Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases.

Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.

Systematic analysis of molecular mechanism of resveratrol for treating pulmonary hypertension based on network pharmacology technology.

Resveratrol is a polyphenolic antioxidant derived from plant products such as grapes. Previous studies explored the effects of resveratrol on pulmonary hypertension (PH). However, systematic research on the exact mechanism of action of resveratrol is still lacking; in particular, our knowledge on the molecule-gene interaction is limited. In this study, systematic pharmacology and bioinformatic approaches were employed to identify the potential targets of resveratrol for treating PH. Furthermore, core genes were identified by constructing a protein-protein interaction network and by conducting topology analyses. The results showed that the effect of resveratrol may be closely associated with targets such as AKT serine/threonine kinase 1 (AKT1), mitogen-activated protein kinase 3 (MAPK3), Sirtuin-1 (SIRT1) and proto-oncogene tyrosine-protein kinase Src (SRC), as well as biological processes such as cell proliferation, inflammatory response, and redox balance. The present study systematically elucidates the mechanisms by which resveratrol alleviates PH and provides a new perspective on drug research for this disease.

Design and Discovery of N-(3-(2-(2-Hydroxyethoxy)-6-morpholinopyridin-4-yl)-4-methylphenyl)-2-(trifluoromethyl)isonicotinamide, a Selective, Efficacious, and Well-Tolerated RAF Inhibitor Targeting RAS Mutant Cancers: The Path to the Clinic.

Direct pharmacological inhibition of RAS has remained elusive, and efforts to target CRAF have been challenging due to the complex nature of RAF signaling, downstream of activated RAS, and the poor overall kinase selectivity of putative RAF inhibitors. Herein, we describe 15 (LXH254, Aversa, R.; et al. Int. Patent WO2014151616A1, 2014), a selective B/C RAF inhibitor, which was developed by focusing on drug-like properties and selectivity. Our previous tool compound, 3 (RAF709; Nishiguchi, G. A.; et al. J. Med. Chem. 2017, 60, 4969), was potent, selective, efficacious, and well tolerated in preclinical models, but the high human intrinsic clearance precluded further development and prompted further investigation of close analogues. A structure-based approach led to a pyridine series with an alcohol side chain that could interact with the DFG loop and significantly improved cell potency. Further mitigation of human intrinsic clearance and time-dependent inhibition led to the discovery of 15. Due to its excellent properties, it was progressed through toxicology studies and is being tested in phase 1 clinical trials.

An update on Drug Repurposing: Re-written saga of the drug's fate.

Drug repurposing is an unconventional drug discovery approach to explore new therapeutic benefits of existing, shelved and the drugs in clinical trials. This approach is currently emerging to overcome the bottleneck constraints faced during traditional drug discovery in grounds of financial support, timeline and resources. In this direction, several efforts were made for the construction of stratagems based on bioinformatics and computational tools to intensify the repurposing process off-late. Further, advanced research has succeeded in widening its boundaries in identification of gene targets and subsequent molecular interactions of the drugs depending on available omics data. Currently, the advent of data repositories like Connectivity Map (CMap), Library Integrated Network based Cellular Signatures (LINCS), Genome Wide Association Studies (GWAS), Side Effect Resource (SIDER), and Directionality Map (DMAP) has bestowed great oppurtunity to the researchers in improving their drug repurposing research exponentially. On the otherhand, in silico approaches like pharmacophore modelling and docking techniques circumvent the routine tedious in vitro and in vivo techniques involved in former screening phases of the drugs and disease specific targets. This review elaborates on currently designed contemporary tools, databases and strategies with relevant case studies.

In-Silico Screening of Ligand Based Pharmacophore, Database Mining and Molecular Docking on 2, 5-Diaminopyrimidines Azapurines as Potential Inhibitors of Glycogen Synthase Kinase-3ß.

BACKGROUND: Glycogen synthase kinase-3ß plays a significant role in the regulation of various pathological pathways relating to the Central Nervous System (CNS). Dysregulation of Glycogen synthase kinase 3 (GSK-3) activity gives rise to numerous neuroinflammation and neurodegenerative related disorders that affect the whole central nervous system. OBJECTIVE: By the sequential application of in-silico tools, efforts have been attempted to design the novel GSK-3ß inhibitors. METHOD: Owing to the potential role of GSK-3ß in nervous disorders, we have attempted to develop the quantitative four featured pharmacophore model comprising two Hydrogen Bond Acceptors (HBA), one Ring Aromatic (RA), and one Hydrophobe (HY), which were further affirmed by costfunction analysis, rm2 matrices, internal and external test set validation and Guner-Henry (GH) scoring analysis. Validated pharmacophoric model was used for virtual screening and out of 345 compounds, two potential virtual hits were finalized that were on the basis of fit value, estimated activity and Lipinski's violation. The chosen compounds were subjected to dock within the active site of GSK-3ß. RESULT: Four essential features, i.e., two Hydrogen Bond Acceptors (HBA), one Ring Aromatic (RA), and one Hydrophobe (HY), were subjected to build the pharmacophoric model and showed good correlation coefficient, RMSD and cost difference values of 0.91, 0.94 and 42.9 respectively and further model was validated employing cost-function analysis, rm2-matrices, internal and external test set prediction with r2 value of 0.77 and 0.84. Docked conformations showed potential interactions in between the features of the identified hits (NCI 4296, NCI 3034) and the amino acids present in the active site. CONCLUSION: In line with the overhead discussion, and through our stepwise computational approaches, we have identified novel, structurally diverse glycogen synthase kinase inhibitors.

Evolving Strategies for the Treatment of T-Cell Lymphoma: A Systematic Review and Recent Patents.

OBJECTIVE: Mature T-cell lymphomas are a heterogeneous group of T-cell malignancies with a poor outcome. The discovery of new molecular biomarkers has led to the emergence of new drugs in recent years that target various signaling pathways. METHODS: We examined all pertinent published patents through 2015 that analyzed novel methods for the diagnosis and treatment of T cell lymphoma, as well as related published and unpublished studies. Selection criteria were established before data collection. An exhaustive literature search was performed using MEDLINE and Science Direct databases. The search criteria were T-cell lymphoma, diagnosis, and treatment. RESULTS: Recent papers have identified recurrent epigenetic factor mutations in RHOA and FYN kinase in PTCL allowing new perspectives for epigenetic-based therapy, molecular classification model using CD28, ABCA5 transporter, coiled-coil domain-containing protein 3, and angiogenic factor SMOC2 biomarkers for differentiating forms of lymphomas, as well as expression of receptors forTNFR-1, TNFR-2, and IL12p40/70 in CTCL. New therapeutic targets have been reported such as MicroRNAs - 155 inhibitors and synthetic Toll-Like Receptor 7/8 agonists for treating CTCL, Anti CTLA-4 antibodies, anti- Killer cell immunoglobulin-like receptors 3DL2 and NK-p46 (NCR receptors) antibodies for treating PTCL, Cd1d antagonist-restricted gamma/delta-T cell lymphomas, antiEZH2, novel antihistone deacetylase, and NK cells engineered therapy. In the transplantation setting, the objective was to eradicate overcoming of the residual disease immunity and to induce an immune tolerance by anti-third part cells with a central memory T-lymphocyte phenotype. CONCLUSION: Therapeutic strategies based on a better molecular characterization of various histological types are certain to be used in the future.

Computational Approaches to Studying Voltage-Gated Ion Channel Modulation by General Anesthetics.

Voltage-gated ion channels (VGICs) are responsible for the propagation of electrical signals in excitable cells. Small-molecule modulation of VGICs affects transmission of action potentials in neurons and thus can modulate the activity of the central nervous system. For this reason, VGICs are considered key players in the medically induced state of general anesthesia. Consistently, VGICs have been shown to respond to several general anesthetics. However, in spite of extensive electrophysiological characterizations, modulation of VGICs by anesthetics is still only partially understood. Among the challenging aspects are the presence of multiple binding sites and the observation of paradoxical effects, i.e., evidence, for the same channel, of inhibition and potentiation. In this context, molecular simulations emerged in the recent past as the tool of choice to complement electrophysiology studies with a microscopic picture of binding and allosteric regulation. In this chapter, we describe the most effective computational techniques to study VGIC modulation by general anesthetics. We start by reviewing the VGIC conduction cycle, the corresponding set of channel conformations, and the approaches used to model them. We then review the most successful strategies to identify binding sites and estimate binding affinities.

Molecular Modeling Studies of Novel Fluoroquinolone Molecules.

BACKGROUND: Fluoroquinolones have been the centre of considerable scientific and clinical interest due to their broad spectrum pharmacological activities. Pefloxacin is an analogue of norfloxacin, which is a 3rd generation of fluoroquinolone antibiotic similar to ciprofloxacin. Pefloxacin is used to treat a variety of bacterial infections like respiratory tract, ear, nose and throat (ENT) infections, skin infections, and urinary tract infections. Hydrazone as a pharmacophore unit that attracts the medicinal chemists because of structure activity relationship (SAR) studies of fluoroquinolones especially the functionality at C-3 position. Consequently, recognition and development of potential ligands specifically for a protein target forms the primary goal in drug discovery process. Among the different theoretical approaches available, Gold and Glide are the molecular docking methods which find application protein ligand studies. In the current study, the DNA gyrase of Staphylococcus aureus has been used as the target protein to understand their possible interactions. METHODS: The crystal structure of DNA gyrase (topoisomerase II) was downloaded from the Protein Data Bank (PDB ID: 2XCS, 3FOE) and molecular docking studies were performed using the docking programs like Gold 3.2 (Genetic Algorithm for Ligand Docking), Glide 5.0 (Grid Based Ligand Docking with Energetic). Melting points were uncorrected and determined in open capillary tubes in a melting point apparatus. TLC was performed on silica gel-G and spotting was done using iodine/ KMnO4 staining or UV-light. The following experimental procedures are representive of the general procedures used to synthesize all compounds. RESULTS: The docking experiments of the title compounds with 2.1 Å crystal structure of DNA gyrase 2XCS, 3FOE using Gold 3.2 and Glide 5.0 is carried out to understand the binding interactions of the novel ligands with the protein, contributing for antibacterial activity. The compounds in general exhibited good binding interactions like H-bonding interaction and π-π interactions which stabilize the protein-ligand complexes and responsible for good fitness scores in both the protocols. CONCLUSION: In summary, a new series of novel pefloxacin hydrazones 5a-5n were studied for their interactions with Staphylococcus aureus DNA gyrase protein by Glide 5.0 and Gold 3.2 molecular docking protocols [PDB IDS: 2XCS, 3FOE]. Among the tested molecules, compound 5g exhibited a good Glide score value of - 7.73 and Glide energy -51.24 with emodel value of -66.16. The nice docking scores of 5g, 5a, 8h, 5m and 5b revealed that these compounds are well accommodated on the active site residues of DNA gyrase enzyme. From the docking study, we have explored the probable binding mode and the binding pattern of compounds 5f, 5l, 5h, 5d, and 5n showed that they strongly interact with in the active site of Staphylococcus aureus of DNA gyrase enzyme. From screening results it is found that compounds having aromatic ring substituted with electron releasing groups are showing potent docking scores and exhibited better fitness than reference compounds CPF and CA4. An efficient combination of molecular modeling and biological activity provided an insight into QSAR guide lines that could aid in further development and optimization of the pefloxacin derivatives.

Homology Modeling and Molecular Docking Studies of Bacillomycin and Iturin Synthetases with Novel Ligands for the Production of Therapeutic Lipopeptides.

BACKGROUND: Lipopeptide synthetases play an important role in the production of lipopeptides. Lipopeptides are molecules made up of peptides and fatty acid moieties and have shown to have a broad range of antimicrobial activity. As infectious diseases have caused severe health problems mainly resulting from the development of antibiotic resistant strains of disease causing microorganisms there is a need of alternatives to antibiotics. The lipopeptide synthetase of the corresponding lipopeptides can be used as template to design these as drugs using computational techniques. OBJECTIVE: The objective of this study was homology modeling and molecular docking of two lipopeptide synthetases, bacillomycin D synthetase and iturin A synthetase, with their ligands as a means of drug design. METHOD: Schrödinger software was used for homology modeling and molecular docking. RESULTS: After the identification of ligands, molecular docking of these ligands with the lipopeptide (bacillomycin and iturin) synthetases was performed. The docking was tested on the parameters of docking score and glide energy. 5 out of 21 ligands were found to dock with bacillomycin D synthetase whereas 8 out of 20 ligands docked with the iturin A synthetase. CONCLUSION: The knowledge of the docking sites and docking characteristics of the lipopeptide synthetases mentioned in the paper with the ligands can provide advantages of high speed and reliability, reduced costs on chemicals and experiments and the ethical issues concerned with the use of animal models for screening of drug toxicity.

Poly-glutamic dendrimer-based conjugates for cancer vaccination - a computational design for targeted delivery of antigens.

Computational techniques are useful to predict interaction models and molecular properties for the design of drug delivery systems, such as dendrimers. This work evaluated the impact of surface modifications of mannosamine-conjugated multifunctional poly(glutamic acid) (PG)-dendrimers as nanocarriers of the tumour associated antigens (TAA) MART-1, gp100:44 and gp100:209. Molecular dynamics simulations and docking studies were performed. Nitrobenzoxadiazole (NBD)-PG-G4-dendrimer displayed 64 carboxylic groups, however, the Frontier Molecular Orbital Theory study evidenced that only 32 of those were available to form covalent bonds. When the number of mannosamines conjugated to dendrimer was increased from 16 to 32, the dendrimer interacted with the receptor with higher affinity. However, 16 mannosamines-NBD-PG-G4-dendrimer was chosen to conjugate TAA for added functionality as no carboxylic end groups were available for further conjugation in the 32 mannosamines-dendrimer. Docking results showed that the majority of TAA-conjugated NBD-PG-G4-dendrimer demonstrated a favourable interaction with mannosamine binding site on mannose receptor, thus constituting a promising tool for TAA targeted delivery. Our in silico approach effectively narrows down the selection of the best candidates for the synthesis of functionalised PG-dendrimers with desired functionalities. These results will significantly reduce the time and efforts required to experimentally synthesise modified dendrimers for optimal antigen delivery.

Design strategies of oxidosqualene cyclase inhibitors: Targeting the sterol biosynthetic pathway.

Targeting the sterol biosynthesis pathway has been explored for the development of new bioactive compounds. Among the enzymes of this pathway, oxidosqualene cyclase (OSC) which catalyzes lanosterol cyclization from 2,3-oxidosqualene has emerged as an attractive target. In this work, we reviewed the most promising OSC inhibitors from different organisms and their potential for the development of new antiparasitic, antifungal, hypocholesterolemic and anticancer drugs. Different strategies have been adopted for the discovery of new OSC inhibitors, such as structural modifications of the natural substrate or the reaction intermediates, the use of the enzyme's structural information to discover compounds with novel chemotypes, modifications of known inhibitors and the use of molecular modeling techniques such as docking and virtual screening to search for new inhibitors. This review brings new perspectives on structural insights of OSC from different organisms and reveals the broad structural diversity of OSC inhibitors which may help evidence lead compounds for further investigations with various therapeutic applications.

Virtual screening applications in short-chain dehydrogenase/reductase research.

Several members of the short-chain dehydrogenase/reductase (SDR) enzyme family play fundamental roles in adrenal and gonadal steroidogenesis as well as in the metabolism of steroids, oxysterols, bile acids, and retinoids in peripheral tissues, thereby controlling the local activation of their cognate receptors. Some of these SDRs are considered as promising therapeutic targets, for example to treat estrogen-/androgen-dependent and corticosteroid-related diseases, whereas others are considered as anti-targets as their inhibition may lead to disturbances of endocrine functions, thereby contributing to the development and progression of diseases. Nevertheless, the physiological functions of about half of all SDR members are still unknown. In this respect, in silico tools are highly valuable in drug discovery for lead molecule identification, in toxicology screenings to facilitate the identification of hazardous chemicals, and in fundamental research for substrate identification and enzyme characterization. Regarding SDRs, computational methods have been employed for a variety of applications including drug discovery, enzyme characterization and substrate identification, as well as identification of potential endocrine disrupting chemicals (EDC). This review provides an overview of the efforts undertaken in the field of virtual screening supported identification of bioactive molecules in SDR research. In addition, it presents an outlook and addresses the opportunities and limitations of computational modeling and in vitro validation methods.

Computer-Aided Drug Discovery from Marine Compounds: Identification of the Three-Dimensional Structural Features Responsible for Antimalarial Activity.

An integrated computational approach, based on molecular dynamics/mechanics, semi-empirical, and DFT calculations as well as dynamic docking studies, has been employed to gain insight into the mechanism of action of new antimalarial agents characterized by the scaffold of the marine compounds plakortin and aplidinone. The results of this approach show that these molecules, after interaction with Fe(II), likely coming from the heme molecule, give rise to the formation of radical species, that should represent the toxic intermediates responsible for subsequent reactions leading to plasmodium death. The three-dimensional structural requirements necessary for the activity of these new classes of antimalarial agents have been identified and discussed throughout the chapter.

Improvements, trends, and new ideas in molecular docking: 2012-2013 in review.

Molecular docking is a computational method for predicting the placement of ligands in the binding sites of their receptor(s). In this review, we discuss the methodological developments that occurred in the docking field in 2012 and 2013, with a particular focus on the more difficult aspects of this computational discipline. The main challenges and therefore focal points for developments in docking, covered in this review, are receptor flexibility, solvation, scoring, and virtual screening. We specifically deal with such aspects of molecular docking and its applications as selection criteria for constructing receptor ensembles, target dependence of scoring functions, integration of higher-level theory into scoring, implicit and explicit handling of solvation in the binding process, and comparison and evaluation of docking and scoring methods.

Métodos computacionales en toxicología predictiva: aplicación a la reducción de ensayos con animales en el contexto de la legislación comunitaria REACH / Computational methods in predictive toxicology: application to the reduction of animal tests in the context of the EU REACH regulation

Los métodos de química informática y modelado molecular han sido utilizados desde hace décadas para la selección y optimización de nuevos compuestos con propiedades terapéuticas. Su aplicación en toxicología predictiva es más reciente, y dadas las nuevas necesidades regulatorias impuestas por la normativa europea REACH, estas técnicas gozan actualmente de un interés creciente. En efecto, el reglamento REACH supone a priori la necesidad de una cantidad ingente de ensayos con animales para demostrar la seguridad de los nuevos compuestos químicos sometidos a registro, ensayos que pueden reducirse mediante el uso de métodos alternativos como los estudios in vitro e in silico, siempre que cumplan ciertas condiciones específicas que garanticen su calidad y eficacia predictiva. La toxicología computacional es pues una subdisciplina de la toxicología que tiene como objetivo utilizar las matemáticas, la estadística, el modelado químico y las herramientas informáticas para predecir los efectos tóxicos de las sustancias químicas en la salud humana y/o el medio ambiente, y adicionalmente comprender mejor los mecanismos por los que un producto químico determinado induce daño. En esta revisión resumimos el estado del arte de los diferentes métodos existentes en materia de toxicología computacional, citamos las bases de datos y programas más adecuados para la generación de predicciones robustas y fiables, y se discuten sus limitaciones y el grado de aceptación en el ámbito normativo (AU)

Molecular modeling and chemoinformatics have been used for decades for the selection and optimization of new compounds with therapeutic properties. The application of these techniques in predictive toxicology is more recent, and they are experiencing an increasingly interest because of the new legal requirements imposed by the EU REACH regulation. Indeed, a large amount of animal testing is needed under REACH to demonstrate the safety of new chemical entities subjected to registration, and these assays can be significantly reduced by using alternative in vitro and in silico methods, provided they meet specific conditions to ensure their quality and predictive power. Computational toxicology is as a subdiscipline of toxicology that aims to use mathematics, statistics, chemistry and computer modeling tools to predict the toxic effects of chemicals on human health and/or environment. Additionally, computation studies can help also to better understand the mechanisms by which a given chemical induces harm. In this review we summarize the state of art of the main in silico methods, the toxicological databases and computer programs more suitable for the generation of robust and reliable predictions will be listed, and the limitations and acceptability of computational toxicology will be discussed in the context of the UE regulation (AU)

Latest developments in molecular docking: 2010-2011 in review.

The aim of docking is to accurately predict the structure of a ligand within the constraints of a receptor binding site and to correctly estimate the strength of binding. We discuss, in detail, methodological developments that occurred in the docking field in 2010 and 2011, with a particular focus on the more difficult, and sometimes controversial, aspects of this promising computational discipline. The main developments in docking in this period, covered in this review, are receptor flexibility, solvation, fragment docking, postprocessing, docking into homology models, and docking comparisons. Several new, or at least newly invigorated, advances occurred in areas such as nonlinear scoring functions, using machine-learning approaches. This review is strongly focused on docking advances in the context of drug design, specifically in virtual screening and fragment-based drug design. Where appropriate, we refer readers to exemplar case studies.