钙调蛋白抑制剂预测模型研究

选用30个结构多样的caM抑制剂分子作为数据集,采用多元线性回归(MLR)方法及主成分回归分析(PCA)方法对每个化合物的194个分子参数进行回归分析,分别建立了各自的最优预测模型.结果表明:多元线性回归分析方法所建模型与主成分回归所建模型相对比,发现逐步筛选法为最优建模方法?该方法所建模型统计结果良好(R2=0.952,SEE为0.289),应用于检验集时结果也比较令人满意(R2=0.941,SEP为0.295),模型表现出较强的可靠性和预测性.     

Amplification of bifunctional ligands for calmodulin from a dynamic combinatorial library

A well known strategy to prepare high affinity ligands for a biological receptor is to link together low affinity ligands. DCC (dynamic combinatorial chemistry) was used to select bifunctional protein ligands with high affinity relative to the corresponding monofunctional ligands. Thiol to disulfide linkage generated a small dynamic library of bifunctional ligands in the presence of calmodulin, a protein with two independently mobile domains. The binding constant of the bifunctional ligand (disulfide) most amplified by the presence of calmodulin is nearly two orders of magnitude higher than that of the corresponding monofunctional ligand (thiol).     

Calculation of affinities of peptides for proteins

Several methodologies were employed to calculate the Gibbs standard free energy of binding for a collection of protein-ligand complexes, where the ligand is a peptide and the protein is representative for various protein families. Almost 40 protein-ligand complexes were employed for a continuum approach, which considers the protein and the peptide at the atomic level, but includes solvent as a polarizable continuum. Five protein-ligand complexes were employed for an all-atom approach that relies on a combination of the double decoupling method with thermodynamic integration and molecular dynamics. These affinities were also computed by means of the linear interaction energy method. Although it generally proved rather difficult to predict the absolute free energies correctly, for some protein families the experimental ranking order was correctly reproduced by the continuum and all-atom approach. Considerable attention has also been given to correctly analyze the affinities of charged peptides, where it is required to judge the effect of one or more ions that are being decoupled in an all-atom approach to preserve electroneutrality. The various methods are further judged upon their merits.     

Prediction and analysis of binding affinities for chemically diverse HIV-1 PR inhibitors by the modified SAFE_p approach

One of the biggest challenges in the "in silico" screening of enzyme ligands is to have a protocol that could predict the ligand binding free energies. In our group we have developed a very simple screening function (referred to as solvent accessibility free energy of binding predictor, SAFE_p) which we have applied previously to the study of peptidic HIV-1 protease (HIV-1 PR) inhibitors and later to cyclic urea type HIV-1 PR inhibitors. In this work, we have extended the SAFE_p protocol to a chemically diverse set of HIV-1 PR inhibitors with binding constants that differ by several orders of magnitude. The resulting function is able to reproduce the ranking and in many cases the value of the inhibitor binding affinities for the HIV-1 PR, with accuracy comparable with that of costlier protocols. We also demonstrate that the binding pocket SAFE_p analysis can contribute to the understanding of the physical forces that participate in ligand binding. The analysis tools afforded by our protocol have allowed us to identify an induced fit phenomena mediated by the inhibitor and have demonstrated that larger fragments do not necessarily contribute the most to the binding free energy, an outcome partially brought about by the substantial role the desolvation penalty plays in the energetics of binding. Finally, we have revisited the effect of the Asp dyad protonation state on the predicted binding affinities.     

Synthetic receptors for the differentiation of phosphorylated peptides with nanomolar affinities

Artificial ditopic receptors for the differentiation of phosphorylated peptides varying in i+3 amino acid side chains were synthesized, and their binding affinities and selectivities were determined. The synthetic receptors show the highest binding affinities to phosphorylated peptides under physiological conditions (HEPES, pH 7.5, 154 mM NaCl) reported thus far for artificial systems. The tight and selective binding was achieved by high cooperativity of the two binding moieties in the receptor molecules. All receptors interact with phosphorylated serine by bis(ZnII-cyclen) complex coordination and a second binding site recognizing a carboxylate or imidazole amino acid side chain functionality.     

Efficient estimation of binding free energies between peptides and an MHC class II molecule using coarse‐grained molecular dynamics simulations with a weighted histogram analysis method

We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with the weighted histogram analysis method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse‐grained (CG) force field (MARTINI) is less prone to significant error induced by inadequate‐sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3–4 residue peptide segments while leaving the remaining peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and reliably estimate the binding free energy between an arbitrary peptide and an MHC class II molecule. © 2017 Wiley Periodicals, Inc.     

Highly specific affinities of short peptides against synthetic polymers

We investigated polymer-binding 7-mer peptides that recognize differences in the polymer stereoregularity of all-purpose poly(methyl methacrylate)s (PMMAs) with simple chemical structures. Quantitative surface plasmon resonance measurements detected association/dissociation processes of the peptides against PMMA film surfaces, followed by an estimation of kinetic parameters such as association/dissociation rate constants and affinity constants. Greater association and smaller dissociation constants of the peptides were observed against a target isotactic PMMA than the structurally similar reference syndiotactic PMMA, followed by greater affinity constants against the target. A c02 peptide composed of the Glu-Leu-Trp-Arg-Pro-Thr-Arg sequence showed the greatest affinity constant (2.8x10(5) M(-1)) for the target, which was 41-fold greater than that for the reference, thus demonstrating extremely high peptide specificities. The substitution of each amino acid of the c02 peptide to Ala (Ala scanning) clearly revealed the essential amino acids for the affinity constants; the essential order was Pro5>Thr6>Arg7>Glu1>Arg4. In fact, the shorter 4-mer peptide composed of the C-terminal Arg-Pro-Thr-Arg sequence of the c02 peptide still demonstrated strong target specificity, although the N-terminal 4-mer peptide Glu-Leu-Trp-Arg completely lost its specificity. The possible conformations modeled with Molecular Mechanics supported the significance of the Arg-Pro-Thr-Arg sequence. The thermodynamic parameters of the c02 peptide suggested an induced fit mechanism for the specific affinity. The present affinity analyses of polymer-recognizing peptides revealed significant and general information that was essential for potential applications in peptidyl nanomaterials.     

Prediction for understanding the effectiveness of antiviral peptides

The low efficacy of current antivirals in conjunction with the resistance of viruses against existing antiviral drugs has resulted in the demand for the development of novel antiviral agents. Antiviral peptides (AVPs) are those bioactive peptides having virucidal activity and they can be developed into promising antiviral drugs. They are shorter length peptides having the ability to cease the progression of viral infections. The use of antiviral peptides in therapeutics has recently attracted the attention of the research community. The development and identification of AVPs is imperative for the discovery of novel therapeutics for viral infections. In the present work, a meta classifier (stacking) based approach is implemented for the prediction of IC₅₀ (half maximal inhibitory concentration) and pIC₅₀ (negative log of half maximal inhibitory concentration) values. The best prediction model with evolutionary information and local alignment scores as features achieved a correlation coefficient values of 0.670 and 0.753 on the training and testing sets respectively for IC₅₀. Further, the prediction of pIC₅₀ reached a correlation coefficient value of 0.797 and 0.789 for training and testing sets respectively. For the development of machine learning models involved in the prediction of IC₅₀, the use of pIC₅₀ over IC₅₀ is recommended as the target variable. Further on a systematic comparison of AVPs with high IC₅₀ values and Low IC₅₀ values, it is revealed that higher mean charge and tiny amino acids are preferred and higher length and consecutive hydrophilic amino acids are avoided in the former.     

Adding energy minimization strategy to peptide‐design algorithm enables better search for RNA‐binding peptides: Redesigned λ N peptide binds boxB RNA

Our previously developed peptide‐design algorithm was improved by adding an energy minimization strategy which allows the amino acid sidechains to move in a broad configuration space during sequence evolution. In this work, the new algorithm was used to generate a library of 21‐mer peptides which could substitute for λ N peptide in binding to boxB RNA. Six potential peptides were obtained from the algorithm, all of which exhibited good binding capability with boxB RNA. Atomistic molecular dynamics simulations were then conducted to examine the ability of the λ N peptide and three best evolved peptides, viz. Pept01, Pept26, and Pept28, to bind to boxB RNA. Simulation results demonstrated that our evolved peptides are better at binding to boxB RNA than the λ N peptide. Sequence searches using the old (without energy minimization strategy) and new (with energy minimization strategy) algorithms confirm that the new algorithm is more effective at finding good RNA‐binding peptides than the old algorithm. © 2016 Wiley Periodicals, Inc.     

Prediction, Synthesis and Antigenicity of the Antigenic Peptides of 26kDa Glutathione S-Transferasc of Schistosoma Japonicum (Sj26)

Schistosomiasisisaworldwideparasiticdiseasethataffectsmorethan200millionpersonsin70countriesallovertheworld.Itisveryimportanttodevelopaneffectivevaccineincludingsignificantlevelsofprotectionagainsttheinvasivestageoftheparasiteforthepreventionofrapidr...     

THPep: A machine learning-based approach for predicting tumor homing peptides

In the present era, a major drawback of current anti-cancer drugs is the lack of satisfactory specificity towards tumor cells. Despite the presence of several therapies against cancer, tumor homing peptides are gaining importance as therapeutic agents. In this regard, the huge number of therapeutic peptides generated in recent years, demands the need to develop an effective and interpretable computational model for rapidly, effectively and automatically predicting tumor homing peptides. Therefore, a sequence-based approach referred herein as THPep has been developed to predict and analyze tumor homing peptides by using an interpretable random forest classifier in concomitant with amino acid composition, dipeptide composition and pseudo amino acid composition. An overall accuracy and Matthews correlation coefficient of 90.13% and 0.76, respectively, were achieved from the independent test set on an objective benchmark dataset. Upon comparison, it was found that THPep was superior to the existing method and holds high potential as a useful tool for predicting tumor homing peptides. For the convenience of experimental scientists, a web server for this proposed method is provided publicly at http://codes.bio/thpep/.     

Metal remediation and preconcentration using immobilized short-chain peptides composed of aspartic acid and cysteine

Short-chain peptides (two and seven residues) consisting of a glycine (Gly) attachment group and various combinations of cysteine (Cys) and/or aspartic acid (Asp) were synthesized by Fmoc solid phase peptide synthesis (SPPS) on Tentagel resin. One selected peptide was synthesized on controlled pore glass (CPG) for comparison. The objective was to evaluate metal binding capacities and selectivities of short-chain peptides when minor alterations in the amino acid sequences were made. Metal binding of Ni²⁺, Cd²⁺, Co²⁺, and Mg²⁺ to the synthesized peptides was evaluated using breakthrough curves from a packed microcolumn and flame atomic absorption spectrophotometry (FAAS) detection. Peptides composed primarily of Asp showed single metal capacities as large as 720 μmol metal/g Tentagel resin and 130 μmol metal/g CPG. Simultaneous elution of a multi-metal solution demonstrated that peptides possessing only two Cys residues and four Asp residues were sufficient to yield selective binding of Cd²⁺ over Ni²⁺ and Co²⁺ similar to the selectivity of a six-Cys residue chain but with 60% more Cd²⁺ capacity. Interestingly, peptides supported on Tentagel resin appeared to reach equilibrium with metal-containing influent flow rates of at most 2 ml/min (or a linear velocity of 11 cm/s) and is attributed to better mass transport with the resin than with the CPG. Conditional stability constants calculated for the six-Asp residue chain and each metal showed the majority of sites having a log K in the range of 4.6-4.8. The peptides studied were also able to efficiently preconcentrate solutions containing as little as 0.05 μg/ml Cd²⁺ or Ni²⁺ in an artificial seawater matrix. Uniquely, the seven residue peptides showed surprisingly high metal capacities and metal-to-residue binding ratios (reaching ∼1:2), and are an order of magnitude better than results previously obtained for longer chain polyamino acids (50-70 residues) attached to CPG via silane chemistry.     

Macrocyclic peptides as regulators of protein-protein interactions

Protein-protein interactions are attractive but challenging targets for drug discovery. Recent technological progress and examples using macrocyclic peptides as protein interaction modulators are reviewed.     

Hydration of small peptides

The results for the sequential hydration of small peptides (<15 residues) obtained in our group are reviewed and put in perspective with other work published in the literature where appropriate. Our findings are based on hydration equilibrium measurements in a high-pressure drift cell inserted into an electrospray mass spectrometer and on calculations employing molecular mechanics and density functional theory methods. It is found that the ionic functional groups typically present in peptides, the ammonium, guanidinium, and carboxylate groups, are the primary target of water molecules binding to peptides. Whereas the water–guanidinium binding energy is fairly constant at 9 ± 1 kcal/mol, the water binding energy of an ammonium group ranges from 7 to 15 kcal/mol depending on how exposed the ammonium group is. A five-residue peptide containing an ammonium group is in favorable cases large enough to fully self-solvate the charge, but a pentapeptide containing a guanidinium group is too small to efficiently shield the charge of this much larger ionic group. The water–carboxylate interaction amounts to 13 kcal/mol with smaller values for a shielded carboxylate group. Both water bound to water in a second solvation shell and charge remote water molecules on the surface of the peptide are bound by 7–8 kcal/mol. The presence of several ionic groups in multiply charged peptides increases the number of favorable hydration sites, but does not enhance the water–peptide binding energy significantly. Water binding energies measured for the first four water molecules bound to protonated bradykinin do not show the declining trend typically observed for other peptides but are constant at 10 kcal/mol, a result consistent with a molecule containing a salt bridge with several good hydration sites. Questions regarding peptide structural changes as a function of number of solvating water molecules are discussed. Not much is known at present about the effect of individual water molecules on the conformation of peptides and on the stability of peptide zwitterions.     

Skin and wound delivery systems for antimicrobial peptides

Non-healing wounds cause hundreds of thousands of deaths every year, and result in large costs for society. A key reason for this is the prevalence of challenging bacterial infections, which may dramatically hinder wound healing. With resistance development among bacteria against antibiotics, this situation has deteriorated during the last couple of decades, pointing to an urgent need for new wound treatments. In particular, this applies to wound dressings able to combat bacterial infection locally in wounds and impaired skin, including those formed by bacteria resistant to conventional antibiotics. Within this context, antimicrobial peptides (AMPs) are currently receiving intense interest. AMPs are amphiphilic peptides, frequently net positively charged, and with a sizable fraction of hydrophobic amino acids. Through destabilization of bacterial membranes, neutralization of inflammatory lipopolysaccharides, and other mechanisms, AMPs can be designed for potent antimicrobial effects, also against antibiotics-resistant strains, and to provide immunomodulatory effects while simultaneously displaying low toxicity. While considerable attention has been placed on AMP optimization and clarification of their mode(s)-of-action, much less attention has been paid on efficient AMP delivery. Considering that AMPs are large molecules, net positively charged, amphiphilic, and susceptible to infection-mediated proteolytic degradation, efficient in vivo delivery of such peptides is, however, challenging and delivery systems needed for the realization of AMP-based therapeutics. In the present work, recent developments regarding AMP delivery systems for treatment of wounds and skin infections are discussed, with the aim to link results from physicochemical studies on, e.g., peptide loading/release, membrane interactions, and self-assembly, with those on the biological functional performance of AMP delivery systems in terms of antimicrobial effects, cell toxicity, inflammation, and wound healing.     

Metal binding discrimination of the calmodulin Q41C/K75C mutant on Ca~(2+) and La~(3+)

Calmodulin (CaM) is a multifunctional Ca2+-binding protein regulating the activity of many enzymes in response to fluctuation of the intracellular Ca2+ level. It has been shown that a CaM Q41C/K75C mutant (CaMSS) with a disulfide bond in the N-terminal domain exhibits greatly reduced affinity to Ca2+. In the present study, the experimental results revealed a unique metal binding pattern in CaMSS towards La3+ and Ca2+ separately: the mutant protein binds Ca2+ at site Ⅰ, Ⅲ and IV; however, it binds La3+ at si...     

Identification of novel peptides that stimulate human neutrophils

Neutrophils play a key role in innate immunity, and the identification of new stimuli that stimulate neutrophil activity is a very important issue. In this study, we identified three novel peptides by screening a synthetic hexapeptide combinatorial library. The identified peptides GMMWAI, MMHWAM, and MMHWFM caused an increase in intracellular Ca2+ in a concentration-dependent manner via phospholipase C activity in human neutrophils. The three peptides acted specifically on neutrophils and monocytes and not on other non-leukocytic cells. As a physiological characteristic of the peptides, we observed that the three peptides induced chemotactic migration of neutrophils as well as stimulated superoxide anion production. Studying receptor specificity, we observed that two of the peptides (GMMWAI and MMHWFM) acted on formyl peptide receptor (FPR)1 while the other peptide (MMHWAM) acted on FPR2. Since the three novel peptides were specific agonists for FPR1 or FPR2, they might be useful tools to study FPR1- or FPR2-mediated immune response and signaling.     

Design of peptides that form amyloid-like fibrils capturing amyloid beta1-42 peptides

Amyloid beta-peptide (Abeta) plays a critical role in Alzheimer's disease (AD). The monomeric state of Abeta can self-assemble into oligomers, protofibrils, and amyloid fibrils. Since the fibrils and soluble oligomers are believed to be responsible for AD, the construction of molecules capable of capturing these species could prove valuable as a means of detecting these potentially toxic species and of providing information pertinent for designing drugs effective against AD. To this aim, we have designed short peptides with various hydrophobicities based on the sequence of Abeta14-23, which is a critical region for amyloid fibril formation. The binding of the designed peptides to Abeta and the amplification of the formation of peptide amyloid-like fibrils coassembled with Abeta are elucidated. A fluorescence assay utilizing thioflavin T, known to bind specifically to amyloid fibrils, revealed that two designed peptides (LF and VF, with the leucine and valine residues, respectively, in the hydrophobic core region) could form amyloid-like fibrils effectively by using mature Abeta1-42 fibrils as nuclei. Peptide LF also coassembled with soluble Abeta oligomers into peptide fibrils. Various analyses, including immunostaining with gold nanoparticles, enzyme-linked immunosorbent assays, and size-exclusion chromatography, confirmed that the LF and VF peptides formed amyloid-like fibrils by capturing and incorporating Abeta1-42 aggregates into their peptide fibrils. In this system, small amounts of mature Abeta1-42 fibrils or soluble oligomers could be transformed into peptide fibrils and detected by amplifying the amyloid-like fibrils with the designed peptides.     

Relative binding affinities of molecular capsules investigated by ESI-mass spectrometry

ESI-MS(/MS) has been used as a method which allows the fast, unambiguous and sensitive simultaneous detection and relative stability approximation of supramolecular assemblies in mixtures. In spite of the obvious fundamental differences between solution and gas phase, ESI-MS in the case of self-assembled molecular capsules has been shown to produce very similar results to single binding experiments monitored by NMR titrations as well as conformational searches performed by Monte-Carlo simulations. MS/MS experiments reveal the same relative order of gas phase stabilities as previously found in solution. Moreover, proton transfer reactions which lead to new molecular capsules, are not detectable in the time-averaged NMR spectrum. However, the newly produced species are found in the complex mixtures by ESI-MS and can be conveniently characterized by subsequent MS/MS experiments: in a collision-induced dissociation the single half-spheres are easily discovered and structurally assigned. Thus, ESI-MS has worked as a valuable tool for the rapid screening of complex supramolecular mixtures and in combination with MS/MS experiments elucidated both the path of unexpected side reactions as well as the thermodynamic gas-phase stabilities of all components in the mixture.     

Application of plug–plug technique to ACE experiments for discovery of peptides binding to a larger target protein: A model study of calmodulin‐binding fragments selected from a digested mixture of reduced BSA

To discover peptide ligands that bind to a target protein with a higher molecular mass, a concise screening methodology has been established, by applying a “plug–plug” technique to ACE experiments. Exploratory experiments using three mixed peptides, mastoparan‐X, β‐endorphin, and oxytocin, as candidates for calmodulin‐binding ligands, revealed that the technique not only reduces the consumption of the protein sample, but also increases the flexibility of the experimental conditions, by allowing the use of MS detection in the ACE experiments. With the plug–plug technique, the ACE–MS screening methodology successfully selected calmodulin‐binding peptides from a random library with diverse constituents, such as protease digests of BSA. Three peptides with K_d values between 8–147 μM for calmodulin were obtained from a Glu‐C endoprotease digest of reduced BSA, although the digest showed more than 70 peaks in its ACE–MS electropherogram. The method established here will be quite useful for the screening of peptide ligands, which have only low affinities due to their flexible chain structures but could potentially provide primary information for designing inhibitors against the target protein.