Computer-assisted Drug Design Research Articles

Virtual Screening in the Cloud: How Big Is Big Enough?

Virtual screening is a standard tool in Computer-Assisted Drug Design (CADD). Early in a project, it is typical to use ligand-based similarity search methods to find suitable hit molecules. However, the number of compounds which can be screened and the time required are usually limited by computational resources. We describe here a high-throughput virtual screening project using 3D similarity (FastROCS) and automated evaluation workflows on Orion, a cloud computing platform. Cloud resources make this approach fully scalable and flexible, allowing the generation and search of billions of virtual molecules, and give access to an explicit 3D virtual chemistry space not available before. We discuss the impact of the size of the search space with respect to finding novel chemical hits and the size of the required hit list, as well as computational and economical aspects of resource scaling.

Rationally Designed, Conformationally Constrained Inverse Agonists of RORγt-Identification of a Potent, Selective Series with Biologic-Like in Vivo Efficacy.

RORγt is an important nuclear receptor that regulates the production of several pro-inflammatory cytokines such as IL-17 and IL-22. As a result, RORγt has been identified as a potential target for the treatment of various immunological disorders such as psoriasis, psoriatic arthritis, and inflammatory bowel diseases. Structure and computer-assisted drug design led to the identification of a novel series of tricyclic RORγt inverse agonists with significantly improved in vitro activity in the reporter (Gal4) and human whole blood assays compared to our previous chemotype. Through careful structure activity relationship, several potent and selective RORγt inverse agonists have been identified. Pharmacokinetic studies allowed the identification of the lead molecule 32 with a low peak-to-trough ratio. This molecule showed excellent activity in an IL-2/IL-23-induced mouse pharmacodynamic study and demonstrated biologic-like efficacy in an IL-23-induced preclinical model of psoriasis.

Epigenetic re-wiring of breast cancer by pharmacological targeting of C-terminal binding protein

The C-terminal binding protein (CtBP) is an NADH-dependent dimeric family of nuclear proteins that scaffold interactions between transcriptional regulators and chromatin-modifying complexes. Its association with poor survival in several cancers implicates CtBP as a promising target for pharmacological intervention. We employed computer-assisted drug design to search for CtBP inhibitors, using quantitative structure-activity relationship (QSAR) modeling and docking. Functional screening of these drugs identified 4 compounds with low toxicity and high water solubility. Micro molar concentrations of these CtBP inhibitors produces significant de-repression of epigenetically silenced pro-epithelial genes, preferentially in the triple-negative breast cancer cell line MDA-MB-231. This epigenetic reprogramming occurs through eviction of CtBP from gene promoters; disrupted recruitment of chromatin-modifying protein complexes containing LSD1, and HDAC1; and re-wiring of activating histone marks at targeted genes. In functional assays, CtBP inhibition disrupts CtBP dimerization, decreases cell migration, abolishes cellular invasion, and improves DNA repair. Combinatorial use of CtBP inhibitors with the LSD1 inhibitor pargyline has synergistic influence. Finally, integrated correlation of gene expression in breast cancer patients with nuclear levels of CtBP1 and LSD1, reveals new potential therapeutic vulnerabilities. These findings implicate a broad role for this class of compounds in strategies for epigenetically targeted therapeutic intervention.

Progress in molecular docking

BackgroundIn recent years, since the molecular docking technique can greatly improve the efficiency and reduce the research cost, it has become a key tool in computer‐assisted drug design to predict the binding affinity and analyze the interactive mode.ResultsThis study introduces the key principles, procedures and the widely‐used applications for molecular docking. Also, it compares the commonly used docking applications and recommends which research areas are suitable for them. Lastly, it briefly reviews the latest progress in molecular docking such as the integrated method and deep learning.ConclusionLimited to the incomplete molecular structure and the shortcomings of the scoring function, current docking applications are not accurate enough to predict the binding affinity. However, we could improve the current molecular docking technique by integrating the big biological data into scoring function.

Computer Assisted Drug Design of Larotrectinib for treatment of Cancer: A Combined Density Functional and Molecular Docking Study

This article talks about hypothesis behind the most critical strategies and later effective uses of halogen-coordinated Larotrectinib, ligand-based techniques utilize just ligand data for foreseeing action contingent upon its similitude/uniqueness to recently known dynamic ligands. We audit generally utilized ligand-based techniques, for example, ligand-based pharmacophores, atomic descriptors, and quantitative structure-action connections. What's more, vital instruments, for example, target/ligand information bases, homology displaying, ligand ADMET and so on. And fundamental for fruitful usage of different PC supported medication revelation/structure strategies in best simple of Larotrectinib disclosure are talked about. At long last, computational strategies for poisonous quality expectation and improvement for positive physiologic properties are talked about with fruitful lead for Larotrectinib from writing. The helpful capability of Larotrectinib has been examined widely and the dynamic mixes of Larotrctinib are appeared to be engaged with adjusting different physiological reactions. In addition this article will audit the structure of arrangement of halogen-coordinated tinosporides before outline on how the atoms apply their capacities by means of cooperations with different flag transducer and activator proteins of interpretation which were planned by homology demonstrating. Procedures for CADD change contingent upon the degree of basic and other data accessible in regards to the objective (chemical/receptor) and the ligands. The procedure by which another Larotrectinib item is conveyed to showcase arrange is alluded to by various names most normally as the improvement chain and comprises of various unmistakable stages. Keywords : CADD; ADMET; Molecular Modeling; Larotrectinib. DOI : 10.7176/JNSR/9-9-08 Publication date :May 31 st 2019

Methodologies Related to Computational Models in View of Developing Anti-Alzheimer Drugs: An Overview.

Since the last two decades, there has been more focus on the development strategies related to Anti-Alzheimer's drug research. This may be attributed to the fact that most of the Alzheimer's cases are still mostly unknown except for a few cases, where genetic differences have been identified. With the progress of the disease, the symptoms involve intellectual deterioration, memory impairment, abnormal personality and behavioural patterns, confusion, aggression, mood swings, irritability Current therapies available for this disease give only symptomatic relief and do not focus on manipulations of biololecular processes. Nearly all the therapies to treat Alzheimer's disease, target to change the amyloid cascade which is considered to be important in AD pathogenesis. New drug regimens are not able to keep pace with the ever-increasing understanding about dementia at the molecular level. Looking into these aggravated problems, we thought to put forth molecular modeling as a drug discovery approach for developing novel drugs to treat Alzheimer disease. The disease is incurable and it gets worst as it advances and finally causes death. Due to this, the design of drugs to treat this disease has become an utmost priority for research. One of the most important emerging technologies applied for this has been Computer-assisted drug design (CADD). It is a research tool that employs large-scale computing strategies in an attempt to develop a model receptor site which can be used for designing of an anti-Alzheimer drug. Various models of amyloid-based calcium channels have been computationally optimized. Docking and De novo evolution are used to design the compounds. They are further subjected to absorption, distribution, metabolism, excretion and toxicity (ADMET) studies to finally bring about active compounds that are able to cross BBB. Many novel compounds have been designed which might be promising ones for the treatment of AD. The present review describes the research carried out on various heterocyclic scaffolds that can serve as lead compounds to design Anti-Alzheimer's drugs in the future. The molecular modeling methods can thus become a better alternative for the discovery of newer Anti- Alzheimer agents. This methodology is extremely useful to design drugs in minimum time with enhanced activity keeping balanced ethical considerations. Thus, the researchers are opting for this improved process over the conventional methods hoping to achieve a sure shot way out for the sufferings of people affected by Alzheimer besides other diseases.

Selection and evaluation of quality markers from Yinlan capsule and its LXRα-mediated therapy for hyperlipidemia

The selection of active compounds for the quality evaluation of traditional Chinese medicine (TCM), specifically complex formulas, remains a challenge for researchers, as components selected as indexes usually have no clear relation with the therapeutic effects of interest. As a suggested resolution, quality control markers (Q-markers) showed good perspective for discriminating numerous compounds found for specific efficacies. In the presented study, the components of the Yinlan (YL) capsule, a TCM patent formula comprising four ingredients, were evaluated and selected for their lipid regulatory effects using principles for Q-marker selection. The mechanism of TCM therapeutic effects involves several pathways and targets that combine to become an integrated action in the body. Therefore, it is assumed that specific compounds in YL should have good affinity for related targets and obvious effects (both up- and downregulating). Thus, a series of experiments, including cytobiology, animal-based pharmacodynamics, computer-assisted drug design, conventional content determination and pharmacokinetics, would be helpful for the selection and final confirmation of Q-markers. The capsule was first administered to Wistar mice fed a high-fat diet and tested for their triglycerides (TG) and total cholesterol (TC) values to evaluate the effectiveness of YL. Then, liver tissue was extracted for gene expression. According to the results, the compounds in YL with good affiliation were selected and determined using UHPLC-MS-MS, and those with adequate results in the capsule were chosen as Q-marker candidates. Finally, pharmacokinetics research was performed; the candidates with desirable metabolite and bioavailability parameters were confirmed as Q-markers of YL. YL capsule was capable of lowering TG and TC levels. For target selection, the expression of LXR mRNA increased significantly at all three tested dosages. Downstream genes, such as LCAT, CYP7A1, and ABCA1, and intestinal FXR mRNA also showed significant increases in expression. For screening of the Q-marker candidates, 5 compounds were selected according to abovementioned results. The pharmacokinetics research demonstrated that the rats exploited lupeol and ginsenoside Rb3 in a desirable pattern with adequate bioavailability, which confirmed their roles as lipid regulatory Q-markers. The YL capsule was demonstrated to have obvious lipid regulatory effects, which are mainly exerted by targeting LXR and its related pathway. Lupeol and ginsenoside Rb3 were validated as Q-markers that represent the anti-hyperlipidemia activity of the capsule.

Molecular Docking of New Active Compounds Towards the Acetylcholinesterase Enzyme

Molecular docking is a key instrument in structural molecular biology and computer-assisted drug design. The objective of ligand-protein docking is to expect the main binding mode(s) of a ligand with a protein of known three-dimensional structure. Effective docking methods search high-dimensional spaces effectively and finding a scoring function that correctly ranks candidate dockings (Morris et al., 2008). In this study molecular docking study was performed for 54 Acetylcholinesterase Inhibitors compounds.

In Silico Approaches for TRP Channel Modulation.

The implication of several TRP ion channels (e.g., TRPV1) in diverse physiological and pathological processes has signaled them as pivotal drug targets. Consequently, the identification of selective and potent ligands for these channels is of great interest in pharmacology and biomedicine. However, a major challenge in the design of modulators is ensuring the specificity for their intended targets. In recent years, the emergence of high-resolution structures of ion channels facilitates the computer-assisted drug design at molecular levels. Here we describe some computational methods and general protocols to discover channel modulators, including homology modelling, docking and virtual screening, and structure-based peptide design.

Moracin derivatives from Morus Radix as dual BACE1 and cholinesterase inhibitors with antioxidant and anti-glycation capacities

AimsMorus, a member of the family Moraceae and commonly known as the mulberry, comprises a pharmaceutically important plant group whose major constituents are the moracins. Moracin derivatives have received great attention because they exhibit a diverse range of biological functionalities. However, no studies have considered the anti-Alzheimer's disease (AD) and anti-glycation potential of moracin derivatives. Main methodsWe designed the current study to explore the anti-AD activity of moracin derivatives via in vitro inhibition of BACE1 and cholinesterase, their antioxidant activity via scavenging ONOO− and ABTS+ radicals, and their anti-diabetic activity through inhibition of advanced glycation end-products (AGEs) formation. Moreover, to define the mechanism of action of moracin derivatives in depth, we performed in silico molecular modeling using a computer-assisted drug design and modeling program. Key findingsAmong the four Morus-derived moracins tested, moracin S, which has a prenyl moiety in the 2-aryl benzofuran scaffold, possessed the highest BACE1 inhibitory activity. It also, in a dose-dependent fashion, decreased ONOO−-mediated bovine serum albumin (BSA) nitration and formation of AGEs and amyloid cross-β structures in the glycated BSA system, and it showed notable radical scavenging activity. In addition, enzyme kinetic and molecular docking studies demonstrated that moracin S is a potent, competitive BACE1 inhibitor that could interact with key catalytic aspartyl residues. SignificanceThe prenyl moiety in the 2-aryl benzofuran structure plays a crucial role in inhibition of BACE1. These in vitro and in silico results provide valuable information for the design of anti-AD drugs.

Advances in the Application and Development of Non-Linear Global Optimization Techniques in Computational Structural Biology

Computational structural biology is an important, growing research area that includes diverse problems, such as protein structure prediction, computational molecular assembly, and computer-assisted drug design problems, that include protein-ligand binding, protein-protein, protein-RNA, and protein-DNA docking, as well as computer assisted wet-laboratory structure resolving problems, like registration, reconstruction, and refinement. The focus of this special section is on the application of non-linear optimization to problems in structural biology, thus turning the spotlight on a growing area of interdisciplinary research that brings together expertise in meta-heuristic optimization and computational structural biology. The five articles included in this section provide a glimpse of the diversity of work in this area, highlighting the adaptation and use of a variety of state-of-the-art meta-heuristics for a range of problems linked to the wider area of structural biology.

Development and Uses of Offline and Web-Searchable Metabolism Databases - The Case of Benzo[a]pyrene

The present work describes development of offline and web-searchable metabolism databases for drugs, other chemicals, and physiological compounds using human and model species, prompted by the large amount of data published after year 1990. The intent was to provide a rapid and accurate approach to published data to be applied both in science and to assist therapy. Searches for the data were done using the Pub Med database, accessing the Medline database of references and abstracts. In addition, data presented at scientific conferences (e.g., ISSX conferences) are included covering the publishing period beginning with the year 1976. Application of the data is illustrated by the properties of benzo[a]pyrene (B[a]P) and its metabolites. Analysis show higher activity of P450 1A1 for activation of the (-)- isomer of trans-B[a]P-7,8-diol, while P4501B1 exerts higher activity for the (+)- isomer. P450 1A2 showed equally low activity in the metabolic activation of both isomers. The information collected in the databases is applicable in prediction of metabolic drug-drug and/or drug-chemical interactions in clinical and environmental studies. The data on the metabolism of searched compound (exemplified by benzo[a]pyrene and its metabolites) also indicate toxicological properties of the products of specific reactions. The offline and web-searchable databases had wide range of applications (e.g. computer assisted drug design and development, optimization of clinical therapy, toxicological applications) and adjustment in everyday life styles.

Open source software tools for computer aided drug design

Computer-aided drug design (CADD) has revolutionized the drug discovery arena and it has reduced the costs associated with finding novel compounds which are having pharmaceutical importance. In CADD, the scientists use the computer software to discover biological active compounds. Molecular docking and energy minimization tools are essential components of structure based drug design. It is a significant tool in structural molecular biology and computer-assisted drug design. It reduces the laboratory workload of the end user and allows researchers to restrict their docking studies to the smallest and the most representative set of macromolecules and small molecules possible. This greatly enhances the productivity of researchers. Energy minimization is an important criterion for selecting a potential 3D molecule. In modeled structures, the 3D structure is affected is due to steric clashes. These clashes happen in a protein structure due to the overlap of non bonding atoms and with the assistance of energy minimization, steric clashes can be eradicated. The open software’s and databases provides a platform for scientists and scholars to carry out their research work in a better way. The docking tools are discussed in this review cover protein-ligand, protein-peptide as well as protein-nucleic acid docking. The tools described include AutoDock 4 and Vina, UCSF DOCK, FLIPDock, EADock, HADDOCK 2.2, SwissDock, PatchDock and ClusPro. In addition to the docking tools, energy minimization tools such as YASARA minimization server, KoBaMIN server and 3D refine server have also been discussed. This mini-review concentrates on open software tools which are free of cost and can be easily downloaded in the computers that are useful for CADD.
 Keywords: Molecular docking; Energy minimization; Structure refinement; Drug design; CADD

Target-based drug discovery through inversion of quantitative structure-drug-property relationships and molecular simulation: CA IX-sulphonamide complexes

In this work, a target-based drug screening method is proposed exploiting the synergy effect of ligand-based and structure-based computer-assisted drug design. The new method provides great flexibility in drug design and drug candidates with considerably lower risk in an efficient manner. As a model system, 45 sulphonamides (33 training, 12 testing ligands) in complex with carbonic anhydrase IX were used for development of quantitative structure-activity-lipophilicity (property)-relationships (QSPRs). For each ligand, nearly 5,000 molecular descriptors were calculated, while lipophilicity (logkw) and inhibitory activity (logKi) were used as drug properties. Genetic algorithm-partial least squares (GA-PLS) provided a QSPR model with high prediction capability employing only seven molecular descriptors. As a proof-of-concept, optimal drug structure was obtained by inverting the model with respect to reference drug properties. 3509 ligands were ranked accordingly. Top 10 ligands were further validated through molecular docking. Large-scale MD simulations were performed to test the stability of structures of selected ligands obtained through docking complemented with biophysical experiments.

15N-Labelling and structure determination of adamantylated azolo-azines in solution.

Determining the accurate chemical structures of synthesized compounds is essential for biomedical studies and computer-assisted drug design. The unequivocal determination of N-adamantylation or N-arylation site(s) in nitrogen-rich heterocycles, characterized by a low density of hydrogen atoms, using NMR methods at natural isotopic abundance is difficult. In these compounds, the heterocyclic moiety is covalently attached to the carbon atom of the substituent group that has no bound hydrogen atoms, and the connection between the two moieties of the compound cannot always be established via conventional 1H-1H and 1H-13C NMR correlation experiments (COSY and HMBC, respectively) or nuclear Overhauser effect spectroscopy (NOESY or ROESY). The selective incorporation of 15N-labelled atoms in different positions of the heterocyclic core allowed for the use of 1H-15N (JHN) and 13C-15N (JCN) coupling constants for the structure determinations of N-alkylated nitrogen-containing heterocycles in solution. This method was tested on the N-adamantylated products in a series of azolo-1,2,4-triazines and 1,2,4-triazolo[1,5-a]pyrimidine. The syntheses of adamantylated azolo-azines were based on the interactions of azolo-azines and 1-adamatanol in TFA solution. For azolo-1,2,4-triazinones, the formation of mixtures of N-adamantyl derivatives was observed. The JHN and JCN values were measured using amplitude-modulated 1D 1H spin-echo experiments with the selective inversion of the 15N nuclei and line-shape analysis in the 1D 13С spectra acquired with selective 15N decoupling, respectively. Additional spin–spin interactions were detected in the 15N-HMBC spectra. NMR data and DFT (density functional theory) calculations permitted to suggest a possible mechanism of isomerization for the adamantylated products of the azolo-1,2,4-triazines. The combined analysis of the JHN and JCN couplings in 15N-labelled compounds provides an efficient method for the structure determination of N-alkylated azolo-azines even in the case of isomer formation. The isomerization of adamantylated tetrazolo[1,5-b][1,2,4]triazin-7-ones in acidic conditions occurs through the formation of the adamantyl cation.

Chalcone Derivatives: Promising Starting Points for Drug Design.

Medicinal chemists continue to be fascinated by chalcone derivatives because of their simple chemistry, ease of hydrogen atom manipulation, straightforward synthesis, and a variety of promising biological activities. However, chalcones have still not garnered deserved attention, especially considering their high potential as chemical sources for designing and developing new effective drugs. In this review, we summarize current methodological developments towards the design and synthesis of new chalcone derivatives and state-of-the-art medicinal chemistry strategies (bioisosterism, molecular hybridization, and pro-drug design). We also highlight the applicability of computer-assisted drug design approaches to chalcones and address how this may contribute to optimizing research outputs and lead to more successful and cost-effective drug discovery endeavors. Lastly, we present successful examples of the use of chalcones and suggest possible solutions to existing limitations.

Abstract 1156: Epigenetic re-wiring of breast cancer by pharmacological targeting of C-terminal binding protein

Abstract The C-terminal binding protein (CtBP) is a family of dimeric nuclear proteins whose levels are increased in cancers of the colon, ovaries, prostate and breast. Elevated CtBP expression is associated with poor cancer survival and can also distinguish those node negative breast cancer patients who will show worse survival. This implicates CtBP as both a biomarker and a promising candidate for therapeutic intervention. As a dimer, CtBP provides a scaffold that couples multiple different DNA-binding transcriptional regulators with a variety of chromatin modifying protein complexes to alter the epigenetic landscape throughout the nucleus. These properties provide the rationale for pharmacological targeting of CtBP to change epigenetically regulated gene expression in cancer cells. In this study, we employ computer assisted drug design to screen for optimal quantitative structure-activity relationships (QSARs) between small molecules and CtBP to identify 24 potential CtBP inhibitors. Functional screening of these compounds identifies 4 lead compounds with low toxicity and high water solubility. Treatment of breast cancer cells at micro-molar concentrations of these small molecular inhibitors induces significant de-repression of epigenetically silenced pro-epithelial genes in the mesenchymal, triple negative breast cancer cell line, MDA-MB-231. This re-activation is associated with eviction of CtBP from the respective gene promoters, disrupted recruitment of CtBP-chromatin modifying protein complexes, increased deposition of activating epigenetic histone marks, and upregulation of both pro-epithelial gene mRNA and protein expression. In functional assays, CtBP inhibition by these small molecular inhibitors decreases cellular invasion, and improves DNA repair. FRET (Förster resonance energy transfer) analysis demonstrates that CTBP inhibition results in decreased FRET intensity, suggesting that CTBP dimerization is repressed by CTBP inhibition. In addition, pharmacological inhibition of CtBP combines with established epigenetically targeted drugs to synergistically decrease cell migration and potentiate the reactivation of silenced pro-epithelial gene expression in triple negative cancer cells. Finally, CTBP inhibition results in transcriptional repression of MDR1 expression and reduces the population of Doxorubicin resistant cells in the triple negative breast cancer cell lines. These findings implicate the possible use of this class of compounds in strategies for therapeutic intervention that may increase the efficacy and decrease the acquired resistance to targeted therapeutic intervention in breast cancer. Citation Format: Jung S. Byun, Samson Park, Dae IK Yi, Mohamed Kabbout, Genqing Liang, Kevin L. Gardner. Epigenetic re-wiring of breast cancer by pharmacological targeting of C-terminal binding protein [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1156. doi:10.1158/1538-7445.AM2017-1156

Epigenetic re‐programming of breast cancer by pharmacological targeting of C‐terminal binding protein

The C‐terminal binding protein (CtBP) is a family of dimeric nuclear proteins whose levels are increased in cancers of the colon, ovaries, prostate and breast. Elevated CtBP protein expression is associated with poor cancer survival, thus implicating CtBP as both a biomarker and a promising candidate for therapeutic intervention. As a dimer, CtBP provides a scaffold that couples multiple different DNA‐binding transcriptional regulators with a variety of chromatin modifying protein complexes to alter the epigenetic landscape throughout the nucleus. These properties provide the rationale for pharmacological targeting of CtBP to alter or epigenetically change regulated gene expression in cancer cells. In this study, we employ computer assisted drug design to screen for optimal quantitative structure‐activity relationships (QSARs) between small molecules and CtBP to identify 24 potential CtBP inhibitors. Functional screening of these compounds identifies 4 lead compounds with low toxicity and high water solubility. Treatment of breast cancer cells at micro‐molar concentrations of these small molecular inhibitors induces significant de‐repression of epigenetically silenced pro‐epithelial genes in the mesenchymal, triple negative breast cancer cell line, MDA‐MB‐231. This re‐activation is associated with eviction of CtBP from the respective gene promoters, disrupted recruitment of CtBP‐chromatin modifying protein complexes, increased deposition of activating epigenetic histone marks, and upregulation of both pro‐epithelial gene mRNA and protein expression. In functional assays, CtBP inhibition by these small molecular inhibitors decreases cellular invasion, and improves DNA repair.FRET (Förster resonance energy transfer) analysis demonstrates that CTBP inhibition results in decreased FRET intensity, suggesting the CTBP dimerization interaction is repressed by CTBP inhibition. In addition, pharmacological inhibition of CtBP combines with established epigenetically targeted drugs to synergistically decrease cell migration and potentiate the reactivation of silenced pro‐epithelial gene expression in triple negative cancer cells. Finally, CTBP inhibition results in transcriptional repression of MDR1 expression and reduces the population of Doxorubicin resistant cells in triple negative breast cancer cell lines.These findings implicate the possible use of this compound in strategies for therapeutic intervention that may increase the efficacy and decrease the acquired resistance to targeted therapeutic intervention in breast cancer.

Chembench: A Publicly Accessible, Integrated Cheminformatics Portal.

The enormous increase in the amount of publicly available chemical genomics data and the growing emphasis on data sharing and open science mandates that cheminformaticians also make their models publicly available for broad use by the scientific community. Chembench is one of the first publicly accessible, integrated cheminformatics Web portals. It has been extensively used by researchers from different fields for curation, visualization, analysis, and modeling of chemogenomics data. Since its launch in 2008, Chembench has been accessed more than 1 million times by more than 5000 users from a total of 98 countries. We report on the recent updates and improvements that increase the simplicity of use, computational efficiency, accuracy, and accessibility of a broad range of tools and services for computer-assisted drug design and computational toxicology available on Chembench. Chembench remains freely accessible at https://chembench.mml.unc.edu.

Mimetic peptide of ubiquitin-interacting motif of epsin as a cancer therapeutic-perspective in brain tumor therapy through regulating VEGFR2 signaling.

Epsins, endocytic adaptor proteins required for internalization of ubiquitylated receptors, are generally upregulated in human cancers. It has been characterized that mice deficient of epsins in the endothelium inhibit tumor growth by dysregulating vascular endothelial growth factor receptor-2 (VEGFR2) signaling and non-productive tumor angiogenesis. Binding of the epsin ubiquitin (Ub)-interacting motif (UIM) with ubiquitylated VEGFR2 is a critical mechanism for epsin-dependent VEGFR2 endocytosis and degradation, indicative of epsin UIM as a potential therapeutic target. A Computer Assisted Drug Design approach was utilized to create the UIM mimetic peptides for the functional competition of epsin binding sites in ubiquitylated VEGFR2 in vivo. Specifically targeting VEGFR2 in the tumor vasculature, the chemically synthesized chimeric UIM peptide, UPI, causes non-functional tumor angiogenesis, retards tumor growth, and increases survival rates in several tumor models. The authors showed that UPI binds ubiquitylated VEGFR2 to form a supercomplex in an Ub-dependent fashion. Collectively, the UPI targeting strategy offers a potentially novel treatment for cancer patients who are resistant to current anti-angiogenic therapies. In this review, the authors outline the main points of this research specifically as a potential application for glioma tumor therapy.