Fast and reliable prediction of domain–peptide binding affinity using coarse-grained structure models

Computational insight into stability-enhanced systems of anthocyanin with protein/peptide

Anthocyanins, which belong to the flavonoid group, are commonly found in the organs of plants native to South and Central America. However, these pigments are unstable under conditions of varying pH, heat, etc., which limits their potential applications. One method for preserving the stability of anthocyanins is through encapsulation using proteins or peptides. Nevertheless, the complex and diverse structure of these molecules, as well as the limitation of experimental technologies, have hindered a comprehensive understanding of the encapsulation processes and the mechanisms by which stability is enhanced. To address these challenges, computational methods, such as molecular docking and molecular dynamics simulation have been used to study the binding affinity and dynamics of interactions between proteins/peptides and anthocyanins. This review summarizes the mechanisms of interaction between these systems, based on computational approaches, and highlights the role of proteins and peptides in the stability enhancement of anthocyanins. It also discusses the current limitations of these methods and suggests possible solutions.

HLA Class I Supertype Classification Based on Structural Similarity

HLA class I proteins, a critical component in adaptive immunity, bind and present intracellular Ags to CD8+ T cells. The extreme polymorphism of HLA genes and associated peptide binding specificities leads to challenges in various endeavors, including neoantigen vaccine development, disease association studies, and HLA typing. Supertype classification, defined by clustering functionally similar HLA alleles, has proven helpful in reducing the complexity of distinguishing alleles. However, determining supertypes via experiments is impractical, and current in silico classification methods exhibit limitations in stability and functional relevance. In this study, by incorporating three-dimensional structures we present a method for classifying HLA class I molecules with improved breadth, accuracy, stability, and flexibility. Critical for these advances is our finding that structural similarity highly correlates with peptide binding specificity. The new classification should be broadly useful in peptide-based vaccine development and HLA-disease association studies.

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.

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.

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.

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.

Machine Learning in Quantitative Protein–peptide Affinity Prediction: Implications for Therapeutic Peptide Design

Background:

Protein–peptide recognition plays an essential role in the orchestration and regulation of cell signaling networks, which is estimated to be responsible for up to 40% of biological interaction events in the human interactome and has recently been recognized as a new and attractive druggable target for drug development and disease intervention.

Methods:

We present a systematic review on the application of machine learning techniques in the quantitative modeling and prediction of protein–peptide binding affinity, particularly focusing on its implications for therapeutic peptide design. We also briefly introduce the physical quantities used to characterize protein–peptide affinity and attempt to extend the content of generalized machine learning methods.

Results:

Existing issues and future perspective on the statistical modeling and regression prediction of protein– peptide binding affinity are discussed.

Conclusion:

There is still a long way to go before establishment of general, reliable and efficient machine leaningbased protein–peptide affinity predictors.

Systematic analysis and identification of unexpected interactions from the neuroprotein drug interactome in hydrocephalus pharmacological intervention

Hydrocephalus is a neurological condition caused by an abnormal accumulation of cerebrospinal fluid; pharmacological intervention of the disease has been found to elicit a variety of adverse drug reactions (ADRs) in central nervous system (CNS) by unexpectedly targeting certain functional neuroproteins. Here, a systematic neuroprotein drug interactome (SNDI) is created for 11 hydrocephalus drugs/metabolites plus 20 control drugs across 518 druggable pockets on the surface of 472 CNS neuroproteins via a large-scale molecular docking approach. Heuristic clustering analysis of the SNDI profile divides the 31 investigated drug ligands into a distinct panel and a background panel; the former consists of two hydrocephalus drugs (Furosemide and Triamterene) and their respective metabolites (Furosemide glucuronide and Hydroxytriamterene) that are inferred to have generally high affinity towards the whole array of neuroprotein pockets. A total of 13 neuroproteins are enriched in gene ontology semantic mining as putative unexpected targets of the distinct panel, and their intermolecular interactions with hydrocephalus drugs/metabolites are investigated in detail using dynamics simulation and energetics analysis. We also perform kinase assay and viability test to substantiate the interactome analysis. It is found that the Furosemide and Triamterene have significant cytotoxic effects on normal human astrocytes, in which the Triamterene can inhibit the neurokinase ROCK2, a representative of putative unexpected targets, with a high activity, which is comparable with the sophisticated ROCK2 inhibitor Fasudil.

Rational cyclization-based minimization of entropy penalty upon the binding of Nrf2-derived linear peptides to Keap1: A new strategy to improve therapeutic peptide activity against sepsis

Nrf2 is a critical regulator of innate immune response and survival during sepsis, which is constitutively degraded through binding to the Keap1 adapter protein of E3 ubiquitin ligase. Two linear peptides DLG and ETG derived from, respectively, the low-affinity and high-affinity motifs of Nrf2 binding site exhibit self-binding affinity to Keap1 central hole (active pocket); they can be exploited as therapeutic self-inhibitory peptides to disrupt the Nrf2-Keap1 interaction. Molecular dynamics simulation and binding energetics decomposition reveal that the two peptides possess large flexibility and intrinsic disorder in unbound free state, and thus would incur a considerable entropy penalty upon binding to Keap1. In order to improve Keap1-peptide binding affinity (or free energy ΔG), instead of traditionally increasing favorable enthalpy contribution (ΔH) we herein describe a rational peptide cyclization strategy to minimize unfavorable entropy penalty (ΔS) upon the binding of Nrf2-derived linear peptides to Keap1. Crystal structure analysis impart that the native active conformations of DLG and ETG peptides bound with Keap1 are folded into U-shape and hairpin configurations, respectively, and adopt their turning head to insert into the central hole of Keap1. Here, cyclization is designed by adding a disulfide bond across the two arms of DLG U-shape or ETG hairpin, which would not influence the direct intermolecular interaction between Keap1 and peptide as well as desolvation effect involved in the interaction, but can effectively constrain the conformational flexibility and disorder of the two peptides in free state, thus largely minimizing entropy penalty upon the binding. Both free energy calculation and binding affinity assay substantiate that the cyclization, as might be expected, can moderately or considerably enhance peptide binding potency to Keap1, with affinity (dissociation constant K_d) increase by 1.4-7.5-fold for designed cyclic peptides relative to their linear counterparts.

Systematic analysis and integrative discovery of active-site subpocket-specific dehydroquinate synthase inhibitors combating antibiotic-resistant Staphylococcus aureus infection

Shikimate pathway plays an essential role in the biosynthesis of aromatic amino acids in various plants and bacteria, which consists of seven key enzymes and they are all attractive targets for antibacterial agent development due to their absence in humans. The Staphylococcus aureus dehydroquinate synthase (SaDHQS) is involved in the second step of shikimate pathway, which catalyzes the NAD <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow/><mml:mrow><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math> -dependent conversion of 3-deoxy-D-arabino-heptulosonate-7-phosphate to dehydroquinate via multiple steps. The enzyme active site can be characterized by two spatially separated subpockets 1 and 2, which represent the reaction center of substrate adduct with NAD <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow/><mml:mrow><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math> nicotinamide moiety and the assistant binding site of NAD <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow/><mml:mrow><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math> adenine moiety, respectively. In silico virtual screening is performed against a biogenic compound library to discover SaDHQS subpocket-specific inhibitors, which were then tested against both antibiotic-sensitive and antibiotic-resistant S. aureus strains by using in vitro susceptibility test. The activity profile of hit compounds has no considerable difference between the antibiotic-sensitive and -resistant strains. The subpocket 1-specific inhibitors exhibit a generally higher activity than subpocket 2-specific inhibitors, and they also hold a strong selectivity between their cognate and noncognate subpockets. Dynamics and energetics analyses reveal that the SaDHQS active site prefers to interact with amphipathic and polar inhibitors by forming multiple hydrogen bonds and van der Waals packing at the complex interfaces of the two subpockets with their cognate inhibitors.

Design, cyclization, and optimization of MMP13-TIMP1 interaction-derived self-inhibitory peptides against chondrocyte senescence in osteoarthritis

The matrix metallopeptidase 13 (MMP13) is a central regulator of chondrocyte senescence that contributes to the development and progression of osteoarthritis (OA). In the present study, the native inhibitory structure of MMP13 in complex with its natural cognate inhibitor, the tissue inhibitor of metalloproteinases 1 (TIMP1), was modeled at atomic level using a grafting-based structural bioinformatics method with existing crystal structures. The modeled complex structure was then examined in detail, from which a TIMP1 inhibitory site that directly inserts into the active site of MMP13 enzyme was identified. The inhibitory site contains a coiled inhibitory loop (ILP) and a stretched N-terminal tail (NTT); they are highly structured in the intact MMP13-TIMP1 complex interface, but exhibit a large flexibility and intrinsic disorder when split from the interface context. In vitro binding assays demonstrated that the isolated ILP and NTT peptides cannot effectively rebind at the MMP13 active site (K_d > ~100 μM or = n.d.), although they have all key interacting residues in the enzyme inhibition. In silico simulations revealed that splitting of the peptide segments from TIMP1 inhibitory site does not influence the direct intermolecular interaction between MMP13 and the peptides substantially; instead, the large conformational flexibility of these isolated peptides in absence of interface context is primarily responsible for the affinity impairment, which would incur a considerable entropy penalty upon the peptide binding to MMP13. An extended version of ILP peptide, namely eILP (⁶³TPAMESVCGY⁷²), was redesigned with a rational strategy to derive a number of its cyclized counterparts by introducing a disulfide bridge across the peptide two-termini; the redesign reduces the peptide flexibility in free state and constrains the peptide pre-folding to a native-like conformation, which would help the peptide binding with minimized entropy penalty. Binding assays substantiated that the affinity K_d values of four designed cyclic peptides (, , and ) were improved to 23, 67, 42 and 18 μM, respectively, from the 96 μM of linear eILP peptide.

Binding affinity prediction of S. cerevisiae 14-3-3 and GYF peptide-recognition domains using support vector regression

Proteins interact with other proteins and bio-molecules to carry out biological processes in a cell. Computational models help understanding complex biochemical processes that happens throughout the life of a cell. Domain-mediated protein interaction to peptides one such complex problem in bioinformatics that requires computational predictive models to identify meaningful bindings. In this study, domain-peptide binding affinity prediction models are proposed based on support vector regression. Proposed models are applied to yeast bmh 14-3-3 and syh GYF peptide-recognition domains. The cross validated results of the domain-peptide binding affinity data sets show that predictive performance of the support vector based models are efficient.