Identification of potent EGFR inhibitors from TCM Database@Taiwan

Deciphering the Precise Target for Saroglitazar Associated Antiangiogenic Effect: A Computational Synergistic Approach

Antidiabetic drugs that have a secondary pharmacological effect on angiogenesis inhibition may help diabetic patients delay or avoid comorbidities caused by angiogenesis including malignancies. In recent studies, saroglitazar has exhibited antiangiogenic effects in diabetic retinopathy. The current study investigates the antiangiogenic effects of saroglitazar utilizing the chicken chorioallantoic membrane (CAM) assay and then identifies its precise mode of action on system-level protein networks. To determine the regulatory effect of saroglitazar on the protein-protein interaction network (PIN), 104 target genes were retrieved and tested using an acid server and Swiss target prediction tools. A string-based interactome was created and analyzed using Cytoscape. It was determined that the constructed network was scale-free, making it biologically relevant. Upon topological analysis of the network, 37 targets were screened on the basis of centrality values. Submodularization of the interactome resulted in the formation of four clusters. A total of 20 common targets identified in topological analysis and modular analysis were filtered. A total of 20 targets were compiled and were integrated into the pathway enrichment analysis using ShinyGO. The majority of hub genes were associated with cancer and PI3-AKT signaling pathways. Molecular docking was utilized to reveal the most potent target, which was validated by using molecular dynamic simulations and immunohistochemical staining on the chicken CAM. The comprehensive study offers an alternate research paradigm for the investigation of antiangiogenic effects using CAM assays. This was followed by the identification of the precise off-target use of saroglitazar using system biology and network pharmacology to inhibit angiogenesis.

Development of database structure and indexing for siddha medicine system - A platform for siddha literature analytics

Background

Siddha Medicine system is one among the oldest traditional systems of medicines in India and has its entire literature in the Tamil language in the form of poems (padal in tamil). Even if the siddha poems are available in public domain, they are not known to other parts of the world because, researchers of other languages are not able to understand the contents of these poems and there exists a language barrier. Hence there is a need to develop a system to extract structured information from these texts to facilitate searching, comparing, analysis and implementing.

Objective

This study aimed at creating a comprehensive digital database system that systematically stores information from classical Siddha poems and to develop a web portal to facilitate information retrieval for comparative and logical analysis of Siddha content.

Methods

We developed an expert system for siddha (eSS) that can collect, annotate classical siddha text, and visualizes the pattern in siddha medical prescriptions (Siddha Formulations) that can be useful for exploration in this system using modern techniques like machine learning and artificial learning. eSS has the following three aspects: (1) extracting data from Siddha classical text (2) defining the annotation method and (3) visualizing the patterns in the medical prescriptions based on multiple factors mentioned in the Siddha system of medicine. The data from three books were extracted, annotated and integrated into the developed eSS database. The annotations were used for analyzing the pattern in the drug prescriptions as a pilot work.

Results

Overall, 110 medicinal preparations from 2 Siddhars (Agathiyar and Theran) were extracted and annotated. The generated annotations were indexed into the data repository created in eSS. The system can compare and visualize individual and multiple prescriptions to generate a hypothesis for siddha practitioners and researchers.

Conclusions

We propose an eSS framework using standard siddha terminologies created by WHO to have a standard expert system for siddha. This proof-of-concept work demonstrated that the database can effectively process and visualize data from siddha formulations which can help students, researchers from siddha and other various fields to expand their research in herbal medicines.

Topomer-CoMFA proposed as a tool to construct dual EGFR/HER-2 models

Protein kinases (in this case, HER-2 and EGFR) are involved in cancer-related diseases. Some reports have shown unique CoMFA models using the sum of activities expressed as pIC₅₀ (-log IC₅₀), as the classical CoMFA technique would not be the best strategy to construct models for multitarget therapy considering that the molecular alignment will not be the same for different targets. An alternative for this problem is the use of Topomer-CoMFA, a variation of CoMFA, which does not require the alignment step in the generation of 3D models. In this study, we propose the combined use of the sum of activities and Topomer-CoMFA for the construction of a unique dual 3D model considering the inhibitory activities against EGFR and HER-2. For this, 88 compounds from the literature were divided into two groups: training (71) and test (17) sets. The biological activity of each compound, expressed as IC₅₀ for EGFR and HER-2, was transformed into pIC₅₀, summed, and used as the dependent variable in the Topomer-CoMFA analyses. The obtained model was considered statistically robust in the prediction of the dual activity of new compounds. Finally, based on the obtained model, we proposed structural modifications to some of the compounds used to improve the biological data. From the 3D model, we suggested new derivative compounds with improved biological activity for both targets. Therefore, the combination of the techniques proposed in this study proves to be a good strategy to construct better statistical models that can predict biological activities in multitarget systems.

Identification of New Mycobacterium tuberculosis Proteasome Inhibitors Using a Knowledge-Based Computational Screening Approach

Mycobacterium tuberculosis (Mtb) is a deadly tuberculosis (TB)-causing pathogen. The proteasome is vital to the survival of Mtb and is therefore validated as a potential target for anti-TB therapy. Mtb resistance to existing antibacterial agents has enhanced drastically, becoming a worldwide health issue. Therefore, new potential therapeutic agents need to be developed that can overcome the complications of TB. With this purpose, in the present study, 224,205 natural compounds from the ZINC database have been screened against the catalytic site of Mtb proteasome by the computational approach. The best scoring hits, ZINC3875469, ZINC4076131, and ZINC1883067, demonstrated robust interaction with Mtb proteasome with binding energy values of −7.19, −7.95, and −7.21 kcal/mol for the monomer (K-chain) and −8.05, −9.10, and −7.07 kcal/mol for the dimer (both K and L chains) of the beta subunit, which is relatively higher than that of reference compound HT1171 (−5.83 kcal/mol (monomer) and −5.97 kcal/mol (dimer)). In-depth molecular docking of top-scoring compounds with Mtb proteasome reveals that amino acid residues Thr1, Arg19, Ser20, Thr21, Gln22, Gly23, Asn24, Lys33, Gly47, Asp124, Ala126, Trp129, and Ala180 are crucial in binding. Furthermore, a molecular dynamics study showed steady-state interaction of hit compounds with Mtb proteasome. Computational prediction of physicochemical property assessment showed that these hits are non-toxic and possess good drug-likeness properties. This study proposed that these compounds could be utilized as potential inhibitors of Mtb proteasome to combat TB infection. However, there is a need for further bench work experiments for their validation as inhibitors of Mtb proteasome.

Defining the mobility range of a hinge-type connection using molecular dynamics and metadynamics

A designed disulfide-rich β-hairpin peptide that dimerizes spontaneously served as a hinge-type connection between proteins. Here, we analyze the range of dynamics of this hinge dimer with the aim of proposing new applications for the DNA-encodable peptide and establishing guidelines for the computational analysis of other disulfide hinges. A recent structural analysis based on nuclear magnetic resonance spectroscopy and ion mobility spectrometry revealed an averaged conformation in the hinge region which motivated us to investigate the dynamic behavior using a combination of molecular dynamics simulation, metadynamics and free energy surface analysis to characterize the conformational space available to the hinge. Principal component analysis uncovered two slow modes of the peptide, namely, the opening and closing motion and twisting of the two β-hairpins assembling the hinge. Applying a collective variable (CV) that mimics the first dominating mode, led to a major expansion of the conformational space. The description of the dynamics could be achieved by analysis of the opening angle and the twisting of the β-hairpins and, thus, offers a methodology that can also be transferred to other derivatives. It has been demonstrated that the hinge peptide’s lowest energy conformation consists of a large opening angle and strong twist but is separated by small energy barriers and can, thus, adopt a closed and untwisted structure. With the aim of proposing further applications for the hinge peptide, we simulated its behavior in the sterically congested environment of a four-helix bundle. Preliminary investigations show that one helix is pushed out and a three-helix bundle forms. The insights gained into the dynamics of the tetra-disulfide peptide and analytical guidelines developed in this study may contribute to the understanding of the structure and function of more complex hinge-type proteins, such as the IgG antibody family.

Freely Accessible Chemical Database Resources of Compounds for In Silico Drug Discovery

BACKGROUND

In silico drug discovery has been proved to be a solidly established key component in early drug discovery. However, this task is hampered by the limitation of quantity and quality of compound databases for screening. In order to overcome these obstacles, freely accessible database resources of compounds have bloomed in recent years. Nevertheless, how to choose appropriate tools to treat these freely accessible databases is crucial. To the best of our knowledge, this is the first systematic review on this issue.

OBJECTIVE

The existed advantages and drawbacks of chemical databases were analyzed and summarized based on the collected six categories of freely accessible chemical databases from literature in this review.

RESULTS

Suggestions on how and in which conditions the usage of these databases could be reasonable were provided. Tools and procedures for building 3D structure chemical libraries were also introduced.

CONCLUSION

In this review, we described the freely accessible chemical database resources for in silico drug discovery. In particular, the chemical information for building chemical database appears as attractive resources for drug design to alleviate experimental pressure.

TNF Receptor Type II as an Emerging Drug Target for the Treatment of Cancer, Autoimmune Diseases, and Graft-Versus-Host Disease: Current Perspectives and In Silico Search for Small Molecule Binders

There is now compelling evidence that TNF receptor type II (TNFR2) is predominantly expressed on CD4⁺Foxp3⁺ regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs), and plays a major role in the expansion and function of Tregs and MDSCs. Consequently, targeting of TNFR2 by either antagonists or agonists may represent a novel strategy in the treatment of cancer and autoimmune diseases, by downregulating or upregulating suppressor cell activity. The advance in the understanding of complex structure of TNFR2 and its binding with TNF at molecular levels offers opportunity for structure-guided drug discovery. This article reviews the current evidences regarding the decisive role of TNFR2 in immunosuppressive function of Tregs and MDSCs, and the current effort to develop novel TNFR2-targeting therapeutic agents in the treatment of cancer, autoimmune diseases, and graft-versus-host disease. To shed light on the potential TNFR2-targeting small molecules, we for the first time performed virtual screening of 400,000 natural compounds against the two TNF-binding sites, regions 3 and 4, of TNFR2. Our result showed that the top hits at region 4 had slightly higher docking energies than those at region 3. Nevertheless, free energy calculation from the TNF–TNFR2 molecular dynamics simulation revealed that the binding strength of TNF in region 3 is only one-tenth of that in region 4. This suggests that region 3 is a potentially more viable binding site to be targeted by small molecules than region 4. Therefore, the effectiveness in targeting region 3 of TNFR2 deserves further investigation.

Discovery of Potential Inhibitors of Squalene Synthase from Traditional Chinese Medicine Based on Virtual Screening and In Vitro Evaluation of Lipid-Lowering Effect

Squalene synthase (SQS), a key downstream enzyme involved in the cholesterol biosynthetic pathway, plays an important role in treating hyperlipidemia. Compared to statins, SQS inhibitors have shown a very significant lipid-lowering effect and do not cause myotoxicity. Thus, the paper aims to discover potential SQS inhibitors from Traditional Chinese Medicine (TCM) by the combination of molecular modeling methods and biological assays. In this study, cynarin was selected as a potential SQS inhibitor candidate compound based on its pharmacophoric properties, molecular docking studies and molecular dynamics (MD) simulations. Cynarin could form hydrophobic interactions with PHE54, LEU211, LEU183 and PRO292, which are regarded as important interactions for the SQS inhibitors. In addition, the lipid-lowering effect of cynarin was tested in sodium oleate-induced HepG2 cells by decreasing the lipidemic parameter triglyceride (TG) level by 22.50%. Finally. cynarin was reversely screened against other anti-hyperlipidemia targets which existed in HepG2 cells and cynarin was unable to map with the pharmacophore of these targets, which indicated that the lipid-lowering effects of cynarin might be due to the inhibition of SQS. This study discovered cynarin is a potential SQS inhibitor from TCM, which could be further clinically explored for the treatment of hyperlipidemia.

Structural and energetic basis for the molecular recognition of dual synthetic vs. natural inhibitors of EGFR/HER2

Activation of EGFR starts by ligand binding at the extracellular domain which results in homo and heterodimerization, leading to phosphorylation, activation of downstream signaling pathways which upregulate expression of genes, proliferation and angiogenesis. Abnormalities in the expression of EGFR play a critical role in the development of different types of cancer. HER2 is the preferred heterodimerization partner for EGFR; this biological characteristic together with the high percentage of structural homology has been exploited in the design of dual synthetic inhibitors against EGFR/HER2. Herein we combined structural data and molecular dynamics (MD) simulations coupled to an MMGBSA approach to provide insight into the binding mechanism between two dual synthetics (lapatinib and TAK-285) and one dual natural inhibitor (EGCG) which target EGFR/HER2. In addition, we proposed some EGCG derivatives which were filtered through in silico screening. Structural analysis demonstrated that the coupling of synthetic, natural or newly designed compounds impacts the conformational space of EGFR and HER2 differently. Energetic analysis points out that lapatinib and TAK-285 have better affinity for inactive EGFR than the active EGFR state or HER2, whereas some EGCG derivatives seem to form binding affinities similar to those observed for lapatinib or TAK-285.

New sulfurated derivatives of cinnamic acids and rosmaricine as inhibitors of STAT3 and NF-κB transcription factors

A set of new sulfurated drug hybrids, mainly derived from caffeic and ferulic acids and rosmaricine, has been synthesized and their ability to inhibit both STAT3 and NF-κB transcription factors have been evaluated. Results showed that most of the new hybrid compounds were able to strongly and selectively bind to STAT3, whereas the parent drugs were devoid of this ability at the tested concentrations. Some of them were also able to inhibit the NF-κB transcriptional activity in HCT-116 cell line and inhibited HCT-116 cell proliferation in vitro with IC50 in micromolar range, thus suggesting a potential anticancer activity. Taken together, our study described the identification of new derivatives with dual STAT3/NF-κB inhibitory activity, which may represent hit compounds for developing multi-target anticancer agents.

Investigation of naphthofuran moiety as potential dual inhibitor against BACE-1 and GSK-3β: molecular dynamics simulations, binding energy, and network analysis to identify first-in-class dual inhibitors against Alzheimer's disease

BACE-1 and GSK-3β are potential therapeutic drug targets for Alzheimer's disease. Recently, both the targets received attention for designing dual inhibitors for Alzheimer's disease. Until now, only two-scaffold triazinone and curcumin have been reported as BACE-1 and GSK-3β dual inhibitors. Docking, molecular dynamics, clustering, binding energy, and network analysis of triazinone derivatives with BACE-1 and GSK-3β was performed to get molecular insight into the first reported dual inhibitor. Further, we designed and evaluated a naphthofuran series for its ability to inhibit BACE-1 and GSK-3β with the computational approaches. Docking study of naphthofuran series showed a good binding affinity towards both the targets. Molecular dynamics, binding energy, and network analysis were performed to compare their binding with the targets and amino acids responsible for binding. Naphthofuran series derivatives showed good interaction within the active site residues of both of the targets. Hydrogen bond occupancy and binding energy suggested strong binding with the targets. Dual-inhibitor binding was mostly governed by the hydrophobic interactions for both of the targets. Per residue energy decomposition and network analysis identified the key residues involved in the binding and inhibiting BACE-1 and GSK-3β. The results indicated that naphthofuran series derivative 11 may be a promising first-in-class dual inhibitor against BACE-1 and GSK-3β. This naphthofuran series may be further explored to design better dual inhibitors. Graphical abstract Naphthofuran derivative as a dual inhibitor for BACE-1 and GSK-3β.

Computational Investigation into the Interactions of Traditional Chinese Medicine Molecules of WenQingYin with GluR2

Docking and molecular dynamics simulations have been carried out to investigate the interaction of a traditional Chinese medicine, WenQingYin, with the glutamate receptor 2 (GluR2) subunit of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor. Four representative drug components of WenQingYin, namely 2-(3,4-dihydroxyphenyl)-5,6,7-trihydroxy-4H-chromen-4-one (PHF), 4-hydroxy-3-methoxybenzoic acid (HMB), 4-(2,3-dihydroxy-3-methylbutoxy)-7H-furo[3,2-g]chromen-7-one (DHMBP) and methyl 7-formylcyclopenta[c]pyran-4-carboxylate (cerbinal), and their complexes with GluR2 were simulated. Our results show that PHF, HMB, and DHMBP formed a partial hydrogen bond with GluR2 in its ligand-binding domain. However, cerbinal was not stable in the ligand-binding domain of GluR2 and induced a significant change in the structure of GluR2. Three-dimensional plots represent the contact and movement situation of the traditional Chinese medicine molecules in the ligand-binding domain. The combined results of the docking and molecular dynamics simulations provide insight into the interaction between these traditional Chinese medicine molecules and proteins.

Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)

We present an in silico drug discovery pipeline developed and applied for the identification and virtual screening of small-molecule Protein-Protein Interaction (PPI) compounds that act as dual inhibitors of TNF and RANKL through the trimerization interface. The cheminformatics part of the pipeline was developed by combining structure-based with ligand-based modeling using the largest available set of known TNF inhibitors in the literature (2481 small molecules). To facilitate virtual screening, the consensus predictive model was made freely available at: http://enalos.insilicotox.com/TNFPubChem/. We thus generated a priority list of nine small molecules as candidates for direct TNF function inhibition. In vitro evaluation of these compounds led to the selection of two small molecules that act as potent direct inhibitors of TNF function, with IC50 values comparable to those of a previously-described direct inhibitor (SPD304), but with significantly reduced toxicity. These molecules were also identified as RANKL inhibitors and validated in vitro with respect to this second functionality. Direct binding of the two compounds was confirmed both for TNF and RANKL, as well as their ability to inhibit the biologically-active trimer forms. Molecular dynamics calculations were also carried out for the two small molecules in each protein to offer additional insight into the interactions that govern TNF and RANKL complex formation. To our knowledge, these compounds, namely T8 and T23, constitute the second and third published examples of dual small-molecule direct function inhibitors of TNF and RANKL, and could serve as lead compounds for the development of novel treatments for inflammatory and autoimmune diseases.

Recent Advancements in Docking Methodologies

Nowadays molecular docking has become an important methodology in CADD (Computer-Aided Drug Design)-assisted drug discovery process. It is an important computational tool widely used to predict binding mode, binding affinity and binding free energy of a protein-ligand complex. The important factors responsible for accurate results in docking studies are correct binding site prediction, use of suitable small-molecule databases, consistent docking pose, high dock score with good MD (Molecular Dynamics), clarity whether the compound is an inhibitor or agonist, etc. However, still there are several limitations which make it difficult to obtain accurate results from docking studies. In this chapter, the main focus is on recent advancements in various aspects of molecular docking such as ligand sampling, protein flexibility, scoring functions, fragment docking, post-processing, docking into homology models and protein-protein docking.

Gliptins in managing diabetes - Reviewing computational strategy

The pace of anti-diabetic drug discovery is very slow in spite of increasing rate of prevalence of Type 2 Diabetes which remains a major public health concern. Though extensive research steps are taken in the past decade, yet craves for better new treatment strategies to overcome the current scenario. One such general finding is the evolution of gliptins which discriminately inhibits DPP4 (Dipeptidyl peptidase-4) enzyme. Although the mechanism of action of gliptin is highly target oriented and accurate, still its long-term use stands unknown. This step calls for a fast, flexible, and cost-effective strategies to meet the demands of producing arrays of high-content lead compounds with improved efficiency for better clinical success. The present review highlights the available gliptins in the market and also other naturally occurring DPP4 enzyme inhibitors. Along with describing the known inhibitors and their origin in this review, we attempted to identify a probable new lead compounds using advanced computational techniques. In this context, computational methods that integrate the knowledge of proteins and drug responses were utilized in prioritizing targets and designing drugs towards clinical trials with better efficacy. The compounds obtained as a result of virtual screening were compared with the commercially available gliptin in the market to have better efficiency in the identification and validation of the potential DPP4 inhibitors. The combinatorial computational methods used in the present study identified Compound 1: 25022354 as promising inhibitor.

Simultaneous targeting of MyD88 and Nur77 as an effective approach for the treatment of inflammatory diseases

Myeloid differentiation primary response protein 88 (MyD88) has long been considered a central player in the inflammatory pathway. Recent studies clearly suggest that it is an important therapeutic target in inflammation. On the other hand, a recent study on the interaction between the orphan nuclear receptor (Nur77) and p38α, leading to increased lipopolysaccharide-induced hyperinflammatory response, suggests this binary complex as a therapeutic target. In this study, we have designed inhibitors that can inhibit both MyD88 and Nur77 at the same time. Since both MyD88 and Nur77 are an integral part of the pathways involving lipopolysaccharide-induced activation of NF-κB-mediated inflammation, we tried to target both proteins with the same library in order to retrieve compounds having dual inhibitory properties. To perform this, we developed a homodimeric model of MyD88 and, along with the crystal structure of Nur77, screened a virtual library of compounds from the traditional Chinese medicine database containing ~61,000 compounds. We analyzed the resulting hits for their efficacy for dual binding and probed them for developing a common pharmacophore model that could be used as a prototype to screen compound libraries as well as to guide combinatorial library design to search for ideal dual-target inhibitors. Thus, our study explores the identification of novel leads having dual inhibiting effects due to binding to both MyD88 and Nur77 targets.

Computationally Guided Identification of Novel Mycobacterium tuberculosis GlmU Inhibitory Leads, Their Optimization, and in Vitro Validation

Mycobacterium tuberculosis (Mtb) infections are causing serious health concerns worldwide. Antituberculosis drug resistance threatens the current therapies and causes further need to develop effective antituberculosis therapy. GlmU represents an interesting target for developing novel Mtb drug candidates. It is a bifunctional acetyltransferase/uridyltransferase enzyme that catalyzes the biosynthesis of UDP-N-acetyl-glucosamine (UDP-GlcNAc) from glucosamine-1-phosphate (GlcN-1-P). UDP-GlcNAc is a substrate for the biosynthesis of lipopolysaccharide and peptidoglycan that are constituents of the bacterial cell wall. In the current study, structure and ligand based computational models were developed and rationally applied to screen a drug-like compound repository of 20,000 compounds procured from ChemBridge DIVERSet database for the identification of probable inhibitors of Mtb GlmU. The in vitro evaluation of the in silico identified inhibitor candidates resulted in the identification of 15 inhibitory leads of this target. Literature search of these leads through SciFinder and their similarity analysis with the PubChem training data set (AID 1376) revealed the structural novelty of these hits with respect to Mtb GlmU. IC50 of the most potent identified inhibitory lead (5810599) was found to be 9.018 ± 0.04 μM. Molecular dynamics (MD) simulation of this inhibitory lead (5810599) in complex with protein affirms the stability of the lead within the binding pocket and also emphasizes on the key interactive residues for further designing. Binding site analysis of the acetyltransferase pocket with respect to the identified structural moieties provides a thorough analysis for carrying out the lead optimization studies.

Network pharmacology applications to map the unexplored target space and therapeutic potential of natural products

It is widely accepted that drug discovery often requires a systems-level polypharmacology approach to tackle problems such as lack of efficacy and emerging resistance of single-targeted compounds. Network pharmacology approaches are increasingly being developed and applied to find new therapeutic opportunities and to re-purpose approved drugs. However, these recent advances have been relatively slow to be translated into the field of natural products. Here, we argue that a network pharmacology approach would enable an effective mapping of the yet unexplored target space of natural products, hence providing a systematic means to extend the druggable space of proteins implicated in various complex diseases. We give an overview of the key network pharmacology concepts and recent experimental-computational approaches that have been successfully applied to natural product research, including unbiased elucidation of mechanisms of action as well as systematic prediction of effective therapeutic combinations. We focus specifically on anticancer applications that use in vivo and in vitro functional phenotypic measurements, such as genome-wide transcriptomic response profiles, which enable a global modelling of the multi-target activity at the level of the biological pathways and interaction networks. We also provide representative examples of other disease applications, databases and tools as well as existing and emerging resources, which may prove useful for future natural product research. Finally, we offer our personal view of the current limitations, prospective developments and open questions in this exciting field.

Discovery of new Mycobacterium tuberculosis proteasome inhibitors using a knowledge-based computational screening approach

Mycobacterium tuberculosis bacteria cause deadly infections in patients [Corrected]. The rise of multidrug resistance associated with tuberculosis further makes the situation worse in treating the disease. M. tuberculosis proteasome is necessary for the pathogenesis of the bacterium validated as an anti-tubercular target, thus making it an attractive enzyme for designing Mtb inhibitors. In this study, a computational screening approach was applied to identify new proteasome inhibitor candidates from a library of 50,000 compounds. This chemical library was procured from the ChemBridge (20,000 compounds) and the ChemDiv (30,000 compounds) databases. After a detailed analysis of the computational screening results, 50 in silico hits were retrieved and tested in vitro finding 15 compounds with IC₅₀ values ranging from 35.32 to 64.15 μM on lysate. A structural analysis of these hits revealed that 14 of these compounds probably have non-covalent mode of binding to the target and have not reported for anti-tubercular or anti-proteasome activity. The binding interactions of all the 14 protein-inhibitor complexes were analyzed using molecular docking studies. Further, molecular dynamics simulations of the protein in complex with the two most promising hits were carried out so as to identify the key interactions and validate the structural stability.

Susceptible gene of stasis-stagnation constitution from genome-wide association study related to cardiovascular disturbance and possible regulated traditional Chinese medicine

Background

This study identified susceptible loci related to the Yu-Zhi (YZ) constitution, which indicates stasis-stagnation, found in a genome-wide association study (GWAS) in patients with type 2 diabetes and possible regulated traditional Chinese medicine (TCM) using docking and molecular dynamics (MD) simulation.

Methods

Non-aboriginal Taiwanese with type 2 diabetes were recruited. Components of the YZ constitution were assessed by a self-reported questionnaire. Genome-wide SNP genotypes were obtained using the Illumina HumanHap550 platform. The world’s largest TCM database (http://tcm.cmu.edu.tw/) was employed to investigate potential compounds for PON2 interactions.

Results

The study involved 1,021 unrelated individuals with type 2 diabetes. Genotyping data were obtained from 947 of the 1,021 participants. The GWAS identified 22 susceptible single nucleotide polymorphisms on 13 regions of 11 chromosomes for the YZ constitution. Genotypic distribution showed that PON2 on chromosome 7 was most significantly associated with the risk of the YZ constitution. Docking and MD simulation indicated 13-hydroxy-(9E_11E)-octadecadienoic acid was the most stable TCM ligand.

Conclusions

Risk loci occurred in PON2, which has antioxidant properties that might protect against atherosclerosis and hyperglycemia, showing it is a susceptible gene for the YZ constitution and possible regulation by 13-hydroxy-(9E_11E)-octadecadienoic acid.

Electronic supplementary material

The online version of this article (doi:10.1186/s12906-015-0761-x) contains supplementary material, which is available to authorized users.

Potential smoothened inhibitor from traditional Chinese medicine against the disease of diabetes, obesity, and cancer

Nowadays, obesity becomes a serious global problem, which can induce a series of diseases such as type 2 diabetes mellitus, cancer, cardiovascular disease, metabolic syndrome, and stoke. For the mechanisms of diseases, the hedgehog signaling pathway plays an important role in body patterning during embryogenesis. For this reason, smoothened homologue (Smo) protein had been indicated as the drug target. In addition, the small-molecule Smo inhibitor had also been used in oncology clinical trials. To improve drug development of TCM compounds, we aim to investigate the potent lead compounds as Smo inhibitor from the TCM compounds in TCM Database@Taiwan. The top three TCM compounds, precatorine, labiatic acid, and 2,2′-[benzene-1,4-diylbis(methanediyloxybenzene-4,1-diyl)]bis(oxoacetic acid), have displayed higher potent binding affinities than the positive control, LY2940680, in the docking simulation. After MD simulations, which can optimize the result of docking simulation and validate the stability of H-bonds between each ligand and Smo protein under dynamic conditions, top three TCM compounds maintain most of interactions with Smo protein, which keep the ligand binding stable in the binding domain. Hence, we propose precatorine, labiatic acid, and 2,2′-[benzene-1,4-diylbis(methanediyloxybenzene-4,1-diyl)]bis(oxoacetic acid) as potential lead compounds for further study in drug development process with the Smo protein.

In silico investigation of potential TRAF6 inhibitor from traditional Chinese medicine against cancers

It has been indicated that tumor necrosis factor receptor-associated factor-6 (TRAF6) will upregulate the expression of hypoxia-inducible factor-1α (HIF-1α) and promote tumor angiogenesis. TRAF6 proteins can be treated as drug target proteins for a differentiation therapy against cancers. As structural disordered disposition in the protein may induce the side-effect and reduce the occupancy for ligand to bind with target protein, PONDR-Fit protocol was performed to predict the disordered disposition in TRAF6 protein before virtual screening. TCM compounds from the TCM Database@Taiwan were employed for virtual screening to identify potent compounds as lead compounds of TRAF6 inhibitor. After virtual screening, the MD simulation was performed to validate the stability of interactions between TRAF6 proteins and each ligand. The top TCM compounds, tryptophan, diiodotyrosine, and saussureamine C, extracted from Saussurea lappa Clarke, Bos taurus domesticus Gmelin, and Lycium chinense Mill., have higher binding affinities with target protein in docking simulation. However, the docking pose of TRAF6 protein with tryptophan is not stable under dynamic condition. For the other two TCM candidates, diiodotyrosine and saussureamine C maintain the similar docking poses under dynamic conditions. Hence, we propose the TCM compounds, diiodotyrosine and saussureamine C, as potential candidates as lead compounds for further study in drug development process with the TRAF6 protein against cancer.

The inhibition of folylpolyglutamate synthetase (folC) in the prevention of drug resistance in Mycobacterium tuberculosis by traditional Chinese medicine

Tuberculosis (TB) is an infectious disease caused by many strains of mycobacteria, but commonly Mycobacterium tuberculosis. As a possible method of reducing the drug resistance of M. tuberculosis, this research investigates the inhibition of Folylpolyglutamate synthetase, a protein transcript from the resistance association gene folC. After molecular docking to screen the traditional Chinese medicine (TCM) database, the candidate TCM compounds, with Folylpolyglutamate synthetase, were selected by molecular dynamics. The 10,000 ps simulation in association with RMSD analysis and total energy and structural variation defined the protein-ligand interaction. The selected TCM compounds Saussureamine C, methyl 3-O-feruloylquinate, and Labiatic acid have been found to inhibit the activity of bacteria and viruses and to regulate immunity. We also suggest the possible pathway in protein for each ligand. Compared with the control, similar interactions and structural variations indicate that these compounds might have an effect on Folylpolyglutamate synthetase. Finally, we suggest Saussureamine C is the best candidate compound as the complex has a high score, maintains its structural composition, and has a larger variation value than the control, thus inhibiting the drug resistance ability of Mycobacterium tuberculosis.

Possible inhibitor from traditional Chinese medicine for the β form of calcium-dependent protein kinase type II in the treatment of major depressive disorder

Recently, an important topic of major depressive disorder (MDD) had been published in 2013. MDD is one of the most prevalent and disabling mental disorders. Consequently, much research is being undertaken into the causes and treatment. It has been found that inhibition of the β form of calcium/calmodulin-dependent protein kinase type II (β-CaMKII) can ameliorate the disorder. Upon screening the traditional Chinese medicine (TCM) database by molecular docking, sengesterone, labiatic acid, and methyl 3-O-feruloylquinate were selected for molecular dynamics. After 20 ns simulation, the RMSD, total energy, and structure variation could define the protein-ligand interaction. Furthermore, sengesterone, the principle candidate compound, has been found to have an effect on the regulation of emotions and memory development. In structure variation, we find the sample functional group of important amino acids make the protein stable and have limited variation. Due to similarity of structure variations, we suggest that these compounds may have an effect on β-CaMKII and that sengesterone may have a similar efficacy as the control. However labiatic acid may be a stronger inhibitor of β-CaMKII based on the larger RMSD and variation.

In silico investigation of potential mTOR inhibitors from traditional Chinese medicine for treatment of Leigh syndrome

A recent research demonstrates that the inhibition of mammalian target of rapamycin (mTOR) improves survival and health for patients with Leigh syndrome. mTOR proteins can be treated as drug target proteins against Leigh syndrome and other mitochondrial disorders. In this study, we aim to identify potent TCM compounds from the TCM Database@Taiwan as lead compounds of mTOR inhibitors. PONDR-Fit protocol was employed to predict the disordered disposition in mTOR protein before virtual screening. After virtual screening, the MD simulation was employed to validate the stability of interactions between each ligand and mTOR protein in the docking poses from docking simulation. The top TCM compounds, picrasidine M and acerosin, have higher binding affinities with target protein in docking simulation than control. There have H-bonds with residues Val2240 and π interactions with common residue Trp2239. After MD simulation, the top TCM compounds maintain similar docking poses under dynamic conditions. The top two TCM compounds, picrasidine M and acerosin, were extracted from Picrasma quassioides (D. Don) Benn. and Vitex negundo L. Hence, we propose the TCM compounds, picrasidine M and acerosin, as potential candidates as lead compounds for further study in drug development process with the mTOR protein against Leigh syndrome and other mitochondrial disorders.

Lead screening for CXCR4 of the human HIV infection receptor inhibited by traditional Chinese medicine

The acquired immunodeficiency syndrome (AIDS) is a serious worldwide disease caused by the human immunodeficiency virus (HIV) infection. Recent research has pointed out that the G protein-coupled chemokine receptor CXCR4 and the coreceptor C-C chemokine receptor type 5 (CCR5) are important targets for HIV infection. The traditional Chinese medicine (TCM) database has been screened for candidate compounds by simulating molecular docking and molecular dynamics against HIV. Saussureamine C, 5-hydroxy-L-tryptophan, and diiodotyrosine are selected based on the highest docking score. The molecular dynamics is helpful in the analysis and detection of protein-ligand interactions. According to the analysis of docking poses, hydrophobic interactions, hydrogen bond variations, and the comparison of the effect on CXCR4 and CCR5, these results indicate Saussureamine C may have better effect on these two receptors. But for some considerations, diiodotyrosine could make the largest variation and may have some efficacy contrary to expectations.

QSAR-based models for designing quinazoline/imidazothiazoles/pyrazolopyrimidines based inhibitors against wild and mutant EGFR

Overexpression of EGFR is responsible for causing a number of cancers, including lung cancer as it activates various downstream signaling pathways. Thus, it is important to control EGFR function in order to treat the cancer patients. It is well established that inhibiting ATP binding within the EGFR kinase domain regulates its function. The existing quinazoline derivative based drugs used for treating lung cancer that inhibits the wild type of EGFR. In this study, we have made a systematic attempt to develop QSAR models for designing quinazoline derivatives that could inhibit wild EGFR and imidazothiazoles/pyrazolopyrimidines derivatives against mutant EGFR. In this study, three types of prediction methods have been developed to design inhibitors against EGFR (wild, mutant and both). First, we developed models for predicting inhibitors against wild type EGFR by training and testing on dataset containing 128 quinazoline based inhibitors. This dataset was divided into two subsets called wild_train and wild_valid containing 103 and 25 inhibitors respectively. The models were trained and tested on wild_train dataset while performance was evaluated on the wild_valid called validation dataset. We achieved a maximum correlation between predicted and experimentally determined inhibition (IC₅₀) of 0.90 on validation dataset. Secondly, we developed models for predicting inhibitors against mutant EGFR (L858R) on mutant_train, and mutant_valid dataset and achieved a maximum correlation between 0.834 to 0.850 on these datasets. Finally, an integrated hybrid model has been developed on a dataset containing wild and mutant inhibitors and got maximum correlation between 0.761 to 0.850 on different datasets. In order to promote open source drug discovery, we developed a webserver for designing inhibitors against wild and mutant EGFR along with providing standalone (http://osddlinux.osdd.net/) and Galaxy (http://osddlinux.osdd.net:8001) version of software. We hope our webserver (http://crdd.osdd.net/oscadd/ntegfr/) will play a vital role in designing new anticancer drugs.

In silico investigation of potential pyruvate kinase M2 regulators from traditional Chinese medicine against cancers

A recent research in cancer research demonstrates that tumor-specific pyruvate kinase M2 (PKM2) plays an important role in chromosome segregation and mitosis progression of tumor cells. To improve the drug development of TCM compounds, we aim to identify potent TCM compounds as lead compounds of PKM2 regulators. PONDR-Fit protocol was utilized to predict the disordered disposition in the binding domain of PKM2 protein before virtual screening as the disordered structure in the protein may cause the side effect and downregulation of the possibility of ligand to bind with target protein. MD simulation was performed to validate the stability of interactions between PKM2 proteins and each ligand after virtual screening. The top TCM compounds, saussureamine C and precatorine, extracted from Lycium chinense Mill. and Abrus precatorius L., respectively, have higher binding affinities with target protein in docking simulation than control. They have stable H-bonds with residues A:Lys311 and some other residues in both chains of PKM2 protein. Hence, we propose the TCM compounds, saussureamine C and precatorine, as potential candidates as lead compounds for further study in drug development process with the PKM2 protein against cancer.

Treatment of cardiovascular disease by traditional Chinese medicine against pregnane X receptor

Recently, cardiovascular disease, also known as loop circulatory system diseases or disorders, is one of the serious diseases including heart disease, stroke, atherosclerosis, myocardial infarction, hypertension, hypotension, and thrombosis. Human pregnane X receptor, PXR, plays a crucial role in exogenous and endobiotic metabolism for rabbit, rat, mouse, and human. The PXR activation can protect the blood vessels from damage of hazardous substances. In this study we aim to investigate the potent lead compounds as PXR receptor agonist against cardiovascular disease. To improve drug development of TCM compounds, we aim to investigate the potent lead compounds as PXR agonists from the TCM compounds in TCM Database@Taiwan. The top three TCM compounds, bis(4-hydroxybenzyl) ether mono-β-D-glucopyranoside (BEMG), ixerisoside, and tangshenoside II, have displayed higher potent binding affinities than the positive control, PNU-142721, in the docking simulation. After MD simulations, which can optimize the result of docking simulation and validate the stability of H-bonds between each ligand and PXR protein under dynamic conditions, top TCM compounds, BEMG and tangshenoside II, maintain most of interactions with PXR protein, which keep the ligand binding stable in the binding domain. Hence, we propose BEMG and tangshenoside II as potential lead compounds for further study in drug development process with the PXR protein.

Drug design of cyclin-dependent kinase 2 inhibitor for melanoma from traditional Chinese medicine

One has found an important cell cycle controller. This guard can decide the cell cycle toward proliferation or quiescence. Cyclin-dependent kinase 2 (CDK2) is a unique target among the CDK family in melanoma therapy. We attempted to find out TCM compounds from TCM Database@Taiwan that have the ability to inhibit the activity of CDK2 by systems biology. We selected Tetrahydropalmatine, Reserpiline, and (+)-Corydaline as the candidates by docking and screening results for further survey. We utilized support vector machine (SVM), multiple linear regression (MLR) models and Bayesian network for validation of predicted activity. By overall analysis of docking results, predicted activity, and molecular dynamics (MD) simulation, we could conclude that Tetrahydropalmatine, Reserpiline, and (+)-Corydaline had better binding affinity than the control. All of them had the ability to inhibit the activity of CDK2 and might have the opportunity to be applied in melanoma therapy.

Investigation of potent lead for acquired immunodeficiency syndrome from traditional Chinese medicine

Acquired immunodeficiency syndrome (AIDS), caused by human immunodeficiency virus (HIV), has become, because of the rapid spread of the disease, a serious global problem and cannot be treated. Recent studies indicate that VIF is a protein of HIV to prevent all of human immunity to attack HIV. Molecular compounds of traditional Chinese medicine (TCM) database filtered through molecular docking and molecular dynamics simulations to inhibit VIF can protect against HIV. Glutamic acid, plantagoguanidinic acid, and Aurantiamide acetate based docking score higher with other TCM compounds selected. Molecular dynamics are useful for analysis and detection ligand interactions. According to the docking position, hydrophobic interactions, hydrogen bonding changes, and structure variation, the study try to select the efficacy of traditional Chinese medicine compound Aurantiamide acetate is better than the other for protein-ligand interactions to maintain the protein composition, based on changes in the structure.

Lead screening for HIV-1 integrase (IN) inhibited by traditional Chinese medicine

Human immunodeficiency virus causes the acquired immunodeficiency syndrome (AIDS) and becomes a serious world-wide problem because of this disease's rapid propagation and incurability. Integrase strand transfer inhibitors (INSTIs) supports HIV have rapid drug resistance for antitreatment. Screening the traditional Chinese medicine (TCM) database by simulating molecular docking and molecular dynamics may select molecular compounds to inhibit INSTIs against HIV drug resistance. (S)-cathinone and (1S,2S)-norpseudoephedrine are selected based on structure and ligand-based drugs are designed and then get higher bioactivity predicted score from SVM than Raltegravir and other TCM compounds. The molecular dynamics are helpful in the analysis and detection of protein-ligand interactions. According to the docking poses, hydrophobic interactions and hydrogen bond variations define the main regions of important amino acids in integrase. In addition to the detection of TCM compound efficacy, we suggest (1S,2S)-norpseudoephedrine is better than the others based on the analysis of interaction and the effect on the structural variation.

In silico design for adenosine monophosphate-activated protein kinase agonist from traditional chinese medicine for treatment of metabolic syndromes

Adenosine monophosphate-activated protein kinase (AMPK) acts as a master mediator of metabolic homeostasis. It is considered as a significant millstone to treat metabolic syndromes including obesity, diabetes, and fatty liver. It can sense cellular energy or nutrient status by switching on the catabolic pathways. Investigation of AMPK has new findings recently. AMPK can inhibit cell growth by the way of autophagy. Thus AMPK has become a hot target for small molecular drug design of tumor inhibition. Activation of AMPK must undergo certain extent change of the structure. Through the methods of structure-based virtual screening and molecular dynamics simulation, we attempted to find out appropriate small compounds from the world's largest TCM Database@Taiwan that had the ability to activate the function of AMPK. Finally, we found that two TCM compounds, eugenyl_beta-D-glucopyranoside and 6-O-cinnamoyl-D-glucopyranose, had the qualification to be AMPK agonist.

Potential mitochondrial isocitrate dehydrogenase R140Q mutant inhibitor from traditional Chinese medicine against cancers

A recent research of cancer has indicated that the mutant of isocitrate dehydrogenase 1 and 2 (IDH1 and 2) genes will induce various cancers, including chondrosarcoma, cholangiocarcinomas, and acute myelogenous leukemia due to the effect of point mutations in the active-site arginine residues of isocitrate dehydrogenase (IDH), such as IDH1/R132, IDH2/R140, and IDH2/R172. As the inhibition for those tumor-associated mutant IDH proteins may induce differentiation of those cancer cells, these tumor-associated mutant IDH proteins can be treated as a drug target proteins for a differentiation therapy against cancers. In this study, we aim to identify the potent TCM compounds from the TCM Database@Taiwan as lead compounds of IDH2 R140Q mutant inhibitor. Comparing to the IDH2 R140Q mutant protein inhibitor, AGI-6780, the top two TCM compounds, precatorine and abrine, have higher binding affinities with target protein in docking simulation. After MD simulation, the top two TCM compounds remain as the same docking poses under dynamic conditions. In addition, precatorine is extracted from Abrus precatorius L., which represents the cytotoxic and proapoptotic effects for breast cancer and several tumor lines. Hence, we propose the TCM compounds, precatorine and abrine, as potential candidates as lead compounds for further study in drug development process with the IDH2 R140Q mutant protein against cancer.

Treatment of rheumatoid arthritis with traditional chinese medicine

Rheumatoid arthritis (RA) is a chronic inflammatory disease that will affect quality of life and, working efficiency, and produce negative thoughts for patients. Current therapy of RA is treated with disease-modifying antirheumatic drugs (DMARDs). Although most of these treatment methods are effective, most patients still have a pleasant experience either due to poor efficacy or side effects or both. Interleukin-6 receptor (IL6R) is important in the pathogenesis of RA. In this study, we would like to detect the potential candidates which inhibit IL6R against RA from traditional Chinese medicine (TCM). We use TCM compounds from the TCM Database@Taiwan for virtually screening the potential IL6R inhibitors. The TCM candidate compound, calycosin, has potent binding affinity with IL6R protein. The molecular dynamics simulation was employed to validate the stability of interaction in the protein complex with calycosin. The analysis indicates that protein complex with calycosin is more stable. In addition, calycosin is known to be one of the components of Angelica sinensis, which has been indicated to have an important role in the treatment of rheumatoid arthritis. Therefore, calycosin is a potential candidate as lead compounds for further study in drug development process with IL6R protein against rheumatoid arthritis.

Lead discovery for Alzheimer's disease related target protein RbAp48 from traditional Chinese medicine

Deficiency or loss of function of Retinoblastoma-associated proteins (RbAp48) is related with Alzheimer's disease (AD), and AD disease is associated with age-related memory loss. During normal function, RbAp48 forms a complex with the peptide FOG-1 (friend of GATA-1) and has a role in gene transcription, but an unstable complex may affect the function of RbAp48. This study utilizes the world's largest traditional Chinese medicine (TCM) database and virtual screening to provide potential compounds for RbAp48 binding. A molecular dynamics (MD) simulation was employed to understand the variations after protein-ligand interaction. FOG1 was found to exhibit low stability after RbAp48 binding; the peptide displayed significant movement from the initial docking position, a phenomenon which matched the docking results. The protein structure of the other TCM candidates was not variable during MD simulation and had a greater stable affinity for RbAp48 binding than FOG1. Our results reveal that the protein structure does not affect ligand binding, and the top three TCM candidates Bittersweet alkaloid II, Eicosandioic acid, and Perivine might resolve the instability of the RbAp48-FOG1 complex and thus be used in AD therapy.

Lead Screening for Chronic Obstructive Pulmonary Disease of IKK2 Inhibited by Traditional Chinese Medicine

Chronic obstructive pulmonary disease (COPD) is a chronic obstructive lung disease and is frequently found in well-developed countries due to the issue of aging populations. Not all forms of medical treatment are unable to return a patient's limited pulmonary function back to normal and eventually they could require a lung transplant. At this time, COPD is the leading cause of death in the world. Studies surveying I-kappa-B-kinase beta (IKK2) are very relevant to the occurrence and deterioration of the condition COPD. The sinapic acid-4-O-sulfate, kaempferol, and alpha-terpineol were found to be IKK2 inhibitors and helped prevent COPD occurrence and worsening according to a screening of the traditional Chinese medicine (TCM) database. The protein-ligand interaction of these three compounds with regard to IKK2 was also done by molecular dynamics. The docking poses, hydrogen bond variation, and hydrophobic interactions found Asp103 and Lys106 are crucial to IKK2 binding areas for IKK2 inhibition. Finally, we found the three compounds that have an equally strong effect in terms of IKK2 binding proven by the TCM database and perhaps these may be an alternative treatment for COPD in the future.

In Silico Investigation of Potential PARP-1 Inhibitors from Traditional Chinese Medicine

Poly(ADP-ribose) polymerases (PARPs) are nuclear enzymes which catalyze the poly-ADP-ribosylation involved in gene transcription, DNA damage repair, and cell-death signaling. As PARP-1 protein contains a DNA-binding domain, which can bind to DNA strand breaks and repair the damaged DNA over a low basal level, the inhibitors of poly(ADP-ribose) polymerase 1 (PARP-1) have been indicated as the agents treated for cancer. This study employed the compounds from TCM Database@Taiwan to identify the potential PARP-1 inhibitors from the vast repertoire of TCM compounds. The binding affinities of the potential TCM compounds were also predicted utilized several distinct scoring functions. Molecular dynamics simulations were performed to optimize the result of docking simulation and analyze the stability of interactions between protein and ligand. The top TCM candidates, isopraeroside IV, picrasidine M, and aurantiamide acetate, had higher potent binding affinities than control, A927929. They have stable H-bonds with residues Gly202 and, Ser243 as A927929 and stable H-bonds with residues Asp105, Tyr228, and His248 in the other side of the binding domain, which may strengthen and stabilize ligand inside the binding domain of PARP-1 protein. Hence, we propose isopraeroside IV and aurantiamide acetate as potential lead compounds for further study in drug development process with the PARP-1 protein.

In Silico Identification of Potent PPAR-γ Agonists from Traditional Chinese Medicine: A Bioactivity Prediction, Virtual Screening, and Molecular Dynamics Study

The peroxisome proliferator-activated receptors (PPARs) related to regulation of lipid metabolism, inflammation, cell proliferation, differentiation, and glucose homeostasis by controlling the related ligand-dependent transcription of networks of genes. They are used to be served as therapeutic targets against metabolic disorder, such as obesity, dyslipidemia, and diabetes; especially, PPAR-γ is the most extensively investigated isoform for the treatment of dyslipidemic type 2 diabetes. In this study, we filter compounds of traditional Chinese medicine (TCM) using bioactivities predicted by three distinct prediction models before the virtual screening. For the top candidates, the molecular dynamics (MD) simulations were also utilized to investigate the stability of interactions between ligand and PPAR-γ protein. The top two TCM candidates, 5-hydroxy-L-tryptophan and abrine, have an indole ring and carboxyl group to form the H-bonds with the key residues of PPAR-γ protein, such as residues Ser289 and Lys367. The secondary amine group of abrine also stabilized an H-bond with residue Ser289. From the figures of root mean square fluctuations (RMSFs), the key residues were stabilized in protein complexes with 5-Hydroxy-L-tryptophan and abrine as control. Hence, we propose 5-hydroxy-L-tryptophan and abrine as potential lead compounds for further study in drug development process with the PPAR-γ protein.

Treatment of acute lymphoblastic leukemia from traditional chinese medicine

Acute lymphoblastic leukemia (ALL) is a cancer that immature white blood cells continuously overproduce in the bone marrow. These cells crowd out normal cells in the bone marrow bringing damage and death. Methotrexate (MTX) is a drug used in the treatment of various cancer and autoimmune diseases. In particular, for the treatment of childhood acute lymphoblastic leukemia, it had significant effect. MTX competitively inhibits dihydrofolate reductase (DHFR), an enzyme that participates in the tetrahydrofolate synthesis so as to inhibit purine synthesis. In addition, its downstream metabolite methotrexate polyglutamates (MTX-PGs) inhibit the thymidylate synthase (TS). Therefore, MTX can inhibit the synthesis of DNA. However, MTX has cytotoxicity and neurotoxin may cause multiple organ injury and is potentially lethal. Thus, the lower toxicity drugs are necessary to be developed. Recently, diseases treatments with Traditional Chinese Medicine (TCM) as complements are getting more and more attention. In this study, we attempted to discover the compounds with drug-like potential for ALL treatment from the components in TCM. We applied virtual screen and QSAR models based on structure-based and ligand-based studies to identify the potential TCM component compounds. Our results show that the TCM compounds adenosine triphosphate, manninotriose, raffinose, and stachyose could have potential to improve the side effects of MTX for ALL treatment.

Computational design of apolipoprotein E4 inhibitors for Alzheimer's disease therapy from traditional Chinese medicine

Apolipoprotein E4 (Apo E4) is the major genetic risk factor in the causation of Alzheimer's disease (AD). In this study we utilize virtual screening of the world's largest traditional Chinese medicine (TCM) database and investigate potential compounds for the inhibition of ApoE4. We present the top three TCM candidates: Solapalmitine, Isodesacetyluvaricin, and Budmunchiamine L5 for further investigation. Dynamics analysis and molecular dynamics (MD) simulation were used to simulate protein-ligand complexes for observing the interactions and protein variations. Budmunchiamine L5 did not have the highest score from virtual screening; however, the dynamics pose is similar to the initial docking pose after MD simulation. Trajectory analysis reveals that Budmunchiamine L5 was stable over all simulation times. The migration distance of Budmunchiamine L5 illustrates that docked ligands are not variable from the initial docked site. Interestingly, Arg158 was observed to form H-bonds with Budmunchiamine L5 in the docking pose and MD snapshot, which indicates that the TCM compounds could stably bind to ApoE4. Our results show that Budmunchiamine L5 has good absorption, blood brain barrier (BBB) penetration, and less toxicity according to absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction and could, therefore, be safely used for developing novel ApoE4 inhibitors.

Virtual screening of traditional Chinese medicine (TCM) database: identification of fragment-like lead molecules for filariasis target asparaginyl-tRNA synthetase

Lymphatic filariasis (LF) is a vector borne infectious disease caused by the nematode Wuchereria bancrofti, Brugia malayi, and Brugia timori. Over 120 million people are affected by LF in the world, of which two-thirds are in Asia. The infection restricts the normal flow of lymph from the infected area resulting in swelling of the extremities and causing permanent disability. As the available drugs for the treatment of LF are becoming ineffective due to the development of resistance, there is an urgent need to find new leads for drug development. In this study, asparaginyl-tRNA synthetase (AsnRS; PDB ID: 2XGT) essential for the protein bio-synthesis in the filarial nematode was used to carry out virtual screening (VS) of plant constituents from traditional Chinese medicine (TCM) database. Docking as well as E-pharmacophore based VS were carried out to identify the hits. The top scoring hits, Agri 1 (1,3,8-trihydroxy-4,5-dimethoxyxanthen-9-one-3-O-beta-D-glucopyranoside) and Agri 2 (5,7-dihydroxy-2-propylchromone 7-O-beta-D-glucopyranoside), constituents of Agrimonia pilosa, were selected for molecular dynamics (MD) simulation study for 10 ns. MD simulation showed that both the glycosides Agri 1 and Agri 2 were forming stable interactions with the target protein. Moreover, docking and MD simulation of the lead A (1,3,8-trihydroxy-4,5-dimethoxyxanthen-9-one; Mol. Wt.: 304.25; CLogP: 3.07) and lead B (5,7-dihydroxy-2-propylchromone; Mol. Wt.: 220.22; CLogP: 3.02), the aglycones of Agri 1 and Agri 2, respectively, were carried out with the target AsnRS. The in silico investigations of the aglycones suggest that the lead B could be a suitable fragment-like lead molecule for anti-filarial drug discovery.

Finding inhibitors of mutant superoxide dismutase-1 for amyotrophic lateral sclerosis therapy from traditional chinese medicine

Superoxide dismutase type 1 (SOD1) mutations cause protein aggregation and decrease protein stability, which are linked to amyotrophic lateral sclerosis (ALS) disease. This research utilizes the world's largest traditional Chinese medicine (TCM) database to search novel inhibitors of mutant SOD1, and molecular dynamics (MD) simulations were used to analyze the stability of protein that interacted with docked ligands. Docking results show that hesperidin and 2,3,5,4'-tetrahydroxystilbene-2-O- β -D-glucoside (THSG) have high affinity to mutant SOD1 and then dopamine. For MD simulation analysis, hesperidin and THSG displayed similar value of RMSD with dopamine, and the migration analysis reveals stable fluctuation at the end of MD simulation time. Interestingly, distance between the protein and ligand has distinct difference, and hesperidin changes the position from initial binding site to the other place. In flexibility of residues analysis, the secondary structure among all complexes does not change, indicating that the structure are not affect ligand binding. The binding poses of hesperidin and THSG are similar to dopamine after molecular simulation. Our result indicated that hesperidin and THSG might be potential lead compound to design inhibitors of mutant SOD1 for ALS therapy.