Computer-aided Drug Design Approaches Research Articles

Structure-Based Drug Design for Tuberculosis: Challenges Still Ahead

Structure-based and computer-aided drug design approaches are commonly considered to have been successful in the fields of cancer and antiviral drug discovery but not as much for antibacterial drug development. The search for novel anti-tuberculosis agents is indeed an emblematic example of this trend. Although huge efforts, by consortiums and groups worldwide, dramatically increased the structural coverage of the Mycobacterium tuberculosis proteome, the vast majority of candidate drugs included in clinical trials during the last decade were issued from phenotypic screenings on whole mycobacterial cells. We developed here three selected case studies, i.e., the serine/threonine (Ser/Thr) kinases—protein kinase (Pkn) B and PknG, considered as very promising targets for a long time, and the DNA gyrase of M. tuberculosis, a well-known, pharmacologically validated target. We illustrated some of the challenges that rational, target-based drug discovery programs in tuberculosis (TB) still have to face, and, finally, discussed the perspectives opened by the recent, methodological developments in structural biology and integrative techniques.

Discovery of New Hydroxyethylamine Analogs against 3CLpro Protein Target of SARS-CoV-2: Molecular Docking, Molecular Dynamics Simulation, and Structure-Activity Relationship Studies.

The novel coronavirus, SARS-CoV-2, has caused a recent pandemic called COVID-19 and a severe health threat around the world. In the current situation, the virus is rapidly spreading worldwide, and the discovery of a vaccine and potential therapeutics are critically essential. The crystal structure for the main protease (Mpro) of SARS-CoV-2, 3-chymotrypsin-like cysteine protease (3CLpro), was recently made available and is considerably similar to the previously reported SARS-CoV. Due to its essentiality in viral replication, it represents a potential drug target. Herein, a computer-aided drug design (CADD) approach was implemented for the initial screening of 13 approved antiviral drugs. Molecular docking of 13 antivirals against the 3-chymotrypsin-like cysteine protease (3CLpro) enzyme was accomplished, and indinavir was described as a lead drug with a docking score of −8.824 and a XP Gscore of −9.466 kcal/mol. Indinavir possesses an important pharmacophore, hydroxyethylamine (HEA), and thus, a new library of HEA compounds (>2500) was subjected to virtual screening that led to 25 hits with a docking score more than indinavir. Exclusively, compound 16 with a docking score of −8.955 adhered to drug-like parameters, and the structure–activity relationship (SAR) analysis was demonstrated to highlight the importance of chemical scaffolds therein. Molecular dynamics (MD) simulation analysis performed at 100 ns supported the stability of 16 within the binding pocket. Largely, our results supported that this novel compound 16 binds with domains I and II, and the domain II–III linker of the 3CLpro protein, suggesting its suitability as a strong candidate for therapeutic discovery against COVID-19.

Organophosphorus insecticide interacts with the pheromone-binding proteins of Athetis lepigone: Implication for olfactory dysfunction

Athetis lepigone is one of the most severe polyphagous pests, and it has developed resistance to different chemical insecticides. Insects primarily rely on the olfactory system to recognize various environmental chemicals, including xenobiotics such as insecticides. Here, we expressed two A. lepigone pheromone-binding proteins (AlepPBP2 and AlepPBP3), and observed they had higher binding affinities to phoxim than other insecticides, with Ki was 3.30 ± 0.38 μM and 3.27 ± 0.10 μM, respectively. Molecular dynamics simulation, binding mode analysis, and computational alanine scanning showed that six residues (Phe15, Phe39, Ile55, Leu65, Ile97, and Phe122) of AlepPBP2 and three residues (Phe12, Ile52, and Ile134) of AlepPBP3 maybe as potential residues that can change protein ability to bind an organophosphorus insecticide phoxim. Then, we used site-directed mutagenesis assay to mutate these residues into alanine, respectively. Subsequently, the binding assays displayed that Phe15, Phe39, and Ile97 of AlepPBP2, Phe12 and Ile134 of AlepPBP3 caused a significant decrease of AlepPBPs binding ability to phoxim, suggesting they should play crucial roles in the AlepPBPs/phoxim interactions. Our findings could further advance in using PBPs as unique targets to design and develop precise and environmentally-friendly pest control agents with high insecticidal potential using a computer-aided drug design (CADD) approach.

Chalcones as a basis for computer-aided drug design: innovative approaches to tackle malaria.

Aim: Computer-aided drug design approaches were applied to identify chalcones with antiplasmodial activity. Methodology: The virtual screening was performed as follows: structural standardization of in-house database of chalcones; identification of potential Plasmodium falciparum protein targets for the chalcones; homology modeling of the predicted P. falciparum targets; molecular docking studies; and in vitro experimental validation. Results: Using these models, we prioritized 16 chalcones with potential antiplasmodial activity, for further experimental evaluation. Among them, LabMol-86 and LabMol-87 showed potent in vitro antiplasmodial activity against P. falciparum, while LabMol-63 and LabMol-73 were potent inhibitors of Plasmodium berghei progression into mosquito stages. Conclusion: Our results encourage the exploration of chalcones in hit-to-lead optimization studies for tackling malaria.

Multi-Armed 1,2,3-Selenadiazole and 1,2,3-Thiadiazole Benzene Derivatives as Novel Glyoxalase-I Inhibitors.

Glyoxalase-I (Glo-I) enzyme was established to be a valid target for anticancer drug design. It performs the essential detoxification step of harmful byproducts, especially methylglyoxal. A robust computer-aided drug design approach was used to design and validate a series of compounds with selenium or sulfur based heterorings. A series of in-house multi-armed 1,2,3-selenadiazole and 1,2,3-thiadiazole benzene derivatives were tested for their Glo-I inhibitory activity. Results showed that these compounds bind Glo-I active sites competitively with strong potential to inhibit this enzyme with IC50 values in micro-molar concentration. Docking poses revealed that these compounds interact with the zinc atom at the bottom of the active site, which plays an essential role in its viability.

Identification of a Novel Scaffold for Inhibition of Dipeptidyl Peptidase-4.

Dipeptidyl peptidase-4 (DPP-4) is considered a major drug target for type 2 diabetes mellitus (T2DM). In addition to T2DM, a regulatory role of DPP-4 was also found in cardiovascular diseases. Existing DPP-4 inhibitors have been reported to have several adverse effects. In this study, a computer-aided drug design approach and its use to detect a novel class of inhibitor for DPP-4 are reported. Through structure and pharmacophore-based screening, we identified 13 hit compounds from an ∼4-million-compound library. Physical interactions of these hits with DPP-4 were studied using docking and explicit solvent molecular dynamics (MD) simulations. Later, MMPBSA binding energy was calculated for the ligand/protein simulation trajectories to determine the stability of compounds in the binding cavity. These compounds have a novel scaffold and exhibited a stable binding mode. "Best-in-screen" compounds (or their closest available analogs) were resourced and their inhibition of DPP-4 activity was experimentally validated using an in vitro enzyme activity assay in the presence of 100 and 10 μM compounds. These assays identified a compound with a spirochromanone center with 53% inhibition activity at a 100 μM concentration. A further five spirochromanone compounds were synthesized and examined in silico and in vitro; again, one compound showed 53% inhibitory activity action at 100 μM. Overall, this study identified two novel "spirochromanone" compounds that lowered DPP-4 activity by more than ∼50% at 100 μM. This study also showed the impact of fast in silico drug design techniques utilizing virtual screening and MD to identify novel scaffolds to bind and inhibit DPP-4. Spirochromanone motif identified here may be used to design molecules to achieve drug-like inhibitory action against DPP-4.

On the discovery of a potential survivin inhibitor combining computational tools and cytotoxicity studies

Survivin protein is a metalloprotein member of the inhibitors of apoptosis proteins family, involved in the regulation of programmed cell death. Due to the recent development of antitumor therapies having survivin as molecular target, several strategies to interfere with the expression or function of survivin have emerged. This work describes the discovery of a new potential inhibitor of survivin function using a computer-aided drug design approach. Structure-based virtual screening and molecular dynamic simulations were carried out to select two compounds as possible inhibitors. According to the binding energy, possible ligand localization is in a cavity, close to dimerization interface. Next, cell-based assays were performed on three cell lines: two with tumor phenotype and over-expression of survivin, and another with normal phenotype and low expression of survivin. One of the selected compounds shows a selectively antitumor effect on panel cell lines suggesting that the compound effect could be correlated with the survivin expression.

Computational Studies in Drug Design Against Cancer.

The application of in silico tools in the development of anti cancer drugs. The summing of different computer aided drug design approaches that have been applied in the development of anti cancer drugs. Structure based, ligand based, hybrid protein-ligand pharmacophore methods, Homology modeling, molecular docking aids in different steps of drug discovery pipeline with considerable saving in time and expenditure. In silico tools also find applications in the domain of cancer drug development. Structure-based pharmacophore modeling aided in the identification of PUMA inhibitors, structure based approach with high throughput screening for the development of Bcl-2 inhibitors, to derive the most relevant protein-protein interactions, anti mitotic agents; I-Kappa-B Kinase β (IKK- β) inhibitor, screening of new class of aromatase inhibitors that can be important targets in cancer therapy. Application of computational methods in the design of anti cancer drugs was found to be effective.

Nrf2 Activation by SK-119 Attenuates Oxidative Stress, UVB, and LPS-Induced Damage

Background/Aims: The Nrf2 signaling pathway plays a pivotal role in neutralizing excess reactive oxygen species formation and therefore enhancing the endogenous cellular protection mechanism. Thus, activating this pathway may provide therapeutic options against oxidative stress-related disorders. We have recently applied a computer-aided drug design approach to the design and synthesis of novel Nrf2 enhancers. The current study was aimed at investigating the potential beneficial impact of (E)-5-oxo-1-(4-((2,4,6-trihydroxybenzylidene)amino)phenyl)pyrrolidine-3-carboxylic acid (SK-119) in skin oxidative damage models. Methods: SK-119, tested initially in PC-12 cells, attenuated oxidative stress-induced cytotoxicity concomitantly with Nrf2 activation. The potential impact of this compound was evaluated in skin-based disease models both in vitro (HaCaT cells) and ex vivo (human skin organ culture). Results: The data clearly showed the marked anti-inflammatory and photoprotection properties of the compound; SK-119-treated cells or tissues displayed a reduction in cytokine secretion induced by lipopolysaccharides (LPS) in a manner comparable with dexamethasone. In addition, topical application of SK-119 was able to block UVB-induced oxidative stress and attenuated caspase-mediated apoptosis, DNA adduct formation, and the concomitant cellular damage. Conclusion: These results indicate that SK-119 is an Nrf2 activator that can be used as a prototype molecule for the development of novel treatments of dermatological disorders related to oxidative stress.

Combination of pharmacophore modeling and 3D-QSAR analysis of potential glyoxalase-I inhibitors as anticancer agents

Glyoxalase system is an ubiquitous system in human cells which has been examined thoroughly for its role in different diseases. It comprises two enzymes; Glyoxalase I (Glo-I) and Glyoxalase II (Glo-II) which perform detoxifying endogenous harmful metabolites, mainly methylglyoxal (MG) into non-toxic bystanders. In silico computer Aided Drug Design approaches were used and ninety two diverse pharmacophore models were generated from eighteen Glyoxalase I crystallographic complexes. Subsequent QSAR modeling followed by ROC evaluation identified a single pharmacophore model which was able to predict the expected Glyoxalase I inhibition. Screening of the National Cancer Institute (NCI) database using the optimal pharmacophore Hypo(3VW9) identified several promising hits. Thirty eight hits were successfully predicted then ordered and evaluated in vitro. Seven hits out of the thirty eight tested compounds showed more than 50% inhibition with low micromolar IC50.

Binding pocket-based design, synthesis and biological evaluation of novel selective BRD4-BD1 inhibitors.

Bromodomain-containing protein 4 (BRD4), consisting of two tandem bromodomains (BD1 and BD2), is key epigenetic regulator in fibrosis and cancer, which has been reported that BD1 and BD2 have distinct roles in post-translational modification. But there are few selective inhibitors toward those two domains. Herein, this study designed and synthesized a series of novel selective BRD4-BD1 inhibitors, using computer-aided drug design (CADD) approach focused on exploring the difference of the binding pockets of BD1 and BD2, and finding the His437 a crucial way to achieve BRD4-BD1 selectivity. Our results revealed that the compound 3u is a potent selective BRD4-BD1 inhibitor with IC50 values of 0.56 μM for BD1 but >100 μM for BD2. The compound exhibited a broad spectrum of anti-proliferative activity against several human cancer and fibroblastic cell lines, which might be related to its capability of reducing the expression of c-Myc and collagen I. Furthermore, it could induce apoptosis in A375 cells. To the contrary, the selective BD2 inhibitor, RVX-208, did not indicate any of these activities. Our findings highlight that the function of BRD4-BD1 might be predominant in fibrosis and cancer. And it is rational to further develop novel selective BRD4-BD1 inhibitors.

Novel glitazones as PPAR\u03b3 agonists: molecular design, synthesis, glucose uptake activity and 3D QSAR studies

BackgroundAn alarming requirement for finding newer antidiabetic glitazones as agonists to PPARγ are on its utmost need from past few years as the side effects associated with the available drug therapy is dreadful. In this context, herein, we have made an attempt to develop some novel glitazones as PPARγ agonists, by rational and computer aided drug design approach by implementing the principles of bioisosterism. The designed glitazones are scored for similarity with the developed 3D pharmacophore model and subjected for docking studies against PPARγ proteins. Synthesized by adopting appropriate synthetic methodology and evaluated for in vitro cytotoxicity and glucose uptake assay. Illustrations about the molecular design of glitazones, synthesis, analysis, glucose uptake activity and SAR via 3D QSAR studies are reported.ResultsThe computationally designed and synthesized ligands such as 2-(4-((substituted phenylimino)methyl)phenoxy)acetic acid derivatives were analysed by IR, 1H-NMR, 13C-NMR and MS-spectral techniques. The synthesized compounds were evaluated for their in vitro cytotoxicity and glucose uptake assay on 3T3-L1 and L6 cells. Further the activity data was used to develop 3D QSAR model to establish structure activity relationships for glucose uptake activity via CoMSIA studies.ConclusionThe results of pharmacophore, molecular docking study and in vitro evaluation of synthesized compounds were found to be in good correlation. Specifically, CPD03, 07, 08, 18, 19, 21 and 24 are the candidate glitazones exhibited significant glucose uptake activity. 3D-QSAR model revealed the scope for possible further modifications as part of optimisation to find potent anti-diabetic agents.

COMPUTER AIDED DRUG DESIGN: AN OVERVIEW

Discovery and development of a new drug is generally known as a very complex process which takes a lot of time and resources. So now a day’s computer aided drug design approaches are used very widely to increase the efficiency of the drug discovery and development course. Various approaches of CADD are evaluated as promising techniques according to their need, in between all these structure-based drug design and ligand-based drug design approaches are known as very efficient and powerful techniques in drug discovery and development. These both methods can be applied with molecular docking to virtual screening for lead identification and optimization. In the recent times computational tools are widely used in pharmaceutical industries and research areas to improve effectiveness and efficacy of drug discovery and development pipeline. In this article we give an overview of computational approaches, which is inventive process of finding novel leads and aid in the process of drug discovery and development research.
 Keywords: computer aided drug discovery, structure-based drug design, ligand-based drug design, virtual screening and molecular docking

Computer Aided Drug Design and its Application to the Development of Potential Drugs for Neurodegenerative Disorders.

BackgroundNeurodegenerative disorders (NDs) are diverse group of disorders characterized by escalating loss of neurons (structural and functional). The development of potential therapeutics for NDs presents an important challenge, as traditional treatments are inefficient and usually are unable to stop or retard the process of neurodegeneration. Computer-Aided Drug Design (CADD) has emerged as an efficient means of developing candidate drugs for the treatment of many disease types. Applications of CADD approach to drug discovery are progressing day by day. The recent tendency in drug design is to rationally design potent therapeutics with multi-targeting effects, higher efficacies, and fewer side effects, especially in terms of toxicity.MethodsA wide literature search was performed for writing this review. An updated view on different types of NDs, their effect on human population and a brief introduction to CADD, various approaches involved in this technique, ranging from structural-based to ligand-based drug design has been discussed. The successful application of CADD approaches for the treatment of neurodegenerative disorders is also included in this review.ResultsIn this review, we have briefly described about CADD and its use in the development of the therapeutic drug candidates against NDs. The successful applications, limitations and future prospects of this approach have also been discussed.ConclusionCADD can assist researchers studying interactions between drugs and receptors. We believe this review will be helpful for better understanding of CADD and its applications towards the discovery of new drug candidates against various fatal NDs.

Molecular Docking and 3D-Pharmacophore Modeling to Study the Interactions of Chalcone Derivatives with Estrogen Receptor Alpha.

Tamoxifen is the most frequently used anti-estrogen adjuvant treatment for estrogen receptor-positive breast cancer. However, it is associated with an increased risk of several serious side–effects, such as uterine cancer, stroke, and pulmonary embolism. The 2′,4′-dihydroxy-6-methoxy-3,5-dimethylchalcone (ChalcEA) from plant leaves of Eugenia aquea, has been found to inhibit the proliferation of MCF-7 human breast cancer cells in a dose-dependent manner, with an IC50 of 74.5 μg/mL (250 μM). The aim of this work was to study the molecular interactions of new ChalcEA derivatives formed with the Estrogen Receptor α (ERα) using computer aided drug design approaches. Molecular docking using Autodock 4.2 was employed to explore the modes of binding of ChalcEA derivatives with ERα. The 3D structure-based pharmacophore model was derived using LigandScout 4.1 Advanced to investigate the important chemical interactions of the ERα-tamoxifen complex structure. The binding energy and the tamoxifen-pharmacophore fit score of the best ChalcEA derivative (HNS10) were −12.33 kcal/mol and 67.07 kcal/mol, respectively. The HNS10 interacted with Leu346, Thr347, Leu349, Ala350, Glu353, Leu387, Met388, Leu391, Arg394, Met421, and Leu525. These results suggest that the new ChalcEA derivatives could serve as the lead compound for potent ERα inhibitor in the fight against breast cancer.

Drug Design Workshop: A Web-Based Educational Tool To Introduce Computer-Aided Drug Design to the General Public

Due to its impact on society, the design of new drugs has the potential to interest a wide audience, and provides a rare opportunity to introduce several concepts in chemistry and biochemistry. Drug design can be seen as a multiobjective cyclic optimization process. Indeed, it is important to develop the understanding not only that a drug is generally an effective ligand for a protein of therapeutic interest, but also that these molecules need to have drug-like properties. Computer-aided drug design and bioinformatics approaches play a fundamental role in addressing these different challenges. Here we introduce a new freely available integrated web-based educational tool, Drug Design Workshop, which presents the basics of drug design and provides anyone with access to computational methods and resources to conceive and evaluate molecules for their potential to become actual drugs. We provide 3 examples of drug design targets for the discovery of common or state-of-the-art drugs, which can be used by educa...

New Medications for the Treatment of Diabetes.

New Medications for the Treatment of Diabetes.

Computer-Aided Drug Design Methods.

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

Design, Synthesis and Bioactivity Evaluation of Novel Dabigatran Derivatives as Potential Thrombin Inhibitors

With the help of computer-aided drug design approach, five dabigatran derivatives were designed and synthesized. The structures of these compounds were elucidated by 1H NMR, 13C NMR, HRMS analyses. All the compounds were evaluated for their thrombin inhibitory activitiy in vitro (IC50) and they showed significant thrombin inhibition with IC50 values from 2.74 to 20.31 nM. Especially, compound 7a, and 7b were potent thrombin inhibitor with IC50 values of 2.74 and 2.99 nM, respectively, which were comporable to dabigatran (1.20 nM) and much better than argatroban (9.88 nM). Moreover, molecular docking study was performed to determine the inhibitory mechanism of active compounds. Keywords: Dabigatran derivaties, synthesis, antithrombin activity, molecular docking.

Computer Aided Drug Design Approaches for Identification of Novel Autotaxin (ATX) Inhibitors.

Autotaxin (ATX) has become an attractive target with a huge pharmacological and pharmacochemical interest in LPA-related diseases and to date many small organic molecules have been explored as potential ATX inhibitors. As a useful aid in the various efforts of identifying novel effective ATX inhibitors, in silico methods can serve as an important and valuable tool. Especially, Virtual Screening (VS) has recently received increased attention due to the large datasets made available, the development of advanced VS techniques and the encouraging fact that VS has contributed to the discovery of several compounds that have either reached the market or entered clinical trials. Different techniques and workflows have been reported in literature with the goal to prioritize possible potent hits. In this review article several deployed virtual screening strategies for the identification of novel potent ATX inhibitors are described.