Alessandro Pedretti - Academia.edu (original) (raw)

Papers by Alessandro Pedretti

Molecules

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Molecules

(1) Background: Machine learning algorithms are finding fruitful applications in predicting the A... more (1) Background: Machine learning algorithms are finding fruitful applications in predicting the ADME profile of new molecules, with a particular focus on metabolism predictions. However, the development of comprehensive metabolism predictors is hampered by the lack of highly accurate metabolic resources. Hence, we recently proposed a manually curated metabolic database (MetaQSAR), the level of accuracy of which is well suited to the development of predictive models. (2) Methods: MetaQSAR was used to extract datasets to predict the metabolic reactions subdivided into major classes, classes and subclasses. The collected datasets comprised a total of 3788 first-generation metabolic reactions. Predictive models were developed by using standard random forest algorithms and sets of physicochemical, stereo-electronic and constitutional descriptors. (3) Results: The developed models showed satisfactory performance, especially for hydrolyses and conjugations, while redox reactions were predicted with greater difficulty, which was reasonable as they depend on many complex features that are not properly encoded by the included descriptors. (4) Conclusions: The generated models allowed a precise comparison of the propensity of each metabolic reaction to be predicted and the factors affecting their predictability were discussed in detail. Overall, the study led to the development of a freely downloadable global predictor, MetaClass, which correctly predicts 80% of the reported reactions, as assessed by an explorative validation analysis on an external dataset, with an overall MCC = 0.44.

Molecules

The 3CL-Protease appears to be a very promising medicinal target to develop anti-SARS-CoV-2 agent... more The 3CL-Protease appears to be a very promising medicinal target to develop anti-SARS-CoV-2 agents. The availability of resolved structures allows structure-based computational approaches to be carried out even though the lack of known inhibitors prevents a proper validation of the performed simulations. The innovative idea of the study is to exploit known inhibitors of SARS-CoV 3CL-Pro as a training set to perform and validate multiple virtual screening campaigns. Docking simulations using four different programs (Fred, Glide, LiGen, and PLANTS) were performed investigating the role of both multiple binding modes (by binding space) and multiple isomers/states (by developing the corresponding isomeric space). The computed docking scores were used to develop consensus models, which allow an in-depth comparison of the resulting performances. On average, the reached performances revealed the different sensitivity to isomeric differences and multiple binding modes between the four docki...

International Journal of Molecular Sciences

Structure-based virtual screening is a truly productive repurposing approach provided that reliab... more Structure-based virtual screening is a truly productive repurposing approach provided that reliable target structures are available. Recent progresses in the structural resolution of the G-Protein Coupled Receptors (GPCRs) render these targets amenable for structure-based repurposing studies. Hence, the present study describes structure-based virtual screening campaigns with a view to repurposing known drugs as potential allosteric (and/or orthosteric) ligands for the hM2 muscarinic subtype which was indeed resolved in complex with an allosteric modulator thus allowing a precise identification of this binding cavity. First, a docking protocol was developed and optimized based on binding space concept and enrichment factor optimization algorithm (EFO) consensus approach by using a purposely collected database including known allosteric modulators. The so-developed consensus models were then utilized to virtually screen the DrugBank database. Based on the computational results, six pr...

Applied Sciences

Despite the increasing role played by artificial intelligence methods (AI) in pharmaceutical scie... more Despite the increasing role played by artificial intelligence methods (AI) in pharmaceutical sciences, model deployment remains an issue, which only can be addressed with great difficulty. This leads to a marked discrepancy between the number of published predictive studies based on AI methods and the models, which can be used for new predictions by everyone. On these grounds, the present paper describes the Tree2C tool which automatically translates a tree-based predictive model into a source code with a view to easily generating applications which can run as a standalone software or can be inserted into an online web service. Moreover, the Tree2C tool is implemented within the VEGA environment and the generated program can include the source code to calculate the required attributes/descriptors. Tree2C supports various programming languages (i.e., C/C++, Fortran 90, Java, JavaScript, JScript, Lua, PHP, Python, REBOL and VBScript and C-Script). Along with a detailed description of ...

International Journal of Molecular Sciences

(1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe ... more (1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) require a detailed characterization of their druggable binding sites, and, more generally, a convenient pocket mapping represents a key step for structure-based in silico studies; (2) Methods: Along with a careful literature search on SARS-CoV-2 protein targets, the study presents a novel strategy for pocket mapping based on the combination of pocket (as performed by the well-known FPocket tool) and docking searches (as performed by PLANTS or AutoDock/Vina engines); such an approach is implemented by the Pockets 2.0 plug-in for the VEGA ZZ suite of programs; (3) Results: The literature analysis allowed the identification of 16 promising binding cavities within the SARS-CoV-2 proteins and the here proposed approach was able to recognize them showing performances clearly better than those reached by the sole pocket detection; and (4) Conclusions: Even though the presented strategy should require more extended validations, this proved successful in precisely characterizing a set of SARS-CoV-2 druggable binding pockets including both orthosteric and allosteric sites, which are clearly amenable for virtual screening campaigns and drug repurposing studies. All results generated by the study and the Pockets 2.0 plug-in are available for download.

Molecules

Diabetes Mellitus (DM) is a multi-factorial chronic health condition that affects a large part of... more Diabetes Mellitus (DM) is a multi-factorial chronic health condition that affects a large part of population and according to the World Health Organization (WHO) the number of adults living with diabetes is expected to increase. Since type 2 diabetes mellitus (T2DM) is suffered by the majority of diabetic patients (around 90–95%) and often the mono-target therapy fails in managing blood glucose levels and the other comorbidities, this review focuses on the potential drugs acting on multi-targets involved in the treatment of this type of diabetes. In particular, the review considers the main systems directly involved in T2DM or involved in diabetes comorbidities. Agonists acting on incretin, glucagon systems, as well as on peroxisome proliferation activated receptors are considered. Inhibitors which target either aldose reductase and tyrosine phosphatase 1B or sodium glucose transporters 1 and 2 are taken into account. Moreover, with a view at the multi-target approaches for T2DM som...

International Journal of Molecular Sciences

The study proposes a novel consensus strategy based on linear combinations of different docking s... more The study proposes a novel consensus strategy based on linear combinations of different docking scores to be used in the evaluation of virtual screening campaigns. The consensus models are generated by applying the recently proposed Enrichment Factor Optimization (EFO) method, which develops the linear equations by exhaustively combining the available docking scores and by optimizing the resulting enrichment factors. The performances of such a consensus strategy were evaluated by simulating the entire Directory of Useful Decoys (DUD datasets). In detail, the poses were initially generated by the PLANTS docking program and then rescored by ReScore+ with and without the minimization of the complexes. The so calculated scores were then used to generate the mentioned consensus models including two or three different scoring functions. The reliability of the generated models was assessed by a per target validation as performed by default by the EFO approach. The encouraging performances ...

Journal of chemical information and modeling, Jan 25, 2018

The manuscript describes WarpEngine, a novel platform implemented within the VEGA ZZ suite of sof... more The manuscript describes WarpEngine, a novel platform implemented within the VEGA ZZ suite of software for performing distributed simulations both in local and wide area networks. Despite being tailored for structure-based virtual screening campaigns, WarpEngine possesses the required flexibility to carry out distributed calculations utilizing various pieces of software, which can be easily encapsulated within this platform without changing their source codes. WarpEngine takes advantages of all cheminformatics features implemented in the VEGA ZZ program as well as of its largely customizable scripting architecture thus allowing an efficient distribution of various time-demanding simulations. To offer an example of the WarpEngine potentials, the manuscript includes a set of virtual screening campaigns based on the ACE data set of the DUD-E collections using PLANTS as the docking application. Benchmarking analyses revealed a satisfactory linearity of the WarpEngine performances, the s...

Methods in molecular biology (Clifton, N.J.), 2018

With a view to introducing the concept of pharmacological space and its potential applications in... more With a view to introducing the concept of pharmacological space and its potential applications in investigating and predicting the toxic mechanisms of xenobiotics, this opening chapter describes the logical relations between conformational behavior, physicochemical properties and binding spaces, which are seen as the three key elements composing the pharmacological space. While the concept of conformational space is routinely used to encode molecular flexibility, the concepts of property spaces and, particularly, of binding spaces are more innovative. Indeed, their descriptors can find fruitful applications (a) in describing the dynamic adaptability a given ligand experiences when inserted into a specific environment, and (b) in parameterizing the flexibility a ligand retains when bound to a biological target. Overall, these descriptors can conveniently account for the often disregarded entropic factors and as such they prove successful when inserted in ligand- or structure-based pr...

Molecules

The study is aimed at developing linear classifiers to predict the capacity of a given substrate ... more The study is aimed at developing linear classifiers to predict the capacity of a given substrate to yield reactive metabolites. While most of the hitherto reported predictive models are based on the occurrence of known structural alerts (e.g., the presence of toxophoric groups), the present study is focused on the generation of predictive models involving linear combinations of physicochemical and stereo-electronic descriptors. The development of these models is carried out by using a novel classification approach based on enrichment factor optimization (EFO) as implemented in the VEGA suite of programs. The study took advantage of metabolic data as collected by manually curated analysis of the primary literature and published in the years 2004–2009. The learning set included 977 substrates among which 138 compounds yielded reactive first-generation metabolites, plus 212 substrates generating reactive metabolites in all generations (i.e., metabolic steps). The results emphasized the...

Scientific reports, Jan 6, 2018

A correction to this article has been published and is linked from the HTML and PDF versions of t... more A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Journal of medicinal chemistry, Jan 17, 2018

The study describes the MetaQSAR tool, a new database engine specifically tailored to collect and... more The study describes the MetaQSAR tool, a new database engine specifically tailored to collect and analyze metabolic data. This is a plug-in embedded in the VEGA suite of programs (freely downloadable at www.vegazz.net ) and takes advantage from all cheminformatics features implemented in the software with additional tools aimed to perform statistical analyses, similarity searches, and physicochemical profiling of the stored molecules. MetaQSAR also implements a novel metabolism classification, which groups the metabolic reactions in 101 classes and can find numerous applications in metabolic analyses. The potentials of MetaQSAR are here assessed by using it to store and analyze an extended database focused on metabolism of xenobiotics, which was collected by manually curated meta-analysis of the recent literature. The database includes 1890 substrates taken from about 1500 original papers in the years 2004-2015. The database was utilized in both physicochemical analyses and similari...

Scientific Reports

Transient receptor potential melastatin 8 (TRPM8), a nonselective cation channel, is the predomin... more Transient receptor potential melastatin 8 (TRPM8), a nonselective cation channel, is the predominant mammalian cold temperature thermosensor and it is activated by cold temperatures and cooling compounds, such as menthol and icilin. Because of its role in cold allodynia, cold hyperalgesia and painful syndromes TRPM8 antagonists are currently being pursued as potential therapeutic agents for the treatment of pain hypersensitivity. Recently TRPM8 has been found in subsets of bladder sensory nerve fibres, providing an opportunity to understand and treat chronic hypersensitivity. However, most of the known TRPM8 inhibitors lack selectivity, and only three selective compounds have reached clinical trials to date. Here, we applied two virtual screening strategies to find new, clinics suitable, TRPM8 inhibitors. This strategy enabled us to identify naphthyl derivatives as a novel class of potent and selective TRPM8 inhibitors. Further characterization of the pharmacologic properties of the most potent compound identified, compound 1, confirmed that it is a selective, competitive antagonist inhibitor of TRPM8. Compound 1 also proved itself active in a overreactive bladder model in vivo. Thus, the novel naphthyl derivative compound identified here could be optimized for clinical treatment of pain hypersensitivity in bladder disorders but also in different other pathologies. Transient receptor potential (TRP) channels are a group of ion channels located primarily on the plasma membrane of numerous animal cell types 1,2. These channels are characterized by six transmembrane subdomains flanked by intracellular C-and N-terminal regions, and they are capable of homo-or hetero-tetramerization to form cation-permeable pores 3. These channels mediate responses to a wide range of stimuli, such as pain, heat, warmth or coldness, as well as taste, pressure, and vision. Members of the mammalian TRP channel family can be subdivided into seven classes according to their sequence homology: TRP ankyrin (TRPA), TRP canonical (TRPC), TRP melastatin (TRPM), TRP melastatin-like (TRPML), TRP NOMPC (TRPN), TRP polycystic (TRPP) and TRP vanilloid (TRPV). Eight of the family members are recognized as thermo-TRPs in that they are expressed in primary somatosensory neurons and are activated at specific temperatures ranging from noxious heat to painful cold. TRPV1-4 transduce elevated temperatures ranging from warm (TRPV4 and TRPV3) to noxious heat (TRPV1 and TRPV2). By contrast, TRPM8 and TRPA1 are activated by moderate and more extreme cooling, respectively. All thermo-TRPs are also activated by a wide range of natural compounds. TRPM2, TRPM4 and TRPM5 also show temperature sensitivity but are not usually included in the thermo-TRP family because

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences, Jan 30, 2017

Prediction of skin permeability can have manifold applications ranging from drug delivery to toxi... more Prediction of skin permeability can have manifold applications ranging from drug delivery to toxicity prediction. Along with the semi-empirical or mechanistic models proposed in the last decades, Molecular Dynamics simulations have recently become a fruitful tool for investigating membrane permeability, in particular as they allow the involved mechanisms to be modelled at a molecular level. Despite their significant structural complexity, Molecular Dynamics simulations can also be utilized to study permeation through the lipid matrix that characterizes the stratum corneum. In this work, Steered Molecular Dynamics simulations are performed on a suitably developed stratum corneum lipid matrix model. Regardless of their actual tortuous path within the stratum corneum, the permeants, taken from a Fully Validated dataset of 80 compounds of known permeability coefficient, are moved through the bilayer along its normal. This allows the exploration of all the possible conformational and phy...

Data in brief, 2017

The data presented in this article are related to the article titled "Molecular Dynamics as ... more The data presented in this article are related to the article titled "Molecular Dynamics as a tool for in silico screening of skin permeability" (Rocco et al., 2017) [1]. Knowledge of the confidence interval and maximum theoretical value of the correlation coefficient r can prove useful to estimate the reliability of developed predictive models, in particular when there is great variability in compiled experimental datasets. In this Data in Brief article, data from purposely designed numerical simulations are presented to show how much the maximum r value is worsened by increasing the data uncertainty. The corresponding confidence interval of r is determined by using the Fisher r→Z transform.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences, 2017

The present study proposes a method for an in silico calculation of phospholipophilicity. Phospho... more The present study proposes a method for an in silico calculation of phospholipophilicity. Phospholipophilicity is intended as the measure of analyte affinity for phospholipids; it is currently assessed by HPLC measures of analyte retention on phosphatidylcholine-like stationary phases (IAM - Immobilized Artificial Membrane) resulting in log kW(IAM) values. Due to the amphipathic and electrically charged nature of phospholipids, retention on these stationary phases results from complex mechanisms, being affected not only by lipophilicity (as measured by n-octanol/aqueous phase partition coefficients, log P) but also by the occurrence of polar and/or electrostatic intermolecular interaction forces. Differently from log P, to date no method has been proposed for in silico calculation of log kW(IAM). The study is aimed both at shedding new light into the retention mechanism on IAM stationary phases and at offering a high-throughput method to achieve such values. A wide set of physico-ch...

Molecular Informatics, 2016

DNA methylation plays key roles in mammalian cells and is modulated by a set of proteins which re... more DNA methylation plays key roles in mammalian cells and is modulated by a set of proteins which recognize symmetrically methylated nucleotides. Among them, the protein MECP2 shows multifunctional roles repressing and/or activating genes by binding to both methylated and unmethylated regions of the genome. The interest for this protein markedly increased from the observation that its mutations are the primary cause of Rett syndrome, a neurodevelopmental disorder which causes mental retardation in young females. Thus, the present study is aimed to investigate the effects of some of these known pathogenic missense mutations (i.e. R106Q, R106W, R111G, R133C and R133H) on the MECP2 folding and DNA binding by molecular dynamics simulations. The effects of the simulated mutations are also parameterized by using a here proposed new tool, named Rescore+, implemented in the VEGA ZZ suite of programs, which calculates a set of scoring functions on all frames of a trajectory or on all complexes contained in a database thus allowing an easy rescoring of results coming from MD or docking simulations. The obtained results revealed that the reported loss of the MECP2 function induced by the simulated mutations can be ascribed to both stabilizing and destabilizing effect on DNA binding. The study confirms that MD simulations are particularly useful to rationalize and predict the mutation effects offering insightful information for diagnostics and drug design.

Future Medicinal Chemistry, 2016

The inhibition of protein carbonylation can play therapeutic roles in several oxidative-based dis... more The inhibition of protein carbonylation can play therapeutic roles in several oxidative-based diseases and direct carbonyl quenching appears the most effective inhibition strategies. l-carnosine derivatives are effective and selective quenchers toward 4-hydroxy-2-nonenal even though their activity was never investigated in a fully comparable way. The reported results revealed that anserine, homocarnosine and carnosinamide retain a remarkable quenching activity combined with a satisfactory selectivity. In silico analyses confirmed the key role of flexibility, lipophilicity and nucleophilicity parameters in rationalizing the measured reactivity. This study confirms that in silico approaches can be successfully used in the rational design of improved carbonyl quenchers. Physicochemical and stereoelectronic descriptors appear really informative especially when explored by their corresponding property spaces.

Journal of the American Chemical Society, Jun 1, 2002

The objective of this study was to determine if and how a solvent influences internal motions in ... more The objective of this study was to determine if and how a solvent influences internal motions in a solute molecule. Acetylcholine was chosen as the object of study given its interesting molecular structure and major biological significance. Molecular dynamics simulations were carried out in the vacuum (10 ns), water (5 ns), methanol (5 ns), and octanol (1.5 ns). Seven clusters of conformers were identified, namely, +g+g,-g-g, +gt,-gt, t+g, t-g, and tt, where the gauche and trans labels refer to the dihedral angles τ2 and τ3, respectively. As expected, the relative proportion of these conformational clusters was highly solvent-dependent and corresponded to a progressive loss of conformational freedom with increasing molecular weight of the solvent. More importantly, the conformational clusters were used to calculate instantaneous and median angular velocity (ω and ω M, respectively) and instantaneous and median angular acceleration (R and RM, respectively). Angular velocity and angular acceleration were both found to decrease markedly with increasing molecular weight of the solvent, i.e., vacuum () 1) > water > methanol > octanol. The decrease from the vacuum to octanol was ∼40% for τ2 and ∼60% for τ3. Such solventdependent constraints on a solute's internal motions may be biologically and pharmacologically relevant.

Molecules

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Molecules

(1) Background: Machine learning algorithms are finding fruitful applications in predicting the A... more (1) Background: Machine learning algorithms are finding fruitful applications in predicting the ADME profile of new molecules, with a particular focus on metabolism predictions. However, the development of comprehensive metabolism predictors is hampered by the lack of highly accurate metabolic resources. Hence, we recently proposed a manually curated metabolic database (MetaQSAR), the level of accuracy of which is well suited to the development of predictive models. (2) Methods: MetaQSAR was used to extract datasets to predict the metabolic reactions subdivided into major classes, classes and subclasses. The collected datasets comprised a total of 3788 first-generation metabolic reactions. Predictive models were developed by using standard random forest algorithms and sets of physicochemical, stereo-electronic and constitutional descriptors. (3) Results: The developed models showed satisfactory performance, especially for hydrolyses and conjugations, while redox reactions were predicted with greater difficulty, which was reasonable as they depend on many complex features that are not properly encoded by the included descriptors. (4) Conclusions: The generated models allowed a precise comparison of the propensity of each metabolic reaction to be predicted and the factors affecting their predictability were discussed in detail. Overall, the study led to the development of a freely downloadable global predictor, MetaClass, which correctly predicts 80% of the reported reactions, as assessed by an explorative validation analysis on an external dataset, with an overall MCC = 0.44.

Molecules

The 3CL-Protease appears to be a very promising medicinal target to develop anti-SARS-CoV-2 agent... more The 3CL-Protease appears to be a very promising medicinal target to develop anti-SARS-CoV-2 agents. The availability of resolved structures allows structure-based computational approaches to be carried out even though the lack of known inhibitors prevents a proper validation of the performed simulations. The innovative idea of the study is to exploit known inhibitors of SARS-CoV 3CL-Pro as a training set to perform and validate multiple virtual screening campaigns. Docking simulations using four different programs (Fred, Glide, LiGen, and PLANTS) were performed investigating the role of both multiple binding modes (by binding space) and multiple isomers/states (by developing the corresponding isomeric space). The computed docking scores were used to develop consensus models, which allow an in-depth comparison of the resulting performances. On average, the reached performances revealed the different sensitivity to isomeric differences and multiple binding modes between the four docki...

International Journal of Molecular Sciences

Structure-based virtual screening is a truly productive repurposing approach provided that reliab... more Structure-based virtual screening is a truly productive repurposing approach provided that reliable target structures are available. Recent progresses in the structural resolution of the G-Protein Coupled Receptors (GPCRs) render these targets amenable for structure-based repurposing studies. Hence, the present study describes structure-based virtual screening campaigns with a view to repurposing known drugs as potential allosteric (and/or orthosteric) ligands for the hM2 muscarinic subtype which was indeed resolved in complex with an allosteric modulator thus allowing a precise identification of this binding cavity. First, a docking protocol was developed and optimized based on binding space concept and enrichment factor optimization algorithm (EFO) consensus approach by using a purposely collected database including known allosteric modulators. The so-developed consensus models were then utilized to virtually screen the DrugBank database. Based on the computational results, six pr...

Applied Sciences

Despite the increasing role played by artificial intelligence methods (AI) in pharmaceutical scie... more Despite the increasing role played by artificial intelligence methods (AI) in pharmaceutical sciences, model deployment remains an issue, which only can be addressed with great difficulty. This leads to a marked discrepancy between the number of published predictive studies based on AI methods and the models, which can be used for new predictions by everyone. On these grounds, the present paper describes the Tree2C tool which automatically translates a tree-based predictive model into a source code with a view to easily generating applications which can run as a standalone software or can be inserted into an online web service. Moreover, the Tree2C tool is implemented within the VEGA environment and the generated program can include the source code to calculate the required attributes/descriptors. Tree2C supports various programming languages (i.e., C/C++, Fortran 90, Java, JavaScript, JScript, Lua, PHP, Python, REBOL and VBScript and C-Script). Along with a detailed description of ...

International Journal of Molecular Sciences

(1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe ... more (1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) require a detailed characterization of their druggable binding sites, and, more generally, a convenient pocket mapping represents a key step for structure-based in silico studies; (2) Methods: Along with a careful literature search on SARS-CoV-2 protein targets, the study presents a novel strategy for pocket mapping based on the combination of pocket (as performed by the well-known FPocket tool) and docking searches (as performed by PLANTS or AutoDock/Vina engines); such an approach is implemented by the Pockets 2.0 plug-in for the VEGA ZZ suite of programs; (3) Results: The literature analysis allowed the identification of 16 promising binding cavities within the SARS-CoV-2 proteins and the here proposed approach was able to recognize them showing performances clearly better than those reached by the sole pocket detection; and (4) Conclusions: Even though the presented strategy should require more extended validations, this proved successful in precisely characterizing a set of SARS-CoV-2 druggable binding pockets including both orthosteric and allosteric sites, which are clearly amenable for virtual screening campaigns and drug repurposing studies. All results generated by the study and the Pockets 2.0 plug-in are available for download.

Molecules

Diabetes Mellitus (DM) is a multi-factorial chronic health condition that affects a large part of... more Diabetes Mellitus (DM) is a multi-factorial chronic health condition that affects a large part of population and according to the World Health Organization (WHO) the number of adults living with diabetes is expected to increase. Since type 2 diabetes mellitus (T2DM) is suffered by the majority of diabetic patients (around 90–95%) and often the mono-target therapy fails in managing blood glucose levels and the other comorbidities, this review focuses on the potential drugs acting on multi-targets involved in the treatment of this type of diabetes. In particular, the review considers the main systems directly involved in T2DM or involved in diabetes comorbidities. Agonists acting on incretin, glucagon systems, as well as on peroxisome proliferation activated receptors are considered. Inhibitors which target either aldose reductase and tyrosine phosphatase 1B or sodium glucose transporters 1 and 2 are taken into account. Moreover, with a view at the multi-target approaches for T2DM som...

International Journal of Molecular Sciences

The study proposes a novel consensus strategy based on linear combinations of different docking s... more The study proposes a novel consensus strategy based on linear combinations of different docking scores to be used in the evaluation of virtual screening campaigns. The consensus models are generated by applying the recently proposed Enrichment Factor Optimization (EFO) method, which develops the linear equations by exhaustively combining the available docking scores and by optimizing the resulting enrichment factors. The performances of such a consensus strategy were evaluated by simulating the entire Directory of Useful Decoys (DUD datasets). In detail, the poses were initially generated by the PLANTS docking program and then rescored by ReScore+ with and without the minimization of the complexes. The so calculated scores were then used to generate the mentioned consensus models including two or three different scoring functions. The reliability of the generated models was assessed by a per target validation as performed by default by the EFO approach. The encouraging performances ...

Journal of chemical information and modeling, Jan 25, 2018

The manuscript describes WarpEngine, a novel platform implemented within the VEGA ZZ suite of sof... more The manuscript describes WarpEngine, a novel platform implemented within the VEGA ZZ suite of software for performing distributed simulations both in local and wide area networks. Despite being tailored for structure-based virtual screening campaigns, WarpEngine possesses the required flexibility to carry out distributed calculations utilizing various pieces of software, which can be easily encapsulated within this platform without changing their source codes. WarpEngine takes advantages of all cheminformatics features implemented in the VEGA ZZ program as well as of its largely customizable scripting architecture thus allowing an efficient distribution of various time-demanding simulations. To offer an example of the WarpEngine potentials, the manuscript includes a set of virtual screening campaigns based on the ACE data set of the DUD-E collections using PLANTS as the docking application. Benchmarking analyses revealed a satisfactory linearity of the WarpEngine performances, the s...

Methods in molecular biology (Clifton, N.J.), 2018

With a view to introducing the concept of pharmacological space and its potential applications in... more With a view to introducing the concept of pharmacological space and its potential applications in investigating and predicting the toxic mechanisms of xenobiotics, this opening chapter describes the logical relations between conformational behavior, physicochemical properties and binding spaces, which are seen as the three key elements composing the pharmacological space. While the concept of conformational space is routinely used to encode molecular flexibility, the concepts of property spaces and, particularly, of binding spaces are more innovative. Indeed, their descriptors can find fruitful applications (a) in describing the dynamic adaptability a given ligand experiences when inserted into a specific environment, and (b) in parameterizing the flexibility a ligand retains when bound to a biological target. Overall, these descriptors can conveniently account for the often disregarded entropic factors and as such they prove successful when inserted in ligand- or structure-based pr...

Molecules

The study is aimed at developing linear classifiers to predict the capacity of a given substrate ... more The study is aimed at developing linear classifiers to predict the capacity of a given substrate to yield reactive metabolites. While most of the hitherto reported predictive models are based on the occurrence of known structural alerts (e.g., the presence of toxophoric groups), the present study is focused on the generation of predictive models involving linear combinations of physicochemical and stereo-electronic descriptors. The development of these models is carried out by using a novel classification approach based on enrichment factor optimization (EFO) as implemented in the VEGA suite of programs. The study took advantage of metabolic data as collected by manually curated analysis of the primary literature and published in the years 2004–2009. The learning set included 977 substrates among which 138 compounds yielded reactive first-generation metabolites, plus 212 substrates generating reactive metabolites in all generations (i.e., metabolic steps). The results emphasized the...

Scientific reports, Jan 6, 2018

A correction to this article has been published and is linked from the HTML and PDF versions of t... more A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Journal of medicinal chemistry, Jan 17, 2018

The study describes the MetaQSAR tool, a new database engine specifically tailored to collect and... more The study describes the MetaQSAR tool, a new database engine specifically tailored to collect and analyze metabolic data. This is a plug-in embedded in the VEGA suite of programs (freely downloadable at www.vegazz.net ) and takes advantage from all cheminformatics features implemented in the software with additional tools aimed to perform statistical analyses, similarity searches, and physicochemical profiling of the stored molecules. MetaQSAR also implements a novel metabolism classification, which groups the metabolic reactions in 101 classes and can find numerous applications in metabolic analyses. The potentials of MetaQSAR are here assessed by using it to store and analyze an extended database focused on metabolism of xenobiotics, which was collected by manually curated meta-analysis of the recent literature. The database includes 1890 substrates taken from about 1500 original papers in the years 2004-2015. The database was utilized in both physicochemical analyses and similari...

Scientific Reports

Transient receptor potential melastatin 8 (TRPM8), a nonselective cation channel, is the predomin... more Transient receptor potential melastatin 8 (TRPM8), a nonselective cation channel, is the predominant mammalian cold temperature thermosensor and it is activated by cold temperatures and cooling compounds, such as menthol and icilin. Because of its role in cold allodynia, cold hyperalgesia and painful syndromes TRPM8 antagonists are currently being pursued as potential therapeutic agents for the treatment of pain hypersensitivity. Recently TRPM8 has been found in subsets of bladder sensory nerve fibres, providing an opportunity to understand and treat chronic hypersensitivity. However, most of the known TRPM8 inhibitors lack selectivity, and only three selective compounds have reached clinical trials to date. Here, we applied two virtual screening strategies to find new, clinics suitable, TRPM8 inhibitors. This strategy enabled us to identify naphthyl derivatives as a novel class of potent and selective TRPM8 inhibitors. Further characterization of the pharmacologic properties of the most potent compound identified, compound 1, confirmed that it is a selective, competitive antagonist inhibitor of TRPM8. Compound 1 also proved itself active in a overreactive bladder model in vivo. Thus, the novel naphthyl derivative compound identified here could be optimized for clinical treatment of pain hypersensitivity in bladder disorders but also in different other pathologies. Transient receptor potential (TRP) channels are a group of ion channels located primarily on the plasma membrane of numerous animal cell types 1,2. These channels are characterized by six transmembrane subdomains flanked by intracellular C-and N-terminal regions, and they are capable of homo-or hetero-tetramerization to form cation-permeable pores 3. These channels mediate responses to a wide range of stimuli, such as pain, heat, warmth or coldness, as well as taste, pressure, and vision. Members of the mammalian TRP channel family can be subdivided into seven classes according to their sequence homology: TRP ankyrin (TRPA), TRP canonical (TRPC), TRP melastatin (TRPM), TRP melastatin-like (TRPML), TRP NOMPC (TRPN), TRP polycystic (TRPP) and TRP vanilloid (TRPV). Eight of the family members are recognized as thermo-TRPs in that they are expressed in primary somatosensory neurons and are activated at specific temperatures ranging from noxious heat to painful cold. TRPV1-4 transduce elevated temperatures ranging from warm (TRPV4 and TRPV3) to noxious heat (TRPV1 and TRPV2). By contrast, TRPM8 and TRPA1 are activated by moderate and more extreme cooling, respectively. All thermo-TRPs are also activated by a wide range of natural compounds. TRPM2, TRPM4 and TRPM5 also show temperature sensitivity but are not usually included in the thermo-TRP family because

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences, Jan 30, 2017

Prediction of skin permeability can have manifold applications ranging from drug delivery to toxi... more Prediction of skin permeability can have manifold applications ranging from drug delivery to toxicity prediction. Along with the semi-empirical or mechanistic models proposed in the last decades, Molecular Dynamics simulations have recently become a fruitful tool for investigating membrane permeability, in particular as they allow the involved mechanisms to be modelled at a molecular level. Despite their significant structural complexity, Molecular Dynamics simulations can also be utilized to study permeation through the lipid matrix that characterizes the stratum corneum. In this work, Steered Molecular Dynamics simulations are performed on a suitably developed stratum corneum lipid matrix model. Regardless of their actual tortuous path within the stratum corneum, the permeants, taken from a Fully Validated dataset of 80 compounds of known permeability coefficient, are moved through the bilayer along its normal. This allows the exploration of all the possible conformational and phy...

Data in brief, 2017

The data presented in this article are related to the article titled "Molecular Dynamics as ... more The data presented in this article are related to the article titled "Molecular Dynamics as a tool for in silico screening of skin permeability" (Rocco et al., 2017) [1]. Knowledge of the confidence interval and maximum theoretical value of the correlation coefficient r can prove useful to estimate the reliability of developed predictive models, in particular when there is great variability in compiled experimental datasets. In this Data in Brief article, data from purposely designed numerical simulations are presented to show how much the maximum r value is worsened by increasing the data uncertainty. The corresponding confidence interval of r is determined by using the Fisher r→Z transform.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences, 2017

The present study proposes a method for an in silico calculation of phospholipophilicity. Phospho... more The present study proposes a method for an in silico calculation of phospholipophilicity. Phospholipophilicity is intended as the measure of analyte affinity for phospholipids; it is currently assessed by HPLC measures of analyte retention on phosphatidylcholine-like stationary phases (IAM - Immobilized Artificial Membrane) resulting in log kW(IAM) values. Due to the amphipathic and electrically charged nature of phospholipids, retention on these stationary phases results from complex mechanisms, being affected not only by lipophilicity (as measured by n-octanol/aqueous phase partition coefficients, log P) but also by the occurrence of polar and/or electrostatic intermolecular interaction forces. Differently from log P, to date no method has been proposed for in silico calculation of log kW(IAM). The study is aimed both at shedding new light into the retention mechanism on IAM stationary phases and at offering a high-throughput method to achieve such values. A wide set of physico-ch...

Molecular Informatics, 2016

DNA methylation plays key roles in mammalian cells and is modulated by a set of proteins which re... more DNA methylation plays key roles in mammalian cells and is modulated by a set of proteins which recognize symmetrically methylated nucleotides. Among them, the protein MECP2 shows multifunctional roles repressing and/or activating genes by binding to both methylated and unmethylated regions of the genome. The interest for this protein markedly increased from the observation that its mutations are the primary cause of Rett syndrome, a neurodevelopmental disorder which causes mental retardation in young females. Thus, the present study is aimed to investigate the effects of some of these known pathogenic missense mutations (i.e. R106Q, R106W, R111G, R133C and R133H) on the MECP2 folding and DNA binding by molecular dynamics simulations. The effects of the simulated mutations are also parameterized by using a here proposed new tool, named Rescore+, implemented in the VEGA ZZ suite of programs, which calculates a set of scoring functions on all frames of a trajectory or on all complexes contained in a database thus allowing an easy rescoring of results coming from MD or docking simulations. The obtained results revealed that the reported loss of the MECP2 function induced by the simulated mutations can be ascribed to both stabilizing and destabilizing effect on DNA binding. The study confirms that MD simulations are particularly useful to rationalize and predict the mutation effects offering insightful information for diagnostics and drug design.

Future Medicinal Chemistry, 2016

The inhibition of protein carbonylation can play therapeutic roles in several oxidative-based dis... more The inhibition of protein carbonylation can play therapeutic roles in several oxidative-based diseases and direct carbonyl quenching appears the most effective inhibition strategies. l-carnosine derivatives are effective and selective quenchers toward 4-hydroxy-2-nonenal even though their activity was never investigated in a fully comparable way. The reported results revealed that anserine, homocarnosine and carnosinamide retain a remarkable quenching activity combined with a satisfactory selectivity. In silico analyses confirmed the key role of flexibility, lipophilicity and nucleophilicity parameters in rationalizing the measured reactivity. This study confirms that in silico approaches can be successfully used in the rational design of improved carbonyl quenchers. Physicochemical and stereoelectronic descriptors appear really informative especially when explored by their corresponding property spaces.

Journal of the American Chemical Society, Jun 1, 2002

The objective of this study was to determine if and how a solvent influences internal motions in ... more The objective of this study was to determine if and how a solvent influences internal motions in a solute molecule. Acetylcholine was chosen as the object of study given its interesting molecular structure and major biological significance. Molecular dynamics simulations were carried out in the vacuum (10 ns), water (5 ns), methanol (5 ns), and octanol (1.5 ns). Seven clusters of conformers were identified, namely, +g+g,-g-g, +gt,-gt, t+g, t-g, and tt, where the gauche and trans labels refer to the dihedral angles τ2 and τ3, respectively. As expected, the relative proportion of these conformational clusters was highly solvent-dependent and corresponded to a progressive loss of conformational freedom with increasing molecular weight of the solvent. More importantly, the conformational clusters were used to calculate instantaneous and median angular velocity (ω and ω M, respectively) and instantaneous and median angular acceleration (R and RM, respectively). Angular velocity and angular acceleration were both found to decrease markedly with increasing molecular weight of the solvent, i.e., vacuum () 1) > water > methanol > octanol. The decrease from the vacuum to octanol was ∼40% for τ2 and ∼60% for τ3. Such solventdependent constraints on a solute's internal motions may be biologically and pharmacologically relevant.