, accumulating biochemical and structural observations strongly support the notion that the proteasome is regulated by precise allosteric interactions arising from protein dynamics, encouraging the active search for allosteric regulators. Here, we discuss properties of several promising compounds that affect substrate gating and processing in antechambers, and interactions of the catalytic core with regulatory proteins.

CRITICAL ISSUES

Given the structural complexity of proteasome assemblies, it is a painstaking process to better understand their allosteric regulation and molecular dynamics. Here, we discuss the challenges and achievements in this field. We place special emphasis on the role of atomic force microscopy imaging in probing the allostery and dynamics of the proteasome, and in dissecting the mechanisms involving small-molecule allosteric regulators.

FUTURE DIRECTIONS

New small-molecule allosteric regulators may become a next generation of drugs targeting the proteasome, which is critical to the development of new therapies in cancers and other diseases.

Survival and innovation: The role of mutational robustness in evolution

Biological systems are resistant to perturbations caused by the environment and by the intrinsic noise of the system. Robustness to mutations is a particular aspect of robustness in which the phenotype is resistant to genotypic variation. Mutational robustness has been linked to the ability of the system to generate heritable genetic variation (a property known as evolvability). It is known that greater robustness leads to increased evolvability. Therefore, mechanisms that increase mutational robustness fuel evolvability. Two such mechanisms, molecular chaperones and gene duplication, have been credited with enormous importance in generating functional diversity through the increase of system's robustness to mutational insults. However, the way in which such mechanisms regulate robustness remains largely uncharacterized. In this review, I provide evidence in support of the role of molecular chaperones and gene duplication in innovation. Specifically, I present evidence that these mechanisms regulate robustness allowing unstable systems to survive long periods of time, and thus they provide opportunity for other mutations to compensate the destabilizing effects of functionally innovative mutations. The findings reported in this study set new questions with regards to the synergy between robustness mechanisms and how this synergy can alter the adaptive landscape of proteins. The ideas proposed in this article set the ground for future research in the understanding of the role of robustness in evolution.

Harnessing allostery: a novel approach to drug discovery

Allostery is the most direct and efficient way for regulation of biological macromolecule function, ranging from the control of metabolic mechanisms to signal transduction pathways. Allosteric modulators target to allosteric sites, offering distinct advantages compared to orthosteric ligands that target to active sites, such as greater specificity, reduced side effects, and lower toxicity. Allosteric modulators have therefore drawn increasing attention as potential therapeutic drugs in the design and development of new drugs. In recent years, advancements in our understanding of the fundamental principles underlying allostery, coupled with the exploitation of powerful techniques and methods in the field of allostery, provide unprecedented opportunities to discover allosteric proteins, detect and characterize allosteric sites, design and develop novel efficient allosteric drugs, and recapitulate the universal features of allosteric proteins and allosteric modulators. In the present review, we summarize the recent advances in the repertoire of allostery, with a particular focus on the aforementioned allosteric compounds.

The free energy landscape in translational science: how can somatic mutations result in constitutive oncogenic activation?

The free energy landscape theory has transformed the field of protein folding. The significance of perceiving function in terms of conformational heterogeneity is gradually shifting the interest in the community from folding to function. From the free energy landscape standpoint the principles are unchanged: rather than considering the entire protein conformational landscape, the focus is on the ensemble around the bottom of the folding funnel. The protein can be viewed as populating one of two states: active or inactive. The basins of the two states are separated by a surmountable barrier, which allows the conformations to switch between the states. Unless the protein is a repressor, under physiological conditions it typically populates the inactive state. Ligand binding (or post-translational modification) triggers a switch to the active state. Constitutive allosteric mutations work by shifting the population from the inactive to the active state and keeping it there. This can happen by either destabilizing the inactive state, stabilizing the active state, or both. Identification of the mechanism through which they work is important since it may assist in drug discovery. Here we spotlight the usefulness of the free energy landscape in translational science, illustrating how oncogenic mutations can work in key proteins from the EGFR/Ras/Raf/Erk/Mek pathway, the main signaling pathway in cancer. Finally, we delineate the key components which are needed in order to trace the mechanism of allosteric events.

Dipeptide analysis of p53 mutations and evolution of p53 family proteins

p53 gain-of-function mutations are similar to driver mutations in cancer genes, with both promoting tumorigenesis. Most previous studies focused on residues lost by mutations, providing information related to a dominantly-negative effect. However, to understand gain-of-function mutations, it is also important to investigate what are the distributions of residues gained by mutations. We compile available p53/p63/p73 protein sequences and construct a non-redundant dataset. We analyze the amino acid and dipeptide composition of p53/p63/p73 proteins across evolution and compare them with the gain/loss of amino acids and dipeptides in human p53 following cancer-related somatic mutations. We find that the ratios of amino acids gained via somatic mutations during evolution to those lost through p53 cancer mutations correlate with the ratios found in single nucleotide polymorphisms in the human proteome. The dipeptide mutational gain/loss ratios are inversely correlated with those observed over p53 evolution but tend to follow the increasing p63/p73-like dipeptide propensities. We successfully simulated the p53 cancer mutation spectrum using the dipeptide composition across the p53 family accounting for the likelihood of mutations in p53 codons. The results revealed that the p53 mutation spectrum is dominated not only by p53 evolution but also by reversal of evolution to a certain degree. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Guest Editor: Yudong Cai.

ASD v2.0: updated content and novel features focusing on allosteric regulation

Allostery is the most direct and efficient way for regulation of biological macromolecule function and is induced by the binding of a ligand at an allosteric site topographically distinct from the orthosteric site. AlloSteric Database (ASD, http://mdl.shsmu.edu.cn/ASD) has been developed to provide comprehensive information on allostery. Owing to the inherent high receptor selectivity and lower target-based toxicity, allosteric regulation is expected to assume a more prominent role in drug discovery and bioengineering, leading to the rapid growth of allosteric findings. In this updated version, ASD v2.0 has expanded to 1286 allosteric proteins, 565 allosteric diseases and 22 008 allosteric modulators. A total of 907 allosteric site-modulator structural complexes and >200 structural pairs of orthosteric/allosteric sites in the allosteric proteins were constructed for researchers to develop allosteric site and pathway tools in response to community demands. Up-to-date allosteric pathways were manually curated in the updated version. In addition, both the front-end and the back-end of ASD have been redesigned and enhanced to allow more efficient access. Taken together, these updates are useful for facilitating the investigation of allosteric mechanisms, allosteric target identification and allosteric drug discovery.

Allostery in disease and in drug discovery

Allostery is largely associated with conformational and functional transitions in individual proteins. This concept can be extended to consider the impact of conformational perturbations on cellular function and disease states. Here, we clarify the concept of allostery and how it controls physiological activities. We focus on the challenging questions of how allostery can both cause disease and contribute to development of new therapeutics. We aim to increase the awareness of the linkage between disease symptoms on the cellular level and specific aberrant allosteric actions on the molecular level and to emphasize the potential of allosteric drugs in innovative therapies.

Function of hyperekplexia-causing α1R271Q/L glycine receptors is restored by shifting the affected residue out of the allosteric signalling pathway

BACKGROUND AND PURPOSE Glycine receptor α1 subunit R271Q and R271L (α1R271Q/L) mutations cause the neuromotor disorder, hereditary hyperekplexia. Studies suggest that the 271 residue is located within the allosteric signalling pathway linking the agonist binding site to the channel gate. The present study aimed to investigate a possible mechanism for restoring the function of the α1R271Q/L glycine receptor. EXPERIMENTAL APPROACH A 12-amino-acid segment incorporating the 271 residue on the glycine receptor α1271Q/L subunit was replaced by the homologous segment from the glycine receptor β subunit (α1(Ch) 271Q/L). The function of the α1(Ch) 271Q/L glycine receptor was examined by whole-cell patch-clamp recording and voltage-clamp fluorometry techniques. KEY RESULTS The function of the α1(Ch) 271Q/L glycine receptor was restored to the level of the wild-type (WT) α1 glycine receptor. Moreover, in the α1(Ch) glycine receptor, in contrast to the α1 glycine receptor, the channel function was not sensitive to various substitutions of the 271 residue, and the conformational change in the vicinity of the 271 residue was uncoupled from the channel gating. CONCLUSIONS AND IMPLICATIONS The 271 residue is shifted out of the allosteric signalling pathway in the α1(Ch) glycine receptor. We propose that this mechanism provides a novel drug design strategy not only for glycine receptor α1R271Q/L-caused hereditary hyperekplexia, but also for any pathological condition that is caused by missense mutation- or covalent modification-induced disorders involving residues in allosteric signalling pathways. Such a strategy makes it possible to design an ideal drug, which only corrects the function of the mutant or modified protein without affecting the WT or naive protein.

How do dynamic cellular signals travel long distances?

Communication is essential. It is vital between cells in multi-cellular organisms, and within cells. A signaling molecule binds to a receptor protein, and initiates a cascade of dynamic events. Signaling is a multistep pathway, which allows signal amplification: if some of the molecules in a pathway transmit the signal to multiple molecules, the result can be a large number of activated molecules across the cell and multiple reactions. That is how a small number of extracellular signaling molecules can produce a major cellular response. The pathway can relay signals from the extracellular space to the nucleus. How do signals travel efficiently over long-distances across the cell? Here we argue that evolution has utilized three properties: a modular functional organization of the cellular network; sequences in some key regions of proteins, such as linkers or loops, which were pre-encoded by evolution to facilitate signaling among domains; and compact interactions between proteins which is achieved via conformational disorder.

Allostery in a disordered protein: oxidative modifications to α-synuclein act distally to regulate membrane binding

Both oxidative stress and aggregation of the protein α-synuclein (aS) have been implicated as key factors in the etiology of Parkinson's disease. Specifically, oxidative modifications to aS disrupt its binding to lipid membranes, an interaction considered critical to its native function. Here we seek to provide a mechanistic explanation for this phenomenon by investigating the effects of oxidative nitration of tyrosine residues on the structure of aS and its interaction with lipid membranes. Membrane binding is mediated by the first ∼95 residues of aS. We find that nitration of the single tyrosine (Y39) in this domain disrupts binding due to electrostatic repulsion. Moreover, we observe that nitration of the three tyrosines (Y125/133/136) in the C-terminal domain is equally effective in perturbing binding, an intriguing result given that the C-terminus is not thought to interact directly with the lipid bilayer. Our investigations show that tyrosine nitration results in a change of the conformational states populated by aS in solution, with the most prominent changes occurring in the C-terminal region. These results lead us to suggest that nitration of Y125/133/136 reduces the membrane-binding affinity of aS through allosteric coupling by altering the ensemble of conformational states and depopulating those capable of membrane binding. While allostery is a well-established concept for structured proteins, it has only recently been discussed in the context of disordered proteins. We propose that allosteric regulation through modification of specific residues in, or ligand binding to, the C-terminus may even be a general mechanism for modulating aS function.

Detection of native-state nonadditivity in double mutant cycles via hydrogen exchange

Proteins have evolved to exploit long-range structural and dynamic effects as a means of regulating function. Understanding communication between sites in proteins is therefore vital to our comprehension of such phenomena as allostery, catalysis, and ligand binding/ejection. Double mutant cycle analysis has long been used to determine the existence of communication between pairs of sites, proximal or distal, in proteins. Typically, nonadditivity (or "thermodynamic coupling") is measured from global transitions in concert with a single probe. Here, we have applied the atomic resolution of NMR in tandem with native-state hydrogen exchange (HX) to probe the structure/energy landscape for information transduction between a large number of distal sites in a protein. Considering the event of amide proton exchange as an energetically quantifiable structural perturbation, m n-dimensional cycles can be constructed from mutation of n-1 residues, where m is the number of residues for which HX data is available. Thus, efficient mapping of a large number of couplings is made possible. We have applied this technique to one additive and two nonadditive double mutant cycles in a model system, eglin c. We find heterogeneity of HX-monitored couplings for each cycle, yet averaging results in strong agreement with traditionally measured values. Furthermore, long-range couplings observed at locally exchanging residues indicate that the basis for communication can occur within the native state ensemble, a conclusion not apparent from traditional measurements. We propose that higher-order couplings can be obtained and show that such couplings provide a mechanistic basis for understanding lower-order couplings via "spheres of perturbation". The method is presented as an additional tool for identifying a large number of couplings with greater coverage of the protein of interest.

A perturbative view of protein structural variation

It was recently found that the lowest-energy collective normal modes dominate the evolutionary divergence of protein structures. This was attributed to a presumed functional importance of such motions, i.e., to natural selection. In contrast to this selectionist explanation, we proposed that the observed behavior could be just the expected physical response of proteins to random mutations. This proposal was based on the success of a linearly forced elastic network model (LFENM) of mutational effects on structure to account for the observed pattern of structural divergence. Here, to further test the mutational explanation and the LFENM, we analyze the structural differences observed not only in homologous (globin-like) proteins but also in unselected experimentally engineered myoglobin mutants and in wild-type variants subject to other perturbations such as ligand-binding and pH changes. We show that the lowest normal modes dominate structural change in all the cases considered and that the LFENM reproduces this behavior quantitatively. The collective nature of the lowest normal modes results in global conformational changes that depend little on the exact nature or location of the perturbation. Significantly, the evolutionarily conserved structural core matches the regions observed to be more robust with respect to mutations, so that the core would be more conserved even under unselected random mutations. In a word, the observed patterns of structural variation can be seen as the natural response of proteins to perturbations and can be adequately modeled using the LFENM, which serves as a common framework to relate a priori different phenomena.

Protein flexibility: coordinate uncertainties and interpretation of structural differences

Valid interpretations of conformational movements in protein structures determined by X-ray crystallography require that the movement magnitudes exceed their uncertainty threshold. Here, it is shown that such thresholds can be obtained from the distance difference matrices (DDMs) of 1014 pairs of independently determined structures of bovine ribonuclease A and sperm whale myoglobin, with no explanations provided for reportedly minor coordinate differences. The smallest magnitudes of reportedly functional motions are just above these thresholds. Uncertainty thresholds can provide objective criteria that distinguish between true conformational changes and apparent 'noise', showing that some previous interpretations of protein coordinate changes attributed to external conditions or mutations may be doubtful or erroneous. The use of uncertainty thresholds, DDMs, the newly introduced CDDMs (contact distance difference matrices) and a novel simple rotation algorithm allows a more meaningful classification and description of protein motions, distinguishing between various rigid-fragment motions and nonrigid conformational deformations. It is also shown that half of 75 pairs of identical molecules, each from the same asymmetric crystallographic cell, exhibit coordinate differences that range from just outside the coordinate uncertainty threshold to the full magnitude of large functional movements. Thus, crystallization might often induce protein conformational changes that are comparable to those related to or induced by the protein function.

A genetic background with low mutational robustness is associated with increased adaptability to a novel host in an RNA virus

Although mutational robustness is central to many evolutionary processes, its relationship to evolvability remains poorly understood and has been very rarely tested experimentally. Here, we measure the evolvability of Vesicular stomatitis virus in two genetic backgrounds with different levels of mutational robustness. We passaged the viruses into a novel cell type to model a host-jump episode, quantified changes in infectivity and fitness in the new host, evaluated the cost of adaptation in the original host and analyzed the genetic basis of this adaptation. Lineages evolved from the less robust genetic background demonstrated increased adaptability, paid similar costs of adaptation to the new host and fixed approximately the same number of mutations as their more robust counterparts. Theory predicts that robustness can promote evolvability only in systems where large sets of genotypes are connected by effectively neutral mutations. We argue that this condition might not be fulfilled generally in RNA viruses.