Computational alanine scanning of protein-protein interfaces

Thermodynamic Details of Pinholin S2168 Activation Revealed Using Alchemical Free Energy Simulations

Pinholin S2168 is a viral integral membrane protein whose function is to form nanoscopic "pinholes" in bacterial cell membranes to induce cell lysis as part of the viral replication cycle. Pinholin can transition from an inactive to an active conformation by exposing a transmembrane domain (TMD1) to the extracellular fluid. Upon activation, several copies of the protein assemble via interactions among a second transmembrane domain (TMD2) to form a single pore, thus hastening cell lysis and viral escape. The following experiments provide conformational descriptors of pinholin in active and inactive states and elucidate the molecular driving forces that control pinholin activity. In the present study, molecular dynamics (MD) simulations have been used to refine experimentally derived conformational descriptors into an atomistically detailed model of irsS2168, an antiholin mutant. To provide additional details about the thermodynamics of pinholin activation and to overcome large intrinsic kinetic barriers to activation, alchemical free energy simulations have been conducted. Alchemical mutations reveal the change in folding free energy upon mutation. The results suggest that alchemical mutations are an effective tool to rationalize experimental observations and predict the effects of site mutations on conformational states for proteins integrated into lipid bilayers. S16F, A17Q, A17Q+G21Q, and A17Q+G21Q+G14Q mutants reveal how changes in hydrophilicity and disruption of the glycine zipper motif influence pinholin's thermodynamic equilibrium, favoring the active conformation. These findings align with experimental observations from DEER spectroscopy, demonstrating that mutations increasing the hydrophilicity of TMD1 promote activation by making TMD1 more likely to exit the membrane and enter the extracellular fluid.

Binding characteristics and structural dynamics of two general odorant-binding proteins with plant volatiles in the olfactory recognition of Glyphodes pyloalis

Glyphodes pyloalis Walker (Lepidoptera: Pyralidae) is the most destructive pest, causing severe damage to mulberry production in China's sericulture industry. The insecticide application in mulberry orchards poses a significant risk of poisoning to Bombyx mori. Shifting from insecticides to odor attractants is a beneficial alternative, but not much data is available on the olfactory system of G. pyloalis. We identified 114 chemosensory genes from the antennal transcriptome database of G. pyloalis, with 18 odorant-binding protein (OBP) and 17 chemosensory protein (CSP) genes significantly expressed in the antennae. Ligand-binding assays for two antennae-biased expressed general odorant-binding proteins (GOBPs) showed high binding affinities of GOBP1 to hexadecanal, β-ionone, and 2-ethylhexyl acrylate, while GOBP2 exhibited binding to 4-tert-octylphenol, benzyl benzoate, β-ionone, and farnesol. Computational simulations indicated that van der Waal forces predominantly contributed to the binding free energy in the binding processes of complexes. Among them, Phe12 of GOBP1 and Phe19 of GOBP2 were demonstrated to play crucial roles in their bindings to plant volatiles using site-directed mutagenesis experiments. Moreover, hexadecanal and β-ionone attracted G. pyloalis male moths in the behavioral assays, while none of the candidate plant volatiles significantly affected female moths. Our findings provide a comprehensive understanding of the molecular mechanisms underlying olfactory recognition in G. pyloalis, setting the groundwork for novel mulberry pests control strategies based on insect olfaction.

Transient Structural Properties of the Rho GDP-Dissociation Inhibitor

Rho GTPases, master spatial regulators of a wide range of cellular processes, are orchestrated by complex formation with guanine nucleotide dissociation inhibitors (RhoGDIs). These have been thought to possess an unstructured N-terminus that inhibits nucleotide exchange of their client upon binding/folding. Via NMR analyses, molecular dynamics simulations, and biochemical assays, we reveal instead pertinent structural properties transiently maintained both, in the presence and absence of the client, imposed onto the terminus context-specifically by modulating interactions with the surface of the folded C-terminal domain. These observations revise the long-standing textbook picture of the GTPases' mechanism of membrane extraction. Rather than by a disorder-to-order transition upon binding of an inhibitory peptide, the intricate and highly selective extraction process of RhoGTPases is orchestrated via a dynamic ensemble bearing preformed transient structural properties, suitably modulated by the specific surrounding along the multi-step process.

Stability Oracle: a structure-based graph-transformer framework for identifying stabilizing mutations

Engineering stabilized proteins is a fundamental challenge in the development of industrial and pharmaceutical biotechnologies. We present Stability Oracle: a structure-based graph-transformer framework that achieves SOTA performance on accurately identifying thermodynamically stabilizing mutations. Our framework introduces several innovations to overcome well-known challenges in data scarcity and bias, generalization, and computation time, such as: Thermodynamic Permutations for data augmentation, structural amino acid embeddings to model a mutation with a single structure, a protein structure-specific attention-bias mechanism that makes transformers a viable alternative to graph neural networks. We provide training/test splits that mitigate data leakage and ensure proper model evaluation. Furthermore, to examine our data engineering contributions, we fine-tune ESM2 representations (Prostata-IFML) and achieve SOTA for sequence-based models. Notably, Stability Oracle outperforms Prostata-IFML even though it was pretrained on 2000X less proteins and has 548X less parameters. Our framework establishes a path for fine-tuning structure-based transformers to virtually any phenotype, a necessary task for accelerating the development of protein-based biotechnologies.

Temperature effect in the inhibition of PLA2 activity of Bothrops brazili venom by Rosmarinic and Chlorogenic acids, experimental and computational approaches

Myotoxicity caused by snakebite envenoming emerges as one of the main problems of ophidic accidents as it is not well neutralized by the current serum therapy. A promising alternative is to search for efficient small molecule inhibitors that can act against multiple venom components. Phospholipase A2 (PLA2) is frequently found in snake venom and is usually associated with myotoxicity. Thus it represents an excellent target for the search of new treatments. This work reports the effect of temperature in the inhibition of catalytic properties of PLA2 from Bothrops brazili venom by Rosmarinic (RSM) and Chlorogenic (CHL) acids through experimental and computational approaches. Three temperatures were evaluated (25, 37 and 50 °C). In the experimental section, enzymatic assays showed that RSM is a better inhibitor in all three temperatures. At 50 °C, the inhibition efficiency decayed significantly for both acids. Docking studies revealed that both ligands bind to the hydrophobic channel of the protein dimer where the phospholipid binds in the catalytic process, interacting with several functional residues. In this context, RSM presents better interaction energies due to stronger interactions with chain B of the dimer. Molecular dynamics simulations showed that RSM can establish selective interactions with ARG112B of PLA2, which is located next to residues of the putative Membrane Disruption Site in PLA2-like structures. The affinity of RSM and CHL acids towards PLA2 is mainly driven by electrostatic interactions, especially salt bridge interactions established with residues ARG33B (for CHL) and ARG112B (RSM) and hydrogen bonds with residue ASP89A. The inability of CHL to establish a stable interaction with ARG112B was identified as the reason for its lower inhibition efficiency compared to RSM at the three temperatures. Furthermore, extensive structural analysis was performed to explain the lower inhibition efficiency at 50 °C for both ligands. The analysis performed in this work provides important information for the future design of new inhibitors.Communicated by Ramaswamy H. Sarma.

ProBASS - a language model with sequence and structural features for predicting the effect of mutations on binding affinity

Protein-protein interactions (PPIs) govern virtually all cellular processes. Even a single mutation within PPI can significantly influence overall protein functionality and potentially lead to various types of diseases. To date, numerous approaches have emerged for predicting the change in free energy of binding (ΔΔGbind) resulting from mutations, yet the majority of these methods lack precision. In recent years, protein language models (PLMs) have been developed and shown powerful predictive capabilities by leveraging both sequence and structural data from protein-protein complexes. Yet, PLMs have not been optimized specifically for predicting ΔΔGbind. We developed an approach to predict effects of mutations on PPI binding affinity based on two most advanced protein language models ESM2 and ESM-IF1 that incorporate PPI sequence and structural features, respectively. We used the two models to generate embeddings for each PPI mutant and subsequently fine-tuned our model by training on a large dataset of experimental ΔΔGbind values. Our model, ProBASS (Protein Binding Affinity from Structure and Sequence) achieved a correlation with experimental ΔΔGbind values of 0.83 ± 0.05 for single mutations and 0.69 ± 0.04 for double mutations when model training and testing was done on the same PDB. Moreover, ProBASS exhibited very high correlation (0.81 ± 0.02) between prediction and experiment when training and testing was performed on a dataset containing 2325 single mutations in 132 PPIs. ProBASS surpasses the state-of-the-art methods in correlation with experimental data and could be further trained as more experimental data becomes available. Our results demonstrate that the integration of extensive datasets containing ΔΔGbind values across multiple PPIs to refine the pre-trained PLMs represents a successful approach for achieving a precise and broadly applicable model for ΔΔGbind prediction, greatly facilitating future protein engineering and design studies.

Thermostable WW-Domain Scaffold to Design Functional β-Sheet Miniproteins

There has been a recent surge in the design of miniproteins for medicinal chemistry, biomaterial design, or synthetic biology. In particular, there is an interest in peptide scaffolds that fold reliably, predictably, and with solid stability. In this article, we present the design of a highly thermostable WW domain, a three-stranded β-sheet motif, with a superior melting temperature of about 90 °C to serve as a core scaffold onto which receptor-like properties can be grafted. We have performed specific rounds of sequence iteration on a WW-domain consensus sequence to decipher sequence positions that affect structural and, thus, thermal stability. We identified a sequence-structure relationship that yields a highly thermostable WW-domain scaffold. High-resolution NMR spectroscopy was applied, which enabled the identification of structural features at the atomic scale that contribute to this high thermostability. Finally, we grafted the binding motifs of the three WW-domain groups─Group I, Group II/III, and Group IV─and organophosphate and metal binding onto the highly thermostable WW-domain scaffold and obtained thermostable de novo WW domains that indeed display the different binding modes that were intended. The organophosphate-binding WW domains exhibit melting temperatures that are up to 34 K higher than previously reported top-down designs. These results impressively demonstrate that the highly thermostable WW-domain core scaffold is a solid platform for the design of discrete and reliably folding functional β-sheet peptide miniproteins, providing an essential addition to the toolbox of peptide scaffolds previously used in synthetic biology and material design.

Validation of aminodeoxychorismate synthase and anthranilate synthase as novel targets for bispecific antibiotics inhibiting conserved protein-protein interactions

Multi-resistant bacteria are a rapidly emerging threat to modern medicine. It is thus essential to identify and validate novel antibacterial targets that promise high robustness against resistance-mediating mutations. This can be achieved by simultaneously targeting several conserved function-determining protein-protein interactions in enzyme complexes from prokaryotic primary metabolism. Here, we selected two evolutionary related glutamine amidotransferase complexes, aminodeoxychorismate synthase and anthranilate synthase, that are required for the biosynthesis of folate and tryptophan in most prokaryotic organisms. Both enzymes rely on the interplay of a glutaminase and a synthase subunit that is conferred by a highly conserved subunit interface. Consequently, inhibiting subunit association in both enzymes by one competing bispecific inhibitor has the potential to suppress bacterial proliferation. We comprehensively verified two conserved interface hot-spot residues as potential inhibitor-binding sites in vitro by demonstrating their crucial role in subunit association and enzymatic activity. For in vivo target validation, we generated genomically modified Escherichia coli strains in which subunit association was disrupted by modifying these central interface residues. The growth of such strains was drastically retarded on liquid and solid minimal medium due to a lack of folate and tryptophan. Remarkably, the bacteriostatic effect was observed even in the presence of heat-inactivated human plasma, demonstrating that accessible host metabolite concentrations do not compensate for the lack of folate and tryptophan within the tested bacterial cells. We conclude that a potential inhibitor targeting both enzyme complexes will be effective against a broad spectrum of pathogens and offer increased resilience against antibiotic resistance.

IMPORTANCE

Antibiotics are indispensable for the treatment of bacterial infections in human and veterinary medicine and are thus a major pillar of modern medicine. However, the exposure of bacteria to antibiotics generates an unintentional selective pressure on bacterial assemblies that over time promotes the development or acquisition of resistance mechanisms, allowing pathogens to escape the treatment. In that manner, humanity is in an ever-lasting race with pathogens to come up with new treatment options before resistances emerge. In general, antibiotics with novel modes of action require more complex pathogen adaptations as compared to chemical derivates of existing entities, thus delaying the emergence of resistance. In this contribution, we use modified Escherichia coli strains to validate two novel targets required for folate and tryptophan biosynthesis that can potentially be targeted by one and the same bispecific protein-protein interaction inhibitor and promise increased robustness against bacterial resistances.

Pathophysiology of chikungunya virus infection associated with fatal outcomes

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes acute, subacute, and chronic human arthritogenic diseases and, in rare instances, can lead to neurological complications and death. Here, we combined epidemiological, virological, histopathological, cytokine, molecular dynamics, metabolomic, proteomic, and genomic analyses to investigate viral and host factors that contribute to chikungunya-associated (CHIK) death. Our results indicate that CHIK deaths are associated with multi-organ infection, central nervous system damage, and elevated serum levels of pro-inflammatory cytokines and chemokines compared with survivors. The histopathologic, metabolite, and proteomic signatures of CHIK deaths reveal hemodynamic disorders and dysregulated immune responses. The CHIKV East-Central-South-African lineage infecting our study population causes both fatal and survival cases. Additionally, CHIKV infection impairs the integrity of the blood-brain barrier, as evidenced by an increase in permeability and altered tight junction protein expression. Overall, our findings improve the understanding of CHIK pathophysiology and the causes of fatal infections.

Emergence of an Orphan Nitrogenase Protein Following Atmospheric Oxygenation

Molecular innovations within key metabolisms can have profound impacts on element cycling and ecological distribution. Yet, much of the molecular foundations of early evolved enzymes and metabolisms are unknown. Here, we bring one such mystery to relief by probing the birth and evolution of the G-subunit protein, an integral component of certain members of the nitrogenase family, the only enzymes capable of biological nitrogen fixation. The G-subunit is a Paleoproterozoic-age orphan protein that appears more than 1 billion years after the origin of nitrogenases. We show that the G-subunit arose with novel nitrogenase metal dependence and the ecological expansion of nitrogen-fixing microbes following the transition in environmental metal availabilities and atmospheric oxygenation that began ∼2.5 billion years ago. We identify molecular features that suggest early G-subunit proteins mediated cofactor or protein interactions required for novel metal dependency, priming ancient nitrogenases and their hosts to exploit these newly diversified geochemical environments. We further examined the degree of functional specialization in G-subunit evolution with extant and ancestral homologs using laboratory reconstruction experiments. Our results indicate that permanent recruitment of the orphan protein depended on the prior establishment of conserved molecular features and showcase how contingent evolutionary novelties might shape ecologically important microbial innovations.

Prediction of virus-host interactions and identification of hot spot residues of DENV-2 and SH3 domain interactions

Dengue virus, particularly serotype 2 (DENV-2), poses a significant global health threat, and understanding the molecular basis of its interactions with host cell proteins is imperative for developing targeted therapeutic strategies. This study elucidated the interactions between proline-enriched motifs and Src homology 3 (SH3) domain. The SH3 domain is pivotal in mediating protein-protein interactions, particularly by recognizing and binding to proline-rich regions in partner proteins. Through a computational pipeline, we analyzed the interactions and binding modes of proline-enriched motifs with SH3 domains, identified new potential DENV-2 interactions with the SH3 domain, and revealed potential hot spot residues, underscoring their significance in the viral life cycle. This comprehensive analysis provides crucial insights into the molecular basis of DENV-2 infection, highlighting conserved and serotype-specific interactions. The identified hot spot residues offer potential targets for therapeutic intervention, laying the foundation for developing antiviral strategies against Dengue virus infection. These findings contribute to the broader understanding of viral-host interactions and provide a roadmap for future research on Dengue virus pathogenesis and treatment.

Cytokines inhibitory mechanism of Prunus domestica L. (Plum) peptides as potential immunomodulators against systemic lupus erythematosus: an in-silico screening

Natural bioactive peptides exhibit various chemical and structural properties to enhance the immune response against multiple inflammatory and autoimmune related disorders. The immunomodulatory function and bioactivity of seed peptides show the capability for the development of biotherapeutics that could prevent autoimmune diseases. The aim of current study is to determine the immunomodulatory function of bioactive peptides derived from the seed of plum (Prunus domestica L.) by applying various immunoinformatic approaches. A thorough analysis of forty-one peptides was performed including drug likeliness, pharmacokinetic, and bioactivity profiling studies. Further, molecular docking and molecular dynamics (MD) simulations of screened peptides were carried out with the two interleukin targets (IL-17A and IL-23) of systemic lupus erythematosus (SLE). After the systematic screening, four peptides, namely HLLP, LPLL, LPAGV, and NLPL, were found as potential inhibitors against SLE. Additionally, site-directed mutagenesis analysis was conducted to explore the role of essential amino acid residues in the binding pattern/energy change. Computational alanine screening analysis found that CYS123, CYS121 of IL-17A and ASP270, and SER249 of IL-23 as hot spot residues that could play an important role in the inhibition property of screened peptides. Overall, the methodology described in the study can be utilized for developing unique peptide inhibitors that have a preventative role against SLE.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00188-8.

Putative staphylococcal enterotoxin possesses two common structural motifs for MHC-II binding

Staphylococcus aureus has become a significant cause of health risks in humankind. Staphylococcal superantigens (SAgs) or enterotoxins are the key virulent factors that can exhibit acute diseases to severe life-threatening conditions. Recent literature reports S. aureus has steadily gained new enterotoxin genes over the past few decades. In spite of current knowledge of the established SAgs, several questions on putative enterotoxins are still remaining unanswered. Keeping that in mind, this study sheds light on a putative enterotoxin SEl26 to characterize its structural and functional properties. In-silico analyses indicate its close relation with the conventional SAgs, especially the zinc-binding SAgs. Additionally, important residues that are vital for the T-cell receptor (TcR) and major histocompatibility complex class II (MHC-II) interaction were predicted and compared with established SAgs. Besides, our biochemical analyses exhibited the binding of this putative enterotoxin with MHC-II, followed by regulating pro-inflammatory and anti-inflammatory cytokines.

Structural study of UFL1-UFC1 interaction uncovers the role of UFL1 N-terminal helix in ufmylation

Ufmylation plays a crucial role in various cellular processes including DNA damage response, protein translation, and ER homeostasis. To date, little is known about how the enzymes responsible for ufmylation coordinate their action. Here, we study the details of UFL1 (E3) activity, its binding to UFC1 (E2), and its relation to UBA5 (E1), using a combination of structural modeling, X-ray crystallography, NMR, and biochemical assays. Guided by Alphafold2 models, we generate an active UFL1 fusion construct that includes its partner DDRGK1 and solve the crystal structure of this critical interaction. This fusion construct also unveiled the importance of the UFL1 N-terminal helix for binding to UFC1. The binding site suggested by our UFL1-UFC1 model reveals a conserved interface, and competition between UFL1 and UBA5 for binding to UFC1. This competition changes in the favor of UFL1 following UFM1 charging of UFC1. Altogether, our study reveals a novel, terminal helix-mediated regulatory mechanism, which coordinates the cascade of E1-E2-E3-mediated transfer of UFM1 to its substrate and provides new leads to target this modification.

Streamlined Protein-Protein Interface Loop Mimicry

Cyclic peptides comprising endocyclic organic fragments, "cyclo-organopeptides", can be probes for perturbing protein-protein interactions (PPIs). Finding loop mimics is difficult because of high conformational variability amongst targets. Backbone Matching (BM), introduced here, helps solve this problem in the illustrative cases by facilitating efficient evaluation of virtual cyclo-organopeptide core-structure libraries. Thus, 86 rigid organic fragments were selected to build a library of 602 cyclo-organopeptides comprising Ala and organic parts: "cyclo-{-(Ala)n -organo-}". The central hypothesis is "hit" library members have accessible low energy conformers corresponding to backbone structures of target protein loops, while library members which cannot attain this conformation are probably unworthy of further evaluation. BM thereby prioritizes candidate loop mimics, so that less than 10 cyclo-organopeptides are needed to be prepared to find leads for two illustrative PPIs: iNOS ⋅ SPSB2, and uPA ⋅ uPAR.

A regulatory node involving Gαq, PLCβ, and RGS proteins modulates platelet reactivity to critical agonists

BACKGROUND

Most platelet agonists work through G protein-coupled receptors, activating pathways that involve members of the Gq, Gi, and G12/G13 families of heterotrimeric G proteins. Gq signaling has been shown to be critical for efficient platelet activation. Growing evidence suggests that regulatory mechanisms converge on G protein-coupled receptors and Gq to prevent overly robust platelet reactivity.

OBJECTIVES

To identify and characterize mechanisms by which Gq signaling is regulated in platelets.

METHODS

Based on our prior experience with a Gαi2 variant that escapes regulation by regulator of G protein signaling (RGS) proteins, a Gαq variant was designed with glycine 188 replaced with serine (G188S) and then incorporated into a mouse line so that its effects on platelet activation and thrombus formation could be studied in vitro and in vivo.

RESULTS AND CONCLUSIONS

As predicted, the G188S substitution in Gαq disrupted its interaction with RGS18. Unexpectedly, it also uncoupled PLCβ-3 from activation by platelet agonists as evidenced by a loss rather than a gain of platelet function in vitro and in vivo. Binding studies showed that in addition to preventing the binding of RGS18 to Gαq, the G188S substitution also prevented the binding of PLCβ-3 to Gαq. Structural analysis revealed that G188 resides in the region that is also important for Gαq binding to PLCβ-3 in platelets. We conclude that the Gαq signaling node is more complex than that has been previously understood, suggesting that there is cross-talk between RGS proteins and PLCβ-3 in the context of Gαq signaling.

SARS-CoV-2 infection establishes a stable and age-independent CD8+ T cell response against a dominant nucleocapsid epitope using restricted T cell receptors

The resolution of SARS-CoV-2 replication hinges on cell-mediated immunity, wherein CD8+ T cells play a vital role. Nonetheless, the characterization of the specificity and TCR composition of CD8+ T cells targeting non-spike protein of SARS-CoV-2 before and after infection remains incomplete. Here, we analyzed CD8+ T cells recognizing six epitopes from the SARS-CoV-2 nucleocapsid (N) protein and found that SARS-CoV-2 infection slightly increased the frequencies of N-recognizing CD8+ T cells but significantly enhanced activation-induced proliferation compared to that of the uninfected donors. The frequencies of N-specific CD8+ T cells and their proliferative response to stimulation did not decrease over one year. We identified the N222-230 peptide (LLLDRLNQL, referred to as LLL thereafter) as a dominant epitope that elicited the greatest proliferative response from both convalescent and uninfected donors. Single-cell sequencing of T cell receptors (TCR) from LLL-specific CD8+ T cells revealed highly restricted Vα gene usage (TRAV12-2) with limited CDR3α motifs, supported by structural characterization of the TCR-LLL-HLA-A2 complex. Lastly, transcriptome analysis of LLL-specific CD8+ T cells from donors who had expansion (expanders) or no expansion (non-expanders) after in vitro stimulation identified increased chromatin modification and innate immune functions of CD8+ T cells in non-expanders. These results suggests that SARS-CoV-2 infection induces LLL-specific CD8+ T cell responses with a restricted TCR repertoire.

In silico investigation on the mutational analysis of BRCA1-BARD1 RING domains and its effect on nucleosome recognition and ubiquitination

The BRCA1-BARD1 complex is a crucial tumor suppressor E3 ubiquitin ligase involved in DNA double-stranded break repair. The BRCA1-BARD1 RING domains interact with UBE2D3 through the BRCA1 interface and this complex flexibly tether to the nucleosome core particle (NCP), where BRCA1 and BARD1 interacts with histone H2A and H2B of NCP. Mutations in the BRCA1-BARD1 RING domains have been linked to familial breast and ovarian cancer. Seven mutations were analyzed to understand their effect on the binding interface of protein partners and changes in conformational dynamics. Molecular dynamics simulations revealed that mutant complexes were less conformationally flexible than the wildtype complex. Protein-protein interaction profiling showed the importance of specific molecular interactions, hotspot and hub residues, and some of these were lost in the mutant complexes. Two mutations (BRCA1L51W-K65R and BARD1C53W) hindered significant interaction between protein partners and may prevent signaling for ubiquitination of histones in NCP and other cellular targets. The structural compactness and reduced significant interaction in mutant complexes may be the possible reason of preventing ubiquitination and hinder DNA repair, resulting cancer.

Categorization of hotspots into three types - weak, moderate and strong to distinguish protein-protein versus protein-peptide interactions

Protein-protein and protein-peptide interactions (PPI and PPepI) belong to a similar category of interactions, yet seemingly subtle differences exist among them. To characterize differences between protein-protein (PP) and protein-peptide (PPep) interactions, we have focussed on two important classes of residues-hotspot and anchor residues. Using implicit solvation-based free energy calculations, a very large-scale alanine scanning has been performed on benchmark datasets, consisting of over 5700 interface residues. The differences in the two categories are more pronounced, if the data were divided into three distinct types, namely - weak hotspots (having binding free energy loss upon Ala mutation, ΔΔG, ∼2-10 kcal/mol), moderate hotspots (ΔΔG, ∼10-20 kcal/mol) and strong hotspots (ΔΔG ≥ ∼20 kcal/mol). The analysis suggests that for PPI, weak hotspots are predominantly populated by polar and hydrophobic residues. The distribution shifts towards charged and polar residues for moderate hotspot and charged residues (principally Arg) are overwhelmingly present in the strong hotspot. On the other hand, in the PPepI dataset, the distribution shifts from predominantly hydrophobic and polar (in the weak type) to almost similar preference for polar, hydrophobic and charged residues (in moderate type) and finally the charged residue (Arg) and Trp are mostly occupied in the strong type. The preferred anchor residues in both categories are Arg, Tyr and Leu, possessing bulky side chain and which also strike a delicate balance between side chain flexibility and rigidity. The present knowledge should aid in effective design of biologics, by augmentation or disruption of PPIs with peptides or peptidomimetics.Communicated by Ramaswamy H. Sarma.

Computational and experimental analyses of alanine racemase suggest new avenues for developing allosteric small-molecule antibiotics

Given the ever-present threat of antibacterial resistance, there is an urgent need to identify new antibacterial drugs and targets. One such target is alanine racemase (Alr), an enzyme required for bacterial cell-wall biosynthesis. Alr is an attractive drug target because it is essential for bacterial survival but is absent in humans. Existing drugs targeting Alr lack specificity and have severe side effects. We here investigate alternative mechanisms of Alr inhibition. Alr functions exclusively as an obligate homodimer, so we probed seven conserved interactions on the dimer interface, distant from the enzymatic active site, to identify possible allosteric influences on activity. Using the Alr from Mycobacterium tuberculosis (MT) as a model, we found that the Lys261/Asp135 salt bridge is critical for catalytic activity. The Lys261Ala mutation completely inactivated the enzyme, and the Asp135Ala mutation reduced catalytic activity eight-fold. Further investigation suggested a potential drug-binding site near the Lys261/Asp135 salt bridge that may be useful for allosteric drug discovery.

Elucidating Residue-Level Determinants Affecting Dimerization of Ebola Virus Matrix Protein Using High-Throughput Site Saturation Mutagenesis and Biophysical Approaches

The Ebola virus (EBOV) is a filamentous virus that acquires its lipid envelope from the plasma membrane of the host cell it infects. EBOV assembly and budding from the host cell plasma membrane are mediated by a peripheral protein, known as the matrix protein VP40. VP40 is a 326 amino acid protein with two domains that are loosely linked. The VP40 N-terminal domain (NTD) contains a hydrophobic α-helix, which mediates VP40 dimerization. The VP40 C-terminal domain has a cationic patch, which mediates interactions with anionic lipids and a hydrophobic region that mediates VP40 dimer-dimer interactions. The VP40 dimer is necessary for trafficking to the plasma membrane inner leaflet and interactions with anionic lipids to mediate the VP40 assembly and oligomerization. Despite significant structural information available on the VP40 dimer structure, little is known on how the VP40 dimer is stabilized and how residues outside the NTD hydrophobic portion of the α-helical dimer interface contribute to dimer stability. To better understand how VP40 dimer stability is maintained, we performed computational studies using per-residue energy decomposition and site saturation mutagenesis. These studies revealed a number of novel keystone residues for VP40 dimer stability just adjacent to the α-helical dimer interface as well as distant residues in the VP40 CTD that can stabilize the VP40 dimer form. Experimental studies with representative VP40 mutants in vitro and in cells were performed to test computational predictions that reveal residues that alter VP40 dimer stability. Taken together, these studies provide important biophysical insights into VP40 dimerization and may be useful in strategies to weaken or alter the VP40 dimer structure as a means of inhibiting the EBOV assembly.

In silico mutagenesis-based designing of oncogenic SHP2 peptide to inhibit cancer progression

Cancer is among the top causes of death, accounting for an estimated 9.6 million deaths in 2018, it appeared that approximately 500,000 people die from cancer in the United States alone annually. The SHP2 plays a major role in regulation of cell growth, proliferation, and differentiation, and functional upregulation of this enzyme is linked to oncogenesis and developmental disorders. SHP2 activity has been linked to several cancer types for which no drugs are currently available. In our study, we aimed to design peptide inhibitors against the SHP2 mutant. The crystal structure of the human Src SH2-PQpYEEIPI peptide mutant was downloaded from the protein databank. We generated several peptides from the native wild peptide using an in silico mutagenesis method, which showed that changes (P302W, Y304F, E306Q, and Q303A) might boost the peptide's affinity for binding to SHP2. Furthermore, the dynamical stability and binding affinities of the mutated peptide were confirmed using Molecular dynamics simulation and Molecular Mechanics with Generalized Born and Surface Area Solvation free energy calculations. The proposed substitution greatly enhanced the binding affinity at the residue level, according to a study that decomposed energy into its component residues. Our proposed peptide may prevent the spread of cancer by inhibiting SHP2, according to our detailed analyses of binding affinities.

Germline-encoded amino acid-binding motifs drive immunodominant public antibody responses

Despite the vast diversity of the antibody repertoire, infected individuals often mount antibody responses to precisely the same epitopes within antigens. The immunological mechanisms underpinning this phenomenon remain unknown. By mapping 376 immunodominant "public epitopes" at high resolution and characterizing several of their cognate antibodies, we concluded that germline-encoded sequences in antibodies drive recurrent recognition. Systematic analysis of antibody-antigen structures uncovered 18 human and 21 partially overlapping mouse germline-encoded amino acid-binding (GRAB) motifs within heavy and light V gene segments that in case studies proved critical for public epitope recognition. GRAB motifs represent a fundamental component of the immune system's architecture that promotes recognition of pathogens and leads to species-specific public antibody responses that can exert selective pressure on pathogens.

De novo design of modular peptide-binding proteins by superhelical matching

General approaches for designing sequence-specific peptide-binding proteins would have wide utility in proteomics and synthetic biology. However, designing peptide-binding proteins is challenging, as most peptides do not have defined structures in isolation, and hydrogen bonds must be made to the buried polar groups in the peptide backbone1-3. Here, inspired by natural and re-engineered protein-peptide systems4-11, we set out to design proteins made out of repeating units that bind peptides with repeating sequences, with a one-to-one correspondence between the repeat units of the protein and those of the peptide. We use geometric hashing to identify protein backbones and peptide-docking arrangements that are compatible with bidentate hydrogen bonds between the side chains of the protein and the peptide backbone12. The remainder of the protein sequence is then optimized for folding and peptide binding. We design repeat proteins to bind to six different tripeptide-repeat sequences in polyproline II conformations. The proteins are hyperstable and bind to four to six tandem repeats of their tripeptide targets with nanomolar to picomolar affinities in vitro and in living cells. Crystal structures reveal repeating interactions between protein and peptide interactions as designed, including ladders of hydrogen bonds from protein side chains to peptide backbones. By redesigning the binding interfaces of individual repeat units, specificity can be achieved for non-repeating peptide sequences and for disordered regions of native proteins.

Orthogonal threading-through-β-sheet design of lung cancer EGFR extracellular domain-derived peptidic mimotopes binding to anti-EGFR antibody

Human epidermal growth factor receptor (EGFR) has been established as a therapeutic target of lung cancer and other diverse tumors. The antibody drug Cetuximab has been developed to target the third subdomain III (TSDIII) of EGFR extracellular domain (ECD) by competitively inhibiting epidermal growth factor binding. In this study, we performed systematic investigation on the crystal complex structure of EGFR ECD domain with Cetuximab to create a residue importance profile for the TSDIII subdomain, based on which a number of U-shaped, double-stranded linear peptides were derived and cyclized to orthogonally thread through most hotspot residues and many responsible residues within the TSDIII β-sheet plane; they represent mimotopes of the key antibody-recognition site of TSDIII subdomain. Computational analyses revealed that these linear peptides cannot spontaneously fold to the desired conformation in free state due to their intrinsic flexibility. Cell-free assays confirmed that the stapling can considerably improve the binding affinity of linear peptides to Cetuximab by up to 18-fold. The cOrt1 [3-18] cyclic peptide was measured to have the highest affinity in all designed linear and cyclic peptides.

Design of a protease-activated PD-L1 inhibitor

Immune checkpoint inhibitors that bind to the cell surface receptor PD-L1 are effective anti-cancer agents but suffer from immune-related adverse events as PD-L1 is expressed on both healthy and cancer cells. To mitigate toxicity, researchers are testing prodrugs that have low affinity for checkpoint targets until activated with proteases enriched in the tumor microenvironment. Here, we engineer a prodrug form of a PD-L1 inhibitor. The inhibitor is a soluble PD-1 mimetic that was previously engineered to have high affinity for PD-L1. In the basal state, the binding surface of the PD-1 mimetic is masked by fusing it to a soluble variant of its natural ligand, PD-L1. Proteolytic cleavage of the linker that connects the mask to the inhibitor activates the molecule. To optimize the mask so that it effectively blocks binding to PD-L1 but releases upon cleavage, we tested a set of mutants with varied affinity for the inhibitor. The top-performing mask reduces the affinity of the prodrug for PD-L1 120-fold, and binding is nearly fully recovered upon cleavage. In a cell-based assay measuring inhibition of the PD-1:PD-L1 interaction on the surface of cells, the IC50s of the masked inhibitors were up to 40-fold higher than their protease-treated counterparts. The changes in activity we observe upon protease treatment are comparable to systems currently tested in the clinic and provide evidence that natural binding partners are an excellent starting point for creating a prodrug.

Molecular Simulation Study on the Interaction between Porcine CR1-like and C3b

The molecular basis of porcine red blood cell immune adhesion function stems from the complement receptor type 1-like (CR1-like) on its cell membrane. The ligand for CR1-like is C3b, which is produced by the cleavage of complement C3; however, the molecular mechanism of the immune adhesion of porcine erythrocytes is still unclear. Here, homology modeling was used to construct three-dimensional models of C3b and two fragments of CR1-like. An interaction model of C3b-CR1-like was constructed by molecular docking, and molecular structure optimization was achieved using molecular dynamics simulation. A simulated alanine mutation scan revealed that the amino acids Tyr761, Arg763, Phe765, Thr789, and Val873 of CR1-like SCR 12-14 and the amino acid residues Tyr1210, Asn1244, Val1249, Thr1253, Tyr1267, Val1322, and Val1339 of CR1-like SCR 19-21 are key residues involved in the interaction of porcine C3b with CR1-like. This study investigated the interaction between porcine CR1-like and C3b using molecular simulation to clarify the molecular mechanism of the immune adhesion of porcine erythrocytes.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Molecular dynamics simulations reveal the effect of mutations in the RING domains of BRCA1-BARD1 complex and its relevance to the prognosis of breast cancer

The N-terminal RING-RING domain of BRCA1-BARD1 is an E3 ubiquitin ligase complex that plays a critical role in tumor suppression through DNA double stranded repair mechanism. Mutations in the BRCA1-BARD1 heterodimer RING domains were found to have an association with breast and ovarian cancer by a way of hampering the E3 ubiquitin ligase activity. Herein, the molecular mechanism of interaction, conformational change due to the specific mutations on the BRCA1-BARD1 complex at atomic level has been examined by employing molecular modeling techniques. Sixteen mutations have been selected for the study. Molecular dynamics simulation results reveal that the mutant complexes have more local perturbation with a high residual fluctuation in the zinc binding sites and central helix. A few of the BRCA1 (V11A, I21V, I42V, R71G, I31M and L51W) mutants have been experimentally identified that do not impair E3 ligase activity, display an enhanced number of H-bonds and non-bonded contacts at the interacting interface as revealed by MD simulation. The mutation of BRCA1 (C61G, C64Y, C39Y and C24R) and BARD1 (C53W, C71Y and C83R) zinc binding residues displayed a smaller number of significant H-bonds, other interactions and also loss of some of the hotspot residues. Additionally, most of the mutant complexes display relatively lower electrostatic energy, H-bonding and total stabilizing energy as compared to wild-type. The current study attempts to unravel the role of BRCA1-BARD1 mutations and delineates the structural and conformational dynamics in the progression of breast cancer.Communicated by Ramaswamy H. Sarma.

Coupled folding-upon-binding of human tumor suppressor MIG6 to lung cancer EGFR kinase domain and molecular trimming/stapling of MIG6-derived β-hairpins to target the coupling event

Human epidermal growth factor receptor (EGFR) is involved in strong association with malignant proliferation, which has been shown to play a central role in the development and progression of non-small cell lung cancer and other solid tumors. The tumor-suppressor protein MIG6 is a negative regulator of EGFR kinase activity by binding at the activation interface of asymmetric dimer of EGFR kinase domain to disrupt EGFR dimerization and then inactivate the kinase. The protein adopts two discrete fragments 1 and 2 to directly interact with EGFR. It is revealed that the MIG6 fragment 2 is intrinsically disordered in free unbound state, but would fold into a well-structured β-hairpin when binding to EGFR, thus characterized by a so-called coupled folding-upon-binding process, which can be regarded as a compromise between favorable direct readout and unfavorable indirect readout. Here, a 23-mer F2P peptide was derived from MIG6 fragment 2, trimmed into a 17-mer tF2P peptide that contains the binding hotspot region of the fragment 2, and then constrained with an ordered hairpin conformation in free unbound state by disulfide stapling, finally resulting in a rationally stapled/trimmed stF2P peptide that largely minimizes the unfavorable indirect readout effect upon its binding to EGFR kinase domain, with affinity improved considerably upon the trimming and stapling/trimming. These rationally designed β-hairpin peptides may be further exploited as potent anti-lung cancer agents to target the activation event of EGFR dimerization.

In silico engineering a CD80 variant with increased affinity to CTLA-4 and decreased affinity to CD28 for optimized cancer immunotherapy

CD80 or cluster of differentiation 80, also known as B7-1, is a member of the immunoglobulin super family, which binds to CTLA-4 and CD28 T cell receptors and induces inhibitory and inductive signals respectively. Although CTLA-4 and CD28 receptors belong to the same protein family, slight differences in their structures leads to CD80 having a higher binding affinity to CTLA-4 (-14.55 kcal/mol) compared with CD28(-12.51 kcal/mol). In this study, we constructed a variant of CD80 protein with increased binding affinity to CTLA-4 and decreased binding affinity to CD28. This variant has no signaling capability, and can act as a cap for these receptors to protect them from natural CD80 proteins existing in the body. The first step was the evolutionary and alanine scanning analysis of CD80 protein to determine conserved regions in this protein. Next, complex alanine scanning technique was employed to determine CD80 protein hotspots in CD80-CTLA-4 and CD80-CD28 protein complexes. This information was fed into a computational model developed in R for in silico mutagenesis and CD80 variant library construction. The 3D structures of variants were modeled using the Swiss model webserver. After modeling the 3D structures, HADDOCK server was employed to build all protein-protein complexes, which contain CTLA-4-CD80 variant complexes, Wild type CD80-CD28 complexes and CD28-CD80 variant complexes. Protein-protein binding free energy was determined using FoldX and the variant number 316 with mutations at 29, 31, 33 positions showed increased binding affinity to CTLA-4 (-21.43 kcal/mol) and decreased binding affinity to CD28 (- 9.54 kcal/mol). Finally, molecular dynamics (MD) simulations confirmed the stability of variant 316. In conclusion, we designed a new CD80 protein variant with potential immunotherapeutic applications.

Trimeric Architecture Ensures the Stability and Biological Activity of the Calf Purine Nucleoside Phosphorylase: In Silico and In Vitro Studies of Monomeric and Trimeric Forms of the Enzyme

Mammalian purine nucleoside phosphorylase (PNP) is biologically active as a homotrimer, in which each monomer catalyzes a reaction independently of the others. To answer the question of why the native PNP forms a trimeric structure, we constructed, in silico and in vitro, the monomeric form of the enzyme. Molecular dynamics simulations showed different geometries of the active site in the non-mutated trimeric and monomeric PNP forms, which suggested that the active site in the isolated monomer could be non-functional. To confirm this hypothesis, six amino acids located at the interface of the subunits were selected and mutated to alanines to disrupt the trimer and obtain a monomer (6Ala PNP). The effects of these mutations on the enzyme structure, stability, conformational dynamics, and activity were examined. The solution experiments confirmed that the 6Ala PNP mutant occurs mainly as a monomer, with a secondary structure almost identical to the wild type, WT PNP, and importantly, it shows no enzymatic activity. Simulations confirmed that, although the secondary structure of the 6Ala monomer is similar to the WT PNP, the positions of the amino acids building the 6Ala PNP active site significantly differ. These data suggest that a trimeric structure is necessary to stabilize the geometry of the active site of this enzyme.

Atomic-level thermodynamics analysis of the binding free energy of SARS-CoV-2 neutralizing antibodies

Understanding how protein-protein binding affinity is determined from molecular interactions at the interface is essential in developing protein therapeutics such as antibodies, but this has not yet been fully achieved. Among the major difficulties are the facts that it is generally difficult to decompose thermodynamic quantities into contributions from individual molecular interactions and that the solvent effect-dehydration penalty-must also be taken into consideration for every contact formation at the binding interface. Here, we present an atomic-level thermodynamics analysis that overcomes these difficulties and illustrate its utility through application to SARS-CoV-2 neutralizing antibodies. Our analysis is based on the direct interaction energy computed from simulated antibody-protein complex structures and on the decomposition of solvation free energy change upon complex formation. We find that the formation of a single contact such as a hydrogen bond at the interface barely contributes to binding free energy due to the dehydration penalty. On the other hand, the simultaneous formation of multiple contacts between two interface residues favorably contributes to binding affinity. This is because the dehydration penalty is significantly alleviated: the total penalty for multiple contacts is smaller than a sum of what would be expected for individual dehydrations of those contacts. Our results thus provide a new perspective for designing protein therapeutics of improved binding affinity.

Deep learning of protein sequence design of protein-protein interactions

MOTIVATION

As more data of experimentally determined protein structures are becoming available, data-driven models to describe protein sequence-structure relationships become more feasible. Within this space, the amino acid sequence design of protein-protein interactions is still a rather challenging subproblem with very low success rates-yet, it is central to most biological processes.

RESULTS

We developed an attention-based deep learning model inspired by algorithms used for image-caption assignments to design peptides or protein fragment sequences. Our trained model can be applied for the redesign of natural protein interfaces or the designed protein interaction fragments. Here, we validate the potential by recapitulating naturally occurring protein-protein interactions including antibody-antigen complexes. The designed interfaces accurately capture essential native interactions and have comparable native-like binding affinities in silico. Furthermore, our model does not need a precise backbone location, making it an attractive tool for working with de novo design of protein-protein interactions.

AVAILABILITY AND IMPLEMENTATION

The source code of the method is available at https://github.com/strauchlab/iNNterfaceDesign.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Elucidating the Interaction between Pyridoxine 5'-Phosphate Oxidase and Dopa Decarboxylase: Activation of B6-Dependent Enzyme

Pyridoxal 5'-phosphate (PLP), the active form of vitamin B6, serves as a cofactor for scores of B6-dependent (PLP-dependent) enzymes involved in many cellular processes. One such B6 enzyme is dopa decarboxylase (DDC), which is required for the biosynthesis of key neurotransmitters, e.g., dopamine and serotonin. PLP-dependent enzymes are biosynthesized as apo-B6 enzymes and then converted to the catalytically active holo-B6 enzymes by Schiff base formation between the aldehyde of PLP and an active site lysine of the protein. In eukaryotes, PLP is made available to the B6 enzymes through the activity of the B6-salvage enzymes, pyridoxine 5'-phosphate oxidase (PNPO) and pyridoxal kinase (PLK). To minimize toxicity, the cell keeps the content of free PLP (unbound) very low through dephosphorylation and PLP feedback inhibition of PNPO and PLK. This has led to a proposed mechanism of complex formation between the B6-salvage enzymes and apo-B6 enzymes prior to the transfer of PLP, although such complexes are yet to be characterized at the atomic level, presumably due to their transient nature. A computational study, for the first time, was used to predict a likely PNPO and DDC complex, which suggested contact between the allosteric PLP tight-binding site on PNPO and the active site of DDC. Using isothermal calorimetry and/or surface plasmon resonance, we also show that PNPO binds both apoDDC and holoDDC with dissociation constants of 0.93 ± 0.07 μM and 2.59 ± 0.11 μM, respectively. Finally, in the presence of apoDDC, the tightly bound PLP on PNPO is transferred to apoDDC, resulting in the formation of about 35% holoDDC.

Integrating deep mutational scanning and low-throughput mutagenesis data to predict the impact of amino acid variants

BACKGROUND

Evaluating the impact of amino acid variants has been a critical challenge for studying protein function and interpreting genomic data. High-throughput experimental methods like deep mutational scanning (DMS) can measure the effect of large numbers of variants in a target protein, but because DMS studies have not been performed on all proteins, researchers also model DMS data computationally to estimate variant impacts by predictors.

RESULTS

In this study, we extended a linear regression-based predictor to explore whether incorporating data from alanine scanning (AS), a widely used low-throughput mutagenesis method, would improve prediction results. To evaluate our model, we collected 146 AS datasets, mapping to 54 DMS datasets across 22 distinct proteins.

CONCLUSIONS

We show that improved model performance depends on the compatibility of the DMS and AS assays, and the scale of improvement is closely related to the correlation between DMS and AS results.

Design of human immunodeficiency virus-1 neutralizing peptides targeting CD4-binding site: An integrative computational biologics approach

Peptide therapeutics have recently gained momentum in antiviral therapy due to their increased potency and cost-effectiveness. Interaction of the HIV-1 envelope gp120 with the host CD4 receptor is a critical step for viral entry, and therefore the CD4-binding site (CD4bs) of gp120 is a potential hotspot for blocking HIV-1 infection. The present study aimed to design short peptides from well-characterized CD4bs targeting broadly neutralizing antibodies (bNAbs), which could be utilized as bNAb mimetics for viral neutralization. Co-crystallized structures of HIV-1 gp120 in complex with CD4bs-directed bNAbs were used to derive hexameric peptides using the Rosetta Peptiderive protocol. Based on empirical insights into co-crystallized structures, peptides derived from the heavy chain alone were considered. The peptides were docked with both HIV-1 subtype B and C gp120, and the stability of the peptide–antigen complexes was validated using extensive Molecular Dynamics (MD) simulations. Two peptides identified in the study demonstrated stable intermolecular interactions with SER365, GLY366, and GLY367 of the PHE43 cavity in the CD4 binding pocket, and with ASP368 of HIV-1 gp120, thereby mimicking the natural interaction between ASP368gp120 and ARG59CD4–RECEPTOR. Furthermore, the peptides featured favorable physico-chemical properties for virus neutralization suggesting that these peptides may be highly promising bNAb mimetic candidates that may be taken up for experimental validation.

Molecular analysis of a public cross-neutralizing antibody response to SARS-CoV-2

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concerns (VOCs) continue to emerge, cross-neutralizing antibody responses become key toward next-generation design of a more universal COVID-19 vaccine. By analyzing published data from the literature, we report here that the combination of germline genes IGHV2-5/IGLV2-14 represents a public antibody response to the receptor-binding domain (RBD) that potently cross-neutralizes a broad range of VOCs, including Omicron and its sub-lineages. Detailed molecular analysis shows that the complementarity-determining region H3 sequences of IGHV2-5/IGLV2-14-encoded RBD antibodies have a preferred length of 11 amino acids and a conserved HxIxxI motif. In addition, these antibodies have a strong allelic preference due to an allelic polymorphism at amino acid residue 54 of IGHV2-5, which is located at the paratope. These findings have important implications for understanding cross-neutralizing antibody responses to SARS-CoV-2 and its heterogenicity at the population level as well as the development of a universal COVID-19 vaccine.

Hybrid in vitro/in silico analysis of low-affinity protein-protein interactions that regulate signal transduction by Sema6D

Semaphorins constitute a large family of secreted and membrane-bound proteins that signal through cell-surface receptors, plexins. Semaphorins generally use low-affinity protein-protein interactions to bind with their specific plexin(s) and regulate distinct cellular processes such as neurogenesis, immune response, and organogenesis. Sema6D is a membrane-bound semaphorin that interacts with class A plexins. Sema6D exhibited differential binding affinities to class A plexins in prior cell-based assays, but the molecular mechanism underlying this selectivity is not well understood. Therefore, we performed hybrid in vitro/in silico analysis to examine the binding mode of Sema6D to class A plexins and to identify residues that give rise to the differential affinities and thus contribute to the selectivity within the same class of semaphorins. Our biophysical binding analysis indeed confirmed that Sema6D has a higher affinity for Plexin-A1 than for other class A plexins, consistent with the binding selectivity observed in the previous cell-based assays. Unexpectedly, our present crystallographic analysis of the Sema6D-Plexin-A1 complex showed that the pattern of polar interactions is not interaction-specific because it matches the pattern in the prior structure of the Sema6A-Plexin-A2 complex. Thus, we performed in silico alanine scanning analysis and discovered hotspot residues that selectively stabilized the Sema6D-Plexin-A1 pair via Van der Waals interactions. We then validated the contribution of these hotspot residues to the variation in binding affinity with biophysical binding analysis and molecular dynamics simulations on the mutants. Ultimately, our present results suggest that shape complementarity in the binding interfaces is a determinant for binding selectivity.

Densest subgraph-based methods for protein-protein interaction hot spot prediction

Background

Hot spots play an important role in protein binding analysis. The residue interaction network is a key point in hot spot prediction, and several graph theory-based methods have been proposed to detect hot spots. Although the existing methods can yield some interesting residues by network analysis, low recall has limited their abilities in finding more potential hot spots.

Result

In this study, we develop three graph theory-based methods to predict hot spots from only a single residue interaction network. We detect the important residues by finding subgraphs with high densities, i.e., high average degrees. Generally, a high degree implies a high binding possibility between protein chains, and thus a subgraph with high density usually relates to binding sites that have a high rate of hot spots. By evaluating the results on 67 complexes from the SKEMPI database, our methods clearly outperform existing graph theory-based methods on recall and F-score. In particular, our main method, Min-SDS, has an average recall of over 0.665 and an f2-score of over 0.364, while the recall and f2-score of the existing methods are less than 0.400 and 0.224, respectively.

Conclusion

The Min-SDS method performs best among all tested methods on the hot spot prediction problem, and all three of our methods provide useful approaches for analyzing bionetworks. In addition, the densest subgraph-based methods predict hot spots with only one residue interaction network, which is constructed from spatial atomic coordinate data to mitigate the shortage of data from wet-lab experiments.

A Computational Study on the Interaction of NSP10 and NSP14: Unraveling the RNA Synthesis Proofreading Mechanism in SARS-CoV-2, SARS-CoV, and MERS-CoV

The interaction of exoribonuclease (ExoN) nonstructural protein (NSP14) with NSP10 co-factors is crucial for high-fidelity proofreading activity of coronavirus replication and transcription. Proofreading function is critical for maintaining the large genomes to ensure replication proficiency; therefore, while maintaining the viral replication fitness, quick resistance has been reported to the nucleotide analogue (NA) drugs. Therefore, targeting the NSP14 and NSP10 interacting interface with small molecules or peptides could be a better strategy to obstruct replication processes of coronaviruses (CoVs). A comparative study on the binding mechanism of NSP10 with the NSP14 ExoN domain of SARS-CoV-2, SARS-CoV, MERS-CoV, and four SARS-CoV-2 NSP14mutant complexes has been carried out. Protein-protein interaction (PPI) dynamics, per-residue binding free energy (BFE) analyses, and the identification of interface hotspot residues have been studied using molecular dynamics simulations and various computational tools. The BFE of the SARS-CoV NSP14-NSP10 complex was higher when compared to novel SARS-CoV-2 and MERS. However, SARS-CoV-2 NSP14mutant systems display a higher BFE as compared to the wild type (WT) but lower than SARS-CoV and MERS. Despite the high BFE, the SARS-CoV NSP14-NSP10 complex appears to be structurally more flexible in many regions especially the catalytic site, which is not seen in SARS-CoV-2 and its mutant or MERS complexes. The significantly high residue energy contribution of key interface residues and hotspots reveals that the high binding energy between NSP14 and NSP10 may enhance the functional activity of the proofreading complex, as the NSP10-NSP14 interaction is essential in maintaining the stability of the ExoN domain for the replicative fitness of CoVs. The factors discussed for SARS-CoV-2 complexes may be responsible for NSP14 ExoN having a high replication proficiency, significantly leading to the evolution of new variants of SARS-CoV-2. The NSP14 residues V66, T69, D126, and I201and eight residues of NSP10 (L16, F19, V21, V42, M44, H80, K93, and F96) are identified as common hotspots. Overall, the interface area, hotspot locations, bonded/nonbonded contacts, and energies between NSP14 and NSP10 may pave a way in designing potential inhibitors to disrupt NSP14-NSP10 interactions of CoVs especially SARS-CoV-2.

Key Residues Affecting Binding Affinity of Sirex noctilio Fabricius Odorant-Binding Protein (SnocOBP9) to Aggregation Pheromone

Sirex noctilio Fabricius (Hymenoptera Siricidae) is a major quarantine pest responsible for substantial economic losses in the pine industry. To achieve better pest control, (Z)-3-decen-ol was identified as the male pheromone and used as a field chemical trapping agent. However, the interactions between odorant-binding proteins (OBPs) and pheromones are poorly described. In this study, SnocOBP9 had a higher binding affinity with Z3D (Ki = 1.53 ± 0.09 μM) than other chemical ligands. Molecular dynamics simulation and binding mode analysis revealed that several nonpolar residues were the main drivers for hydrophobic interactions between SnocOBP9 and Z3D. Additionally, computational alanine scanning results indicated that five amino acids (MET54, PHE57, PHE71, PHE74, LEU116) in SnocOBP9 could potentially alter the binding affinity to Z3D. Finally, we used single-site-directed mutagenesis to substitute these five residues with alanine. These results imply that the five residues play crucial roles in the SnocOBP9-Z3D complex. Our research confirmed the function of SnocOBP9, uncovered the key residues involved in SnocOBP9-Z3D interactions, and provides an inspiration to improve the effects of pheromone agent traps.

Structural basis for the calmodulin-mediated activation of eukaryotic elongation factor 2 kinase

Translation is a tightly regulated process that ensures optimal protein quality and enables adaptation to energy/nutrient availability. The α-kinase eukaryotic elongation factor 2 kinase (eEF-2K), a key regulator of translation, specifically phosphorylates the guanosine triphosphatase eEF-2, thereby reducing its affinity for the ribosome and suppressing the elongation phase of protein synthesis. eEF-2K activation requires calmodulin binding and autophosphorylation at the primary stimulatory site, T348. Biochemical studies predict a calmodulin-mediated activation mechanism for eEF-2K distinct from other calmodulin-dependent kinases. Here, we resolve the atomic details of this mechanism through a 2.3-Å crystal structure of the heterodimeric complex of calmodulin and the functional core of eEF-2K (eEF-2KTR). This structure, which represents the activated T348-phosphorylated state of eEF-2KTR, highlights an intimate association of the kinase with the calmodulin C-lobe, creating an "activation spine" that connects its amino-terminal calmodulin-targeting motif to its active site through a conserved regulatory element.

Computational Assessment of Protein-Protein Binding Specificity within a Family of Synaptic Surface Receptors

Atomic-level information is essential to explain the formation of specific protein complexes in terms of structure and dynamics. The set of Dpr and DIP proteins, which play a key role in the neuromorphogenesis in the nervous system of Drosophila melanogaster, offer a rich paradigm to learn about protein-protein recognition. Many members of the DIP subfamily cross-react with several members of the Dpr family and vice versa. While there exists a total of 231 possible Dpr-DIP heterodimer complexes from the 21 Dpr and 11 DIP proteins, only 57 "cognate" pairs have been detected by surface plasmon resonance (SPR) experiments, suggesting that the remaining 174 pairs have low or unreliable binding affinity. Our goal is to assess the performance of computational approaches to characterize the global set of interactions between Dpr and DIP proteins and identify the specificity of binding between each DIP with their corresponding Dpr binding partners. In addition, we aim to characterize how mutations influence the specificity of the binding interaction. In this work, a wide range of knowledge-based and physics-based approaches are utilized, including mutual information, linear discriminant analysis, homology modeling, molecular dynamics simulations, Poisson-Boltzmann continuum electrostatics calculations, and alchemical free energy perturbation to decipher the origin of binding specificity of the Dpr-DIP complexes examined. Ultimately, the results show that those two broad strategies are complementary, with different strengths and limitations. Biological inter-relations are more clearly revealed through knowledge-based approaches combining evolutionary and structural features, the molecular determinants controlling binding specificity can be predicted accurately with physics-based approaches based on atomic models.

Fragment hopping protocol for the design of small-molecule protein-protein interaction inhibitors

Fragment-based ligand discovery (FBLD) is one of the most successful approaches to designing small-molecule protein-protein interaction (PPI) inhibitors. The incorporation of computational tools to FBLD allows the exploration of chemical space in a time- and cost-efficient manner. Herein, a computational protocol for the development of small-molecule PPI inhibitors using fragment hopping, a fragment-based de novo design approach, is described and a case study is presented to illustrate the efficiency of this protocol. Fragment hopping facilitates the design of PPI inhibitors from scratch solely based on key binding features in the PPI complex structure. This approach is an open system that enables the inclusion of different state-of-the-art programs and softwares to improve its performances.

Protein-protein interaction of RdRp with its co-factor NSP8 and NSP7 to decipher the interface hotspot residues for drug targeting: A comparison between SARS-CoV-2 and SARS-CoV

In this study we explored the molecular mechanism of RdRp (Non-Structural Protein, NSP12) interaction with its co-factors NSP7 and NSP8 which is the main toolbox for RNA replication and transcription of SARS-CoV-2 and SARS-CoV. The replication complex is a heterotetramer consists of one NSP12, one NSP7 and two NSP8. Extensive molecular dynamics (MD) simulations were applied on both the heterotetramer complexes to generate the conformations and were used to estimate the MMPBSA binding free energy (BFE) and per-residue energy decomposition of NSP12-NSP8 and NSP12-NSP7 and NSP7-NSP8 complexes. The BFE of SARS-CoV-2 heterotetramer complex with its corresponding partner protein was significantly higher as compared to SARS-CoV. Interface hotspot residues were predicted using different methods implemented in KFC (Knowledge-based FADA and Contracts), HotRegion and Robetta web servers. Per-residue energy decomposition analysis showed that the predicted interface hotspot residues contribute more energy towards the formation of complexes and most of the predicted hotspot residues are clustered together. However, there is a slight difference in the residue-wise energy contribution in the interface NSPs on heterotetramer viral replication complex of both coronaviruses. While the overall replication complex of SARS-CoV-2 was found to be slightly flexible as compared to SARS-CoV. This difference in terms of structural flexibility/stability and energetic characteristics of interface residues including hotspots at PPI interface in the viral replication complexes may be the reason of higher rate of RNA replication of SARS-CoV-2 as compared to SARS-CoV. Overall, the interaction profile at PPI interface such as, interface area, hotspot residues, nature of bonds and energies between NSPs, may provide valuable insights in designing of small molecules or peptide/peptidomimetic ligands which can fit into the PPI interface to disrupt the interaction.

In Silico Prediction of Plasmodium falciparum Cytoadherence Inhibitors That Disrupt Interaction between gC1qR-DBLβ12 Complex

Malaria causes about half a million deaths per year, mainly in children below 5 years of age. Cytoadherence of Plasmodium falciparum infected erythrocytes in brain and placenta has been linked to severe malaria and malarial related deaths. Cytoadherence is mediated by binding of human receptor gC1qR to the DBLβ12 domain of a P. falciparum erythrocyte membrane protein family 1 (PfEMP1) protein. In the present work, molecular dynamic simulation was extensively studied for the gC1qR-DBLβ12 complex. The stabilized protein complex was used to study the protein–protein interface interactions and mapping of interactive amino acid residues as hotspot were performed. Prediction of inhibitors were performed by using virtual protein–protein inhibitor database Timbal screening of about 15,000 compounds. In silico mutagenesis studies, binding profile and protein ligand interaction fingerprinting were used to strengthen the screening of the potential inhibitors of gC1qR-DBLβ12 interface. Six compounds were selected and were further subjected to the MAIP analysis and ADMET studies. From these six compounds, the compounds 3, 5, and 6 were found to outperform on all screening criteria from the rest selected compounds. These compounds may provide novel drugs to treat and manage severe falciparum malaria. Additionally. the identified hotspots can be used in future for designing novel interventions for disruption of interface interactions, such as through peptides or vaccines. Futher in vitro and in vivo studies are required for the confirmation of these compounds as potential inhibitors of gC1qR-DBLβ12 interaction.

Interleukin-1α, Interleukin-1β and Interleukin-1 Receptor Antagonist Share a Common U-shaped Recognition Epitope on Interleukin-1 Receptor Surface

Interleukin-1 (IL-1) plays a central role in the regulation of immune and inflammatory responses. There are two forms of IL-1 agonists (IL-1α and IL-1β) and one form of IL-1 antagonist (IL-1Ra); they share a similar binding mode to IL-1 receptor (IL-1R) but exhibit opposite biological functions on the receptor. In this study, the intermolecular interactions of IL-1R receptor with IL-1α, IL-1β and IL-1Ra ligands were systematically investigated at structural, energetic and dynamic levels. It was found that the receptor primarily adopts a U-shaped, double-stranded and linear/conformational-hybrid epitope to commonly interact with the three ligands. The epitope covers a common protein segment (residues 107-127), which is fully located within in the C2T2 subsdomain of IL-1R extracellular domain (ECD) and contributes ~40% to the total binding energy of IL-1R/ligand association. The epitope is natively folded into an ordered conformation in IL-1R protein context but would become largely disordered out of the context. Here, we adopted a disulfide bridge to staple U-shaped epitope-derived peptides, which can be effectively constrained into a native-like conformation and thus exhibit an improved affinity to ligands as compared to their unstapled counterpart, with affinity increase by up to ~15-fold. These disulfide bridges were designed to point out of ligand/peptide complex interface and thus would not disrupt the direct complex interaction. Energetic decomposition imparted that the stapling has only a modest influence on the interaction enthalpy and desolvation effect of ligand/peptide binding, but can substantially reduce entropy penalty upon the binding. For a peptide, the stapling-addressed entropic reduction can be roughly regarded as a constant, which only improves peptide affinity to these ligands, but does not change peptide selectivity over different ligands. This article is protected by copyright. All rights reserved.