Protein sialylation affects the pH-dependent binding of ferric ion to human serum transferrin

Physiological or pathophysiological changes lead to posttranslational changes in the sialic acid content of human serum transferrin (hTf), an essential mediator of iron transport in the human body, resulting in a significantly increased concentration of desialylated hTf. The intrinsic fluorescence quenching upon binding of iron to hTf was successfully modeled using the binding polynomial for two iron-binding sites, allowing measurements in a high-throughput format. Removal of sialic acid residues resulted in a 3-fold increase in iron binding affinity for both sites of hTf at pH 7.4. The pH-dependence of iron binding showed significant differences in equilibrium constants, resulting in a 10-fold increase in binding affinity for desialylated hTf at pH 5.9. The changes in hTf sialylation apparently result in tuning of the stability of the conformational state, which in turn contributes to the stability of the diferric hTf. The observed differences in the conditional thermodynamic equilibrium constants suggest that the desialylated protein has a higher preference for diferric hTf over monoferric hTf species down to pH 6.5, which may also influence the interaction with transferrin receptors that preferentially bind to diferric hTf. The results suggest a link between changes in hTf glycan structure and alterations in iron binding equilibrium associated with tissue acidosis.

Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches

Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.

Investigation of iron release from the N- and C-lobes of human serum transferrin by quantum chemical calculations

Cluster models of iron binding sites of the N- and C-lobes highlights the inequivalence of each lobe in iron release.

Conformational transitions of caspase-6 in substrate-induced activation process explored by perturbation-response scanning combined with targeted molecular dynamics

Caspase-6 participates in a series of neurodegenerative pathways, and has aroused widespread attentions as a promising molecular target for the treatment of neurodegeneration. Caspase-6 is a homodimer with 6 central-stranded β-sheets and 5 α-helices in each monomer. Previous crystallographic studies suggested that the 60′s, 90′s and 130′s helices of caspase-6 undergo a distinctive conformational transition upon substrate binding. Although the caspase-6 structures in apo and active states have been determined, the conformational transition process between the two states remains poorly understood. In this work, perturbation-response scanning (PRS) combined with targeted molecular dynamics (TMD) simulations was employed to unravel the atomistic mechanism of the dynamic conformational transitions underlying the substrate-induced activation process of caspase-6. The results showed that the conformational transition of caspase-6 from apo to active states is mainly characterized by structural rearrangements of the substrate-binding site as well as the conformational changes of 60′s and 130′s extended helices. The H-bond interactions between L1, 130′s helix and 90′s helix are proved to be key determinant factors for substrate-induced conformational transition. These findings provide valuable insights into the activation mechanism of caspase-6 as well as the molecular design of caspase-6 inhibitors.

A Coarse-Grained Methodology Identifies Intrinsic Mechanisms That Dissociate Interacting Protein Pairs

We address the problem of triggering dissociation events between proteins that have formed a complex. We have collected a set of 25 non-redundant, functionally diverse protein complexes having high-resolution three-dimensional structures in both the unbound and bound forms. We unify elastic network models with perturbation response scanning (PRS) methodology as an efficient approach for predicting residues that have the propensity to trigger dissociation of an interacting protein pair, using the three-dimensional structures of the bound and unbound proteins as input. PRS reveals that while for a group of protein pairs, residues involved in the conformational shifts are confined to regions with large motions, there are others where they originate from parts of the protein unaffected structurally by binding. Strikingly, only a few of the complexes have interface residues responsible for dissociation. We find two main modes of response: In one mode, remote control of dissociation in which disruption of the electrostatic potential distribution along protein surfaces play the major role; in the alternative mode, mechanical control of dissociation by remote residues prevail. In the former, dissociation is triggered by changes in the local environment of the protein, e.g., pH or ionic strength, while in the latter, specific perturbations arriving at the controlling residues, e.g., via binding to a third interacting partner is required for decomplexation. We resolve the observations by relying on an electromechanical coupling model which reduces to the usual elastic network result in the limit of the lack of coupling. We validate the approach by illustrating the biological significance of top residues selected by PRS on select cases where we show that the residues whose perturbation leads to the observed conformational changes correspond to either functionally important or highly conserved residues in the complex.

Molecular Simulations and Network Modeling Reveal an Allosteric Signaling in the SARS-CoV-2 Spike Proteins

The development of computational strategies for the quantitative characterization of the functional mechanisms of SARS-CoV-2 spike proteins is of paramount importance in efforts to accelerate the discovery of novel therapeutic agents and vaccines combating the COVID-19 pandemic. Structural and biophysical studies have recently characterized the conformational landscapes of the SARS-CoV-2 spike glycoproteins in the prefusion form, revealing a spectrum of stable and more dynamic states. By employing molecular simulations and network modeling approaches, this study systematically examined functional dynamics and identified the regulatory centers of allosteric interactions for distinct functional states of the wild-type and mutant variants of the SARS-CoV-2 prefusion spike trimer. This study presents evidence that the SARS-CoV-2 spike protein can function as an allosteric regulatory engine that fluctuates between dynamically distinct functional states. Perturbation-based modeling of the interaction networks revealed a key role of the cross-talk between the effector hotspots in the receptor binding domain and the fusion peptide proximal region of the SARS-CoV-2 spike protein. The results have shown that the allosteric hotspots of the interaction networks in the SARS-CoV-2 spike protein can control the dynamic switching between functional conformational states that are associated with virus entry to the host receptor. This study offers a useful and novel perspective on the underlying mechanisms of the SARS-CoV-2 spike protein through the lens of allosteric signaling as a regulatory apparatus of virus transmission that could open up opportunities for targeted allosteric drug discovery against SARS-CoV-2 proteins and contribute to the rapid response to the current and potential future pandemic scenarios.

Perturb-Scan-Pull: A Novel Method Facilitating Conformational Transitions in Proteins

Conformational transitions in proteins facilitate precise physiological functions. Therefore, it is crucial to understand the mechanisms underlying these processes to modulate protein function. Yet, studying structural and dynamical properties of proteins is notoriously challenging due to the complexity of the underlying potential energy surfaces (PES). We have previously developed the perturbation-response scanning (PRS) method to identify key residues that participate in the communication network responsible for specific conformational transitions. PRS is based on a residue-by-residue scan of the protein to determine the subset of residues/forces which provide the closest conformational change leading to a target conformational state, inasmuch as linear response theory applies to these motions. Here, we develop a novel method to further evaluate if conformational transitions may be triggered on the PES. We aim to study functionally relevant conformational transitions in proteins by using results obtained from PRS and feeding them as inputs to steered molecular dynamics simulations. The success and the transferability of the method are evaluated on three protein systems having different complexities of motion on the PES: calmodulin, adenylate kinase, and bacterial ferric binding protein. We find that the method captures the target conformation, while providing key residues and the optimum paths with relatively low free energy profiles.

Biophysical simulations and structure-based modeling of residue interaction networks in the tumor suppressor proteins reveal functional role of cancer mutation hotspots in molecular communication

In the current study, we have combined molecular simulations and energetic analysis with dynamics-based network modeling and perturbation response scanning to determine molecular signatures of mutational hotspot residues in the p53, PTEN, and SMAD4 tumor suppressor proteins. By examining structure, energetics and dynamics of these proteins, we have shown that inactivating mutations preferentially target a group of structurally stable residues that play a fundamental role in global propagation of dynamic fluctuations and mediating allosteric interaction networks. Through integration of long-range perturbation dynamics and network-based approaches, we have quantified allosteric potential of residues in the studied proteins. The results have revealed that mutational hotspot sites often correspond to high centrality mediating centers of the residue interaction networks that are responsible for coordination of global dynamic changes and allosteric signaling. Our findings have also suggested that structurally stable mutational hotpots can act as major effectors of allosteric interactions and mutations in these positions are typically associated with severe phenotype. Modeling of shortest inter-residue pathways has shown that mutational hotspot sites can also serve as key mediating bridges of allosteric communication in the p53 and PTEN protein structures. Multiple regression models have indicated that functional significance of mutational hotspots can be strongly associated with the network signatures serving as robust predictors of critical regulatory positions responsible for loss-of-function phenotype. The results of this computational investigation are compared with the experimental studies and reveal molecular signatures of mutational hotspots, providing a plausible rationale for explaining and localizing disease-causing mutations in tumor suppressor genes.

Computational approaches for deciphering the equilibrium and kinetic properties of iron transport proteins

With the advances in three-dimensional structure determination techniques, high quality structures of the iron transport proteins transferrin and the bacterial ferric binding protein (FbpA) have been deposited in the past decade. These are proteins of relatively large size, and developments in hardware and software have only recently made it possible to study their dynamics using standard computational resources. We review computational techniques towards understanding the equilibrium and kinetic properties of iron transport proteins under different environmental conditions. At the level of detail that requires quantum chemical treatments, the octahedral geometry around iron has been scrutinized and it has been established that the iron coordinating tyrosines are in an unusual deprotonated state. At the atomistic level, both the N-lobe and the full bilobal structure of transferrin have been studied under varying conditions of pH, ionic strength and binding of other metal ions by molecular dynamics (MD) simulations. These studies have allowed questions to be answered, among others, on the function of second shell residues in iron release, the role of synergistic anions in preparing the active site for iron binding, and the differences between the kinetics of the N- and the C-lobe. MD simulations on FbpA have led to the detailed observation of the binding kinetics of phosphate to the apo form, and to the conformational preferences of the holo form under conditions mimicking the environmental niches provided by the periplasmic space. To study the dynamics of these proteins with their receptors, one must resort to coarse-grained methodologies, since these systems are prohibitively large for atomistic simulations. A study of the complex of human transferrin (hTf) with its pathogenic receptor by such methods has revealed a potential mechanistic explanation for the defense mechanism that arises in evolutionary warfare. Meanwhile, the motions in the transferrin receptor bound hTf have been shown to disfavor apo hTf dissociation, explaining why the two proteins remain in complex during the recycling process from the endosome to the cell surface. Open problems and possible technological applications related to metal ion binding-release in iron transport proteins that may be handled by hybrid use of quantum mechanical, MD and coarse-grained approaches are discussed.

Increased substrate affinity in the Escherichia coli L28R dihydrofolate reductase mutant causes trimethoprim resistance

Dihydrofolate reductase (DHFR) is a ubiquitous enzyme with an essential role in cell metabolism. DHFR catalyzes the reduction of dihydrofolate to tetrahydrofolate, which is a precursor for purine and thymidylate synthesis. Several DHFR targeting antifolate drugs including trimethoprim, a competitive antibacterial inhibitor, have therefore been developed and are clinically used. Evolution of resistance against antifolates is a common public health problem rendering these drugs ineffective. To combat the resistance problem, it is important to understand resistance-conferring changes in the DHFR structure and accordingly develop alternative strategies. Here, we structurally and dynamically characterize Escherichia coli DHFR in its wild type (WT) and trimethoprim resistant L28R mutant forms in the presence of the substrate and its inhibitor trimethoprim. We use molecular dynamics simulations to determine the conformational space, loop dynamics and hydrogen bond distributions at the active site of DHFR for the WT and the L28R mutant. We also report their experimental kcat, Km, and Ki values, accompanied by isothermal titration calorimetry measurements of DHFR that distinguish enthalpic and entropic contributions to trimethoprim binding. Although mutations that confer resistance to competitive inhibitors typically make enzymes more promiscuous and decrease affinity to both the substrate and the inhibitor, strikingly, we find that the L28R mutant has a unique resistance mechanism. While the binding affinity differences between the WT and the mutant for the inhibitor and the substrate are small, the newly formed extra hydrogen bonds with the aminobenzoyl glutamate tail of DHF in the L28R mutant leads to increased barriers for the dissociation of the substrate and the product. Therefore, the L28R mutant indirectly gains resistance by enjoying prolonged binding times in the enzyme-substrate complex. While this also leads to slower product release and decreases the catalytic rate of the L28R mutant, the overall effect is the maintenance of a sufficient product formation rate. Finally, the experimental and computational analyses together reveal the changes that occur in the energetic landscape of DHFR upon the resistance-conferring L28R mutation. We show that the negative entropy associated with the binding of trimethoprim in WT DHFR is due to water organization at the binding interface. Our study lays the framework to study structural changes in other trimethoprim resistant DHFR mutants.

Dynamics-based community analysis and perturbation response scanning of allosteric interaction networks in the TRAP1 chaperone structures dissect molecular linkage between conformational asymmetry and sequential ATP hydrolysis

Allosteric interactions of the Hsp90 chaperones with cochaperones and diverse protein clients can often exhibit distinct asymmetric features that determine regulatory mechanisms and cellular functions in many signaling networks. The recent crystal structures of the mitochondrial Hsp90 isoform TRAP1 in complexes with ATP analogs have provided first evidence of significant asymmetry in the closed dimerized state that triggers independent activity of the chaperone protomers, whereby preferential hydrolysis of the buckled protomer is followed by conformational flipping between protomers and hydrolysis of the second protomer. Despite significant insights in structural characterizations of the TRAP1 chaperone, the atomistic details and mechanics of allosteric interactions that couple sequential ATP hydrolysis with asymmetric conformational switching in the TRAP1 protomers remain largely unknown. In this work, we explored atomistic and coarse-grained simulations of the TRAP1 dimer structures in combination with the ensemble-based network modeling and perturbation response scanning of residue interaction networks to probe salient features underlying allosteric signaling mechanism. This study has revealed that key effector sites that orchestrate allosteric interactions occupy the ATP binding region and N-terminal interface of the buckled protomer, whereas the main sensors of allosteric signals that drive functional conformational changes during ATPase cycle are consolidated near the client binding region of the straight protomer, channeling the energy of ATP hydrolysis for client remodeling. The community decomposition analysis of the interaction networks and reconstruction of allosteric communication pathways in the TRAP1 structures have quantified mechanism of allosteric regulation, revealing control points and interactions that coordinate asymmetric switching during ATP hydrolysis.

Allosteric Modulation of Human Hsp90α Conformational Dynamics

Central to Hsp90's biological function is its ability to interconvert between various conformational states. Drug targeting of Hsp90's regulatory mechanisms, including its modulation by cochaperone association, presents as an attractive therapeutic strategy for Hsp90 associated pathologies. In this study, we utilized homology modeling techniques to calculate full-length structures of human Hsp90α in closed and partially open conformations and used these structures as a basis for several molecular dynamics based analyses aimed at elucidating allosteric mechanisms and modulation sites in human Hsp90α. Atomistic simulations demonstrated that bound adenosine triphosphate (ATP) stabilizes the dimer by "tensing" each protomer, while adenosine diphosphate (ADP) and apo configurations "relax" the complex by increasing global flexibility, the former case resulting in a fully open "v-like" conformation. Dynamic residue network analysis revealed regions of the protein involved in intraprotein communication and identified several key communication hubs that correlate with known functional sites. Pairwise comparison of betweenness centrality, shortest path, and residue fluctuations revealed that a proportional relationship exists between the latter two measurables and an inverse relationship between these two and betweenness centrality. This analysis showed how protein flexibility, degree of compactness, and the distance cutoff used for network construction influence the correlations between these metrics. These findings are novel and suggest shortest path and betweenness centrality to be more relevant quantities to follow for detecting functional residues in proteins compared to residue fluctuations. Perturbation response scanning analysis identified several potential residue sites capable of modulating conformational change in favor of interstate conversion. For the ATP-bound open conformation, these sites were found to overlap with known Aha1 and client binding sites, demonstrating how naturally occurring forces associated with cofactor binding could allosterically modulate conformational dynamics.

Perturbation-Response Scanning Reveals Key Residues for Allosteric Control in Hsp70

Hsp70 molecular chaperones play an important role in maintaining cellular homeostasis, and are implicated in a wide array of cellular processes, including protein recovery from aggregates, cross-membrane protein translocation, and protein biogenesis. Hsp70 consists of two domains, a nucleotide binding domain (NBD) and a substrate binding domain (SBD), each of which communicates via an allosteric mechanism such that the protein interconverts between two functional states, an ATP-bound open conformation and an ADP-bound closed conformation. The exact mechanism for interstate conversion is not as yet fully understood. However, the ligand-bound states of the NBD and SBD as well as interactions with cochaperones such as DnaJ and nucleotide exchange factor are thought to play crucial regulatory roles. In this study, we apply the perturbation-response scanning (PRS) method in combination with molecular dynamics simulations as a computational tool for the identification of allosteric hot residues in the large multidomain Hsp70 protein. We find evidence in support of the hypothesis that substrate binding triggers ATP hydrolysis and that the ADP-substrate complex favors interstate conversion to the closed state. Furthermore, our data are in agreement with the proposal that there is an allosterically active intermediate state between the open and closed states and vice versa, as we find evidence that ATP binding to the closed structure and peptide binding to the open structure allosterically "activate" the respective complexes. We conclude our analysis by showing how our PRS data fit the current opinion on the Hsp70 conformational cycle and present several allosteric hot residues that may provide a platform for further studies to gain additional insight into Hsp70 allostery.