Discovery of Novel Allosteric Eg5 Inhibitors Through Structure‐Based Virtual Screening

Mitotic kinesin Eg5 is an attractive anticancer drug target. Discovery of Eg5 inhibitors has been focused on targeting the ‘monastrol‐binding site’. However, acquired drug resistance has been reported for such inhibitors. Therefore, identifying new Eg5 inhibitors which function through a different mechanism(s) could complement current drug candidates and improve drug efficacy. In this study, we explored a novel allosteric site of Eg5 and identified new Eg5 inhibitors through structure‐based virtual screening. Experiments with the saturation‐transfer difference NMR demonstrated that the identified Eg5 inhibitor SRI35566 binds directly to Eg5 without involving microtubules. Moreover, SRI35566 and its two analogs significantly induced monopolar spindle formation in colorectal cancer HCT116 cells and suppressed cancer cell viability and colony formation. Together, our findings reveal a new allosteric regulation mechanism of Eg5 and a novel drug targeting site for cancer therapy.     

Virtual design of chemical penetration enhancers for transdermal drug delivery

Traditional drug design is a laborious and expensive process that often challenges the pharmaceutical industries. As a result, researchers have turned to computational methods for computer-assisted molecular design. Recently, genetic and evolutionary algorithms have emerged as efficient methods in solving combinatorial problems associated with computer-aided molecular design. Further, combining genetic algorithms with quantitative structure-property relationship analyses has proved effective in drug design. In this work, we have integrated a new genetic algorithm and nonlinear quantitative structure-property relationship models to develop a reliable virtual screening algorithm for the generation of potential chemical penetration enhancers. The genetic algorithms-quantitative structure-property relationship algorithm has been implemented successfully to identify potential chemical penetration enhancers for transdermal drug delivery of insulin. Validation of the newly identified chemical penetration enhancer molecular structures was conducted through carefully designed experiments, which elucidated the cytotoxicity and permeability of the chemical penetration enhancers.     

Design of chemical libraries for screening

Importance of the field: The ultimate goal of discovery screening is to have a fast and cost-effective strategy to meet the demands of producing high-content lead series with improved prospects for clinical success. While high-throughput screening (HTS) dominates the drug discovery landscape, other processes and technologies have emerged, including high-content screening and fragment-based design to provide alternatives that may be more suitable for certain targets. There has been a growing interest in reducing the number of compounds to be screened to prevent the escalation in the costs, time and resources associated with HTS campaigns. Library design plays a central role in these efforts.

Areas covered in this review: This opinion provides a survey of some recent developments in the diversity based library design process, but within a historical context. In particular, the importance of chemotyping and substructure analysis and the challenges presented by novel lead discovery technologies that require the design of libraries for screening are discussed.

What the reader will gain: Readers will gain an appreciation of some developments in the field of library design and the factors that are driving the development of new library design technologies; specifically, challenges presented for chemoinformatics with the novel screening technologies in diversity based screening and compound filtering.

Take home message: Chemotyping and substrutural analysis are techniques that have been underutilized in the process of library design. However, they offer a direct way to evaluate libraries and have been successfully used to develop predictive methodologies. Tools are available to this end, but the full power of the approach has not been realized yet.     

Discovery of selective protein arginine methyltransferase 5 inhibitors and biological evaluations

Protein arginine methyltransferase 5 (PRMT5) is an important protein arginine methyltransferase that catalyzes the symmetric dimethylation of arginine resides on histones or non‐histone substrate proteins. It has been thought as a promising target for many diseases, particularly cancer. Despite the potential applications of PRMT5 inhibitors in cancer treatment, very few of PRMT5i have been publicly reported. In this investigation, virtual screening and structure–activity relationship studies were carried out to discover novel PRMT5i, which finally led to the identification of a number of new PRMT5i. The most active compound, P5i‐6 , exhibited a considerable inhibitory potency against PRMT5 with an IC₅₀ value of 0.57 μm , and a high selectivity for PRMT5 against other tested PRMTs. It displayed a very good antiviability activity against two colorectal cancer cell lines, HT‐29 and DLD‐1, and one hepatic cancer cell line, HepG2, in a sensitivity assay against 36 different cancer cell lines. Western blot assays indicated that P5i‐6 selectively inhibited the symmetric dimethylations of H4R3 and H3R8 in DLD‐1 cells. Overall, P5i‐6 could be used as a chemical probe to investigate new functions of PRMT5 in biology and also served as a good lead compound for the development of new PRMT5‐targeting therapeutic agents.     

Proposing novel MDM2 inhibitors: Combined physics‐driven high‐throughput virtual screening and in vitro studies

The mouse double minute 2 (MDM2) protein acts as a negative regulator of the p53 tumor suppressor. It directly binds to the N terminus of p53 and promotes p53 ubiquitination and degradation. Since the most common p53‐suppressing mechanisms involve the MDM2, proposing novel inhibitors has been the focus of many in silico and also experimental studies. Thus, here we screened around 500,000 small organic molecules from Enamine database at the binding pocket of this oncogenic target. The screening was achieved systematically with starting from the high‐throughput virtual screening method followed by more sophisticated docking approaches. The initial high number of screened molecules was reduced to 100 hits which then were studied extensively for their therapeutic activity and pharmacokinetic properties using binary QSAR models. The structural and dynamical profiles of the selected molecules at the binding pocket of the target were studied thoroughly by all‐atom molecular dynamics simulations. The free energy of the binding of the hit molecules was estimated by the MM/GBSA method. Based on docking simulations, binary QSAR model results, and free energy calculations, 11 compounds ( E1 – E11 ) were selected for in vitro studies. HUVEC vascular endothelium, colon cancer, and breast cancer cell lines were used for testing the binding affinities of the identified hits and for further cellular effects on human cancer cell. Based on in vitro studies, six compounds ( E1 , E2 , E5 , E6 , E9 , and E11 ) in breast cancer cell lines and six compounds ( E1 , E2 , E5 , E6 , E8 , and E10 ) in colon cancer cell lines were found as active. Our results showed that these compounds inhibit proliferation and lead to apoptosis.     

pso@autodock: a fast flexible molecular docking program based on Swarm intelligence

On the quest of novel therapeutics, molecular docking methods have proven to be valuable tools for screening large libraries of compounds determining the interactions of potential drugs with the target proteins. A widely used docking approach is the simulation of the docking process guided by a binding energy function. On the basis of the molecular docking program autodock, we present pso@autodock as a tool for fast flexible molecular docking. Our novel Particle Swarm Optimization (PSO) algorithms varCPSO and varCPSO-ls are suited for rapid docking of highly flexible ligands. Thus, a ligand with 23 rotatable bonds was successfully docked within as few as 100 000 computing steps (rmsd = 0.87 A), which corresponds to only 10% of the computing time demanded by autodock. In comparison to other docking techniques as gold 3.0, dock 6.0, flexx 2.2.0, autodock 3.05, and sodock, pso@autodock provides the smallest rmsd values for 12 in 37 protein-ligand complexes. The average rmsd value of 1.4 A is significantly lower then those obtained with the other docking programs, which are all above 2.0 A. Thus, pso@autodock is suggested as a highly efficient docking program in terms of speed and quality for flexible peptide-protein docking and virtual screening studies.     

In silico screening strategies for novel inhibitors of parasitic diseases

Introduction: Parasitic diseases are a major global problem causing long-term disability and death, with severe medical and psychological consequences around the world. Despite the prevalence of parasitic disease, the treatment options for many of these illnesses are still inadequate and there is a dire need for new antiparasitic drugs. In silico screening techniques, which are powerful strategies for hit generation, are widely being applied in the design of new ligands for parasitic diseases.

Areas covered: This article analyses the application of ligand- and structure-based virtual screening strategies against a variety of parasitic diseases and discusses the benefits of the integration between computational and experimental approaches toward the discovery of new antiparasitic agents. The analysis is illustrated by recent examples, with emphasis on the strategies reported within the past 2 years.

Expert opinion: Virtual screening techniques are powerful tools commonly used in drug discovery against parasitic diseases, which have provided new opportunities for the identification of several novel compound classes with antiparasitic activity.     

Pharmacophore‐based virtual screening,molecular docking,molecular dynamics simulation,and biological evaluation for the discovery of novel BRD4 inhibitors

Bromodomain is a recognition module in the signal transduction of acetylated histone. BRD4, one of the bromodomain members, is emerging as an attractive therapeutic target for several types of cancer. Therefore, in this study, an attempt has been made to screen compounds from an integrated database containing 5.5 million compounds for BRD4 inhibitors using pharmacophore‐based virtual screening, molecular docking, and molecular dynamics simulations. As a result, two molecules of twelve hits were found to be active in bioactivity tests. Among the molecules, compound 5 exhibited potent anticancer activity, and the IC₅₀ values against human cancer cell lines MV4‐11, A375, and HeLa were 4.2, 7.1, and 11.6 μm , respectively. After that, colony formation assay, cell cycle, apoptosis analysis, wound‐healing migration assay, and Western blotting were carried out to learn the bioactivity of compound 5 .     

The chemical tuning of a weak zinc binding motif for histone deacetylase using electronic effects

The hydroxamic acid moiety is an effective metal-binding warhead for a variety of metalloenzyme targets of interest in drug-discovery. For the zinc-containing histone deacetylase enzymes in particular, this chemical group has been widely incorporated and studied in the clinic. An alternative chemical functionality for binding zinc is the α-aminocarbonyl motif, which has been shown to bind to histone deacetylase enzymes. The current article explores the minimal binding site theoretical approach combined with structural knowledge to explore the ideal chemical substitution pattern of the α-aminocarbonyl motif within HDAC8. The metal-binding strength of the group is predicted to be highly tunable to chemical substitution at the carbonyl and the α-amino carbon. A fixed receptor model approach with a dispersion-corrected density functional, clearly discerned the effect of different substituents at both these positions using either a flexible or partially fixed ligand optimized in the presence of a fixed receptor model of the HDAC8 binding site. An electron donating substituent such as methyl at the C(α) in combination with NMe(2) substitution at the carbonyl position, similar to observed crystal structures, result in the optimal energetic profile for binding the zinc atom in the HDAC8 enzyme.     

Identification of novel antitubulin agents by using a virtual screening approach based on a 7-point pharmacophore model of the tubulin colchi-site

Tubulin inhibition represents an established target in the field of anticancer research, and over the last 20 years, an intensive search for new antimicrotubule agents has occurred. Indeed, in silico models have been presented that might aid the discovery of novel agents. Among these, a 7-point pharmacophore model has been recently proposed. As a formal proof of this model, we carried out a ligand-based virtual screening on the colchicine-binding site. In vitro testing demonstrated that two compounds displayed a cytotoxic profile on neuroblastoma cancer cells (SH-SY5H) and one had an antitubulinic profile.     

Fragment‐ and negative image‐based screening of phosphodiesterase 10A inhibitors

A novel virtual screening methodology called fragment‐ and negative image‐based (F‐NiB) screening is introduced and tested experimentally using phosphodiesterase 10A (PDE10A) as a case study. Potent PDE10A‐specific small‐molecule inhibitors are actively sought after for their antipsychotic and neuroprotective effects. The F‐NiB combines features from both fragment‐based drug discovery and negative image‐based (NIB) screening methodologies to facilitate rational drug discovery. The selected structural parts of protein‐bound ligand(s) are seamlessly combined with the negative image of the target's ligand‐binding cavity. This cavity‐ and fragment‐based hybrid model, namely its shape and electrostatics, is used directly in the rigid docking of ab initio generated ligand 3D conformers. In total, 14 compounds were acquired using the F‐NiB methodology, 3D quantitative structure–activity relationship modeling, and pharmacophore modeling. Three of the small molecules inhibited PDE10A at ~27 to ~67 μM range in a radiometric assay. In a larger context, the study shows that the F‐NiB provides a flexible way to incorporate small‐molecule fragments into the drug discovery.     

Prediction and validation of potent peptides against herpes simplex virus type 1 via immunoinformatic and systems biology approach

The human herpes simplex virus type 1 (HSV‐1) is an extremely rampant human pathogen, and its infection could cause life‐long diseases, including the central nervous system disorders. The glycoproteins of HSV‐1 such as glycoprotein B, glycoprotein C, glycoprotein D, glycoprotein H, and glycoprotein L are highly involved in mediating the viral attachment and infection of the host cell. Therefore, immunoinformatic approaches followed by molecular dynamics simulation and systems biology has been used to analyze these glycoproteins in order to propose effective peptide‐based vaccine candidates against the HSV‐1 infection. The ElliPro and NetCTL.1.2 online tools were employed to forecast the B‐ and T‐lymphocyte (CTL) epitopes for gB, gC, gD, gH, and gL. The 3D coordinates of these epitopes were modeled and docked against the human major histocompatibility complex molecule‐1. The outcomes obtained from postdocking analysis along with TAP (Transporter associated with antigen processing), MHC binding, and C‐terminal cleavage score assisted in the selection of potential epitopes. These epitopes were further subjected to molecular dynamics simulation and systems biology approach which showed significant results. On the basis of these substantial outcomes, peptides are proposed that could be used to provoke immunity against the HSV‐1 infection.     

Survivin小分子抑制剂的计算机虚拟筛选及初步活性研究

目的通过计算机虚拟筛选,寻找生存素(survivin)的小分子抑制剂,并对其活性进行初步研究。方法基于sur-vivin与其抑制性配体Smac/Diablo复合物的三维结构,用分子对接的方法对含有149,214个小分子的三维结构数据库进行筛选。通过初步活性测定确定活性较高的化合物,进一步研究其对凋亡,细胞周期及活性氧产生的影响。利用分子图像学方法分析化合物与survivin之间的作用模式。结果通过能量打分并根据结构多样性和类药性原则,最终选择了35个化合物进行初步活性测定,其中有9个化合物显示出明显的抑制活性,3个化合物的半数抑制浓度在30μmol.L-1以下。选择其中活性最高的化合物1-19进行进一步研究,结果显示小剂量的1-19能够促进细胞的早期凋亡,诱导细胞内活性氧产生,导致细胞发生S和G2/M期阻滞。分子图像学分析显示活性最高的1-19能够与survivin配体结合区的71位天门冬氨酸形成两个稳定的氢键。结论通过计算机辅助药物设计、药理活性测试以及分子图像学分析,初步确定了一个针对survivin的全新的先导化合物,为今后survivin小分子抑制剂的研究奠定了基础。     

Combined pharmacophore and 3D-QSAR study on a series of Staphylococcus aureus Sortase A inhibitors

Methicillin resistant Staphylococcus aureus has become a major health concern and it requires new therapeutic agents. Staphylococcus aureus Sortase A enzyme contributes in adherence of bacteria with the cell wall of host cell; consequently, inhibition of S. aureus Sortase A by small molecules could be employed as potential antibacterial agents against methicillin resistant S. aureus. Current study focused on the identification of 3D pharmacophoric features within a series of rhodanine, pyridazinone, and pyrazolethione analogs as S. aureus Sortase A inhibitors. Pharmacophore model was constructed employing representative molecules using Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database. The identified pharmacophoric points were then utilized to create alignment hypothesis for three-dimensional quantitative structure-activity relationships. Outcome of comparative molecular field analysis and comparative molecular similarity indices analysis experiments were in good agreement (comparative molecular field analysis: q(2) = 0.562 and r(2) = 0.995, comparative molecular similarity indices analysis: q(2) = 0.549 and r(2) = 0.978) and capable of explaining the variance in biological activities coherently with respect to the structural features of compounds. The results were also found in concurrence with the outcome of pharmacophoric features.     

Investigation of potential glycogen synthase kinase 3 inhibitors using pharmacophore mapping and virtual screening

Glycogen synthase kinase-3 is a serine/threonine kinase that has attracted significant drug discovery attention in recent years. To investigate the identification of new potential glycogen synthase kinase-3 inhibitors, a pharmacophore mapping study was carried out using a set of 21 structurally diverse glycogen synthase kinase-3 inhibitors. A hypothesis containing four features: two hydrophobic, one hydrogen bond donor and another hydrogen bond acceptor was found to be the best from the 10 common feature hypotheses produced by HipHop module of Catalyst. The best hypothesis has a high cost of 156.592 and higher best fit values were obtained for the 21 inhibitors using this best hypothesis than the other HipHop hypotheses. The best hypothesis was then used to screen electronically the NCI2000 database. The hits obtained were docked into glycogen synthase kinase-3beta active site. A total of five novel potential leads were proposed after: (i) visual examination of how well they dock into the glycogen synthase kinase-3beta-binding site, (ii) comparative analysis of their FlexX, G-Score, PMF-Score, ChemScore and D-Scores values, (iii) comparison of their best fit value with the known inhibitors and (iv) examination of the how the hits retain interactions with the important amino acid residues of glycogen synthase kinase-3beta-binding site.     

Pharmacophore modelling and virtual screening for identification of new Aurora-A kinase inhibitors

Aurora-A has been identified as one of the most attractive targets for cancer therapy and a considerable number of Aurora-A inhibitors have been reported recently. In order to clarify the essential structure-activity relationship for the known Aurora-A inhibitors as well as identify new lead compounds against Aurora-A, 3D pharmacophore models were developed based on the known inhibitors. The best hypothesis, Hypo1, was used to screen molecular structural databases, including Specs and China Natural Products Database for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rules and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, 39 compounds were purchased for further in vitro assay against several human tumour cell lines including A549, MCF-7, HepG2 and PC-3, in which Aurora-A is overexpressed. Two compounds show very low micromolar inhibition potency against some of these tumour cells. And they have been selected for further investigation.     

Sequential virtual screening approach to the identification of small organic molecules as potential BACE-1 inhibitors

In this letter, we report on the sequential application of two different in silico screening approaches combined with bioassays aimed at the identification of small organic molecules as potential BACE-1 inhibitors. Two hits endowed of micromolar inhibitory potency were selected, and the binding mode of the most potent compound was further characterized through docking simulations.     

Identification of novel HIV-1 integrase inhibitors using shape-based screening, QSAR, and docking approach

The objective of this study is to identify novel HIV‐1 integrase (IN) inhibitors. Here, shape‐based screening and QSAR have been successfully implemented to identify the novel inhibitors for HIV‐1 IN, and in silico validation is performed by docking studies. The 2D QSAR model of benzodithiazine derivatives was built using genetic function approximation (GFA) method with good internal (cross‐validated r² = 0.852) and external prediction (). Best docking pose of highly active molecule of the benzodithiazine derivatives was used as a template for shape‐based screening of ZINC database. Toxicity prediction was also performed using Deductive Estimation of Risk from Existing Knowledge (DEREK) program to filter non‐toxic molecules. Inhibitory activities of screened non‐toxic molecules were predicted using derived QSAR models. Active, non‐toxic screened molecules were also docked into the active site of HIV‐1 IN using Auto Dock and dock program. Some molecules docked similarly as highly active molecule of the benzodithiazine derivatives. These molecules also followed the same docking interactions in both the programs. Finally, four benzodithiazine derivatives were identified as novel HIV‐1 integrase inhibitors based on QSAR predictions and docking interactions. ADME properties of these molecules were also computed using Discovery Studio.