Protein function machinery: from basic structural units to modulation of activity

Peroxiredoxin I and II as novel therapeutic molecular targets in cervical cancer treatment through regulation of endoplasmic reticulum stress induced by bleomycin

Cervical cancer, significantly affecting women worldwide, often involves treatment with bleomycin, an anticancer agent targeting breast, ovarian, and cervical cancers by generating reactive oxygen species (ROS) to induce cancer cell death. The Peroxiredoxin (PRDX) family, particularly PRDX1 and 2, plays a vital role in maintaining cellular balance by scavenging ROS, thus mitigating the damaging effects of bleomycin-induced mitochondrial and cellular oxidative stress. This process reduces endoplasmic reticulum (ER) stress and prevents cell apoptosis. However, reducing PRDX1 and 2 levels reverses their protective effect, increasing apoptosis. This research highlights the importance of PRDX1 and 2 in cervical cancer treatments with bleomycin, showing their potential to enhance treatment efficacy by managing ROS and ER stress and suggesting a therapeutic strategy for improving outcomes in cervical cancer treatment.

Back in time to the Gly-rich prototype of the phosphate binding elementary function

Binding of nucleotides and their derivatives is one of the most ancient elementary functions dating back to the Origin of Life. We review here the works considering one of the key elements in binding of (di)nucleotide-containing ligands - phosphate binding. We start from a brief discussion of major participants, conditions, and events in prebiotic evolution that resulted in the Origin of Life. Tracing back to the basic functions, including metal and phosphate binding, and, potentially, formation of primitive protein-protein interactions, we focus here on the phosphate binding. Critically assessing works on the structural, functional, and evolutionary aspects of phosphate binding, we perform a simple computational experiment reconstructing its most ancient and generic sequence prototype. The profiles of the phosphate binding signatures have been derived in form of position-specific scoring matrices (PSSMs), their peculiarities depending on the type of the ligands have been analyzed, and evolutionary connections between them have been delineated. Then, the apparent prototype that gave rise to all relevant phosphate-binding signatures had also been reconstructed. We show that two major signatures of the phosphate binding that discriminate between the binding of dinucleotide- and nucleotide-containing ligands are GxGxxG and GxxGxG, respectively. It appears that the signature archetypal for dinucleotide-containing ligands is more generic, and it can frequently bind phosphate groups in nucleotide-containing ligands as well. The reconstructed prototype's key signature GxGGxG underlies the role of glycine residues in providing flexibility and interactions necessary for binding the phosphate groups. The prototype also contains other ancient amino acids, valine, and alanine, showing versatility towards evolutionary design and functional diversification.

Conflicting Interfacial Electrostatic Interactions as a Design Principle to Modulate Long-Range Interdomain Communication

The extent and molecular basis of interdomain communication in multidomain proteins, central to understanding allostery and function, is an open question. One simple evolutionary strategy could involve the selection of either conflicting or favorable electrostatic interactions across the interface of two closely spaced domains to tune the magnitude of interdomain connectivity. Here, we study a bilobed domain FF34 from the eukaryotic p190A RhoGAP protein to explore one such design principle that mediates interdomain communication. We find that while the individual structural units in wild-type FF34 are marginally coupled, they exhibit distinct intrinsic stabilities and low cooperativity, manifesting as slow folding. The FF3-FF4 interface harbors a frustrated network of highly conserved electrostatic interactions-a charge troika-that promotes the population of multiple, decoupled, and non-native structural modes on a rugged native landscape. Perturbing this network via a charge-reversal mutation not only enhances stability and cooperativity but also dampens the fluctuations globally and speeds up the folding rate by at least an order of magnitude. Our work highlights how a conserved but nonoptimal network of interfacial electrostatic interactions shapes the native ensemble of a bilobed protein, a feature that could be exploited in designing molecular systems with long-range connectivity and enhanced cooperativity.

Living in trinity of extremes: Genomic and proteomic signatures of halophilic, thermophilic, and pH adaptation

Since nucleic acids and proteins of unicellular prokaryotes are directly exposed to extreme environmental conditions, it is possible to explore the genomic-proteomic compositional determinants of molecular mechanisms of adaptation developed by them in response to harsh environmental conditions. Using a wealth of currently available complete genomes/proteomes we were able to explore signatures of adaptation to three environmental factors, pH, salinity, and temperature, observing major trends in compositions of their nucleic acids and proteins. We derived predictors of thermostability, halophilic, and pH adaptations and complemented them by the principal components analysis. We observed a clear difference between thermophilic and salinity/pH adaptations, whereas latter invoke seemingly overlapping mechanisms. The genome-proteome compositional trade-off reveals an intricate balance between the work of base paring and base stacking in stabilization of coding DNA and r/tRNAs, and, at the same time, universal requirements for the stability and foldability of proteins regardless of the nucleotide biases. Nevertheless, we still found hidden fingerprints of ancient evolutionary connections between the nucleotide and amino acid compositions indicating their emergence, mutual evolution, and adjustment. The evolutionary perspective on the adaptation mechanisms is further studied here by means of the comparative analysis of genomic/proteomic traits of archaeal and bacterial species. The overall picture of genomic/proteomic signals of adaptation obtained here provides a foundation for future engineering and design of functional biomolecules resistant to harsh environments.

Engagement of intrinsic disordered proteins in protein-protein interaction

Proteins from the intrinsically disordered group (IDP) focus the attention of many researchers engaged in protein structure analysis. The main criteria used in their identification are lack of secondary structure and significant structural variability. This variability takes forms that cannot be identified in the X-ray technique. In the present study, different criteria were used to assess the status of IDP proteins and their fragments recognized as intrinsically disordered regions (IDRs). The status of the hydrophobic core in proteins identified as IDPs and in their complexes was assessed. The status of IDRs as components of the ordering structure resulting from the construction of the hydrophobic core was also assessed. The hydrophobic core is understood as a structure encompassing the entire molecule in the form of a centrally located high concentration of hydrophobicity and a shell with a gradually decreasing level of hydrophobicity until it reaches a level close to zero on the protein surface. It is a model assuming that the protein folding process follows a micellization pattern aiming at exposing polar residues on the surface, with the simultaneous isolation of hydrophobic amino acids from the polar aquatic environment. The use of the model of hydrophobicity distribution in proteins in the form of the 3D Gaussian distribution described on the protein particle introduces the possibility of assessing the degree of similarity to the assumed micelle-like distribution and also enables the identification of deviations and mismatch between the actual distribution and the idealized distribution. The FOD (fuzzy oil drop) model and its modified FOD-M version allow for the quantitative assessment of these differences and the assessment of the relationship of these areas to the protein function. In the present work, the sections of IDRs in protein complexes classified as IDPs are analyzed. The classification "disordered" in the structural sense (lack of secondary structure or high flexibility) does not always entail a mismatch with the structure of the hydrophobic core. Particularly, the interface area, often consisting of IDRs, in many analyzed complexes shows the compliance of the hydrophobicity distribution with the idealized distribution, which proves that matching to the structure of the hydrophobic core does not require secondary structure ordering.

A multiepitope vaccine encoding four Eimeria epitopes with PLGA nanospheres: a novel vaccine candidate against coccidiosis in laying chickens

With a worldwide distribution, Eimeria spp. could result in serious economic losses to the poultry industry. Due to drug resistance and residues, there are no ideal drugs and vaccines against Eimeria spp. in food animals. In the current study, a bioinformatics approach was employed to design a multiepitope antigen, named NSLC protein, encoding antigenic epitopes of E. necatrix NA4, E. tenella SAG1, E. acervulina LDH, and E. maxima CDPK. Thereafter, the protective immunity of NSLC protein along with five adjuvants and two nanospheres in laying chickens was evaluated. Based on the humoral immunity, cellular immunity, oocyst burden, and the coefficient of growth, the optimum adjuvant was evaluated. Furthermore, the optimum immune route and dosage were also investigated according to the oocyst burden and coefficient of growth. Accompanied by promoted secretion of antibodies and enhanced CD4⁺ and CD8⁺ T lymphocyte proportions, NSLC proteins entrapped in PLGA nanospheres were more effective in stimulating protective immunity than other adjuvants or nanospheres, indicating that PLGA nanospheres were the optimum adjuvant for NSLC protein. In addition, a significantly inhibited oocyst burden and growth coefficient promotion were also observed in animals vaccinated with NSLC proteins entrapped in PLGA nanospheres, indicating that the optimum adjuvant for NSLC proteins was PLGA nanospheres. The results also suggested that the intramucosal route with PLGA nanospheres containing 300 μg of NSLC protein was the most efficient approach to induce protective immunity against the four Eimeria species. Collectively, PLGA nanospheres loaded with NSLC antigens are potential vaccine candidates against avian coccidiosis.

Current status of PTMs structural databases: applications, limitations and prospects

Protein 3D structures, determined by their amino acid sequences, are the support of major crucial biological functions. Post-translational modifications (PTMs) play an essential role in regulating these functions by altering the physicochemical properties of proteins. By virtue of their importance, several PTM databases have been developed and released in decades, but very few of these databases incorporate real 3D structural data. Since PTMs influence the function of the protein and their aberrant states are frequently implicated in human diseases, providing structural insights to understand the influence and dynamics of PTMs is crucial for unraveling the underlying processes. This review is dedicated to the current status of databases providing 3D structural data on PTM sites in proteins. Some of these databases are general, covering multiple types of PTMs in different organisms, while others are specific to one particular type of PTM, class of proteins or organism. The importance of these databases is illustrated with two major types of in silico applications: predicting PTM sites in proteins using machine learning approaches and investigating protein structure-function relationships involving PTMs. Finally, these databases suffer from multiple problems and care must be taken when analyzing the PTMs data.

Allosteric perspective on the mutability and druggability of the SARS-CoV-2 Spike protein

Recent developments in the SARS-CoV-2 pandemic point to its inevitable transformation into an endemic disease, urging both refinement of diagnostics for emerging variants of concern (VOCs) and design of variant-specific drugs in addition to vaccine adjustments. Exploring the structure and dynamics of the SARS-CoV-2 Spike protein, we argue that the high-mutability characteristic of RNA viruses coupled with the remarkable flexibility and dynamics of viral proteins result in a substantial involvement of allosteric mechanisms. While allosteric effects of mutations should be considered in predictions and diagnostics of new VOCs, allosteric drugs advantageously avoid escape mutations via non-competitive inhibition originating from alternative distal locations. The exhaustive allosteric signaling and probing maps presented herein provide a comprehensive picture of allostery in the spike protein, making it possible to locate potential mutations that could work as new VOC “drivers” and to determine binding patches that may be targeted by newly developed allosteric drugs.

Structure and evolutionary trace-assisted screening of a residue swapping the substrate ambiguity and chiral specificity in an esterase

Our understanding of enzymes with high substrate ambiguity remains limited because their large active sites allow substrate docking freedom to an extent that seems incompatible with stereospecificity. One possibility is that some of these enzymes evolved a set of evolutionarily fitted sequence positions that stringently allow switching substrate ambiguity and chiral specificity. To explore this hypothesis, we targeted for mutation a serine ester hydrolase (EH3) that exhibits an impressive 71-substrate repertoire but is not stereospecific (e.e. 50%). We used structural actions and the computational evolutionary trace method to explore specificity-swapping sequence positions and hypothesized that position I244 was critical. Driven by evolutionary action analysis, this position was substituted to leucine, which together with isoleucine appears to be the amino acid most commonly present in the closest homologous sequences (max. identity, ca. 67.1%), and to phenylalanine, which appears in distant homologues. While the I244L mutation did not have any functional consequences, the I244F mutation allowed the esterase to maintain a remarkable 53-substrate range while gaining stereospecificity properties (e.e. 99.99%). These data support the possibility that some enzymes evolve sequence positions that control the substrate scope and stereospecificity. Such residues, which can be evolutionarily screened, may serve as starting points for further designing substrate-ambiguous, yet chiral-specific, enzymes that are greatly appreciated in biotechnology and synthetic chemistry.

Deriving and Using Descriptors of Elementary Functions in Rational Protein Design

The rational design of proteins with desired functions requires a comprehensive description of the functional building blocks. The evolutionary conserved functional units constitute nature's toolbox; however, they are not readily available to protein designers. This study focuses on protein units of subdomain size that possess structural properties and amino acid residues sufficient to carry out elementary reactions in the catalytic mechanisms. The interactions within such elementary functional loops (ELFs) and the interactions with the surrounding protein scaffolds constitute the descriptor of elementary function. The computational approach to deriving descriptors directly from protein sequences and structures and applying them in rational design was implemented in a proof-of-concept DEFINED-PROTEINS software package. Once the descriptor is obtained, the ELF can be fitted into existing or novel scaffolds to obtain the desired function. For instance, the descriptor may be used to determine the necessary spatial restraints in a fragment-based grafting protocol. We illustrated the approach by applying it to well-known cases of ELFs, including phosphate-binding P-loop, diphosphate-binding glycine-rich motif, and calcium-binding EF-hand motif, which could be used to jumpstart templates for user applications. The DEFINED-PROTEINS package is available for free at https://github.com/MelvinYin/Defined_Proteins.

Exploring the Allosteric Territory of Protein Function

While the pervasiveness of allostery in proteins is commonly accepted, we further show the generic nature of allosteric mechanisms by analyzing here transmembrane ion-channel viroporin 3a and RNA-dependent RNA polymerase (RdRp) from SARS-CoV-2 along with metabolic enzymes isocitrate dehydrogenase 1 (IDH1) and fumarate hydratase (FH) implicated in cancers. Using the previously developed structure-based statistical mechanical model of allostery (SBSMMA), we share our experience in analyzing the allosteric signaling, predicting latent allosteric sites, inducing and tuning targeted allosteric response, and exploring the allosteric effects of mutations. This, yet incomplete list of phenomenology, forms a complex and unique allosteric territory of protein function, which should be thoroughly explored. We propose a generic computational framework, which not only allows one to obtain a comprehensive allosteric control over proteins but also provides an opportunity to approach the fragment-based design of allosteric effectors and drug candidates. The advantages of allosteric drugs over traditional orthosteric compounds, complemented by the emerging role of the allosteric effects of mutations in the expansion of the cancer mutational landscape and in the increased mutability of viral proteins, leave no choice besides further extensive studies of allosteric mechanisms and their biomedical implications.

Analysis of Protein-Protein Interactions by Protein Microarrays

The analysis of the proteome and the interactome would be useful for a better understanding of the pathophysiology of several disorders, allowing the identification of potential specific markers for early diagnosis and prognosis, as well as potential targets of intervention. Among different proteomic approaches, high-density protein microarrays have become an interesting tool for the screening of protein-protein interactions and the interactome definition of disease-associated dysregulated proteins. This information might contribute to the identification of altered signaling pathways and protein functions involved in the pathogenesis of a disease. Remarkably, protein microarrays have been already satisfactorily employed for the study of protein-protein interactions in cancer, allergy, or neurodegenerative diseases. Here, we describe the utilization of recombinant protein microarrays for the identification of protein-protein interactions to help in the definition of disease-specific dysregulated interactomes.

Kinetic coherence underlies the dynamics of disordered proteins

The dynamics of two proteins of similar size, the globular lysozyme and the intrinsically disordered Huntingtin interacting protein, has been simulated in three states resembling a globule, a pre-molten globule, and a molten globule. A coherence time τ has been defined, measuring the delay in the display of a stochastic behaviour after a perturbation of the system. This time has been computed for two sets of collective variables: the projection of the phase point onto the positions and momenta subspaces (τ_r and τ_p), and the principal components (PCs) of positions q and momenta π produced by a covariance analysis in these subspaces (τ_q and τ_π). In all states τ_p ≈ 3.5τ_r, and τ_π ≈ 3.5τ_q. The coherence times of individual PCs, τ^(l)_q and τ^(l)_π, have also been computed, and τ^(l)_π > τ^(l)_q in all states. The prevalence of τ_p over τ_r, or of τ_π over τ_q, drives the dynamics of the protein over a time range of ≈1–2 ps; moreover, a hidden synchronism appears to raise the momenta subspace's coherence above that of its individual PCs. In the transition of lysozyme to the molten globule the τ^(l)_q decrease but, unexpectedly, the τ^(l)_π increase; after this transition τ_p ≈ 5τ_r and τ_π ≈ 5τ_q. A gain of kinetic coherence accompanies thus the loss of structural coherence caused by the denaturation of the protein in the transition from globule to molten globule. The increase of the τ^(l)_π does not take place in the analogous transition of the Huntingtin protein. These results are compared with those of a similar analysis performed on three pseudo-proteins designed by scrambling the primary sequence of the Huntingtin interacting protein, and on two oligopeptides. The hidden synchronism appears to be a generic property of these polypeptides. The τ^(l)_π spectrum is similar in denaturated and in intrinsically disordered biomolecules; but the gain of kinetic coherence as a result of denaturation seems to be a specific property of the biologically functional lysozyme.

In the phase space of a globular or intrinsically disordered protein, the momenta's dynamics is less chaotic than the coordinates' dynamics. When a protein is denaturated, a gain in kinetic coherence accompanies the loss of structural coherence.

Bcr-Abl Allosteric Inhibitors: Where We Are and Where We Are Going to

The fusion oncoprotein Bcr-Abl is an aberrant tyrosine kinase responsible for chronic myeloid leukemia and acute lymphoblastic leukemia. The auto-inhibition regulatory module observed in the progenitor kinase c-Abl is lost in the aberrant Bcr-Abl, because of the lack of the N-myristoylated cap able to bind the myristoyl binding pocket also conserved in the Bcr-Abl kinase domain. A way to overcome the occurrence of resistance phenomena frequently observed for Bcr-Abl orthosteric drugs is the rational design of allosteric ligands approaching the so-called myristoyl binding pocket. The discovery of these allosteric inhibitors although very difficult and extremely challenging, represents a valuable option to minimize drug resistance, mostly due to the occurrence of mutations more frequently affecting orthosteric pockets, and to enhance target selectivity with lower off-target effects. In this perspective, we will elucidate at a molecular level the structural bases behind the Bcr-Abl allosteric control and will show how artificial intelligence can be effective to drive the automated de novo design towards off-patent regions of the chemical space.

A Disordered Loop Mediates Heterogeneous Unfolding of an Ordered Protein by Altering the Native Ensemble

The high flexibility of long disordered or partially structured loops in folded proteins allows for entropic stabilization of native ensembles. Destabilization of such loops could alter the native ensemble or promote alternate conformations within the native ensemble if the ordered regions themselves are held together weakly. This is particularly true of downhill folding systems that exhibit weak unfolding cooperativity. Here, we combine experimental and computational methods to probe the response of the native ensemble of a helical, downhill folding domain PDD, which harbors an 11-residue partially structured loop, to perturbations. Statistical mechanical modeling points to continuous structural changes on both temperature and mutational perturbations driven by entropic stabilization of partially structured conformations within the native ensemble. Long time-scale simulations of the wild-type protein and two mutants showcase a remarkable conformational switching behavior wherein the parallel helices in the wild-type protein sample an antiparallel orientation in the mutants, with the C-terminal helix and the loop connecting the helices displaying high flexibility, disorder, and non-native interactions. We validate these computational predictions via the anomalous fluorescence of a native tyrosine located at the interface of the helices. Our observations highlight the role of long loops in determining the unfolding mechanisms, sensitivity of the native ensembles to mutational perturbations and provide experimentally testable predictions that can be explored in even two-state folding systems.

Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors

BACKGROUND

Pyrazinamide is an important drug against the latent stage of tuberculosis and is used in both first- and second-line treatment regimens. Pyrazinamide-susceptibility test usually takes a week to have a diagnosis to guide initial therapy, implying a delay in receiving appropriate therapy. The continued increase in multi-drug resistant tuberculosis and the prevalence of pyrazinamide resistance in several countries makes the development of assays for prompt identification of resistance necessary. The main cause of pyrazinamide resistance is the impairment of pyrazinamidase function attributed to mutations in the promoter and/or pncA coding gene. However, not all pncA mutations necessarily affect the pyrazinamidase function.

OBJECTIVE

To develop a methodology to predict pyrazinamidase function from detected mutations in the pncA gene.

METHODS

We measured the catalytic constant (kcat), KM, enzymatic efficiency, and enzymatic activity of 35 recombinant mutated pyrazinamidase and the wild type (Protein Data Bank ID = 3pl1). From all the 3D modeled structures, we extracted several predictors based on three categories: structural stability (estimated by normal mode analysis and molecular dynamics), physicochemical, and geometrical characteristics. We used a stepwise Akaike's information criterion forward multiple log-linear regression to model each kinetic parameter with each category of predictors. We also developed weighted models combining the three categories of predictive models for each kinetic parameter. We tested the robustness of the predictive ability of each model by 6-fold cross-validation against random models.

RESULTS

The stability, physicochemical, and geometrical descriptors explained most of the variability (R2) of the kinetic parameters. Our models are best suited to predict kcat, efficiency, and activity based on the root-mean-square error of prediction of the 6-fold cross-validation.

CONCLUSIONS

This study shows a quick approach to predict the pyrazinamidase function only from the pncA sequence when point mutations are present. This can be an important tool to detect pyrazinamide resistance.

AlloMAPS: allosteric mutation analysis and polymorphism of signaling database

AlloMAPS database provides data on the causality and energetics of allosteric communication obtained with the structure-based statistical mechanical model of allostery (SBSMMA). The database contains data on allosteric signaling in three sets of proteins and protein chains: (i) 46 proteins with comprehensively annotated functional and allosteric sites; (ii) 1908 protein chains from PDBselect set of chains with low (<25%) sequence identity; (iii) 33 proteins with more than 50 known pathological SNPs in each molecule. In addition to energetics of allosteric signaling between known functional and regulatory sites, allosteric modulation caused by the binding to these sites, by SNPs, and by mutations designated by the user can be explored. Allosteric Signaling Maps (ASMs), which are produced via the exhaustive computational scanning for stabilizing and destabilizing mutations and for the modulation range caused by the sequence position are available for each protein/protein chain in the database. We propose to use this database for evaluating the effects of allosteric signaling in the search for latent regulatory sites and in the design of allosteric sites and effectors. The database is freely available at: http://allomaps.bii.a-star.edu.sg.

Recent advances suggest increased influence of selective pressure in allostery

Allosteric regulation of protein functions is ubiquitous in organismal biology, but the principles governing its evolution are not well understood. Here we discuss recent studies supporting the large-scale existence of latent allostery in ancestor proteins of superfamilies. As suggested, the evolution of allostery could be driven by the need for specificity in paralogs of slow evolving protein complexes with conserved active sites. The same slow evolution is displayed by purifying selection exhibited in allosteric proteins with somatic mutations involved in cancer, where disease-associated mutations are enriched in both orthosteric and allosteric sites. Consequently, disease-associated variants can be used to identify druggable allosteric sites that are specific for paralogs in protein superfamilies with otherwise similar functions.

Relevance and proteomics challenge of functional posttranslational modifications in Kinetoplastid parasites

Protozoan parasitic infections are health, social and economic issues impacting both humans and animals, with significant morbidity and mortality worldwide. Protozoan parasites have complicated life cycles with both intracellular and extracellular forms. As a consequence, protozoan adapt to changing environments in part through a dynamic enzyme-catalyzed process leading to reversible posttranslational modifications (PTMs). The characterization by proteomics approaches reveals the critical role of the PTMs of the proteins involved in host-pathogen interaction. The complexity of PTMs characterization is increased by the high diversity, stoichiometry, dynamic and also co-existence of several PTMs in the same moieties which crosstalk between them. Here, we review how to understand the complexity and the essential role of PTMs crosstalk in order to provide a new hallmark for vaccines developments, immunotherapies and personalized medicine. In addition, the importance of these motifs in the biology and biological cycle of kinetoplastid parasites is highlighted with key examples showing the potential to act as targets against protozoan diseases.

Electrochemical control of the catalytic activity of immobilized enzymes

Regulation of the catalytic activity of enzymes immobilized on carbon nanotube electrodes was achieved by changing their local pH environment using electrochemical reactions.

A Click-Chemistry-Based Enrichable Crosslinker for Structural and Protein Interaction Analysis by Mass Spectrometry

Mass spectrometry is the method of choice for the characterisation of proteomes. Most proteins operate in protein complexes, in which their close association modulates their function. However, with standard MS analysis, information on protein–protein interactions is lost and no structural information is retained. To gain structural and interactome data, new crosslinking reagents are needed that freeze inter‐ and intramolecular interactions. Herein, the development of a new reagent, which has several features that enable highly sensitive crosslinking MS, is reported. The reagent enables enrichment of crosslinked peptides from the majority of background peptides to facilitate efficient detection of low‐abundant crosslinked peptides. Due to the special cleavable properties, the reagent can be used for MS² and potentially for MS³ experiments. Thus, the new crosslinking reagent, in combination with high‐end MS, should enable sensitive analysis of interactomes, which will help researchers to obtain important insights into cellular states in health and diseases.

Intrinsic dynamics is evolutionarily optimized to enable allosteric behavior

Allosteric behavior is central to the function of many proteins, enabling molecular machinery, metabolism, signaling and regulation. Recent years have shown that the intrinsic dynamics of allosteric proteins defined by their 3-dimensional architecture or by the topology of inter-residue contacts favors cooperative motions that bear close similarity to structural changes they undergo during their allosteric actions. These conformational motions are usually driven by energetically favorable or soft modes at the low frequency end of the mode spectrum, and they are evolutionarily conserved among orthologs. These observations brought into light evolutionary adaptation mechanisms that help maintain, optimize or regulate allosteric behavior as the evolution from bacterial to higher organisms introduces sequential heterogeneities and structural complexities.

Emergence of allosteric drug-resistance mutations: new challenges for allosteric drug discovery

Allosteric drugs have several significant advantages over traditional orthosteric drugs, encompassing higher selectivity and lower toxicity. Although allosteric drugs have potential advantages as therapeutic agents to treat human diseases, allosteric drug-resistance mutations still occur, rendering these drugs ineffective. Here, we review the emergence of allosteric drug-resistance mutations with an emphasis on examples covering clinically important therapeutic targets, including Breakpoint cluster region-Abelson tyrosine kinase (Bcr-Abl), Akt kinase [also called Protein Kinase B (PKB)], isocitrate dehydrogenase (IDH), MAPK/ERK kinase (MEK), and SRC homology 2 domain-containing phosphatase 2 (SHP2). We also discuss challenges associated with tackling allosteric drug resistance and the possible strategies to overcome this issue.

Deep Learning in the Study of Protein-Related Interactions

Protein-related interaction prediction is critical to understanding life processes, biological functions, and mechanisms of drug action. Experimental methods used to determine proteinrelated interactions have always been costly and inefficient. In recent years, advances in biological and medical technology have provided us with explosive biological and physiological data, and deep learning-based algorithms have shown great promise in extracting features and learning patterns from complex data. At present, deep learning in protein research has emerged. In this review, we provide an introductory overview of the deep neural network theory and its unique properties. Mainly focused on the application of this technology in protein-related interactions prediction over the past five years, including protein-protein interactions prediction, protein-RNA\DNA, Protein- drug interactions prediction, and others. Finally, we discuss some of the challenges that deep learning currently faces.

Towards descriptor of elementary functions for protein design

We review studies of the protein evolution that help to formulate rules for protein design. Acknowledging the fundamental importance of Dayhoff's provision on the emergence of functional proteins from short peptides, we discuss multiple evidences of the omnipresent partitioning of protein globules into structural/functional units, using which greatly facilitates the engineering and design efforts. Closed loops and elementary functional loops, which are descendants of ancient ring-like peptides that formed fist protein domains in agreement with Dayhoff's hypothesis, can be considered as basic units of protein structure and function. We argue that future developments in protein design approaches should consider descriptors of the elementary functions, which will help to complement designed scaffolds with functional signatures and flexibility necessary for their functions.

Methodologies and Applications of Proteomics for Study of Yeast Strains: An Update

Yeasts are one of the mostly used microorganisms as models in several studies. A wide range of applications in different processes can be attributed to their intrinsic characteristics. They are eukaryotes and therefore valuable expression hosts that require elaborate post-translational modifications. Their arsenal of proteins has become a valuable biochemical tool for the catalysis of several reactions of great value to the food (beverages), pharmaceutical and energy industries. Currently, the main challenge in systemic yeast biology is the understanding of the expression, function and regulation of the protein pool encoded by such microorganisms. In this review, we will provide an overview of the proteomic methodologies used in the analysis of yeasts. This research focuses on the advantages and improvements in their most recent applications with an understanding of the functionality of the proteins of these microorganisms, as well as an update of the advances of methodologies employed in mass spectrometry.

On the Allosteric Effect of nsSNPs and the Emerging Importance of Allosteric Polymorphism

The molecular mechanisms of pathological non-synonymous single-nucleotide polymorphisms are still the object of intensive research. To this end, we explore here whether non-synonymous single-nucleotide polymorphisms can work via allosteric mechanisms. Using structure-based statistical mechanical model of allostery and analyzing energetics of the effects of mutations in a set of 27 proteins with at least 50 pathological SNPs in each molecule, we found that, indeed, some SNPs can work allosterically. We illustrate the molecular basis of disease phenotypes caused by allosteric SNPs with the case studies of human galactose 1-phosphate uridyltransferase (GALT) and glucose-6-phosphate dehydrogenase (G6PD). We also found that mutations of a number of other residues in the protein may cause modulation comparable to those observed for known pathological SNPs. In order to explain this, we propose a notion of allosteric polymorphism, which implies the presence of a number of critical positions in the protein sequence, whose mutations can allosterically disrupt the protein function and result in a disease phenotype. We conclude that the emerging importance of allosteric polymorphism calls for the development of computational framework for analyzing the allosteric effects of mutations and their role in the modulation of protein activity.

Toward Comprehensive Allosteric Control over Protein Activity

Universality of allosteric signaling in proteins, molecular machines, and receptors complemented by the great advantages of prospected allosteric drugs in the highly specific, non-competitive, and modulatory nature of their actions calls for deeper theoretical understanding of allosteric communication. We present a computational model that makes it possible to tackle the problem of modulating the energetics of protein allosteric communication. In the context of the energy landscape paradigm, allosteric signaling is always a result of perturbations, such as ligand binding, mutations, and intermolecular interactions. The calculation of local partition functions in the protein harmonic model with perturbations allows us to evaluate the energetics of allosteric communication at the single-residue level. In this framework, Allosteric Signaling Maps are proposed as a tool to exhaustively describe allosteric communication in the protein, to tune already existing signaling, and to design new elements of regulation for taking the protein activity under allosteric control.

In silico Prediction, Characterization, Molecular Docking, and Dynamic Studies on Fungal SDRs as Novel Targets for Searching Potential Fungicides Against Fusarium Wilt in Tomato

Vascular wilt of tomato caused by Fusarium oxysporum f.sp. lycopersici (FOL) is one of the most devastating diseases, that delimits the tomato production worldwide. Fungal short-chain dehydrogenases/reductases (SDRs) are NADP(H) dependent oxidoreductases, having shared motifs and common functional mechanism, have been demonstrated as biochemical targets for commercial fungicides. The 1,3,6,8 tetra hydroxynaphthalene reductase (T4HNR) protein, a member of SDRs family, catalyzes the naphthol reduction reaction in fungal melanin biosynthesis. We retrieved an orthologous member of T4HNR, (complexed with NADP(H) and pyroquilon from Magnaporthe grisea) in the FOL (namely; FOXG_04696) based on homology search, percent identity and sequence similarity (93% query cover; 49% identity). The hypothetical protein FOXG_04696 (T4HNR like) had conserved T-G-X-X-X-G-X-G motif (cofactor binding site) at N-terminus, similar to M. grisea (1JA9) and Y-X-X-X-K motif, as a part of the active site, bearing homologies with two fungal keto reductases T4HNR (M. grisea) and 17-β-hydroxysteroid dehydrogenase from Curvularia lunata (teleomorph: Cochliobolus lunatus PDB ID: 3IS3). The catalytic tetrad of T4HNR was replaced with ASN¹¹⁵, SER¹⁴¹, TYR¹⁵⁴, and LYS¹⁵⁸ in the FOXG_04696. The structural alignment and superposition of FOXG_04696 over the template proteins (3IS3 and 1JA9) revealed minimum RMSD deviations of the C alpha atomic coordinates, and therefore, had structural conservation. The best protein model (FOXG_04696) was docked with 37 fungicides, to evaluate their binding affinities. The Glide XP and YASARA docked complexes showed discrepancies in results, for scoring and ranking the binding affinities of fungicides. The docked complexes were further refined and rescored from their docked poses through 50 ns long MD simulations, and binding free energies (ΔG_bind) calculations, using MM/GBSA analysis, revealed Oxathiapiprolin and Famoxadone as better fungicides among the selected one. However, Famoxadone had better interaction of the docked residues, with best protein ligand contacts, minimum RMSD (high accuracy of the docking pose) and RMSF (structural integrity and conformational flexibility of docking) at the specified docking site. The Famoxadone was found to be acceptable based on in silico toxicity and in vitro growth inhibition assessment. We conclude that the FOXG_04696, could be employed as a novel candidate protein, for structure-based design, and screening of target fungicides against the FOL pathogen.

Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response

The omnipresence of allosteric regulation together with the fundamental role of structural dynamics in this phenomenon have initiated a great interest to the detection of regulatory exosites and design of corresponding effectors. However, despite a general consensus on the key role of dynamics most of the earlier efforts on the prediction of allosteric sites are heavily crippled by the static nature of the underlying methods, which are either structure-based approaches seeking for deep surface pockets typical for “traditional” orthosteric drugs or sequence-based techniques exploiting the conservation of protein sequences. Because of the critical role of global protein dynamics in allosteric signaling, we investigate the hypothesis of reversibility in allosteric communication, according to which allosteric sites can be detected via the perturbation of the functional sites. The reversibility is tested here using our structure-based perturbation model of allostery, which allows one to analyze the causality and energetics of allosteric communication. We validate the “reverse perturbation” hypothesis and its predictive power on a set of classical allosteric proteins, then, on the independent extended benchmark set. We also show that, in addition to known allosteric sites, the perturbation of the functional sites unravels rather extended protein regions, which can host latent regulatory exosites. These protein parts that are dynamically coupled with functional sites can also be used for inducing and tuning allosteric communication, and an exhaustive exploration of the per-residue contributions to allosteric effects can eventually lead to the optimal modulation of protein activity. The site-effector interactions necessary for a specific mode and level of allosteric communication can be fine-tuned by adjusting the site’s structure to an available effector molecule and by the design or selection of an appropriate ligand.

Recent advances in the development of allosteric drugs allow one to fully appreciate the sheer power of allosteric effectors in the avoiding toxicity, receptor desensitization and modulatory rather than on/off mode of action, compared to the traditional orthosteric compounds. The detection of allosteric sites is one of the major challenges in the quest for allosteric drugs. This work proposes a “reverse perturbation” approach for identifying allosteric sites as a result of a perturbation applied to the functional ones. We show that according to the traditional Monod-Changeux-Jacob’s definition of allostery, considering non-overlapping regulatory and functional sites is a critical prerequisite for the successful detection of allosteric sites. Using the reverse perturbation method, it is possible to determine wide protein regions with a potential to induce an allosteric response and to adjust its strength. Further studies on inducing and fine-tuning of allosteric signalling seem to be of a great importance for efficient design of non-orthosteric ligands in the development of novel drugs.

Inter-Enzyme Allosteric Regulation of Chorismate Mutase in Corynebacterium glutamicum: Structural Basis of Feedback Activation by Trp

Corynebacterium glutamicum is widely used for the industrial production of amino acids, nucleotides, and vitamins. The shikimate pathway enzymes DAHP synthase (CgDS, Cg2391) and chorismate mutase (CgCM, Cgl0853) play a key role in the biosynthesis of aromatic compounds. Here we show that CgCM requires the formation of a complex with CgDS to achieve full activity, and that both CgCM and CgDS are feedback regulated by aromatic amino acids binding to CgDS. Kinetic analysis showed that Phe and Tyr inhibit CgCM activity by inter-enzyme allostery, whereas binding of Trp to CgDS strongly activates CgCM. Mechanistic insights were gained from crystal structures of the CgCM homodimer, tetrameric CgDS, and the heterooctameric CgCM-CgDS complex, refined to 1.1, 2.5, and 2.2 Å resolution, respectively. Structural details from the allosteric binding sites reveal that DAHP synthase is recruited as the dominant regulatory platform to control the shikimate pathway, similar to the corresponding enzyme complex from Mycobacterium tuberculosis.

Structural and Dynamic Insights into the Mechanism of Allosteric Signal Transmission in ERK2-Mediated MKP3 Activation

The mitogen-activated protein kinases (MAPKs) are key components of cellular signal transduction pathways, which are down-regulated by the MAPK phosphatases (MKPs). Catalytic activity of the MKPs is controlled both by their ability to recognize selective MAPKs and by allosteric activation upon binding to MAPK substrates. Here, we use a combination of experimental and computational techniques to elucidate the molecular mechanism for the ERK2-induced MKP3 activation. Mutational and kinetic study shows that the ³³⁴FNFM³³⁷ motif in the MKP3 catalytic domain is essential for MKP3-mediated ERK2 inactivation and is responsible for ERK2-mediated MKP3 activation. The long-term molecular dynamics (MD) simulations further reveal a complete dynamic process in which the catalytic domain of MKP3 gradually changes to a conformation that resembles an active MKP catalytic domain over the time scale of the simulation, providing a direct time-dependent observation of allosteric signal transmission in ERK2-induced MKP3 activation.