Disrupting the intramolecular interaction between proto-oncogene c-Src SH3 domain and its self-binding peptide PPII with rationally designed peptide ligands

Computational design and experimental confirmation of a disulfide-stapled YAP helixα1-trap derived from TEAD4 helical hairpin to selectively capture YAP α1-helix with potent antitumor activity

Human Hippo signaling pathway is an evolutionarily conserved regulator network that controls organ development and has been implicated in various cancers. Transcriptional enhanced associate domain-4 (TEAD4) is the final nuclear effector of Hippo pathway, which is activated by Yes-associated protein (YAP) through binding to two separated YAP regions of α1-helix and Ω-loop. Previous efforts have all been addressed on deriving peptide inhibitors from the YAP to target TEAD4. Instead, we herein attempted to rationally design a so-called 'YAP helixα1-trap' based on the TEAD4 to target YAP by using dynamics simulation and energetics analysis as well as experimental assays at molecular and cellular levels. The trap represents a native double-stranded helical hairpin covering a specific YAP-binding site on TEAD4 surface, which is expected to form a three-helix bundle with the α1-helical region of YAP, thus competitively disrupting TEAD4-YAP interaction. The hairpin was further stapled by a disulfide bridge across its two helical arms. Circular dichroism characterized that the stapling can effectively constrain the trap into a native-like structured conformation in free state, thus largely minimizing the entropy penalty upon its binding to YAP. Affinity assays revealed that the stapling can considerably improve the trap binding potency to YAP α1-helix by up to 8.5-fold at molecular level, which also exhibited a good tumor-suppressing effect at cellular level if fused with TAT cell permeation sequence. In this respect, it is considered that the YAP helixα1-trap-mediated blockade of Hippo pathway may be a new and promising therapeutic strategy against cancers.

The C-terminal self-binding helical peptide of human estrogen-related receptor γ can be druggably targeted by a novel class of rationally designed peptidic antagonists

Orphan nuclear estrogen-related receptor γ (ERRγ) has been recognized as a potential therapeutic target for cancer, inflammation and metabolic disorder. The ERRγ contains a regulatory AF2 helical tail linked C-terminally to its ligand-binding domain (LBD), which is a self-binding peptide (SBP) and serves as molecular switch to dynamically regulate the receptor alternation between active and inactive states by binding to and unbinding from the AF2-binding site on ERRγ LBD surface, respectively. Traditional ERRγ modulators are all small-molecule chemical ligands that can be classified into agonists and inverse agonists in terms of their action mechanism; the agonists stabilize the AF2 in ABS site with an agonist conformation, while the inverse agonists lock the AF2 out of the site to largely abolish ERRγ transcriptional activity. Here, a class of ERRγ peptidic antagonists was described to compete with native AF2 for the ABS site, thus blocking the active state of AF2 binding to ERRγ LBD domain. Self-inhibitory peptide was derived from the SBP-covering AF2 region and we expected it can rebind potently to the ABS site by reducing its intrinsic disorder and entropy cost upon the rebinding. Hydrocarbon stapling was employed to do so, which employed an all-hydrocarbon bridge across the [i, i + 4]-anchor residue pair in the N-terminal, middle or C-terminal region of the self-inhibitory peptide. As might be expected, it is revealed that the stapled peptides are good binders of ERRγ LBD domain and can effectively compete with the native AF2 helical tail for ERRγ ABS site, which exhibit a basically similar binding mode with AF2 to the site and form diverse noncovalent interactions with the site, thus conferring stability and specificity to the domain-peptide complexes.

Dynamics simulation, energetics calculation and experimental analysis of the intermolecular interaction between human neonatal ABL SH3 domain and its N-substituted peptoid ligands

Non-receptor tyrosine kinase of neonatal ABL (nABL) is distributed in the nucleus and cytoplasm of proliferating cells in embryo and neonate, and has been implicated in the pathogenesis of neonatal leukemia and other hematological diseases. The kinase contains a regulatory Src homology 3 (SH3) domain that can specifically recognize proline-rich peptide segments on its partner protein surface. In this study, we systematically investigated the N-substitution effect on the binding of an empirically designed proline-rich peptide p9 to nABL SH3 domain by integrating dynamics simulations, energetics calculations and fluorescence affinity assays. The p9 is an almost all proline-composed decapeptide, with only a sole tyrosine at its residue 4, which has been found to bind nABL SH3 domain at a micromolar level in a class I mode. Here, the non-key residues of p9 peptide were independently replaced by various N-substituted amino acids to create a systematic N-substitution profile, from which we can identify those favorable, neutral and unfavorable substitutions at each peptide residue. On this basis a combinatorial peptoid library was rationally designed by systematically combining the favorable N-substituted amino acids at non-key residues of p9 peptide, thus resulting in a number of its peptoid counterparts. The binding affinity of top peptoid hits was observed to be comparable with or improved moderately relative to p9 peptide, with Kd ranging between 3.1 and 76 μM. Structural analysis revealed that the peptoids can be divided into exposed, polar and hydrophobic regions from N- to C-termini, in which the polar and hydrophobic regions confer specificity and stability to the domain-peptoid interaction, respectively. In addition, a designed peptoid was also observed to exhibit 5.3-fold SH3-selectivity for nABL over cSRC, suggesting that the N-substitution can be used to improve not only binding affinity but also recognition specificity of SH3 binders.Communicated by Ramaswamy H. Sarma.

Systematic analysis and comparison of peptide specificity and selectivity between their cognate receptors and noncognate decoys

Protein-peptide interactions (PpIs) play an important role in cell signaling networks and have been exploited as new and attractive therapeutic targets. The affinity and specificity are two unity-of-opposite aspects of PpIs (and other biomolecular interactions); the former indicates the absolute binding strength between the peptide ligand and its cognate protein receptor in a PpI, while the latter represents the relative recognition selectivity of the peptide ligand for its cognate protein receptor in a PpI over those noncognate decoys that could be potentially encountered by the peptide in cell. Although the PpI binding affinity has been widely investigated over the past decades, the peptide recognition specificity (and selectivity) still remains largely unexplored to date. In this study, we classified PpI specificity into three types: (i) class-I specificity: peptide selectivity for its cognate wild-type protein receptor over the noncognate mutant decoys of this receptor, (ii) class-II specificity: peptide selectivity for its cognate protein receptor over other noncognate decoys that are homologous with this receptor, and (iii) class-III specificity: peptide selectivity for its cognate protein receptor over other noncognate decoys that are the cognate receptors of other peptides. We performed affinity and selectivity analysis for the three types of PpI specificity and revealed that the PpIs generally exhibit a moderate or modest specificity; peptide selectivity increases in the order: class-I < class-II < class-III. All the three types of PpI specificity were observed to have no statistically significant correlation with peptide length and hydrophobicity, but the class-I and class-II specificities can be influenced considerably by peptide secondary structures; the high specificity is preferentially associated with ordered structure types as compared to undefined structure types. In addition, the mutation distribution (for class-I specificity), sequence conservation (for class-II specificity), and structural similarity (for class-III specificity) seem also to address effects on peptide selectivity.

Targeting peptide-mediated interactions in omics

Peptide-mediated interactions (PMIs) play a crucial role in cell signaling network, which are responsible for about half of cellular protein-protein associations in the human interactome and have recently been recognized as a new kind of promising druggable target for drug development and disease therapy. In this article, we give a systematic review regarding the proteome-wide discovery of PMIs and targeting druggable PMIs (dPMIs) with chemical drugs, self-inhibitory peptides (SIPs) and protein agents, particularly focusing on their implications and applications for therapeutic purpose in omics. We also introduce computational peptidology strategies used to model, analyze, and design PMI-targeted molecular entities and further extend the concepts of protein context, direct/indirect readout, and enthalpy/entropy effect involved in PMIs. Current issues and future perspective on this topic are discussed. There is still a long way to go before establishment of efficient therapeutic strategies to target PMIs on the omics scale.

Molecular insight into the systematic affinity and selectivity of partner recognition sites between the WW1 and WW2 domains of human KIBRA neuroprotein

Human KIBRA, a member of the WWC family proteins, is an upstream regulator of the Salvador/Warts/Hippo (SWH) signaling pathway and predominately expressed in nervous system. The protein has two functionally regulatory domains WW1 and WW2 at N-terminal region, which recognize and bind to the PY-motif segments of their partner proteins to serve as a signaling scaffold role in the SWH pathway. The two domains are highly conserved, but their downstream ligands and biological functions may not be fully consistent. In this study, we attempted to systematically profile the PY-motif affinity to and selectivity between KIBRA WW1 and WW2 domains involved in partner recognition sites. Ontology mining was used to enrich the KIBRA-interacting proteins in literature libraries, from which a variety of PY-motif peptide segments were identified, and their binding behavior to each domain was then analyzed by integrating computational modeling and experimental assay. Most PY-motif peptides were found to interact potently with WW1 and WW2, but they generally only exhibit a moderate or modest selectivity between the two domains. Subsequently, several representative peptides were further examined in detail to elucidate the molecular mechanism underlying their affinity and selectivity. It is revealed that the middle motif region of PY-motif peptides is primarily responsible for the affinity and stability of peptide binding, but only contributes marginally to peptide selectivity. Instead, the N-terminal region and, particularly, C-terminal region of PY-motif peptides play a crucial role in the selectivity. Hydrophobic contacts and hydrogen bonds confer stability and specificity to the domain-peptide interaction, respectively.

BERT-PPII: The Polyproline Type II Helix Structure Prediction Model Based on BERT and Multichannel CNN

Predicting the polyproline type II (PPII) helix structure is crucial important in many research areas, such as the protein folding mechanisms, the drug targets, and the protein functions. However, many existing PPII helix prediction algorithms encode the protein sequence information in a single way, which causes the insufficient learning of protein sequence feature information. To improve the protein sequence encoding performance, this paper proposes a BERT-based PPII helix structure prediction algorithm (BERT-PPII), which learns the protein sequence information based on the BERT model. The BERT model's CLS vector can fairly fuse sample's each amino acid residue information. Thus, we utilize the CLS vector as the global feature to represent the sample's global contextual information. As the interactions among the protein chains' local amino acid residues have an important influence on the formation of PPII helix, we utilize the CNN to extract local amino acid residues' features which can further enhance the information expression of protein sequence samples. In this paper, we fuse the CLS vectors with CNN local features to improve the performance of predicting PPII structure. Compared to the state-of-the-art PPIIPRED method, the experimental results on the unbalanced dataset show that the proposed method improves the accuracy value by 1% on the strict dataset and 2% on the less strict dataset. Correspondingly, the results on the balanced dataset show that the AUCs of the proposed method are 0.826 on the strict dataset and 0.785 on less strict datasets, respectively. For the independent test set, the proposed method has the AUC value of 0.827 on the strict dataset and 0.783 on the less strict dataset. The above experimental results have proved that the proposed BERT-PPII method can achieve a superior performance of predicting the PPII helix.

Comprehensive binary interaction mapping of τ phosphotyrosine sites with SH2 domains in the human genome: Implications for the rational design of self-inhibitory phosphopeptides to target τ hyperphosphorylation signaling in Alzheimer's Disease

Human microtubule-associated protein Tau (τ) is abundant in the axons of neurons where it stabilizes microtubule bundles; abnormally hyperphosphorylated τ is a hallmark of Alzheimer's disease (AD) and related tauopathies. The hyperphosphorylation events can be recognized by phosphotyrosine-recognition domain SH2 (Src homology 2) to elicit downstream τ signaling in AD pathology. In this study, a comprehensive binary interaction map (CBIM) of all the 6 τ phosphotyrosine sites with 120 SH2 domains in the human genome was systematically created at structural level using computational analyses and binding assays, from which we were able to identify those of strong and moderate binding pairs of sites to domains. It is found that the SH2-recognition specificity of different τ phosphotyrosine sites has been evolutionally optimized to become roughly orthogonal to each other, and thus these site phosphorylations would regulate different but probably partially overlapped biological functions in τ signaling. Some SH2 groups such as SRC, RIN, PLCG, SOCS and SH2D were revealed to have effective binding potency as compared to others; they could be regarded as potential τ-associated proteins to transduce the downstream signaling. We further determined the systematic binding affinities of 6 τ-phosphopeptides to the 11 SH2 domains in SRC group, from which the FYN-τ¹⁸ and YES-τ²⁹ pairs were identified as strong binders. Subsequently, rational molecular design was performed on τ¹⁸ and τ²⁹ to derive a number of τ-phosphopeptide mutants with increased affinity; they are self-inhibitory candidates to competitively target τ hyperphosphorylation events in AD. In addition, it is revealed that the primary anchor pY₀ and secondary anchor X₊₃ of τ-phosphopeptides play an important role in SRC-group SH2 recognition, which confer stability and specificity to the SH2-phosphopeptide binding, respectively.

Structural Mapping of BMP Conformational Epitopes and Bioengineering Design of Osteogenic Peptides to Specifically Target the Epitope-Binding Sites

Introduction

Human bone morphogenetic proteins (BMPs) constitute a large family of cytokines related to members of the transforming growth factor-β superfamily, which fulfill biological functions by specificity binding to their cognate type I (BRI) and type II (BRII) receptors through conformational wrist and linear knuckle epitopes, respectively.

Methods and Results

We systematically examined the intermolecular recognition and interaction between the BMP proteins and BRI receptor at structural, energetic and dynamic levels. The BRI-binding site consists of three hotspot regions on BMP surface, which totally contribute ~70% potency to the BMP-BRI binding events and represent the core sections of BMP conformational wrist epitope; the contribution increases in the order: hotspot 2 (~ 8%) < hotspot 3 (~ 20%) < hotspot 1 (~ 40%). Multiple sequence alignment and structural superposition revealed a consensus sequence pattern and a similar binding mode of the three hotspots shared by most BMP members, indicating a high conservation of wrist epitope in BMP family. The three hotspots are natively folded into wellstructured U-shaped,, loop and double-stranded conformations in BMP proteins, which, however, would become largely disordered when splitting from the protein context to derive osteogenic peptides in free state, thus largely impairing their rebinding capability to BRI receptor. In this respect, cyclization strategy was employed to constrain hotspot 1/3-derived peptides into a native-like conformation, which was conducted by adding a disulfide bond across the ending arms of linear peptides based on their native conformations. Fluorescence-based assays substantiated that the cyclization can effectively improve the binding affinities of osteogenic peptides to BRI receptor by 3-6-fold. The cyclic peptides also exhibit a good selectivity for BRI over BRII (> 5-fold), confirming that they can specifically target the wrist epitope-binding site of BRI receptor.

Conclusion

The rationally designed cyclic peptides can be regarded as the promising lead entities that should be further chemically modified to enhance their in vivo biological stability for further bioengineering therapeutic osteogenic peptides against chondrocyte senescence and bone disorder.

Integrated unsupervised-supervised modeling and prediction of protein-peptide affinities at structural level

Cell signal networks are orchestrated directly or indirectly by various peptide-mediated protein-protein interactions, which are normally weak and transient and thus ideal for biological regulation and medicinal intervention. Here, we develop a general-purpose method for modeling and predicting the binding affinities of protein-peptide interactions (PpIs) at the structural level. The method is a hybrid strategy that employs an unsupervised approach to derive a layered PpI atom-residue interaction (ulPpI[a-r]) potential between different protein atom types and peptide residue types from thousands of solved PpI complex structures and then statistically correlates the potential descriptors with experimental affinities (KD values) over hundreds of known PpI samples in a supervised manner to create an integrated unsupervised-supervised PpI affinity (usPpIA) predictor. Although both the ulPpI[a-r] potential and usPpIA predictor can be used to calculate PpI affinities from their complex structures, the latter seems to perform much better than the former, suggesting that the unsupervised potential can be improved substantially with a further correction by supervised statistical learning. We examine the robustness and fault-tolerance of usPpIA predictor when applied to treat the coarse-grained PpI complex structures modeled computationally by sophisticated peptide docking and dynamics simulation. It is revealed that, despite developed solely based on solved structures, the integrated unsupervised-supervised method is also applicable for locally docked structures to reach a quantitative prediction but can only give a qualitative prediction on globally docked structures. The dynamics refinement seems not to change (or improve) the predictive results essentially, although it is computationally expensive and time-consuming relative to peptide docking. We also perform extrapolation of usPpIA predictor to the indirect affinity quantities of HLA-A*0201 binding epitope peptides and NHERF PDZ binding scaffold peptides, consequently resulting in a good and moderate correlation of the predicted KD with experimental IC50 and BLU on the two peptide sets, with Pearson's correlation coefficients Rp = 0.635 and 0.406, respectively.

Molecular conversion of MIG6 hotspot-3 peptide from the nonbinder to a moderate binder of HER2 by rational design of an orthogonal interaction system at the HER2-peptide interface

Human epidermal growth factor receptor 2 (HER2) has been established as an approved druggable target for the treatment of patients with diverse gynecological tumors such as ovarian, cervical and breast cancers. The mitogen-inducible gene 6 (MIG6) protein is a negative regulator of HER2 signaling by using its Seg1 segment to disrupt the allosteric dimerization of HER2 kinase domain. Previous studies found that the Seg1 adopts three separated hotspots to interact with the HER2 dimerization interface, in which the third hotspot (H3) is located at the core region of the interface but its derived H3 peptide (356PKYVS360) and Tyr358Phe mutant (356PKFVS360) cannot bind effectively to the interface in an independent manner. In this study, we demonstrate that the H3 peptide can be converted from nonbinder to a moderate binder of HER2 by just adding an orthogonal noncovalent interaction system (X⋯O┄H) between a halogen bond (X⋯O) and a hydrogen bond (H┄O) involving peptide Phe358 residue and HER2 Val948/Trp951 residues. High-level calculations are utilized to rigorously characterize and rationally design the X⋯O┄H system, which is then optimized with different halogen atoms and at different substituting positions. It is revealed that there is a synergistic effect between the X⋯O and H┄O of the orthogonal interaction system; formation of the halogen bond can enhance the interaction strength of the hydrogen bond. In silico analysis and in vitro assay reach a consistence that Br-substitution at the m-position of peptide Phe358 phenyl moiety is the best choice that can render strong interaction for the X⋯O┄H system, which also makes the peptide 'bindable' to HER2 kinase domain, while F/Cl/I-substitution at the same position can only improve the peptide affinity moderately or modestly. In contrast, the Br-substitution at the o- and p-positions of peptide Phe358 phenyl moiety cannot define effective X⋯O┄H interaction and thus does not confer additional affinity to the HER2-peptide complex.

Mig6 not only inhibits EGFR and HER2 but also targets HER3 and HER4 in a differential specificity: Implications for targeted esophageal cancer therapy

The human EGF receptor family plays pivotal roles in physiology and cancer, which contains four closely-related members: HER1/EGFR, HER2, HER3 and HER4. Previously, it was found that the mitogen-inducible gene 6 (Mig6) protein is a negative regulator of EGFR and HER2 by using its S1 segment to bind at the kinase dimerization interface. However, it is still unclear whether the S1 segment can also effectively target HER3 and HER4? Here, we performed a systematic investigation to address this issue. The segment can bind to all the four HER kinases with a varying affinity and moderate selectivity; breaking of the segment into shorter hotspot peptides would largely impair the affinity and selectivity, indicating that the full-length sequence is required for the effective binding of S1 to these kinases. The hs2 peptide, which corresponds to the middle hotspot region of S1 segment, can partially retain the affinity to HER kinases, can moderately compete with S1 segment at the dimerization interfaces, and can mimic the biological function of Mig6 protein to suppress HER4+ esophageal cancer at cellular level. In addition, we also analyzed the binding potency of S1 segment and hs2 peptide to the kinase domains of other five widely documented growth factor receptors (GFRs). It was showed that both the S1 and hs2 cannot effectively interact with these receptors. Overall, the Mig6 is suggested as a specific pan-HER inhibitor, which can target and suppress HER family members with a broad selectivity, but exhibits weak or no activity towards other GFRs.

Context contribution to the intermolecular recognition of human ACE2-derived peptides by SARS-CoV-2 spike protein: implications for improving the peptide affinity but not altering the peptide specificity by optimizing indirect readout

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an etiological agent of the current rapidly growing outbreak of coronavirus disease (COVID-19), which is straining health systems around the world. Disrupting the intermolecular association of SARS-CoV-2 spike glycoprotein (S protein) with its cell surface receptor human angiotensin-converting enzyme 2 (hACE2) has been recognized as a promising therapeutic strategy against COVID-19. The association is a typical peptide-mediated interaction, where the hACE adopts an α1-helix, which can form a two-helix bundle with the α2-helix, to pack against a flat pocket on the S protein surface. Here, we demonstrate that the protein context of full-length hACE plays an essential role in supporting the hACE2 α1-helix recognition by viral S protein. Energetic analysis reveals that the α1-helical peptide (αHP) and also the two-helix bundle peptide (tBP) cannot bind effectively to S protein when they are split from the hACE protein. The context contributes moderately and considerably to the direct readout (DR) and indirect readout (IR) of peptide recognition, respectively. Dynamics simulation suggests that the two free peptides exhibit a large intrinsic disorder without the support of protein context, which would incur a considerable entropy penalty upon binding to S protein. To restore the IR effect lost by splitting peptides from hACE, we herein propose employing hydrocarbon stapling and cyclization strategies to constrain the free αHP and tBP peptides into their native ordered conformations, respectively. The stapling and cyclization are carefully designed in order to avoid influencing the peptide DR effect, which has been demonstrated to improve the peptide binding affinity (but not specificity) to S protein. The stapling/cyclization-imposed conformational constraint can effectively minimize the unfavorable IR effect (i) by reducing the peptide flexibility and entropy cost upon their binding to S protein, and (ii) by helping peptide pre-folding into their native state to facilitate the conformational selection by S protein.

Rational Design and Intramolecular Cyclization of Hotspot Peptide Segments at YAP–TEAD4 Complex Interface

Background:

The Yes-Associated Protein (YAP) is a central regulator of Hippo pathway involved in carcinogenesis, which functions through interaction with TEA Domain (TEAD) transcription factors. Pharmacological disruption of YAP–TEAD4 complexes has been recognized as a potential therapeutic strategy against diverse cancers by suppressing the oncogenic activity of YAP.

Objective:

Two peptides, termed PS-1 and PS-2 are split from the interfacial context of YAP protein. Dynamics simulations, energetics analyses and fluorescence polarizations are employed to characterize the intrinsic disorder as well as binding energy/affinity of the two YAP peptides to TEAD4 protein.

Methods:

Two peptides, termed PS-1 and PS-2 are split from the interfacial context of YAP protein. Dynamics simulations, energetics analyses and fluorescence polarizations are employed to characterize the intrinsic disorder as well as binding energy/affinity of the two YAP peptides to TEAD4 protein.

Result:

The native conformation of PS-2 peptide is a cyclic loop, which is supposed to be constrained by adding a disulfide bond across the spatially vicinal residue pair Arg87-Phe96 or Met86- Phe95 at the peptide’s two ends, consequently resulting in two intramolecular cyclized counterparts of linear PS-2 peptide, namely PS-2(cyc87,96) and PS-2(cyc86,95). The linear PS-2 peptide is determined as a weak binder of TEAD4 (Kd = 190 μM), while the two cyclic PS-2(cyc87,96) and PS-2(cyc86,95) peptides are measured to have moderate or high affinity towards TEAD4 (Kd = 21 and 45 μM, respectively).

Conclusion:

PS-1 and PS-2 peptides are highly flexible and cannot maintain in native active conformation when splitting from the interfacial context, and thus would incur a considerable entropy penalty upon rebinding to the interface. Cyclization does not influence the direct interaction between PS-2 peptide and TEAD4 protein, but can largely reduce the intrinsic disorder of PS-2 peptide in free state and considerably minimize indirect entropy effect upon the peptide binding.

Inverse in silico-in vitro fishing of unexpected paroxetine kinase targets from tumor druggable kinome

The serotonin selective reuptake inhibitor paroxetine has been clinically observed to reposition a significant suppressing potency on human tumors by unexpectedly targeting diverse kinase pathways involved in tumorigenesis. Here, we describe an inverse in silico-in vitro strategy to fish potential kinase targets using the paroxetine as bait. This is different (inverse) to the traditional drug discovery process that commonly screens small-molecule inhibitors for a specific kinase target. In the procedure, cell viability assays demonstrate that paroxetine has strong cytotoxicity on human tumor cell lines. Various protooncogene protein kinases are ontologically/manually enriched to define a druggable kinome, and a systematic interaction profile of paroxetine with the kinome is created, which indicates that paroxetine can potentially bind to some known targets or key regulators of human tumors. Kinase assays determine that paroxetine can effectively inhibit c-Src family kinases at nanomolar or micromolar levels. It is observed that the paroxetine ligand forms a tightly packed interface against the active site of these unexpected kinase targets to constitute several specific hydrogen bonds/π-π/cation-π stackings and a number of nonspecific hydrophobic/vdW contacts, while exposing a portion of molecular surface to solvent. More significantly, the ligand adopts two distinct binding modes (i.e., class I and class II) to interact with different kinases; the class-I mode has a higher stability and inhibitory activity than class-II mode. Steric clash seems to cause the ligand flipping from class I to class II. Graphical abstract.

Molecular selectivity design of mitogen-inducible gene-derived phosphopeptides between oncogenic HER kinases

Mitogen-inducible gene (MIG) is a natural negative regulator of the oncogenic HER kinase signaling by binding at the activation interface of kinase domain to disrupt the kinase dimerization. In this study, we systematically examine the binding structures, dynamics and energetics of MIG region 2 to four HER kinases based on their crystal or modeled complex structures, and identify an 8-mer phosphopeptide segment pYpY from the core strand sequence of MIG region 2 as the binding hotspot of MIG protein to HER kinases. We demonstrate that the small pYpY phosphopeptide can partially restore the binding affinity of full-length MIG protein, but exhibit a moderate selectivity over different HER kinases (S = 2.3-fold). In addition, the two phosphotyrosine residues pTyr394 and pTyr395 play an essential role in MIG-HER binding; dephosphorylation of them would fully eliminate the binding capability. A machine evolution algorithm is used to optimize the wild-type pYpY phosphopeptide, aiming to simultaneously improve affinity for these kinases and to maximize the affinity gap between different kinases. Consequently, a population is computationally evolved as selective phosphopeptide candidates; the dissociation constants of four representatives with HER kinases are systematically determined using binding affinity analysis, from which their selectivity is derived. The designed pYpYp3 phosphopeptide possesses a high selectivity over different HER kinases (S = 4.8-fold) and satisfactory affinity profile to these kinase (K_D = 140-1000 μM). Structural analysis observes that the global binding modes of pYpYp3 to different kinases are roughly consistent, but its local conformation may vary considerably, thus conferring specificity to the phosphopeptide.

Systematic response of staurosporine scaffold-based inhibitors to drug-resistant cancer kinase mutations

Human protein kinases have been established as promising druggable targets in cancer therapy. However, a large number of acquired drug-resistant kinase mutations are observed after first- and second-line kinase inhibitor treatments, largely limiting the application of small-molecule inhibitors in the targeted cancer therapy. Previously, the pan-kinase inhibitor staurosporine and its derivatives have been reported to selectively inhibit gatekeeper mutants over wild-type kinases, suggesting that the staurosporine scaffold is potentially helpful in developing wild-type-sparing inhibitors of drug-resistant kinase mutants. Here, a systematic response profile of 32 staurosporine scaffold-based inhibitors (SSBIs) for 61 ontology-enriched drug-resistant cancer kinase mutations is created using a combination of in silico analysis and in vitro assay, from which it is possible to identify those mutations that have the potential to cause resistance or confer sensitivity to SSBIs. The profile reveals that SSBIs exhibit distinct responses to kinase gatekeeper and nongatekeeper mutations, and SSBIs bearing p7 substituents can considerably influence their response to kinase gatekeeper mutations, particularly for the mutations of the Ile residue, which possesses a Cβ methyl group that tends to cause steric clash with bound SSBIs. Nongatekeeper mutations generally have a moderate and unfavorable effect on SSBI activity, as most of them are outside the kinase active site and do not directly contact inhibitor ligands. In addition, it is found that resistance is commonly caused by mutation-induced hindrance effects, whereas sensitivity is primarily conferred by mutation-established additional interactions.

Identification, characterization, and comparison of n-alkanols and anesthetics binding to the C1b subdomain of protein kinase cα: similar function with different binding sites

Protein kinase C (PKC) is a family of lipid-activated enzymes involved in anesthetic preconditioning signaling pathways. Previously, n-alkanols and general anesthetics have been found to activate PKC by binding to the kinase C1B subdomain. In the present study, we attempt to ascertain the molecular mechanism and interaction mode of human PKCα C1B subdomain with a variety of exogenous n-alkanols and volatile general anesthetics as well as endogenous activator phorbol ester (PE) and co-activator diacylglycerol (DG). Systematic bioinformatics analysis identifies three spatially vicinal sites on the subdomain surface to potentially accommodate small-molecule ligands, where the site 1 is a narrow, amphipathic pocket, the site 2 is a wide, flat and hydrophobic pocket, and the site 3 is a rugged, polar pocket. Further interaction modeling reveals that site 1 is the cognate binding region of natural PE activator, which can moderately simulate the kinase activity in an independent manner. The short-chain n-alkanols are speculated to also bind at the site to competitively inhibit PE-induced kinase activation. The long-chain n-alkanols and co-activator DG are found to target site 2 in a nonspecific manner, while the volatile anesthetics prefer to interact with site 3 in a specific manner. Since the site 1 is composed of two protein loops that are also shared by sites 2 and 3, binding of n-alkanols, DG and anesthetics to sites 2 and 3 can trigger a conformational displacement on the two loops, which enlarges the pocket size and changes the pocket configuration of site 1 through an allosteric mechanism, consequently enhancing kinase activation by improving PE affinity to the site.

Systematic profiling of staralog response to acquired drug resistant kinase gatekeeper mutations in targeted cancer therapy

Kinase-targeted therapy has been widely used as a lifesaving strategy for cancer patients. However, many patients treated with targeted cancer drugs are clinically observed to rapidly develop acquired resistance. Kinase gatekeeper mutation is one of the most chief factors contributing to the resistance, which modulates the accessibility of kinase's ATP-binding pocket. Previously, the pan-kinase inhibitor Staurosporine and its analogs (termed as Staralogs) have been reported to exhibit wild-type sparing selectivity for some kinase gatekeeper mutants, such as EGFR T790M, Her2 T798M and cSrc T338M. Here, we describe an integrative approach to systematically profile the molecular response of 15 representative Staralogs to 17 kinase gatekeeper mutations in targeted cancer therapy. With the profile we are able to divide gatekeeper mutations into three classes (i.e. classes I, II and III) and to divide Staralogs into two groups (i.e. groups 1 and 2) using heuristic clustering. The class I and II mutations confer consistent sensitivity and resistance for all Staralogs, respectively, while the class III mutations address divergent effects on different Staralogs. The mutations to Ile residue can generally reduce Staralog affinity by inducing unfavorable steric hindrance, whereas the mutations to Met and Leu residues would improve Staralog affinity by establishing favorable S···π interaction, van der Waals packing and/or hydrophobic contact. The group 1 and 2 Staralogs are primarily determined by carbonyl or hydroxyl substitution state at the position 7 of Staralog core, where points to kinase gatekeeper residue and can thus be directly influenced by gatekeeper mutation.

Inverse screening of Simvastatin kinase targets from glioblastoma druggable kinome

The statin drug Simvastatin is a HMG-CoA reductase inhibitor that has been widely used to lower blood lipid. However, the drug is clinically observed to reposition a significant suppressing potency on glioblastoma (GBM) by unexpectedly targeting diverse kinase pathways involved in GBM tumorigensis. Here, an inverse screening strategy is described to discover potential kinase targets of Simvastatin. Various human protein kinases implicated in GBM are enriched to define a druggable kinome; the binding behavior of Simvastatin to the kinome is profiled systematically via an integrative computational approach, from which most kinases have only low or moderate binding potency to Simvastatin, while only few are identified as promising kinase hits. It is revealed that Simvastatin can potentially interact with certain known targets or key regulators of GBM such as ErbB, c-Src and FGFR signaling pathways, but exhibit low affinity to the well-established GBM target of PI3K/Akt/mTOR pathway. Further assays determine that Simvastatin can inhibit kinase hits EGFR, MET, SRC and HER2 at nanomolar level, which are comparable with those of cognate kinase inhibitors. Structural analyses reveal that the sophisticated T790 M gatekeeper mutation can considerably reduce Simvastatin sensitivity to EGFR by inducing the ligand change between different binding modes.

Rational design and improvement of the dimerization-disrupting peptide selectivity between ROCK-I and ROCK-II kinase isoforms in cerebrovascular diseases

Human rho-associated coiled-coil forming kinases (ROCKs) ROCK-I and ROCK-II have been documented as attractive therapeutic targets for cerebrovascular diseases. Although ROCK-I and ROCK-II share a high degree of structural conservation and are both present in classic rho/ROCK signaling pathway, their downstream substrates and pathological functions may be quite different. Selective targeting of the two kinase isoforms with traditional small-molecule inhibitors is a great challenge due to their surprisingly high homology in kinase domain (~90%) and the full identity in kinase active site (100%). Here, instead of developing small-molecule drugs to selectively target the adenosine triphosphate (ATP) site of two isoforms, we attempt to design peptide agents to selectively disrupt the homo-dimerization event of ROCK kinases through their dimerization domains which have a relatively low conservation (~60%). Three helical peptides H1, H2, and H3 are split from the kinase dimerization domain, from which the isolated H2 peptide is found to have the best capability to rebind at the dimerization interface. A simulated annealing (SA) iteration method is used to improve the H2 peptide selectivity between ROCK-I and ROCK-II. The method accepts moderate degradation in peptide affinity in order to maximize the affinity difference between peptide binding to the two isoforms. Consequently, hundreds of parallel SA runs yielded six promising peptide candidates with ROCK-I over ROCK-II (I over II [IoII]) calculated selectivity and four promising peptide candidates with ROCK-II over ROCK-I (II over I [IIoI]) calculated selectivity. Subsequent anisotropy assays confirm that the selectivity values range between 13.2-fold and 83.9-fold for IoII peptides, and between 5.8-fold and 21.2-fold for IIoI peptides, which are considerably increased relative to wild-type H2 peptide (2.6-fold for IoII and 2.0-fold for IIoI). The molecular origin of the designed peptide selectivity is also analyzed at structural level; it is revealed that the peptide residues can be classified into conserved, non-conserved, and others, in which the non-conserved residues play a crucial role in defining peptide selectivity, while conserved residues confer stability to kinase-peptide binding.

SPION decorated exosome delivery of TNF-α to cancer cell membranes through magnetism

Tumor necrosis factor (TNF-α) is capable of inducing apoptosis and is a promising candidate for genetic engineering drugs in cancer therapy; however, the serious side-effects of TNF-α hinder their clinical application. In the present study, a method for preparing fusion proteins of cell-penetrating peptides (CPP) and TNF-α (CTNF-α)-anchored exosomes coupled with superparamagnetic iron oxide nanoparticles (CTNF-α-exosome-SPIONs) with membrane targeting anticancer activity has been demonstrated. To acquire exosomes with TNF-α anchored in its membrane, a CTNF-α expression vector was constructed and a stable mesenchymal stem cell cell line that expressed CTNF-α was established. Conjugating transferrin-modified SPIONs (Tf-SPIONs) onto CTNF-α-exosomes through transferrin-transferrin receptor (Tf-TfR) interaction yields CTNF-α-exosome-SPIONs with good water dispersibility. The incorporation of TNF-α into exosomes and the conjugation of SPIONs significantly enhanced the binding capacity of TNF-α to its membrane-bound receptor TNFR I, thus increasing the therapeutic effects. CTNF-α-exosome-SPIONs significantly enhanced tumor cell growth inhibition via induction of the TNFR I-mediated apoptotic pathway. In vivo studies using murine melanoma subcutaneous cancer models showed that TNF-α-loaded exosome-based vehicle delivery enhanced cancer targeting under an external magnetic field and suppressed tumor growth with mitigating toxicity. Taken together, our results suggest that CTNF-α-exosome-SPIONs showed great potential in membrane targeting therapy.

Molecular modeling and rational design of hydrocarbon-stapled/halogenated helical peptides targeting CETP self-binding site: Therapeutic implication for atherosclerosis

The human plasma cholesteryl ester transfer protein (CETP) collects triglycerides from very-/low-density lipoproteins (V/LDL) and exchanges them for cholesteryl esters from high-density lipoproteins (HDL), which has recognized as an important therapeutic target for atherosclerosis. The protein has a C-terminal amphipathic α-helix that serves as self-binding peptide to fulfill biological function by dynamically binding to/unbinding from its cognate site (termed self-binding site) in the same protein. Previously, we successfully derived and halogenated the helical peptide to competitively disrupt the self-binding behavior of CETP C-terminal tail. However, the halogenated peptides have only a limited affinity increase as compared to native helical peptide (∼3-fold), thus exhibiting only a moderate competitive potency. Here, instead of optimizing the direct intermolecular interaction of peptide with CETP self-binding site we attempt to further improve the peptide competitive potency by reducing its conformational flexibility with hydrocarbon-stapling technique. Computational analysis reveals that the helical peptide has large intrinsic disorder in unbound free state, which would incur a considerable entropy penalty upon rebinding to the self-binding site. All-hydrocarbon bridge is designed and optimized on native and halogenated peptides in terms of the helical pattern and binding mode of self-binding peptide. Dynamics simulation and circular dichroism indicate that the stapling can considerably reduce peptide disorder in free state. Energetics calculation and fluorescence assay conform that the binding affinity of stapled/halogenated peptides is improved substantially (by > 5-fold), thus exhibiting an effective competition potency with native peptide for the self-binding site. Structural examination suggests that the binding modes and nonbonded interactions of native and halogenated peptides are not influenced essentially due to the stapling.

Involvement of Local, Rapid Conformational Dynamics in Binding of Flexible Recognition Motifs

Flexible protein sequences populate ensembles of rapidly interconverting states differentiated by small-scale fluctuations; however, elucidating whether and how the ensembles determine function experimentally is challenged by the combined high spatial and temporal resolution needed to capture the states. We used carbon-deuterium (C-D) bond vibrations incorporated as infrared probes to characterize with residue-specific detail the heterogeneity of states adopted by proline-rich (PR) sequences and assess their involvement in recognition of Src homology 3 domains. The C-D absorption envelopes provided evidence for two or three sub-populations at all proline residues. The changes in the subpopulations induced by binding generally reflected recognition by conformational selection but depended on the residue and the state of the ligand to illuminate distinct mechanisms among the PR ligands. Notably, the spectral data indicate that greater adaptability among the states is associated with reduced recognition specificity and that perturbation to the ensemble populations contributes to differences in binding entropy. Broadly, the study quantifies rapidly interconverting ensembles with residue-specific detail and implicates them in function.

Exploring calcium ion-dependent effect on the intermolecular interaction between human secreted phospholipase A2 and its peptide inhibitors in coronary artery disease

Human secreted phospholipase A₂ (hsPLA₂) is a small calcium ion (Ca²⁺)-regulatory protein secreting from platelets, eosinophils and T-lymphocytes, which has been established as an important biomarker and potential target for the diagnosis and therapy of coronary artery disease. Short peptide inhibitors are used to competitively suppress the enzymatic activity of hsPLA₂. Here, Ca²⁺ effect on the intermolecular recognition and interaction between hsPLA₂ and its peptide inhibitors is investigated systematically by using molecular modeling and bioinformatics analysis. Dynamics simulations reveal that the hsPLA₂ structure bound with Ca²⁺ is rather stable and has low thermal motion; removal of Ca²⁺ considerably increases structural flexibility and intrinsic disorder of the protein. Energetics calculations suggest that presence of Ca²⁺ can effectively promote the interaction of hsPLA₂ with peptide inhibitors. In particular, the local substructures of hsPLA₂ such as helix H1, loop L2 and double-stranded β-sheet DS that participate in peptide recognition are involved in or nearby Ca²⁺-coordinating site and can be directly stabilized by the Ca²⁺. In addition, a significant concentration-dependent effect of Ca²⁺ on peptide-hsPLA₂ binding is observed in vitro, that is, a little of Ca²⁺ can largely improve peptide binding affinity, but high Ca²⁺ concentration does not increase the affinity substantially. The correlation between calculated free energy and experimental binding affinity over different peptide inhibitors is improved considerably by adding Ca²⁺ to hsPLA₂. Specifically, the FLSYK peptide can generally bind to Ca²⁺-bound hsPLA₂ with a moderate or high affinity (K_d ranges between 56 and 210 μM), but have only a modest affinity or even nonbinding to Ca²⁺-free hsPLA₂ (K_d > 400 μM or = n.d.).

Molecular design and optimization of hepatic cancer SLP76-derived PLCγ1 SH3-binding peptide with the systematic N-substitution of peptide PXXP motif

The phospholipase Cγ1 (PLCγ1) is essential for T-cell signaling and activation in hepatic cancer immune response, which has a regulatory Src homology 3 (SH3) domain that can specifically recognize and interact with the PXXP-containing decapeptide segment (¹⁸⁵ QPPVPPQRPM¹⁹⁴ , termed as SLP76^185-194 peptide) of adaptor protein SLP76 following T-cell receptor ligation. The isolated peptide can only bind to the PLCγ1 SH3 domain with a moderate affinity due to lack of protein context support. Instead of the traditional natural residue mutagenesis that is limited by low structural diversity and shifted target specificity, we herein attempt to improve the peptide affinity by replacing the two key proline residues Pro187 and Pro190 of SLP76^185-194 PXXP motif with nonnatural N-substituted amino acids, as the proline is the only endogenous N-substituted amino acid. The replacement would increase peptide flexibility but can restore peptide activity by establishing additional interactions with the domain. Structural analysis reveals that the domain pocket can be divided into a large amphipathic region and a small negatively charged region; they accommodate hydrophobic, aromatic, polar, and moderate-sized N-substituted amino acid types. A systematic replacement combination profile between the peptide residues Pro187 and Pro190 is created by structural modeling, dynamics simulation, and energetics analysis, from which six improved and two reduced N-substituted peptides as well as native SLP76^185-194 peptide are identified and tested for their binding affinity to the recombinant protein of the human PLCγ1 SH3 domain using fluorescence-based assays. Two N-substituted peptides, SLP76^185-194 (N-Leu187/N-Gln190) and SLP76^185-194 (N-Thr187/N-Gln190), are designed to have high potency (K_d  = 0.67 ± 0.18 and 1.7 ± 0.3 μM, respectively), with affinity improvement by, respectively, 8.5-fold and 3.4-fold relative to native peptide (K_d  = 5.7 ± 1.2 μM).

Systematic profiling of clinical missence mutation effects on the intermolecular interaction between human growth hormone and its receptor in isolated growth hormone deficiency

Isolated growth hormone deficiency (IGHD) is the most common pituitary hormone deficiency and can result from congenital or acquired causes. Among the known factors, genetic mutations in human growth hormone (hGH) remain the most frequent cause of IGHD, which influence the binding of hGH to its cognate receptor (hGHbp). Although previous studies have systematically investigated the residue importance at hGH-hGHbp complex interface, the molecular role of IGHD-associated residue mutations in the complex function still remains largely unexplored. Here, a total of 21 known hGH naturally-occurring missence mutations that have been clinically observed to be involved in IGHD disorder are collected and confirmed by original literature; they effects on the conformation, energetics and dynamics of hGH-hGHbp recognition and interaction are dissected at molecular level by using atomistic dynamics simulations, binding energy calculations and fluorescence spectroscopy assays. A systematic profile of hGH-hGHbp binding response to these clinical missence mutations is created, based on which it is revealed that (i) most mutations have appreciably unfavorable effect on the binding, which potentially destabilize the complex interaction, while only very few are predicted as moderate stabilizers for the complex system, and (ii) these disease-related mutations can locate either at complex interface or in hGH protein interior far away from the interface; both can influence the complex binding through either direct interaction or indirect allostericity. Two mutations, E100K (non-interface) and G146R (interface), are identified to address potent destabilization effect on hGH-hGHbp complex system; they can reduce the complex binding affinity by 8-fold (K_d changes from 0.76 to 5.9 nM) and 46-fold (K_d changes from 0.76 to 34.7 nM), respectively.