Computer prediction of biological activity spectra for low-molecular peptides and peptidomimetics

The wide variety of the biological effects of peptides and their high activity are the main reasons for the search for new basic drug structures among them. The most promising compounds can be selected using the PASS computer system (Prediction of Activity Spectra for Substances). This system was originally developed to predict the activities of low-molecular “drug-like” organic compounds. Its predictive capacity is described here by the example of 134 peptides and peptidomimetics with nine known biological activities. Its average predictive power is shown to be approximately 97%. Such an accuracy demonstrates that computer prediction can be applied both to the evaluation of effects and mechanisms of action of endogenous and synthetic peptides and to the screening of new therapeutic agents among the most promising basic structures.     

Fragments of Functional Proteins: Role in Endocrine Regulation

Systematic analysis of structures, localization, formation and biological activities of endogenous peptides derived from functional proteins, such as hemoglobin, myelin basic protein, immunoglobulins, etc., allowed establishing the basic features of that group of compounds. The sets of these peptides in mammalian tissues, or tissue-specific peptide pools are: (i) tissue specific; (ii) stable at normal conditions; (iii) conservative in the same tissues of different mammalian species; (iv) dependent on the general state of homeostasis of tissue or the whole organism. Formation of such peptides has features of both conformation and site specificity and also involves the action of carboxy- and amino-peptidases. As a result, the families of structurally related families of peptides are generated. The fragments of functional proteins exhibit a wide range of the biological effects, characteristic both for hormones and parahormones, from hormone-releasing to growth-regulatory activity. At the same time, the molecular mechanisms of action of the majority of such peptides are unknown. On the basis of the data obtained the components of tissue-specific peptide pools are considered to form a novel regulatory system, complementary to other peptidergic systems such as hormonal, nervous, immune, etc. The biological role of the fragments of functional proteins in vivo and the patterns of interaction with other regulatory systems are suggested.     

Screening for a Potent Antibacterial Peptide to Treat Mupirocin-Resistant MRSA Skin Infections

Mupirocin is the first-line topical antibacterial drug for treating skin infections caused primarily by meticillin-resistant Staphylococcus aureus (MRSA). Its widespread use since its introduction more than 30 years ago has resulted in the global emergence of mupirocin-resistant strains of MRSA. Antimicrobial peptides (AMPs) are a promising class of antibacterial compounds that can potentially be developed to replace mupirocin due to their rapid membrane-targeting bactericidal mode of action and predicted low propensity for resistance development. Herein, we conducted and compared the antibacterial activities of 61 AMPs between 3 and 11 residues in length reported in the literature over the past decade against mupirocin-resistant MRSA. The most potent AMP, 11-residue peptide 50, was selected and tested against a panel of clinical isolates followed by a time-kill and a human dermal keratinocyte cytotoxicity assay. Lastly, peptide 50 was formulated into a topical spray which showed strong in vitro bactericidal effects against mupirocin-resistant MRSA. Our results strongly suggest that peptide 50 has the potential to be further developed into a new class of topical antibacterial agent for treating drug-resistant MRSA skin infections.     

Combinatorial peptide library screening for discovery of diverse α-glucosidase inhibitors using molecular dynamics simulations and binary QSAR models

Human α-glucosidase is an enzyme involved in the catalytic cleavage of the glucoside bond and involved in numerous functionalities of the organism, as well as in the insurgence of diabetes mellitus 2 and obesity. Thus, developing chemicals that inhibit this enzyme is a promising approach for the treatment of several pathologies. Small peptides such as di- and tri-peptides may be in natural organism as well as in the GI tract in high concentration, coming from the digestive process of meat, wheat and milk proteins. In this work, we reported the first tentative hierarchical structure-based virtual screening of peptides for human α-glucosidase. The goal of this work is to discover novel and diverse lead compounds that my act as inhibitors of α-glucosidase such as small peptides by performing a computer aided virtual screening and to find novel scaffolds for further development. Thus, in order to select novel candidates with original structure we performed molecular dynamics (MD) simulations among the 12 top-ranked peptides taking as comparison the MD simulations performed on crystallographic inhibitor acarbose. The compounds with the lower RMSD variability during the MD, were reserved for in vitro biological assay. The selected 4 promising structures were prepared on solid phase peptide synthesis and used for the inhibitory assay, among them compound 2 showed good inhibitory activity, which validated our method as an original strategy to discover novel peptide inhibitors. Moreover, pharmacokinetic profile predictions of these 4 peptides were also carried out with binary QSAR models using MetaCore/MetaDrug applications.     

Bioactive compounds produced by cyanobacteria

Cyanobacteria produce a large number of compounds with varying bioactivities. Prominent among these are toxins: hepatotoxins such as microcystins and nodularins and neurotoxins such as anatoxins and saxitoxins. Cytotoxicity to tumor cells has been demonstrated for other cyanobacterial products, including 9-deazaadenosine, dolastatin 13 and analogs. A number of compounds in cyanobacteria are inhibitors of proteases — micropeptins, cyanopeptolins, oscillapeptin, microviridin, aeruginosins- and other enzymes, while still other compounds have no recognized biological activities. In general cyclic peptides and depsipeptides are the most common structural types, but a wide variety of other types are also found: linear peptides, guanidines, phosphonates, purines and macrolides. The close similarity or identity in structures between cyanobacterial products and compounds isolated from sponges, tunicates and other marine invertebrates suggests the latter compounds may be derived from dietary or symbiotic blue-green algae.     

Novel structures of self-associating stapled peptides

Hydrocarbon stapling of peptides is a powerful technique to transform linear peptides into cell-permeable helical structures that can bind to specific biological targets. In this study, we have used high resolution solution NMR techniques complemented by dynamic light scattering to characterize extensively a family of hydrocarbon stapled peptides with known inhibitory activity against HIV-1 capsid assembly to evaluate the various factors that modulate activity. The helical peptides share a common binding motif but differ in charge, the length, and position of the staple. An important outcome of the study was to show the peptides, share a propensity to self-associate into organized polymeric structures mediated predominantly by hydrophobic interactions between the olefinic chain and the aromatic side-chains from the peptide. We have also investigated in detail the structural significance of the length and position of the staple, and of olefinic bond isomerization in stabilizing the helical conformation of the peptides as potential factors driving polymerization. This study presents the numerous challenges of designing biologically active stapled peptides and the conclusions have broad implications for optimizing a promising new class of compounds in drug discovery.     

Functional continuum of regulatory peptides (RPs): vector model of RP-effects representation

During the past decades, bioactive (regulatory) peptides have been identified as the major players in the regulation of many important biological processes. Dozens of peptides have found their application as pharmaceutical agents, which further stimulated research in this field making it one of the most rapidly developing areas on the edge of biological science and medicine. However, the fast accumulation of enormous amounts of experimental data has revealed a great difficulty in their analysis and demanded the development of a systematic approach for generalization of the obtained information. We propose a new computer-based algorithm for studying biological activities of regulatory peptides and their groups based on their representation as vectors in n -dimensional functional space. Our method allows the rapid analysis of databases containing thousands of polyfunctional regulatory peptides with overlapping spectra of physiological activity. The described method permits to perform several types of correlations which, when applied to the large databases, could reveal new important information about the system of regulatory peptides. It can select the groups of peptides with similar physiological role (peptide constellations) and search for the optimal peptide combinations with predetermined spectrum of effects and minimal side effects for their further pharmacological application. It can also reveal the role of regulatory peptides in induction of chain physiological reactions.     

The biological activities of fish peptides and methods of their isolation

Fish, like other aquatic organisms, are a potential source of structurally diverse bioactive compounds. Studies of the pharmacological effects of fish peptides have revealed their antihypertensive, immunomodulatory, antioxidant, antitumor, and antimicrobial activities. Analysis of the literature data confirms that fish can be used not only for nutritional purposes, but also as a source of unique peptides with a broad spectrum of biological activities. Further investigations will allow the inclusion of fish peptides as acting agents in modern medicinal drugs.     

Novel inhibitors of human histone deacetylases: Design,synthesis and bioactivity of 3-alkenoylcoumarines

Histone deacetylases (HDACs) are well-established, promising targets for anticancer therapy due to their critical role in cancer development. Accordingly, an increasing number of HDAC inhibitors displaying cytotoxic effects against cancer cells have been reported. Among them, a large panel of chemical structures was described including coumarin-containing molecules. In this study, we described synthesis and biological activity of new coumarin-based derivatives as HDAC inhibitors. Among eight derivatives, three compounds showed HDAC inhibitory activities and antitumor activities against leukemia cell lines without affecting the viability of peripheral blood mononuclear cells from healthy donors.     

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds

Background

Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target.

Methodology

We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery.

Conclusions

This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.     

Allenic and cumulenic lipids

Nowadays, about 200 natural allenic metabolites, more than 2700 synthetic allenic compounds, and about 1300 cumulenic structures are known. The present review describes research on natural as well as some biological active allenic and cumulenic lipids and related compounds isolated from different sources. Intensive searches for new classes of pharmacologically potent agents produced by living organisms have resulted in the discovery of dozens of such compounds possessing high anticancer, cytotoxic, antibacterial, antiviral, and other activities. Known allenic and cumulenic compounds can be subdivided on several structural classes: fatty acids, hydrocarbons, terpenes, steroids, carotenoids, marine bromoallenes, peptides, aromatic, cumulenic, and miscellaneous compounds. This review emphasizes the role of natural and synthetic allenic and cumulenic lipids and other related compounds as an important source of leads for drug discovery.     

Rapid Screening of Antimicrobial Synthetic Peptides

Increasing resistance to conventional antibiotics among microorganisms is one of the leading problems of medicine nowadays. Antimicrobial peptides are compounds exhibiting both antibacterial and antifungal activities. However, it is difficult to predict whether a designed new compound would exhibit any biological activity. Moreover, purification of the peptides is one of the most time-consuming and expensive steps of the synthesis that sometimes leads to unnecessary loss of solvents and reagents. In our study we have developed a thin-layer chromatography (TLC) direct bioautography technique for rapid determination of antimicrobial activity of peptides without the necessity of high-performance liquid chromatography purification. In this assay, crude peptides were applied and separated on a TLC plate. Then, pre-prepared plates were dipped into microbial suspension and incubated under optimum conditions for bacteria and fungi as well. The activity of the tested compounds was visualized by spraying the TLC plates with a cell viability reagent, resazurin (7-hydroxy-3H-phenoxazin-3-one 10-oxide). Effectiveness of this assay was compared with minimal inhibitory concentration results obtained by broth microdilution assay. Interestingly, so far such a screening method has not been applied for this group of compounds.     

Imidazo[4,5-<Emphasis Type="Italic">a</Emphasis>]quinindolines as highly effective antibacterial agents

Resistance to antimicrobial agents is a concern that exists globally and has a considerable impact on human and animal health, so that the discovery of new antibacterial compounds has become increasingly more important in combating infectious disease. In this paper, imidazo[4,5-a]quinindolines are introduced as new antibacterial agents against Gram-positive and Gram-negative bacteria. These pentacyclic compounds are synthesized by the reaction of N-alkyl-5-nitrobenzimidazoles with 2-(1-alkyl-1H-3-indolyl)acetonitrile under basic conditions in excellent yields. The structures of newly synthesized compounds were characterized by IR, ¹H NMR, ¹³C NMR, and mass spectral data. The antibacterial activities of the synthesized compounds were screened against standard strains of two Gram-positive and two Gram-negative bacteria using the broth microdilution method. Most of the compounds studied showed promising activities against both types of bacteria.     

Naturally occurring plant isoquinoline N-oxide alkaloids: Their pharmacological and SAR activities

The present review describes research on novel natural isoquinoline alkaloids and their N-oxides isolated from different plant species. More than 200 biological active compounds have shown confirmed antimicrobial, antibacterial, antitumor, and other activities. The structures, origins, and reported biological activities of a selection of isoquinoline N-oxides alkaloids are reviewed. With the computer program PASS some additional SAR (structure–activity relationship) activities are also predicted, which point toward new possible applications of these compounds. This review emphasizes the role of isoquinoline N-oxides alkaloids as an important source of leads for drug discovery.     

Family Juncaceae: promising source of biologically active natural phenanthrenes

Phenanthrenes represent a relatively small group of aromatic secondary metabolites, which can be divided into three main subgroups (mono-, di-, and triphenanthrenes). Phenanthrenes are reported as an intensively researched field in phytochemistry according to their structural diversity and promising biological activities. Because of their limited occurrence phenanthrenes are considered to be as important taxonomic markers. Juncaceae is a relatively large plant family divided into seven genera of which Juncus and Luzula are the most important ones from phytochemical and pharmacological points of view. To date, almost one hundred natural phenanthrenes have been isolated but only from eight (Juncus acutus, J. effusus, J. inflexus, J. maritimus, J. roemerianus, J. setchuensis, J. subulatus, and Luzula luzuloides) Juncaceae species, including mono-, and diphenanthrenes, and phenanthrene glucosides. Great deal of the isolated compounds are substituted with a vinyl group. This substitution is characteristic exclusively to Juncaceae species. Juncusol (2) was isolated from every investigated species. The richest source of phenanthrenes, as well as the most extensively investigated species is J. effusus. Several isolated compounds possessed different biological activities, e.g. antiproliferative, antimicrobial, anti-inflammatory, antioxidant, spasmolytic, anxiolytic, and antialgal effects. Among them, dehydroeffusol (60) is the most promising one, as it showed antimicrobial, anxiolytic, sedative, spasmolytic, cellular protective and antiproliferative activities. The aim of this review is to summarize the occurrence of phenanthrenes in the family Juncaceae, and give a comprehensive overview of their isolation, structural characteristics and biological activities.     

Computational selection of inhibitors of Aβ aggregation and neuronal toxicity

Alzheimer’s disease (AD) is characterized by the cerebral accumulation of misfolded and aggregated amyloid-β protein (Aβ). Disease symptoms can be alleviated, in vitro and in vivo, by ‘β-sheet breaker’ pentapeptides that reduce plaque load. However the peptide nature of these compounds, made them biologically unstable and unable to penetrate membranes with high efficiency. The main goal of this study was to use computational methods to identify small molecule mimetics with better drug-like properties. For this purpose, the docked conformations of the active peptides were used to identify compounds with similar activities. A series of related β-sheet breaker peptides were docked to solid state NMR structures of a fibrillar form of Aβ. The lowest energy conformations of the active peptides were used to design three dimensional (3D)-pharmacophores, suitable for screening the NCI database with Unity. Small molecular weight compounds with physicochemical features and a conformation similar to the active peptides were selected, ranked by docking and biochemical parameters. Of 16 diverse compounds selected for experimental screening, 2 prevented and reversed Aβ aggregation at 2–3 μM concentration, as measured by Thioflavin T (ThT) fluorescence and ELISA assays. They also prevented the toxic effects of aggregated Aβ on neuroblastoma cells. Their low molecular weight and aqueous solubility makes them promising lead compounds for treating AD.     

Synthesis and antibacterial activities of chiral 1,3-oxazinan-2-one derivatives

We report here the design, synthesis, and antibacterial activities of novel classes of compounds containing chiral 1,3-oxazinan-2-ones and oxazolidinones as the basic core structures. These compounds are tertiary amines containing the core structures and two aryl substituents. Several of these molecules exhibit potent antibacterial activities against the tested Gram-positive bacteria, including Staphylococcus aureus, Enterococcus faecalis, and Bacillus subtilis. These compounds represent new structure scaffolds and can be further optimized to give new antibacterial agents with structures significantly different from those of existing classes of antibiotics.     

A structure-based approach for prediction of MHC-binding peptides

Identification of immunodominant peptides is the first step in the rational design of peptide vaccines aimed at T-cell immunity. The advances in sequencing techniques and the accumulation of many protein sequences without the purified protein challenge the development of computer algorithms to identify dominant T-cell epitopes based on sequence data alone. Here, we focus on antigenic peptides recognized by cytotoxic T cells. The selection of T-cell epitopes along a protein sequence is influenced by the specificity of each of the processing stages that precede antigen presentation. The most selective of these processing stages is the binding of the peptides to the major histocompatibility complex molecules, and therefore many of the predictive algorithms focus on this stage. Most of these algorithms are based on known binding peptides whose sequences have been used for the characterization of binding motifs or profiles. Here, we describe a structure-based algorithm that does not rely on previous binding data. It is based on observations from crystal structures that many of the bound peptides adopt similar conformations and placements within the MHC groove. The algorithm uses a structural template of the peptide in the MHC groove upon which peptide candidates are threaded and their fit to the MHC groove is evaluated by statistical pairwise potentials. It can rank all possible peptides along a protein sequence or within a suspected group of peptides, directing the experimental efforts towards the most promising peptides. This approach is especially useful when no previous peptide binding data are available.