Simple, intuitive calculations of free energy of binding for protein-ligand complexes. 1. Models without explicit constrained water

A Combined Molecular Dynamics and Hydropathic INTeraction (HINT) Approach to Investigate Protein Flexibility: The PPARγ Case Study

Molecular Dynamics (MD) is a computational technique widely used to evaluate a molecular system's thermodynamic properties and conformational behavior over time. In particular, the energy analysis of a protein conformation ensemble produced though MD simulations plays a crucial role in explaining the relationship between protein dynamics and its mechanism of action. In this research work, the HINT (Hydropathic INTeractions) LogP-based scoring function was first used to handle MD trajectories and investigate the molecular basis behind the intricate PPARγ mechanism of activation. The Peroxisome Proliferator-Activated Receptor γ (PPARγ) is an emblematic example of a highly flexible protein due to the extended ω-loop delimiting the active site, and it is responsible for the receptor's ability to bind chemically different compounds. In this work, we focused on the PPARγ complex with Rosiglitazone, a common anti-diabetic compound and analyzed the molecular basis of the flexible ω-loop stabilization effect produced by the Oleic Acid co-binding. The HINT-based analysis of the produced MD trajectories allowed us to account for all of the energetic contributions involved in interconverting between conformational states and describe the intramolecular interactions between the flexible ω-loop and the helix H3 triggered by the allosteric binding mechanism.

Nicotinamide riboside activates SIRT5 deacetylation

Human sirtuins play important roles in various cellular events including DNA repair, gene silencing, mitochondrial biogenesis, insulin secretion and apoptosis. They regulate a wide array of protein and enzyme targets through their NAD+ -dependent deacetylase activities. Sirtuins are also thought to mediate the beneficial effects of low-calorie intake to extend longevity in diverse organisms from yeast to mammals. Small molecules mimicking calorie restriction to stimulate sirtuin activity are attractive therapeutics against age-related disorders such as cardiovascular diseases, diabetes and neurodegeneration. Little is known about one of the mitochondrial sirtuins, SIRT5. SIRT5 has emerged as a critical player in maintaining cardiac health and neuronal viability upon stress and functions as a tumour suppressor in a context-specific manner. Much has been debated about whether SIRT5 has evolved away from being a deacetylase because of its weak catalytic activity, especially in the in vitro testing. We have, for the first time, identified a SIRT5-selective allosteric activator, nicotinamide riboside (NR). It can increase SIRT5 catalytic efficiency with different synthetic peptide substrates. The mechanism of action was further explored using a combination of molecular biology and biochemical strategies. Based on the existing structural biology information, the NR binding site was also mapped out. These activators are powerful chemical probes for the elucidation of cellular regulations and biological functions of SIRT5. The knowledge gained in this study can be used to guide the design and synthesis of more potent, isotype-selective SIRT5 activators and to develop them into therapeutics for metabolic disorders and age-related diseases.

Merging cultures and disciplines to create a drug discovery ecosystem at Virginia commonwealth university: Medicinal chemistry, structural biology, molecular and behavioral pharmacology and computational chemistry

The Department of Medicinal Chemistry, together with the Institute for Structural Biology, Drug Discovery and Development, at Virginia Commonwealth University (VCU) has evolved, organically with quite a bit of bootstrapping, into a unique drug discovery ecosystem in response to the environment and culture of the university and the wider research enterprise. Each faculty member that joined the department and/or institute added a layer of expertise, technology and most importantly, innovation, that fertilized numerous collaborations within the University and with outside partners. Despite moderate institutional support with respect to a typical drug discovery enterprise, the VCU drug discovery ecosystem has built and maintained an impressive array of facilities and instrumentation for drug synthesis, drug characterization, biomolecular structural analysis and biophysical analysis, and pharmacological studies. Altogether, this ecosystem has had major impacts on numerous therapeutic areas, such as neurology, psychiatry, drugs of abuse, cancer, sickle cell disease, coagulopathy, inflammation, aging disorders and others. Novel tools and strategies for drug discovery, design and development have been developed at VCU in the last five decades; e.g., fundamental rational structure-activity relationship (SAR)-based drug design, structure-based drug design, orthosteric and allosteric drug design, design of multi-functional agents towards polypharmacy outcomes, principles on designing glycosaminoglycans as drugs, and computational tools and algorithms for quantitative SAR (QSAR) and understanding the roles of water and the hydrophobic effect.

HINT, a code for understanding the interaction between biomolecules: a tribute to Donald J. Abraham

A long-lasting goal of computational biochemists, medicinal chemists, and structural biologists has been the development of tools capable of deciphering the molecule-molecule interaction code that produces a rich variety of complex biomolecular assemblies comprised of the many different simple and biological molecules of life: water, small metabolites, cofactors, substrates, proteins, DNAs, and RNAs. Software applications that can mimic the interactions amongst all of these species, taking account of the laws of thermodynamics, would help gain information for understanding qualitatively and quantitatively key determinants contributing to the energetics of the bimolecular recognition process. This, in turn, would allow the design of novel compounds that might bind at the intermolecular interface by either preventing or reinforcing the recognition. HINT, hydropathic interaction, was a model and software code developed from a deceptively simple idea of Donald Abraham with the close collaboration with Glen Kellogg at Virginia Commonwealth University. HINT is based on a function that scores atom-atom interaction using LogP, the partition coefficient of any molecule between two phases; here, the solvents are water that mimics the cytoplasm milieu and octanol that mimics the protein internal hydropathic environment. This review summarizes the results of the extensive and successful collaboration between Abraham and Kellogg at VCU and the group at the University of Parma for testing HINT in a variety of different biomolecular interactions, from proteins with ligands to proteins with DNA.

Molecular docking in organic, inorganic, and hybrid systems: a tutorial review

Molecular docking simulation is a very popular and well-established computational approach and has been extensively used to understand molecular interactions between a natural organic molecule (ideally taken as a receptor) such as an enzyme, protein, DNA, RNA and a natural or synthetic organic/inorganic molecule (considered as a ligand). But the implementation of docking ideas to synthetic organic, inorganic, or hybrid systems is very limited with respect to their use as a receptor despite their huge popularity in different experimental systems. In this context, molecular docking can be an efficient computational tool for understanding the role of intermolecular interactions in hybrid systems that can help in designing materials on mesoscale for different applications. The current review focuses on the implementation of the docking method in organic, inorganic, and hybrid systems along with examples from different case studies. We describe different resources, including databases and tools required in the docking study and applications. The concept of docking techniques, types of docking models, and the role of different intermolecular interactions involved in the docking process to understand the binding mechanisms are explained. Finally, the challenges and limitations of dockings are also discussed in this review.

Graphical abstract

A deterministic code for transcription factor-DNA recognition through computation of binding interfaces

The recognition code between transcription factor (TF) amino acids and DNA bases remains poorly understood. Here, the determinants of TF amino acid-DNA base binding selectivity were identified through the analysis of crystals of TF-DNA complexes. Selective, high-frequency interactions were identified for the vast majority of amino acid side chains (‘structural code’). DNA binding specificities were then independently assessed by meta-analysis of random-mutagenesis studies of Zn finger-target DNA sequences. Selective, high-frequency interactions were identified for the majority of mutagenized residues (‘mutagenesis code’). The structural code and the mutagenesis code were shown to match to a striking level of accuracy (P = 3.1 × 10−33), suggesting the identification of fundamental rules of TF binding to DNA bases. Additional insight was gained by showing a geometry-dictated choice among DNA-binding TF residues with overlapping specificity. These findings indicate the existence of a DNA recognition mode whereby the physical-chemical characteristics of the interacting residues play a deterministic role. The discovery of this DNA recognition code advances our knowledge on fundamental features of regulation of gene expression and is expected to pave the way for integration with higher-order complexity approaches.

Inhibition and interactions of alpha-amylase by daucosterol from the peel of Chinese water chestnut (Eleocharis dulcis)

The alpha-amylase inhibitory effect of daucosterol purified from the peel of Chinese water chestnut (CWC), a common Chinese vegetable, was assessed. The alpha-amylase inhibitory properties were elucidated by enzyme inhibition, fluorescence quenching and molecular docking experiments. It was found that three saponins from CWC peel exhibited potent inhibitory activity on alpha-amylase and daucosterol was found to be the main inhibitory factor against alpha-amylase with a mixed-type mode. Strong fluorescence quenching of alpha-amylase was observed under static fluorescence quenching with hydrophobic interactions with daucosterol. Molecular docking revealed that the conformation of daucosterol in the high-affinity sites I and II of alpha-amylase was optimum, and hydrophobic interactions were produced by daucosterol aglycone, and hydrogen bonding by the β-D-glucopyranosyl residue. Ingested daucosterol suppressed the elevation of blood glucose levels through inhibition of alpha-amylase in the small intestine in starch-loaded mice. This study provides data supporting the potential benefit of daucosterol from CWC peel in the treatment of diabetes.

Rational Design of a User-Friendly Aptamer/Peptide-Based Device for the Detection of Staphylococcus aureus

The urgent need to develop a detection system for Staphylococcus aureus, one of the most common causes of infection, is prompting research towards novel approaches and devices, with a particular focus on point-of-care analysis. Biosensors are promising systems to achieve this aim. We coupled the selectivity and affinity of aptamers, short nucleic acids sequences able to recognize specific epitopes on bacterial surface, immobilized at high density on a nanostructured zirconium dioxide surface, with the rational design of specifically interacting fluorescent peptides to assemble an easy-to-use detection device. We show that the displacement of fluorescent peptides upon the competitive binding of S. aureus to immobilized aptamers can be detected and quantified through fluorescence loss. This approach could be also applied to the detection of other bacterial species once aptamers interacting with specific antigens will be identified, allowing the development of a platform for easy detection of a pathogen without requiring access to a healthcare environment.

Cyclodextrins Can Entrap Zearalenone-14-Glucoside: Interaction of the Masked Mycotoxin with Cyclodextrins and Cyclodextrin Bead Polymer

Zearalenone (ZEN) is a Fusarium-derived xenoestrogenic mycotoxin. In plants, zearalenone-14-O-β-d-glucoside (Z14G) is the major conjugated metabolite of ZEN, and is a masked mycotoxin. Masked mycotoxins are plant-modified derivatives, which are not routinely screened in food and feed samples. Cyclodextrins (CDs) are cyclic oligosaccharides built up from D-glucopyranose units. CDs can form stable host-guest type complexes with lipophilic molecules (e.g., with some mycotoxins). In this study, the interaction of Z14G with native and chemically modified β- and γ-CDs was examined employing fluorescence spectroscopy and molecular modeling. Furthermore, the removal of Z14G from aqueous solution by insoluble β-CD bead polymer (BBP) was also tested. Our results demonstrate that Z14G forms the most stable complexes with γ-CDs under acidic and neutral conditions (K ≈ 103 L/mol). Among the CDs tested, randomly methylated γ-CD induced the highest increase in the fluorescence of Z14G (7.1-fold) and formed the most stable complexes with the mycotoxin (K = 2 × 103 L/mol). Furthermore, BBP considerably reduced the Z14G content of aqueous solution. Based on these observations, CD technology seems a promising tool to improve the fluorescence analytical detection of Z14G and to discover new mycotoxin binders which can also remove masked mycotoxins (e.g., Z14G).

Interaction of Mycotoxin Alternariol with Serum Albumin

Alternariol (AOH) is a mycotoxin produced by Alternaria species. In vitro studies suggest the genotoxic, mutagenic, and endocrine disruptor effects of AOH, and an increased incidence of esophageal cancer has been reported related to higher AOH exposure. Human serum albumin (HSA) is the most abundant plasma protein in the circulation, it is able to affect toxicokinetic properties of numerous xenobiotics. HSA forms stable complexes with several mycotoxins, however, the interaction of AOH with albumin has not been examined. In this study, the complex formation of AOH with HSA was tested, employing fluorescence spectroscopy, ultrafiltration, and molecular modeling. Each spectroscopic measurement shows the formation of stable AOH-HSA complexes (K = 4 × 10⁵ L/mol). Investigations with site markers (in spectroscopic and ultrafiltration models) as well as modeling studies suggest that AOH occupies Sudlow’s site I as a high-affinity binding site in HSA. The binding affinity of AOH towards bovine, porcine, and rat albumins was also tested, suggesting that AOH binds to rat albumin with considerably higher affinity than other albumins tested. Our results demonstrate the strong interaction of AOH with serum albumins, suggesting the potential in vivo importance of these interactions.

Simulated Gastrointestinal Digestion of Cocoa: Detection of Resistant Peptides and In Silico/In Vitro Prediction of Their Ace Inhibitory Activity

In this study we investigated the oligopeptide pattern in fermented cocoa beans and derived products after simulated gastrointestinal digestion. Peptides in digested cocoa samples were identified based on the mass fragmentation and on the software analysis of vicilin and 21 KDa cocoa seed protein sequences, the most abundant cocoa proteins. Quantification was carried out by liquid chromatography/electrospray ionisation mass spectrometry (LC/ESI-MS) using an internal standard. Sixty five peptides were identified in the digested samples, including three pyroglutamyl derivatives. The in vitro angiotensin-converting enzyme (ACE)-inhibitory activity of cocoa digests were tested, demonstrating a high inhibition activity, especially for digestates of cocoa beans. The peptides identified were screened for their potential ACE inhibitory activity through an in silico approach, and about 20 di-, three- and tetra-peptides actually present in our samples were predicted as active. Two of the potentially active peptides were chemically synthesized and then assessed for their inhibitory activity by using the ACE in vitro assay. These peptides demonstrated an ACE inhibitory activity, however, that was too weak to explain alone the high activity of cocoa digestates, suggesting a synergic effect of all cocoa peptides. As a whole, results showed that an average chocolate portion (30 g) ensures an amount of peptides after digestion that, assuming complete absorption, could reach almost a complete inhibition of ACE.

In Silico Approaches Applied to the Study of Peptide Analogs of Ile-Pro-Ile in Relation to Their Dipeptidyl Peptidase IV Inhibitory Properties

Inhibition of dipeptidyl peptidase IV (DPP-IV) may be exploited to maintain the incretin effect during the postprandial phase. As a result, glycemic regulation and energy homeostasis may be improved. Food protein-derived peptides have been identified as natural agents capable of inhibiting DPP-IV. Ile-Pro-Ile is the most potent DPP-IV inhibitory peptide identified to date. A minimum analog peptide set approach was used to study peptide analogs of Ile-Pro-Ile. The DPP-IV half maximal inhibitory concentration (IC50) values of the 25 peptides evaluated ranged from 3.9 ± 1.0 µM (Ile-Pro-Ile) to 247.0 ± 32.7 µM (Phe-Pro-Phe). The presence of Pro at position 2 of tripeptides was required to achieve high DPP-IV inhibition. Most peptides behaved as competitive inhibitors of DPP-IV with the exception of peptides with a N-terminal Trp, which were mixed-type inhibitors. While possessing the structure of preferred DPP-IV substrates, most peptides studied were particularly stable during 30 min incubation with DPP-IV. Molecular docking revealed that Ile-Pro-Ile and its peptide analogs interacted in a very similar manner with the active site of DPP-IV. In addition, no correlation was found between the Hydropathic INTeraction score and the DPP-IV IC50 values of the peptides studied. This outcome suggests that free energy may not be directly responsible for enzyme inhibition by the peptides. Finally, novel DPP-IV inhibitory peptides were identified using the strategy employed herein. These results may be relevant for the development of food protein-derived peptides with serum glucose lowering and food intake regulatory properties in humans.

Toxicodynamics of Mycotoxins in the Framework of Food Risk Assessment-An In Silico Perspective

Mycotoxins severely threaten the health of humans and animals. For this reason, many countries have enforced regulations and recommendations to reduce the dietary exposure. However, even though regulatory actions must be based on solid scientific knowledge, many aspects of their toxicological activity are still poorly understood. In particular, deepening knowledge on the primal molecular events triggering the toxic stimulus may be relevant to better understand the mechanisms of action of mycotoxins. The present work presents the use of in silico approaches in studying the mycotoxins toxicodynamics, and discusses how they may contribute in widening the background of knowledge. A particular emphasis has been posed on the methods accounting the molecular initiating events of toxic action. In more details, the key concepts and challenges of mycotoxins toxicology have been introduced. Then, topical case studies have been presented and some possible practical implementations of studying mycotoxins toxicodynamics have been discussed.

An integrated in silico/in vitro approach to assess the xenoestrogenic potential of Alternaria mycotoxins and metabolites

Xenoestrogenic mycotoxins may contaminate food and feed posing a public health issue. Besides the zearalenone group, the Alternaria toxin alternariol (AOH) has been described as a potential mycoestrogen. However, the estrogenicity of Alternaria toxins is still largely overlooked and further data are needed to better describe the group toxicity. In the frame of risk assessment, mixed in silico/in vitro approaches already proved to be effective first-line analytical tools. An integrated in silico/in vitro approach was used to investigate the effects of metabolic and chemical modifications on the estrogenicity of AOH. Among the considered modifications, methylation was found critical for enhancing estrogenicity (as seen for alternariol monomethyl ether (AME)) while hydroxylation and glucuronidation had the opposite effect (as seen for 4-hydroxy AOH and 4-hydroxy AME). The structure-activity relationship analysis provided the structural rationale. Our results provide insights to design more efficient risk assessment studies expanding knowledge over the group toxicity.

The Roles of Water in the Protein Matrix: A Largely Untapped Resource for Drug Discovery

The value of thoroughly understanding the thermodynamics specific to a drug discovery/design study is well known. Over the past decade, the crucial roles of water molecules in protein structure, function, and dynamics have also become increasingly appreciated. This Perspective explores water in the biological environment by adopting its point of view in such phenomena. The prevailing thermodynamic models of the past, where water was seen largely in terms of an entropic gain after its displacement by a ligand, are now known to be much too simplistic. We adopt a set of terminology that describes water molecules as being "hot" and "cold", which we have defined as being easy and difficult to displace, respectively. The basis of these designations, which involve both enthalpic and entropic water contributions, are explored in several classes of biomolecules and structural motifs. The hallmarks for characterizing water molecules are examined, and computational tools for evaluating water-centric thermodynamics are reviewed. This Perspective's summary features guidelines for exploiting water molecules in drug discovery.

Molecular Docking: From Lock and Key to Combination Lock

Accurate modeling of protein ligand binding is an important step in structure-based drug design, is a useful starting point for finding new lead compounds or drug candidates. The 'Lock and Key' concept of protein-ligand binding has dominated descriptions of these interactions, and has been effectively translated to computational molecular docking approaches. In turn, molecular docking can reveal key elements in protein-ligand interactions-thereby enabling design of potent small molecule inhibitors directed against specific targets. However, accurate predictions of binding pose and energetic remain challenging problems. The last decade has witnessed more sophisticated molecular docking approaches to modeling protein-ligand binding and energetics. However, the complexities that confront accurate modeling of binding phenomena remain formidable. Subtle recognition and discrimination patterns governed by three-dimensional features and microenvironments of the active site play vital roles in consolidating the key intermolecular interactions that mediates ligand binding. Herein, we briefly review contemporary approaches and suggest that future approaches treat protein-ligand docking problems in the context of a 'combination lock' system.

Degradation of Aflatoxins by Means of Laccases from Trametes versicolor: An In Silico Insight

Mycotoxins are secondary metabolites of fungi that contaminate food and feed, and are involved in a series of foodborne illnesses and disorders in humans and animals. The mitigation of mycotoxin content via enzymatic degradation is a strategy to ensure safer food and feed, and to address the forthcoming issues in view of the global trade and sustainability. Nevertheless, the search for active enzymes is still challenging and time-consuming. The in silico analysis may strongly support the research by providing the evidence-based hierarchization of enzymes for a rational design of more effective experimental trials. The present work dealt with the degradation of aflatoxin B₁ and M₁ by laccase enzymes from Trametes versicolor. The enzymes–substrate interaction for various enzyme isoforms was investigated through 3D molecular modeling techniques. Structural differences among the isoforms have been pinpointed, which may cause different patterns of interaction between aflatoxin B₁ and M₁. The possible formation of different products of degradation can be argued accordingly. Moreover, the laccase gamma isoform was identified as the most suitable for protein engineering aimed at ameliorating the substrate specificity. Overall, 3D modeling proved to be an effective analytical tool to assess the enzyme–substrate interaction and provided a solid foothold for supporting the search of degrading enzyme at the early stage.

Assessing the hydrolytic fate of the masked mycotoxin zearalenone-14-glucoside - A warning light for the need to look at the "maskedome"

Masked mycotoxins are plant metabolites of mycotoxins that contaminate food and feed. They pose health concern as the shortage of toxicological data forces the lack of regulation worldwide. The present work investigated the toxicological relevance of the masked mycotoxin zearalenone-14-glucoside. In vitro, it shows a lower toxicity in respect to the parent compound. However, the major risks related to the consumption of masked mycotoxins depend on the possibility to undergo hydrolysis. Therefore, the hydrolysis and further transformation of zearalenone-14-glucoside in bovine blood and blood components (i.e. plasma, serum and serum albumin) were monitored using LC/MS-MS analysis to gain insights on the possible systemic fate. Hydrolysis was observed in all matrices, and both cell-dependent and -independent contributions were pointed out. Moreover, further metabolism was observed in the whole blood as zearalenol isomers were found. Serum albumin was identified among the active components, and the protein-ligand interaction was investigated via computational analysis. The blood has been pointed out as possible district of reversion and further activation of zearalenone-14-glucoside, and a similar fate cannot be excluded for other masked mycotoxins. Therefore, the systemic hydrolysis should be evaluated beside the absorption, bioavailability and bioaccessibility to deeply understand the toxicity of masked mycotoxins.

Identification of Small-Molecule Inhibitors against Meso-2, 6-Diaminopimelate Dehydrogenase from Porphyromonas gingivalis

Species-specific antimicrobial therapy has the potential to combat the increasing threat of antibiotic resistance and alteration of the human microbiome. We therefore set out to demonstrate the beginning of a pathogen-selective drug discovery method using the periodontal pathogen Porphyromonas gingivalis as a model. Through our knowledge of metabolic networks and essential genes we identified a “druggable” essential target, meso-diaminopimelate dehydrogenase, which is found in a limited number of species. We adopted a high-throughput virtual screen method on the ZINC chemical library to select a group of potential small-molecule inhibitors. Meso-diaminopimelate dehydrogenase from P. gingivalis was first expressed and purified in Escherichia coli then characterized for enzymatic inhibitor screening studies. Several inhibitors with similar structural scaffolds containing a sulfonamide core and aromatic substituents showed dose-dependent inhibition. These compounds were further assayed showing reasonable whole-cell activity and the inhibition mechanism was determined. We conclude that the establishment of this target and screening strategy provides a model for the future development of new antimicrobials.

Hazard identification of cis/trans-zearalenone through the looking-glass

Among the food-related health issues, the presence of contaminants has a prominent role, due to the wide range of exogenous compounds that can occur in food commodities and to their large differences in structure and biological activity. A comprehensive assessment of the related risk is thus actually demanding in terms of time and facilities involved. In this context, the use of computational strategies can be an effective choice for supporting the hazard identification procedure at the early stage. In this work, we focused on the food contaminant zearalenone by comparing the trans and cis isomers, respectively the well-known mycoestrogen and its still largely understudied isomer. We estimated the possible effects exerted by human metabolism on the xenoestrogenicity of cis-ZEN by using a validated in silico strategy based on docking simulations and rescoring procedures. Similarly, the exploitation of the most promising enzymatic detoxifying routes designed for trans-ZEN - which relies on the enzyme lactono hydrolase from Clonostachys rosea - has been assessed for the cis-isomer as well. Our results showed that both isomers can act as functional analogues with respect to xenoestrogenic activity, and several cis-ZEN metabolites with high biological potential have been identified. On the contrary, in spite of the high degree of structural analogy, the cis isomer showed a pattern of interaction with the degrading enzyme in stark contrast with that observed for trans-ZEN. For these reasons, the outcomes presented herein strongly support the inclusion of cis-ZEN in further studies of occurrence, metabolism and bioactivity assessment, and suggest the need for a dedicated handling for the cis isomer in risk assessment studies.

Hybrid in Silico/in Vitro Approach for the Identification of Angiotensin I Converting Enzyme Inhibitory Peptides from Parma Dry-Cured Ham

The bioactivity assessment of foodborne peptides is currently a research area of great relevance, and, in particular, several studies are devoted to the antihypertensive effects through the inhibition of angiotensin I converting enzyme (ACE). In the present work, a straightforward workflow to identify inhibitory peptides from food matrices is proposed, which involves a hybrid in vitro/in silico tandem approach. Parma dry-cured ham was chosen as case study. In particular, the advantage of using the hybrid approach to identify active sequences (in comparison to the experimental trials alone) has been pointed out. Specifically, fractions obtained by in vitro gastrointestinal digestion of ham samples of 18 and 24 months of aging have been assessed for ACE inhibition. At the same time, the released peptidomic profiles, which cannot be entirely evaluated by using in vitro assays, have been screened for the inhibition by using an in silico model. Then, to identify novel inhibitory sequences, a series of strong candidates have been synthesized and assessed for their inhibitory activity through in vitro assay. On the one hand, the use of computational simulations appeared to be an effective strategy to find active sequences, as confirmed by in vitro analysis. On the other hand, strong inhibitory sequences were identified for the first time in Parma dry-cured ham (e.g., LGL and SFVTT with IC50 values of 145 and 395 μM, respectively), which is a product of international dietary and economic relevance. Therefore, these findings demonstrate the usefulness of in silico methodologies coupled to in vitro tests for the identification of potentially bioactive peptides, and they give an important contribution to the study of the overall nutritional value of Parma ham.

Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods--A Case Study of Serotonin Receptors 5-HT(6) and 5-HT(7)

Molecular docking, despite its undeniable usefulness in computer-aided drug design protocols and the increasing sophistication of tools used in the prediction of ligand-protein interaction energies, is still connected with a problem of effective results analysis. In this study, a novel protocol for the automatic evaluation of numerous docking results is presented, being a combination of Structural Interaction Fingerprints and Spectrophores descriptors, machine-learning techniques, and multi-step results analysis. Such an approach takes into consideration the performance of a particular learning algorithm (five machine learning methods were applied), the performance of the docking algorithm itself, the variety of conformations returned from the docking experiment, and the receptor structure (homology models were constructed on five different templates). Evaluation using compounds active toward 5-HT6 and 5-HT7 receptors, as well as additional analysis carried out for beta-2 adrenergic receptor ligands, proved that the methodology is a viable tool for supporting virtual screening protocols, enabling proper discrimination between active and inactive compounds.

Ergot alkaloids: From witchcraft till in silico analysis. Multi-receptor analysis of ergotamine metabolites

The term Ergot is referred to the sclerotium of ascomycetes - a protective kernel produced during resting stage of some fungi - which replaces seeds of susceptible cereals and plants intended for human and animal diet. It contains various composition of tryptophan-derived toxins defined ergot alkaloids. Since sclerotia can be harvested and milled together with cereals, they represent a source of food and feed contamination after breakage and spreading of mycotoxins into the various milling fractions. The effects of ergot alkaloids, including those adverse for human health, have been known since the Middle Ages. Nevertheless, as recently stated by the European Food Safety Authority, further information is needed on metabolism and target receptors-binding of common alkaloids in food. Unfortunately, the experimental investigation is challenging due to the high costs in terms of time and money. This study was thus aimed at assessing whether the in silico modeling can be an effective tool to investigate the interaction between multiple serotonin receptors and a wide set of ergotamine metabolites, including experimentally detected molecules and predicted derivatives. Validated models provided precious insights about the effects exerted by metabolic modifications on the receptor-ligand interaction. Such structural information may be useful to support the design of further experimental analysis.

Modeling the effect of phase II conjugations on topoisomerase I poisoning: pilot study with luteolin and quercetin

Topoisomerases are targeted by several drugs in cancer chemotherapy acting as key enzymes in cell viability. Some flavonoids and their glycosides may exert health protective effects through the poisoning of topoisomerases. However, previous studies did not consider the substantial modifications taking place after ingestion neglecting that only metabolites can interact with the internal compartments of the human body. Since the high number of possible metabolites hinders their systematic analysis, an in silico approach can be a valuable tool to prioritize compounds by identifying candidates for further characterization. Specifically focusing on luteolin and quercetin, among the most ubiquitous flavonoids in the human diet, this work reports a computational procedure to model the effect of hepatic phase II conjugative metabolism on poisoning of human Topoisomerase I. As a general effect, glucuronidation and sulphation might enhance and quench poisoning activity, respectively. Among all, quercetin-3-O-glucuronide represents a promising candidate to be analyzed more thoroughly.

Targeting cystalysin, a virulence factor of treponema denticola-supported periodontitis

Cystalysin from Treponema denticola is a pyridoxal 5'-phosphate dependent lyase that catalyzes the formation of pyruvate, ammonia, and sulfide from cysteine. It is a virulence factor in adult periodontitis because its reaction contributes to hemolysis, which sustains the pathogen. Therefore, it was proposed as a potential antimicrobial target. To identify specific inhibitors by structure-based in silico methods, we first validated the crystal structure of cystalysin as a reliable starting point for the design of ligands. By using single-crystal absorption microspectrophotometry, we found that the enzyme in the crystalline state, with respect to that in solution, exhibits: 1) the same absorption spectra for the catalytic intermediates, 2) a close pKa value for the residue controlling the keto enamine ionization, and 3) similar reactivity with glycine, L-serine, L-methionine, and the nonspecific irreversible inhibitor aminoethoxyvinylglycine. Next, we screened in silico a library of 9357 compounds with the Fingerprints for Ligands and Proteins (FLAP) software, by using the three-dimensional structure of cystalysin as a template. From the library, 17 compounds were selected and experimentally evaluated by enzyme assays and spectroscopic methods. Two compounds were found to competitively inhibit recombinant T. denticola cystalysin, with inhibition constant (Ki ) values of 25 and 37 μM. One of them exhibited a minimum inhibitory concentration (MIC) value of 64 μg mL(-1) on Moraxella catarrhalis ATCC 23246, which proves its ability to cross bacterial membranes.

Multipose binding in molecular docking

Molecular docking has been extensively applied in virtual screening of small molecule libraries for lead identification and optimization. A necessary prerequisite for successful differentiation between active and non-active ligands is the accurate prediction of their binding affinities in the complex by use of docking scoring functions. However, many studies have shown rather poor correlations between docking scores and experimental binding affinities. Our work aimed to improve this correlation by implementing a multipose binding concept in the docking scoring scheme. Multipose binding, i.e., the property of certain protein-ligand complexes to exhibit different ligand binding modes, has been shown to occur in nature for a variety of molecules. We conducted a high-throughput docking study and implemented multipose binding in the scoring procedure by considering multiple docking solutions in binding affinity prediction. In general, improvement of the agreement between docking scores and experimental data was observed, and this was most pronounced in complexes with large and flexible ligands and high binding affinities. Further developments of the selection criteria for docking solutions for each individual complex are still necessary for a general utilization of the multipose binding concept for accurate binding affinity prediction by molecular docking.

Intuitive, but not simple: including explicit water molecules in protein-protein docking simulations improves model quality

Characterizing the nature of interaction between proteins that have not been experimentally cocrystallized requires a computational docking approach that can successfully predict the spatial conformation adopted in the complex. In this work, the Hydropathic INTeractions (HINT) force field model was used for scoring docked models in a data set of 30 high-resolution crystallographically characterized "dry" protein-protein complexes and was shown to reliably identify native-like models. However, most current protein-protein docking algorithms fail to explicitly account for water molecules involved in bridging interactions that mediate and stabilize the association of the protein partners, so we used HINT to illuminate the physical and chemical properties of bridging waters and account for their energetic stabilizing contributions. The HINT water Relevance metric identified the "truly" bridging waters at the 30 protein-protein interfaces and we utilized them in "solvated" docking by manually inserting them into the input files for the rigid body ZDOCK program. By accounting for these interfacial waters, a statistically significant improvement of ∼24% in the average hit-count within the top-10 predictions the protein-protein dataset was seen, compared to standard "dry" docking. The results also show scoring improvement, with medium and high accuracy models ranking much better than incorrect ones. These improvements can be attributed to the physical presence of water molecules that alter surface properties and better represent native shape and hydropathic complementarity between interacting partners, with concomitantly more accurate native-like structure predictions.

Isozyme-specific ligands for O-acetylserine sulfhydrylase, a novel antibiotic target

The last step of cysteine biosynthesis in bacteria and plants is catalyzed by O-acetylserine sulfhydrylase. In bacteria, two isozymes, O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B, have been identified that share similar binding sites, although the respective specific functions are still debated. O-acetylserine sulfhydrylase plays a key role in the adaptation of bacteria to the host environment, in the defense mechanisms to oxidative stress and in antibiotic resistance. Because mammals synthesize cysteine from methionine and lack O-acetylserine sulfhydrylase, the enzyme is a potential target for antimicrobials. With this aim, we first identified potential inhibitors of the two isozymes via a ligand- and structure-based in silico screening of a subset of the ZINC library using FLAP. The binding affinities of the most promising candidates were measured in vitro on purified O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B from Salmonella typhimurium by a direct method that exploits the change in the cofactor fluorescence. Two molecules were identified with dissociation constants of 3.7 and 33 µM for O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B, respectively. Because GRID analysis of the two isoenzymes indicates the presence of a few common pharmacophoric features, cross binding titrations were carried out. It was found that the best binder for O-acetylserine sulfhydrylase-B exhibits a dissociation constant of 29 µM for O-acetylserine sulfhydrylase-A, thus displaying a limited selectivity, whereas the best binder for O-acetylserine sulfhydrylase-A exhibits a dissociation constant of 50 µM for O-acetylserine sulfhydrylase-B and is thus 8-fold selective towards the former isozyme. Therefore, isoform-specific and isoform-independent ligands allow to either selectively target the isozyme that predominantly supports bacteria during infection and long-term survival or to completely block bacterial cysteine biosynthesis.

Pharmacophore selection and redesign of non-nucleotide inhibitors of anthrax edema factor

Antibiotic treatment may fail to protect individuals, if not started early enough, after infection with Bacillus anthracis, due to the continuing activity of toxins that the bacterium produces. Stable and easily stored inhibitors of the edema factor toxin (EF), an adenylyl cyclase, could save lives in the event of an outbreak, due to natural causes or a bioweapon attack. The toxin’s basic activity is to convert ATP to cAMP, and it is thus in principle a simple phosphatase, which means that many mammalian enzymes, including intracellular adenylcyclases, may have a similar activity. While nucleotide based inhibitors, similar to its natural substrate, ATP, were identified early, these compounds had low activity and specificity for EF. We used a combined structural and computational approach to choose small organic molecules in large, web-based compound libraries that would, based on docking scores, bind to residues within the substrate binding pocket of EF. A family of fluorenone-based inhibitors was identified that inhibited the release of cAMP from cells treated with EF. The lead inhibitor was also shown to inhibit the diarrhea caused by enterotoxigenic E. coli (ETEC) in a murine model, perhaps by serving as a quorum sensor. These inhibitors are now being tested for their ability to inhibit Anthrax infection in animal models and may have use against other pathogens that produce toxins similar to EF, such as Bordetella pertussis or Vibrio cholera.

In silico-screening approaches for lead generation: identification of novel allosteric modulators of human-erythrocyte pyruvate kinase

Identification of allosteric binding site modulators have gained increased attention lately for their potential to be developed as selective agents with a novel chemotype and targeting perhaps a new and unique binding site with probable fewer side effects. Erythrocyte pyruvate kinase (R-PK) is an important glycolytic enzyme that can be pharmacologically modulated through its allosteric effectors for the treatment of hemolytic anemia, sickle-cell anemia, hypoxia-related diseases, and other disorders arising from erythrocyte PK malfunction. An in-silico screening approach was applied to identify novel allosteric modulators of pyruvate kinase. A small-molecules database of the National Cancer Institute (NCI), was virtually screened based on structure/ligand-based pharmacophore. The virtual screening campaign led to the identification of several compounds with similar pharmacophoric features as fructose-1,6-bisphosphate (FBP), the natural allosteric activator of the kinase. The compounds were subsequently docked into the FBP-binding site using the programs FlexX and GOLD, and their interactions with the protein were analyzed with the energy-scoring function of HINT. Seven promising candidates were obtained from the NCI and subjected to kinetics analysis, which revealed both activators and inhibitors of the R-isozyme of PK (R-PK).

Computational analysis of structure-based interactions and ligand properties can predict efflux effects on antibiotics

AcrA-AcrB-TolC efflux pumps extrude drugs of multiple classes from bacterial cells and are a leading cause for antimicrobial resistance. Thus, they are of paramount interest to those engaged in antibiotic discovery. Accurate prediction of antibiotic efflux has been elusive, despite several studies aimed at this purpose. Minimum inhibitory concentration (MIC) ratios of 32 β-lactam antibiotics were collected from literature. 3-Dimensional Quantitative Structure-Activity Relationship on the β-lactam antibiotic structures revealed seemingly predictive models (q(2)=0.53), but the lack of a general superposition rule does not allow its use on antibiotics that lack the β-lactam moiety. Since MIC ratios must depend on interactions of antibiotics with lipid membranes and transport proteins during influx, capture and extrusion of antibiotics from the bacterial cell, descriptors representing these factors were calculated and used in building mathematical models that quantitatively classify antibiotics as having high/low efflux (>93% accuracy). Our models provide preliminary evidence that it is possible to predict the effects of antibiotic efflux if the passage of antibiotics into, and out of, bacterial cells is taken into account--something descriptor and field-based QSAR models cannot do. While the paucity of data in the public domain remains the limiting factor in such studies, these models show significant improvements in predictions over simple LogP-based regression models and should pave the path toward further work in this field. This method should also be extensible to other pharmacologically and biologically relevant transport proteins.

Premature activation of the paramyxovirus fusion protein before target cell attachment with corruption of the viral fusion machinery

Paramyxoviruses, including the childhood pathogen human parainfluenza virus type 3, enter host cells by fusion of the viral and target cell membranes. This fusion results from the concerted action of its two envelope glycoproteins, the hemagglutinin-neuraminidase (HN) and the fusion protein (F). The receptor-bound HN triggers F to undergo conformational changes that render it competent to mediate fusion of the viral and cellular membranes. We proposed that, if the fusion process could be activated prematurely before the virion reaches the target host cell, infection could be prevented. We identified a small molecule that inhibits paramyxovirus entry into target cells and prevents infection. We show here that this compound works by an interaction with HN that results in F-activation prior to receptor binding. The fusion process is thereby prematurely activated, preventing fusion of the viral membrane with target cells and precluding viral entry. This first evidence that activation of a paramyxovirus F can be specifically induced before the virus contacts its target cell suggests a new strategy with broad implications for the design of antiviral agents.

CSAR benchmark exercise of 2010: selection of the protein-ligand complexes

A major goal in drug design is the improvement of computational methods for docking and scoring. The Community Structure Activity Resource (CSAR) aims to collect available data from industry and academia which may be used for this purpose (www.csardock.org). Also, CSAR is charged with organizing community-wide exercises based on the collected data. The first of these exercises was aimed to gauge the overall state of docking and scoring, using a large and diverse data set of protein–ligand complexes. Participants were asked to calculate the affinity of the complexes as provided and then recalculate with changes which may improve their specific method. This first data set was selected from existing PDB entries which had binding data (K_d or K_i) in Binding MOAD, augmented with entries from PDBbind. The final data set contains 343 diverse protein–ligand complexes and spans 14 pK_d. Sixteen proteins have three or more complexes in the data set, from which a user could start an inspection of congeneric series. Inherent experimental error limits the possible correlation between scores and measured affinity; R² is limited to ∼0.9 when fitting to the data set without over parametrizing. R² is limited to ∼0.8 when scoring the data set with a method trained on outside data. The details of how the data set was initially selected, and the process by which it matured to better fit the needs of the community are presented. Many groups generously participated in improving the data set, and this underscores the value of a supportive, collaborative effort in moving our field forward.

Factors influencing protein tyrosine nitration--structure-based predictive models

Models for exploring tyrosine nitration in proteins have been created based on 3D structural features of 20 proteins for which high-resolution X-ray crystallographic or NMR data are available and for which nitration of 35 total tyrosines has been experimentally proven under oxidative stress. Factors suggested in previous work to enhance nitration were examined with quantitative structural descriptors. The role of neighboring acidic and basic residues is complex: for the majority of tyrosines that are nitrated the distance to the heteroatom of the closest charged side chain corresponds to the distance needed for suspected nitrating species to form hydrogen bond bridges between the tyrosine and that charged amino acid. This suggests that such bridges play a very important role in tyrosine nitration. Nitration is generally hindered for tyrosines that are buried and for those tyrosines for which there is insufficient space for the nitro group. For in vitro nitration, closed environments with nearby heteroatoms or unsaturated centers that can stabilize radicals are somewhat favored. Four quantitative structure-based models, depending on the conditions of nitration, have been developed for predicting site-specific tyrosine nitration. The best model, relevant for both in vitro and in vivo cases, predicts 30 of 35 tyrosine nitrations (positive predictive value) and has a sensitivity of 60/71 (11 false positives).