Computational identification of new TKI as potential noncovalent reversible EGFRL858R/T790M inhibitors: VHTS, molecular docking, DFT study and molecular dynamic simulation

The mutations concerned with non-small cell lung cancer involving epidermal growth factor receptor of tyrosine kinase family have primarily targeted. In this study, we employed a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 50.000 Erlotinib-derived compounds as noncovalent reversible EGFRL858R/T790M inhibitors. Our HTVS work flow leverages include HTVS, SP (Standard Precision) and XP (Extra Precision) docking protocol along with its relative binding free energy calculation, cluster analysis study and ADMET properties. Then we used multiple ns-time scale molecular dynamics (MD) simulations and density functional theory (DFT) precise calculation techniques to elucidate how the bound ligand interact with the complexes conformational states involving motions both proximal and distal to the binding site. Based on glide score and protein-ligand interactions, the highest scoring molecule was selected for molecular dynamic simulation providing a complete insight into the conformational stability. A hyperfine analysis of DFT based refinement strategy highly supported their stability by strong intermolecular interactions. Together, our results demonstrate that the virtually screened top retained molecules present the best moieties introduced to Erlotinib. They exhibit interesting pharmacokinetic properties that can act as potent antitumor drug candidates than the lead compound drug and in some extent tackling the drug resistance problem which offer a springboard for further therapeutic experiments and applications.Communicated by Ramaswamy H. Sarma.

Exploration of comprehensive marine natural products database against dengue viral non-structural protein 1 using high-throughput computational studies

Dengue virus (DENV) non-structural protein 1 (NS1) is a versatile quasi-protein essential for the multiplication of the virus. This study applied high-throughput virtual screening (HTVS) and molecular dynamics (MD) simulation to detect the potential marine natural compounds against the NS1 of DENV. The structure of the NS1 protein was retrieved from Protein Data Bank with (PDB ID: 4O6B). Missing residues were added using modeler software. Molecular operating environment (MOE) programme was used to prepare the protein before docking. Virtual screening was performed on PyRx software to identify natural compounds retrieved from Comprehensive Marine Natural Products Database (CMNPD) against the NS1 protein, and best-docked compounds were examined by molecular docking and molecular dynamic (MD) simulation. Out of 31,561 marine compounds, the top 10 compounds showed docking scores lesser than -8.0 kcal/mol. One of the best hit compounds, CMNPD6802, was further analyzed using MD simulation study at 100 nanoseconds and Molecular Mechanics with Generalized Born and Surface Area Solvation (MM/GBSA). Based on its total binding energy, determined using the MM/GBSA approach, CMNPD6802 was ranked first. Its pharmacokinetic properties concerning the target protein NS1 were also evaluated. The results of the MD simulation showed that CMNPD6802 remained in close contact with the protein throughout the activation period, mapped using principal component analysis. These findings suggest that CMNPD6802 could serve as an NS1 inhibitor and may be a potential candidate for treating DENV infections.Communicated by Ramaswamy H. Sarma.

Conjoint research of WGCNA, single-cell transcriptome and structural biology reveals the potential targets of IDD development and treatment and JAK3 involvement

OBJECTIVES

This study conducted integrated analysis of bulk RNA sequencing, single-cell RNA sequencing and Weighted Gene Co-expression Network Analysis (WGCNA), to comprehensively decode the most essential genes of intervertebral disc degeneration (IDD); then mainly focused on the JAK3 macromolecule to identify natural compounds to provide more candidate drug options in alleviating IDD.

METHODS

In the first part, we performed single-cell transcriptome analysis and WGCNA workflow to delineate the most pivotal genes of IDD. Then series of structural biology approaches and high-throughput virtual screening techniques were performed to discover potential compounds targeting JAK-STAT signaling pathway, such as Libdock, ADMET, precise molecular docking algorithm and in-vivo drug stability assessment.

RESULTS

Totally 4 hub genes were determined in the development of IDD, namely VEGFA, MMP3, TNFSF11, and TIMP3, respectively. Then, 3 novel natural materials, ZINC000014952116, ZINC000003938642 and ZINC000072131515, were determined as potential compounds, with less toxicities and moderate ADME characteristics. In-vivo drug stability assessment suggested that these drugs could interact with JAK3, and their ligand-JAK3 complexes maintained the homeostasis in-vivo, which acted as regulatory role to JAK3 protein. Among them, ZINC000072131515, also known as Menaquinone, demonstrated significant protective roles to alleviate the progression of IDD in vitro, which proved the nutritional therapy in alleviating IDD.

CONCLUSIONS

This study reported the essential genes in the development of IDD, and also the roles of Menaquinone to ameliorate IDD through inhibiting JAK3 protein. This study also provided more options and resources on JAK3 targeted screening, which may further expand the drug resources in the pharmaceutical market.

Accelerating the Search for New Solid Electrolytes: Exploring Vast Chemical Space with Machine Learning-Enabled Computational Calculations

Discovering new solid electrolytes (SEs) is essential to achieving higher safety and better energy density for all-solid-state lithium batteries. In this work, we report machine learning (ML)-assisted high-throughput virtual screening (HTVS) results to identify new SE materials. This approach expands the chemical space to explore by substituting elements of prototype structures and accelerates an evaluation of properties by applying various ML models. The screening results in a few candidate materials, which are validated by density functional theory calculations and ab initio molecular dynamics simulations. The shortlisted oxysulfide materials satisfy key properties to be successful SEs. The advanced screening method presented in this work will accelerate the discovery of energy materials for related applications.

Low Molecular Weight Inhibitors Targeting the RNA-Binding Protein HuR

The RNA-binding protein human antigen R (HuR) regulates stability, translation, and nucleus-to-cytoplasm shuttling of its target mRNAs. This protein has been progressively recognized as a relevant therapeutic target for several pathologies, like cancer, neurodegeneration, as well as inflammation. Inhibitors of mRNA binding to HuR might thus be beneficial against a variety of diseases. Here, we present the rational identification of structurally novel HuR inhibitors. In particular, by combining chemoinformatic approaches, high-throughput virtual screening, and RNA-protein pulldown assays, we demonstrate that the 4-(2-(2,4,6-trioxotetrahydropyrimidin-5(2H)-ylidene)hydrazineyl)benzoate ligand exhibits a dose-dependent HuR inhibition effect in binding experiments. Importantly, the chemical scaffold is new with respect to the currently known HuR inhibitors, opening up a new avenue for the design of pharmaceutical agents targeting this important protein.

Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening

Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries' display and expression systems. The results of our in silico study are in accordance with existing scientific literature on in vitro peptides that bind to antibody Fc regions. In addition, we postulate an evolving in silico library design workflow that will help circumvent the combinatorial problem of in vitro comprehensive peptide libraries by focusing on peptide subunits that exhibit favorable interaction profiles in initial in silico peptide generation and testing.

Structural and functional characterization of 1-deoxy-D-xylulose-5-phosphate synthase (DXS) from Acinetobacter baumannii: identification of promising lead molecules from virtual screening, molecular docking and molecular dynamics simulations

The advent of multi drug resistance and extensive-drug resistance among various pathogens has caused a rise in nosocomial infections, which in turn has led to rising hospital-acquired infection-related mortality rates. Amongst them, carbapenem-resistant Acinetobacter baumannii is one of the most notorious bacterial species, categorized as a Priority 1: Critical pathogen by the WHO. Therefore, the discovery and development of novel antibiotics, as well as the identification of potential inhibitors, have become the need of the hour. In this study, we have employed computational methods to explore and identify molecules capable of inhibiting enzymes essential in the methylerythritol 4-phosphate (MEP) biosynthetic pathway. The high throughput virtual screening of small molecules (Enamine Advanced Collection (AC) library) against the highly conserved substrate-binding site of the DXS target protein provided us with a total of 1000 molecules. The top four potential candidate molecules, namely-Z3353989070, Z3353989049, Z2295848528, and Z1685501455, alongside fluoropyruvate (control), a known inhibitor of DXS, was chosen for a molecular dynamic simulation study. The molecular dynamic simulation trajectories suggested high structural and thermodynamical stability and strong binding affinity of all the DXS-ligand complexes. Moreover, the MM/PBSA-based binding free energy calculations also exhibited strong interactions of the selected ligand molecules with DXS. In conclusion, we have found that all four molecules displayed better results and stronger binding affinity than the control. In the end, based on all the above-mentioned criteria, we have proposed Z3353989049 to be the promising lead candidate against DXS from A. baumannii.Communicated by Ramaswamy H. Sarma.

Exploration of Novel Scaffolds Targeting Cytochrome b of Pyricularia oryzae

The fulfilment of the European "Farm to Fork" strategy requires a drastic reduction in the use of "at risk" synthetic pesticides; this exposes vulnerable agricultural sectors-among which is the European risiculture-to the lack of efficient means for the management of devastating diseases, thus endangering food security. Therefore, novel scaffolds need to be identified for the synthesis of new and more environmentally friendly fungicides. In the present work, we employed our previously developed 3D model of P. oryzae cytochrome bc1 (cyt bc1) complex to perform a high-throughput virtual screening of two commercially available compound libraries. Three chemotypes were selected, from which a small collection of differently substituted analogues was designed and synthesized. The compounds were tested as inhibitors of the cyt bc1 enzyme function and the mycelium growth of both strobilurin-sensitive (WT) and -resistant (RES) P. oryzae strains. This pipeline has permitted the identification of thirteen compounds active against the RES cyt bc1 and five compounds that inhibited the WT cyt bc1 function while inhibiting the fungal mycelia only minimally. Serendipitously, among the studied compounds we identified a new chemotype that is able to efficiently inhibit the mycelium growth of WT and RES strains by ca. 60%, without inhibiting the cyt bc1 enzymatic function, suggesting a different mechanism of action.

Identification of NS2B-NS3 Protease Inhibitors for Therapeutic Application in ZIKV Infection: A Pharmacophore-Based High-Throughput Virtual Screening and MD Simulations Approaches

Zika virus (ZIKV) pandemic and its implication in congenital malformations and severe neurological disorders had created serious threats to global health. ZIKV is a mosquito-borne flavivirus which spread rapidly and infect a large number of people in a shorter time-span. Due to the lack of effective therapeutics, this had become paramount urgency to discover effective drug molecules to encounter the viral infection. Various anti-ZIKV drug discovery efforts during the past several years had been unsuccessful to develop an effective cure. The NS2B-NS3 protein was reported as an attractive therapeutic target for inhibiting viral proliferation, due to its central role in viral replication and maturation of non-structural viral proteins. Therefore, the current in silico drug exploration aimed to identify the novel inhibitors of Zika NS2B-NS3 protease by implementing an e-pharmacophore-based high-throughput virtual screening. A 3D e-pharmacophore model was generated based on the five-featured (ADPRR) pharmacophore hypothesis. Subsequently, the predicted model is further subjected to the high-throughput virtual screening to reveal top hit molecules from the various small molecule databases. Initial hits were examined in terms of binding free energies and ADME properties to identify the candidate hit exhibiting a favourable pharmacokinetic profile. Eventually, molecular dynamic (MD) simulations studies were conducted to evaluate the binding stability of the hit molecule inside the receptor cavity. The findings of the in silico analysis manifested affirmative evidence for three hit molecules with -64.28, -55.15 and -50.16 kcal/mol binding free energies, as potent inhibitors of Zika NS2B-NS3 protease. Hence, these molecules holds the promising potential to serve as a prospective candidates to design effective drugs against ZIKV and related viral infections.

Quantitative structure-activity relationships, molecular docking and molecular dynamics simulations reveal drug repurposing candidates as potent SARS-CoV-2 main protease inhibitors

The current outbreak of COVID-19 is leading an unprecedented scientific effort focusing on targeting SARS-CoV-2 proteins critical for its viral replication. Herein, we performed high-throughput virtual screening of more than eleven thousand FDA-approved drugs using backpropagation-based artificial neural networks (q²_LOO = 0.60, r² = 0.80 and r²_pred = 0.91), partial-least-square (PLS) regression (q²_LOO = 0.83, r² = 0.62 and r²_pred = 0.70) and sequential minimal optimization (SMO) regression (q²_LOO = 0.70, r² = 0.80 and r²_pred = 0.89). We simulated the stability of Acarbose-derived hexasaccharide, Naratriptan, Peramivir, Dihydrostreptomycin, Enviomycin, Rolitetracycline, Viomycin, Angiotensin II, Angiotensin 1-7, Angiotensinamide, Fenoterol, Zanamivir, Laninamivir and Laninamivir octanoate with 3CL_pro by 100 ns and calculated binding free energy using molecular mechanics combined with Poisson-Boltzmann surface area (MM-PBSA). Our QSAR models and molecular dynamics data suggest that seven repurposed-drug candidates such as Acarbose-derived Hexasaccharide, Angiotensinamide, Dihydrostreptomycin, Enviomycin, Fenoterol, Naratriptan and Viomycin are potential SARS-CoV-2 main protease inhibitors. In addition, our QSAR models and molecular dynamics simulations revealed that His41, Asn142, Cys145, Glu166 and Gln189 are potential pharmacophoric centers for 3CL_pro inhibitors. Glu166 is a potential pharmacophore for drug design and inhibitors that interact with this residue may be critical to avoid dimerization of 3CL_pro. Our results will contribute to future investigations of novel chemical scaffolds and the discovery of novel hits in high-throughput screening as potential anti-SARS-CoV-2 properties.Communicated by Ramaswamy H. Sarma.

The Impact of Software Used and the Type of Target Protein on Molecular Docking Accuracy

The modern development of computer technology and different in silico methods have had an increasing impact on the discovery and development of new drugs. Different molecular docking techniques most widely used in silico methods in drug discovery. Currently, the time and financial costs for the initial hit identification can be significantly reduced due to the ability to perform high-throughput virtual screening of large compound libraries in a short time. However, the selection of potential hit compounds still remains more of a random process, because there is still no consensus on what the binding energy and ligand efficiency (LE) of a potentially active compound should be. In the best cases, only 20-30% of compounds identified by molecular docking are active in biological tests. In this work, we evaluated the impact of the docking software used as well as the type of the target protein on the molecular docking results and their accuracy using an example of the three most popular programs and five target proteins related to neurodegenerative diseases. In addition, we attempted to determine the "reliable range" of the binding energy and LE that would allow selecting compounds with biological activity in the desired concentration range.

Drug Repurposing Against Angiotensin-Converting Enzyme-Related Carboxypeptidase (ACE2) Through Computational Approach

Ongoing novel coronavirus (COVID-19) with high mortality is an infectious disease in the world which epidemic in 2019 with human-human transmission. According to the literature, S-protein is one of the main proteins of COVID-19 that bind to the human cell receptor angiotensin-converting enzyme 2 (ACE2). In this study, it was attempted to identify the main effective drugs approved that may be repurposed to the binding site of ACE2. High throughput virtual screening based on the docking study was performed to know which one of the small-molecules had a potential interaction with ACE2 structure. Forasmuch as investigating and identifying the best ACE2 inhibitors among more than 3,500 small-molecules is time-consuming, supercomputer was utilized to apply docking-based virtual screening. Outputs of the proposed computational model revealed that vincristine, vinbelastin and bisoctrizole can significantly bind to ACE2 and may interface with its normal activity.

Comparative Analyses of Medicinal Chemistry and Cheminformatics Filters with Accessible Implementation in Konstanz Information Miner (KNIME)

High-throughput virtual screening (HTVS) is, in conjunction with rapid advances in computer hardware, becoming a staple in drug design research campaigns and cheminformatics. In this context, virtual compound library design becomes crucial as it generally constitutes the first step where quality filtered databases are essential for the efficient downstream research. Therefore, multiple filters for compound library design were devised and reported in the scientific literature. We collected the most common filters in medicinal chemistry (PAINS, REOS, Aggregators, van de Waterbeemd, Oprea, Fichert, Ghose, Mozzicconacci, Muegge, Egan, Murcko, Veber, Ro3, Ro4, and Ro5) to facilitate their open access use and compared them. Then, we implemented these filters in the open platform Konstanz Information Miner (KNIME) as a freely accessible and simple workflow compatible with small or large compound databases for the benefit of the readers and for the help in the early drug design steps.

Revealing oxidative stress-related genes in osteoporosis and advanced structural biological study for novel natural material discovery regarding MAPKAPK2

OBJECTIVES

This study aimed to find novel oxidative stress (OS)-related biomarkers of osteoporosis (OP), together with targeting the macromolecule Mitogen-activated protein kinase-activated protein kinase 2 (MAPKAPK2) protein to further discover potential novel materials based on an advanced structural biology approach.

METHODS

Gene expression profiles of GSE35958 were obtained from the Gene Expression Omnibus (GEO) database, which were included for weighted gene co-expression network analysis (WGCNA) and differential analysis to identify the most correlated module, to identify OS-related hub genes in the progression of OP. Functional annotations were also analyzed on the interested module to get a comprehensive understanding of these genes. Then, a series of advanced structural biology methods, including high-throughput screening, pharmacological characteristic prediction, precise molecular docking, molecular dynamics simulation, etc., was implemented to discover novel natural inhibitor materials against the MAPKAPK2 protein.

RESULTS

The brown module containing 720 genes was identified as the interested module, and a group set of genes was determined as the hub OS-related genes, including PPP1R15A, CYB5R3, BCL2L1, ABCD1, MAPKAPK2, HSP90AB1, CSF1, RELA, P4HB, AKT1, HSP90B1, and CTNNB1. Functional analysis demonstrated that these genes were primarily enriched in response to chemical stress and several OS-related functions. Then, Novel Materials Discovery demonstrated that two compounds, ZINC000014951634 and ZINC000040976869, were found binding to MAPKAPK2 with a favorable interaction energy together with a high binding affinity, relatively low hepatoxicity and carcinogenicity, high aqueous solubility and intestinal absorption levels, etc., indicating that the two compounds were ideal potential inhibitor materials targeting MAPKAPK2.

CONCLUSION

This study found a group set of OS-related biomarkers of OP, providing further insights for OS functions in the development of OP. This study then focused on one of the macromolecules, MAPKAPK2, to further discover potential novel materials, which was of great significance in guiding the screening of MAPKAPK2 potential materials.

Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein-Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

Discovery of SARS-CoV-2 Nsp14 and Nsp16 Methyltransferase Inhibitors by High-Throughput Virtual Screening

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses mRNA capping to evade the human immune system. The cap formation is performed by the SARS-CoV-2 mRNA cap methyltransferases (MTases) nsp14 and nsp16, which are emerging targets for the development of broad-spectrum antiviral agents. Here, we report results from high-throughput virtual screening against these two enzymes. The docking of seven million commercially available drug-like compounds and S-adenosylmethionine (SAM) co-substrate analogues against both MTases resulted in 80 virtual screening hits (39 against nsp14 and 41 against nsp16), which were purchased and tested using an enzymatic homogeneous time-resolved fluorescent energy transfer (HTRF) assay. Nine compounds showed micromolar inhibition activity (IC₅₀ < 200 μM). The selectivity of the identified inhibitors was evaluated by cross-checking their activity against human glycine N-methyltransferase. The majority of the compounds showed poor selectivity for a specific MTase, no cytotoxic effects, and rather poor cell permeability. Nevertheless, the identified compounds represent good starting points that have the potential to be developed into efficient viral MTase inhibitors.

A computer aided drug discovery based discovery of lead-like compounds against KDM5A for cancers using pharmacophore modeling and high-throughput virtual screening

KDM5A over-expression mediates cancer cell proliferation and promotes resistance toward chemotherapy through epigenetic modifications. As its complete mechanism of action is still unknown, there is no KDM5A specific drug available at clinical level. In the current study, lead compounds for KDM5A were determined through pharmacophore modeling and high-throughput virtual screening from Asinex libraries containing 0.5 million compounds. These virtual hits were further evaluated and filtered for ADMET properties. Finally, 726 compounds were used for docking analysis against KDM5A. On the basis of docking score, 10 top-ranked compounds were selected and further evaluated for non-central nervous system (CNS) and CNS drug-like properties. Among these compounds, N-{[(7-Methyl-4-oxo-1,2,3,4-tetrahydrocyclopenta [c] chromen-9-yl) oxy]acetyl}-l-phenylalanine (G-score: -11.363 kcal/mol) was estimated to exhibit non-CNS properties while 2-(3,4-Dimethoxy-phenyl)-7-methoxy-chromen-4-one (G-score: -7.977 kcal/mol) was evaluated as CNS compound. Docked complexes of both compounds were finally selected for molecular dynamic simulation to examine the stability. This study concluded that both these compounds can serve as lead compounds in the quest of finding therapeutic agents against KDM5A associated cancers.

High-Throughput Virtual Screening of Host Materials and Rational Device Engineering for Highly Efficient Solution-Processed Organic Light-Emitting Diodes

The appropriate choice of host and electron-transporting material (ETM) plays a very crucial role in the generation and collection of radiative excitons in the desired recombination zone of organic light-emitting diodes (OLEDs). Due to the sustainable development of material organic chemistry, there is a big library of functional materials that leads to uncountable combinations of device structures, which might achieve a desirable high device performance. However, there is no appropriate methodology available for the fast virtual screening of organic materials and designing a suitable device structure. Here, we have used the electrical software package SETFOS 4.5 for high-throughput virtual screening of host materials and developed a highly efficient multistack OLED device structure. To further enhance the device performance, a co-host approach has been used, and the final device structure has also been optimized with two different ETMs. The best-optimized Ir(ppy)₃-based solution-processed green OLED device exhibited a maximum power efficiency (PE) of 83.20 lm/W and brightness of 61,362 cd/m² with a driving voltage of 2.1 V without using any light extraction outcoupling techniques, which is the best among the OLEDs in its own category. The developed device structure has also been utilized to fabricate highly efficient blue hazard-free low-color temperature OLEDs for a physiologically friendly light at night. The resultant 2083 K OLED device displayed a maximum PE of 51.4 lm/W and luminance of 44,548 cd/m² with a turn-on voltage of 2.1 V that is also 42 and 104 times safer in terms of retinal protection and ∼4 and ∼11 times safer in terms of melatonin generation when compared with those of a real candle and incandescent bulb, respectively. The observed excellent device performance may be attributed to the balanced charge carrier in the recombination zone, broader emissive layer due to a mixed-host system, less accumulation of charges at the injecting surfaces, well-aligned triplet energy and molecular orbital energy level of the host and guest, and high electron mobility and enhanced hole blocking ability of the employed ETM in the designed OLED device structure.

High-throughput virtual screening approach involving pharmacophore mapping, ADME filtering, molecular docking and MM-GBSA to identify new dual target inhibitors of PfDHODH and PfCytbc1 complex to combat drug resistant malaria

Emerging cases of drug resistance against Artemisinin combination therapies which are the current and the last line of defense against malaria makes the situation very alarming. Due to the liability of single-target drugs to be more prone to drug resistance, the trend of development of dual or multi-target inhibitors is emerging. Recently, a malaria box molecule, MMV007571 which is a well known new permeability pathways inhibitor was investigated to be also multi-targeting Plasmodium falciparum dihydroorotate dehydrogenase and cytochrome bc1 complex. The aspiration behind this study was to use the information of its pharmacophoric features essential for binding as two of its new targets. In this regard, high throughput virtual screening involving pharmacophore mapping, ADME filtering, molecular docking, and MM-GBSA calculations were carried out. This approach has lead to the identification of two new hits namely DT00V1902 and DT00V1922 which binds with -37.85 and -24.65 kcal/mol of more stable ΔG Bind energy at two targets than the lead molecule, MMV007571. The screened compounds are indicated to be carry improvement in binding potential and pharmacokinetic characters as per in silico studies. The authors propose that DT00V1902 and DT00V1922 can be forwarded for experimental validation and clinical studies for antimalarial chemotherapy. Communicated by Ramaswamy H. Sarma.

Structure-Based Discovery of Dual-Target Hits for Acetylcholinesterase and the α7 Nicotinic Acetylcholine Receptors: In Silico Studies and In Vitro Confirmation

Despite extensive efforts in the development of drugs for complex neurodegenerative diseases, treatment often remains challenging or ineffective, and hence new treatment strategies are necessary. One approach is the design of multi-target drugs, which can potentially address the complex nature of disorders such as Alzheimer's disease. We report a method for high throughput virtual screening aimed at identifying new dual target hit molecules. One of the identified hits, N,N-dimethyl-1-(4-(3-methyl-[1,2,4]triazolo[4,3-a]pyrimidin-6-yl)phenyl)ethan-1-amine (Ý;mir-2), has dual-activity as an acetylcholinesterase (AChE) inhibitor and as an α7 nicotinic acetylcholine receptor (α7 nAChR) agonist. Using computational chemistry methods, parallel and independent screening of a virtual compound library consisting of 3,848,234 drug-like and commercially available molecules from the ZINC15 database, resulted in an intersecting set of 57 compounds, that potentially possess activity at both of the two protein targets. Based on ligand efficiency as well as scaffold and molecular diversity, 16 of these compounds were purchased for in vitro validation by Ellman's method and two-electrode voltage-clamp electrophysiology. Ý;mir-2 was shown to exhibit the desired activity profile (AChE IC₅₀ = 2.58 ± 0.96 µM; α7 nAChR activation = 7.0 ± 0.9% at 200 µM) making it the first reported compound with this particular profile and providing further evidence of the feasibility of in silico methods for the identification of novel multi-target hit molecules.

A chemical inhibitor of heat shock protein 78 (HSP78) from Leishmania donovani represents a potential antileishmanial drug candidate

The emergence of resistance to available antileishmanial drugs advocates identification of new drug targets and their inhibitors for visceral leishmaniasis. Here, we identified Leishmania donovani heat shock protein 78 (LdHSP78), a putative caseinolytic protease, as important for parasite infection of host macrophages and a potential therapeutic target. Enrichment of LdHSP78 in infected humans, hamsters, and parasite amastigotes suggested its importance for disease persistence. Heterozygous knockouts of L. donovani HSP78 (LdHSP78+/-) and Leishmania mexicana HSP78 (LmxHSP78+/-) were generated using a flanking UTR-based multifragment ligation strategy and the CRISPR-Cas9 technique, respectively to investigate the significance of HSP78 for disease manifestation. The LdHSP78+/- parasite burden was dramatically reduced in both murine bone marrow-derived macrophages and hamsters, in association with enrichment of proinflammatory cytokines and NO. This finding implies that LdHSP78+/- parasites cannot suppress immune activation and escape NO-mediated toxicity in macrophages. Furthermore, phosphorylation of the mitogen-activated protein kinase p38 was enhanced and phosphorylation of extracellular signal-regulated kinase 1/2 was decreased in cells infected with LdHSP78+/- parasites, compared with WT parasites. Virulence of the LdHSP78+/- strain was restored by episomal addition of the LdHSP78 gene. Finally, using high-throughput virtual screening, we identified P ¹,P ⁵-di(adenosine-5')-pentaphosphate (Ap5A) ammonium salt as an LdHSP78 inhibitor. It selectively induced amastigote death at doses similar to amphotericin B doses, while exhibiting much less cytotoxicity to healthy macrophages than amphotericin B. In summary, using both a genetic knockout approach and pharmacological inhibition, we establish LdHSP78 as a drug target and Ap5A as a potential lead for improved antileishmanial agents.

Vasodilation Elicited by Isoxsuprine, Identified by High-Throughput Virtual Screening of Compound Libraries, Involves Activation of the NO/cGMP and H₂S/KATP Pathways and Blockade of α₁-Adrenoceptors and Calcium Channels

Recently, our research group demonstrated that uvaol and ursolic acid increase NO and H₂S production in aortic tissue. Molecular docking studies showed that both compounds bind with high affinity to endothelial NO synthase (eNOS) and cystathionine gamma-lyase (CSE). The aim of this study was to identify hits with high binding affinity for the triterpene binding-allosteric sites of eNOS and CSE and to evaluate their vasodilator effect. Additionally, the mechanism of action of the most potent compound was explored. A high-throughput virtual screening (HTVS) of 107,373 compounds, obtained from four ZINC database libraries, was performed employing the crystallographic structures of eNOS and CSE. Among the nine top-scoring ligands, isoxsuprine showed the most potent vasodilator effect. Pharmacological evaluation, employing the rat aorta model, indicated that the vasodilation produced by this compound involved activation of the NO/cGMP and H₂S/K_ATP signaling pathways and blockade of α₁-adrenoceptors and L-type voltage-dependent Ca²⁺ channels. Incubation of aorta homogenates in the presence of isoxsuprine caused 2-fold greater levels of H₂S, which supported our preliminary in silico data. This study provides evidence to propose that the vasodilator effect of isoxsuprine involves various mechanisms, which highlights its potential to treat a wide variety of cardiovascular diseases.

The Discovery of Antibacterial Natural Compound Based on Peptide Deformylase

BACKGROUND

In recent years, Staphylococcus aureus have developed resistance to medicines used for the treatment of human infections. Therefore, the search for antibacterial agents of high potency against Staphylococcus aureus is of great concern. Peptide deformylase (PDF), a metalloprotease catalyzing the removal of a formyl group from newly synthesized proteins, has been considered to be an important antibacterial drug target.

OBJECTIVE

To discover novel antibacterial drugs based on Staphylococcus aureus peptide deformylase.

METHOD

PDF-based virtual screening of compounds from Traditional Chinese Medicine Database@Taiwan was performed by Sybyl X2.1 Surflex dock software. Compounds which possess high docking score were used for the following antibacterial experiments to evaluate their antibacterial activities. Kanamycin was also used in the antibacterial experiment as a control substance in the assay. Furthermore, molecular docking studies was applied to elucidate binding interaction between some compounds and PDF. In silico pharmacokinetic and toxicity prediction was explored to explain the reasons why these compounds might stand good chance of providing some pharmaceutical benefits.

RESULTS

Gentiopicroside, protosappanin B, dihydromyricetin and cryptochlorogenic acid with high docking score were used for our subsequent antibacterial assays. The Minimum Inhibitory Concentration (MIC) of kanamycin and gentiopicroside were 0.008 mg·mL-1 and 0.431 mg·mL-1, respectively, other three compounds, protosappanin B, dihydromyricetin and cryptochlorogenic acid have close MIC value of 0.50 mg·mL-1.

CONCLUSION

Dihydromyricetin, with the MIC value of 0.50 mg·mL-1 and relatively high drug score of 0.82, may serve as a novel antibacterial lead compound.

In silico high-throughput virtual screening and molecular dynamics simulation study to identify inhibitor for AdeABC efflux pump of Acinetobacter baumannii

Emergence of multi-drug resistant strains of Acinetobacter baumannii has caused significant health problems and is responsible for high morbidity and mortality. Overexpression of AdeABC efflux system is one of the major mechanisms. In this study, we have focused on overcoming the drug resistance by identifying inhibitors that can effectively bind and inhibit integral membrane protein, AdeB of this efflux pump. We performed homology modeling to generate structure of AdeB using MODELLER v9.16 followed by model refinement using 3D-Refine tool and validated using PSVS, ProsaWeb, ERRAT, etc. The energy minimization of modeled protein was done using Protein preparation wizard application included in Schrodinger suite. High-throughput virtual screening of 159,868 medicinal compounds against AdeB was performed using three sequential docking modes (i.e. HTVS, SP and XP). Furthermore, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis was done using QIKPROP. The selected 123 compounds were further analyzed for binding free energy by molecular mechanics (using prime MM-GBSA). We have also performed enrichment study (ROC curve analysis) to validate our docking results. The selected molecule and its interaction with AdeB were validated by molecular dynamics simulation (MDS) using GROMACS v5.1.4. In silico high-throughput virtual screening and MDS validation identified ZINC01155930 ((4R)-3-(cycloheptoxycarbonyl)-4-(4-etochromen-3-yl)-2-methyl-4,6,7,8-tetrahydroquinolin-5-olate) as a possible inhibitor for AdeB. Hence, it might be a suitable efflux pump inhibitor worthy of further investigation in order to be used for controlling infections caused by Acinetobacter baumannii.

α-Amylase Modulation: Discovery of Inhibitors Using a Multi-Pharmacophore Approach for Virtual Screening

Better control of postprandial hyperglycemia can be achieved by delaying the absorption of glucose resulting from carbohydrate digestion. Because α-amylase initiates the hydrolysis of polysaccharides, the design of α-amylase inhibitors can lead to the development of new treatments for metabolic disorders such as type II diabetes and obesity. In this study, a rational computer-aided approach was developed to identify novel α-amylase inhibitors. Three-dimensional pharmacophores were developed based on the binding mode analysis of six different families of compounds that bind to this enzyme. In a stepwise virtual screening workflow, seven molecules were selected from a library of 1.4 million. Five out of seven biologically tested compounds showed α-amylase inhibition, and the two most potent compounds inhibited α-amylase with IC₅₀ values of 17 and 27 μm. The scaffold benzylideneacetohydrazide was shared by four of the discovered inhibitors, emerging as a novel drug-like non-carbohydrate fragment and constituting a promising lead scaffold for α-amylase inhibition.

Ligand and Structure-Based Approaches for the Identification of Peptide Deformylase Inhibitors as Antibacterial Drugs

Peptide deformylase (PDF) is a metalloprotease catalyzing the removal of a formyl group from newly synthesized proteins, which makes it an important antibacterial drug target. Given the importance of PDF inhibitors like actinonin in antibacterial drug discovery, several reported potent PDF inhibitors were used to develop pharmacophore models using the Galahad module of Sybyl 7.1 software. Generated pharmacophore models were composed of two donor atom centers, four acceptor atom centers and two hydrophobic groups. Model-1 was screened against the Zinc database and several compounds were retrieved as hits. Compounds with Qfit values of more than 60 were employed to perform a molecular docking study with the receptor Escherichia coli PDF, then compounds with docking score values of more than 6 were used to predict the in silico pharmacokinetic and toxicity risk via OSIRIS property explorer. Two known PDF inhibitors were also used to perform a molecular docking study with E. coli PDF as reference molecules. The results of the molecular docking study were validated by reproducing the crystal structure of actinonin. Molecular docking and in silico pharmacokinetic and toxicity prediction studies suggested that ZINC08740166 has a relatively high docking score of 7.44 and a drug score of 0.78.

Structure-Based Drug Design of Small Molecule Peptide Deformylase Inhibitors to Treat Cancer

Human peptide deformylase (HsPDF) is an important target for anticancer drug discovery. In view of the limited HsPDF, inhibitors were reported, and high-throughput virtual screening (HTVS) studies based on HsPDF for developing new PDF inhibitors remain to be reported. We reported here on diverse small molecule inhibitors with excellent anticancer activities designed based on HTVS and molecular docking studies using the crystal structure of HsPDF. The compound M7594_0037 exhibited potent anticancer activities against HeLa, A549 and MCF-7 cell lines with IC_50s of 35.26, 29.63 and 24.63 μM, respectively. Molecular docking studies suggested that M7594_0037 and its three derivatives could interact with HsPDF by several conserved hydrogen bonds. Moreover, the pharmacokinetic and toxicity properties of M7594_0037 and its derivatives were predicted using the OSIRIS property explorer. Thus, M7594_0037 and its derivatives might represent a promising scaffold for the further development of novel anticancer drugs.

Targeting ubiquitination for cancer therapies

Ubiquitination, the structured degradation and turnover of cellular proteins, is regulated by the ubiquitin-proteasome system (UPS). Most proteins that are critical for cellular regulations and functions are targets of the process. Ubiquitination is comprised of a sequence of three enzymatic steps, and aberrations in the pathway can lead to tumor development and progression as observed in many cancer types. Recent evidence indicates that targeting the UPS is effective for certain cancer treatment, but many more potential targets might have been previously overlooked. In this review, we will discuss the current state of small molecules that target various elements of ubiquitination. Special attention will be given to novel inhibitors of E3 ubiquitin ligases, especially those in the SCF family.

Discovery of a new class of liver receptor homolog-1 (LRH-1) antagonists: virtual screening, synthesis and biological evaluation

Targeting LRH-1: Virtual screening and molecular modeling were used to identify novel antagonists of liver receptor homolog-1 (LRH-1), an emerging therapeutic target for breast cancer. Hit compounds were synthesized and biologically assayed, and the preliminary results suggest that raloxifene-based analogues, substituted at the position C-7 of the benzothiophene ring, might generate an inactive protein conformation through binding and thus antagonize this nuclear receptor.