In silico and pharmacological screenings identify novel serine racemase inhibitors

d-Serine is a coagonist of the N-methyl-d-aspartate (NMDA)-type glutamate receptor and its biosynthesis is catalyzed by serine racemase (SR). The overactivation of the NMDA receptor has been implicated in the development of neurodegenerative diseases, strokes, and epileptic seizures, thus, the inhibitors of SR have potential against these pathological states. Here, we have developed novel inhibitors of SR by in silico screening and in vitro enzyme assay. The newly developed inhibitors have lower IC₅₀ value comparing with that of malonate, one of the standard SR inhibitor. The structural features of novel inhibitors suggest the importance of central amide structure having a phenoxy substituent in their structure for the SR inhibitory activity. The present findings suggest the importance and rational development of new drugs for diseases of NMDAR overactivation.     

A scaffold hopping approach to identify novel monoamine oxidase B inhibitors

Monoamine oxidase B (MAO-B) inhibitors are used to treat Parkinson's disease. In this study, we searched for novel MAO-B inhibitors using a scaffold hopping approach based on our experience with the thiazolidinedione (TZD) class of compounds as MAO-B inhibitors. Several novel compounds were identified, with potencies in the low nanomolar and low micromolar range. We also found that derivatives of the natural product sulfuretin are potent MAO-A and MAO-B inhibitors.     

In silico and in vitro methods to identify ebola virus VP35-dsRNA inhibitors

Ebola virus continues to be problematic as sporadic outbreaks in Africa continue to arise, and as terrorist organizations have considered the virus for bioterrorism use. Several proteins within the virus have been targeted for antiviral chemotherapy, including VP35, a dsRNA binding protein that promotes viral replication, protects dsRNA from degradation, and prevents detection of the viral genome by immune complexes. To augment the scope of our antiviral research, we have now employed molecular modeling techniques to enrich the population of compounds for further testing in vitro. In the initial docking of a static VP35 structure with an 80,000 compound library, 40 compounds were selected, of which four compounds inhibited VP35 with IC₅₀ <200 μM, with the best compounds having an IC₅₀ of 20 μM. By superimposing 26 VP35 structures, we determined four aspartic acid residues were highly flexible and the docking was repeated under flexible parameters. Of 14 compounds chosen for testing, five compounds inhibited VP35 with IC₅₀ <200 μM and one compound with an IC₅₀ of 4 μM. These studies demonstrate the value of docking in silico for enriching compounds for testing in vitro, and specifically using multiple structures as a guide for detecting flexibility and provide a foundation for further development of small molecule inhibitors directed towards VP35.     

In silico development of new acetylcholinesterase inhibitors

In this work, we made use of fragment-based drug design (FBDD) and de novo design to obtain more powerful acetylcholinesterase (AChE) inhibitors. AChE is associated with Alzheimer’s disease (AD). It was found that the cholinergic pathways in the cerebral cortex are compromised in AD and the accompanying cholinergic deficiency contributes to the cognitive deterioration of AD patients. In the FBDD approach, fragments are docked into the active site of the protein. As fragments are molecular groups with a low number of atoms, it is possible to study their interaction with localized amino acids. Once the interactions are measured, the fragments are organized by affinity and then linked together to form new molecules with a high degree of interaction with the active site. In the other approach, we used the de novo design technique starting from reference drugs used in the AD treatment. These drugs were broken into fragments (seeds). In the growing strategy, fragments were added to each seed, growing new molecules. In the linking strategy, two or more separated seeds were linked with different fragments. Both strategies combined produced a library of more than 2 million compounds. This library was filtered using absorption, distribution, metabolism, and excretion properties. The resulting library with around six thousand compounds was filtered again. In this case, structures with Tanimoto coefficients >.85 were discarded. The final library with 1500 compounds was submitted to docking studies. As a result, 10 compounds with better interaction energy than the reference drugs were obtained.     

In silico single strand melting curve: a new approach to identify nucleic acid polymorphisms in Totiviridae

Background

The PCR technique and its variations have been increasingly used in the clinical laboratory and recent advances in this field generated new higher resolution techniques based on nucleic acid denaturation dynamics. The principle of these new molecular tools is based on the comparison of melting profiles, after denaturation of a DNA double strand. Until now, the secondary structure of single-stranded nucleic acids has not been exploited to develop identification systems based on PCR. To test the potential of single-strand RNA denaturation as a new alternative to detect specific nucleic acid variations, sequences from viruses of the Totiviridae family were compared using a new in silico melting curve approach. This family comprises double-stranded RNA virus, with a genome constituted by two ORFs, ORF1 and ORF2, which encodes the capsid/RNA binding proteins and an RNA-dependent RNA polymerase (RdRp), respectively.

Results

A phylogenetic tree based on RdRp amino acid sequences was constructed, and eight monophyletic groups were defined. Alignments of RdRp RNA sequences from each group were screened to identify RNA regions with conserved secondary structure. One region in the second half of ORF2 was identified and individually modeled using the RNAfold tool. Afterwards, each DNA or RNA sequence was denatured in silico using the softwares MELTSIM and RNAheat that generate melting curves considering the denaturation of a double stranded DNA and single stranded RNA, respectively. The same groups identified in the RdRp phylogenetic tree were retrieved by a clustering analysis of the melting curves data obtained from RNAheat. Moreover, the same approach was used to successfully discriminate different variants of Trichomonas vaginalis virus, which was not possible by the visual comparison of the double stranded melting curves generated by MELTSIM.

Conclusion

In silico analysis indicate that ssRNA melting curves are more informative than dsDNA melting curves. Furthermore, conserved RNA structures may be determined from analysis of individuals that are phylogenetically related, and these regions may be used to support the reconstitution of their phylogenetic groups. These findings are a robust basis for the development of in vitro systems to ssRNA melting curves detection.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-243) contains supplementary material, which is available to authorized users.     

In vitro and in silico evaluation of new thiazole compounds as monoamine oxidase inhibitors

New twenty compounds bearing thiazole ring (3a-3t) were designed and synthesized as monoamine oxidase (MAO) inhibitors. The fluorometric enzyme inhibition assay was used to determine the biological effects of synthesized compounds. Most of them showed remarkable inhibitory activity against both MAO-A and MAO-B. By comparing their IC₅₀ values, it can be seen that active derivatives displayed generally selectivity on MAO-B enzyme. Compounds 3j and 3t, which bear dihydroxy moiety at the 3rd and 4th position of phenyl ring, were the most active derivatives in the series against both isoenzymes. Compounds 3j and 3t showed significant inhibition profile on MAO-A with the IC₅₀ values of 0.134 ± 0.004 µM and 0.123 ± 0.005 µM, respectively, while they performed selectivity against MAO-B with the IC₅₀ values of 0.027 ± 0.001 µM and 0.025 ± 0.001 µM, respectively. Also, docking studies about these compounds were carried out to evaluate their binding modes on the active regions of MAO-A and MAO-B.     

A scaffold replacement approach towards new sirtuin 2 inhibitors

Sirtuins (SIRT1–SIRT7) are an evolutionary conserved family of NAD⁺-dependent protein deacylases regulating the acylation state of ε-N-lysine residues of proteins thereby controlling key biological processes. Numerous studies have found association of the aberrant enzymatic activity of SIRTs with various diseases like diabetes, cancer and neurodegenerative disorders. Previously, we have shown that substituted 2-alkyl-chroman-4-one/chromone derivatives can serve as selective inhibitors of SIRT2 possessing an antiproliferative effect in two human cancer cell lines. In this study, we have explored the bioisosteric replacement of the chroman-4-one/chromone core structure with different less lipophilic bicyclic scaffolds to overcome problems associated to poor physiochemical properties due to a highly lipophilic substitution pattern required for achieve a good inhibitory effect. Various new derivatives based on the quinolin-4(1H)-one scaffold, bicyclic secondary sulfonamides or saccharins were synthesized and evaluated for their SIRT inhibitory effect. Among the evaluated scaffolds, the benzothiadiazine-1,1-dioxide-based compounds showed the highest SIRT2 inhibitory activity. Molecular modeling studies gave insight into the binding mode of the new scaffold-replacement analogues.     

In vitro and in silico processes to identify differentially expressed proteins

We present an integrated proteomics platform designed for performing differential analyses. Since reproducible results are essential for comparative studies, we explain how we improved reproducibility at every step of our laboratory processes, e.g. by taking advantage of the powerful laboratory information management system we developed. The differential capacity of our platform is validated by detecting known markers in a real sample and by a spiking experiment. We introduce an innovative two-dimensional (2-D) plot for displaying identification results combined with chromatographic data. This 2-D plot is very convenient for detecting differential proteins. We also adapt standard multivariate statistical techniques to show that peptide identification scores can be used for reliable and sensitive differential studies. The interest of the protein separation approach we generally apply is justified by numerous statistics, complemented by a comparison with a simple shotgun analysis performed on a small volume sample. By introducing an automatic integration step after mass spectrometry data identification, we are able to search numerous databases systematically, including the human genome and expressed sequence tags. Finally, we explain how rigorous data processing can be combined with the work of human experts to set high quality standards, and hence obtain reliable (false positive < 0.35%) and nonredundant protein identifications.     

In silico approach towards identification of potential inhibitors of Helicobacter pylori DapE

Helicobacter pylori is a gastric mucosal pathogen and is associated with diseases like peptic ulcer and gastric cancer. To combat H. pylori infection, there is an urgent need for new class of antibiotics due to the emergence of drug-resistant strains. Enzymes involved in bacterial lysine biosynthetic pathways may be potential targets for antibacterial drug development, since lysine is an essential component of the bacterial peptidoglycan cell wall. No pathway exists for lysine biosynthesis in humans; hence, the inhibitors targeting bacterial enzymes may have selective toxicity. dapE-encoded N-succinyl-L,L-diaminopimelic acid desuccinylase (DapE) is a critical enzyme of this pathway and deletion of DapE gene is lethal to H. pylori, since the organism has no alternative pathway for lysine biosynthesis. In this study, we reported a 3D model structure of H. pylorie DapE, which consisted of a catalytic domain and a dimerization domain generated by MODELLER software. We also confirmed the stability of the modeled structure through 10 ns molecular dynamics simulation using GROMACS software. Next, to identify potential small molecule inhibitors of DapE, drug-like small molecule-screening library was generated. This was performed by Tanimoto-based similarity searching in the PubChem Database with DapE substrate L,L-SDAP as a query molecule, followed by fragment-based docking approach using GLIDE XP. This approach identified two potential substrate-competitive small molecule inhibitors of DapE. These new molecules may provide a starting point to search for novel therapeutics.     

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using ‘Receptor-Ligand Pharmacophore Generation’ method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r² of 0.996; for the test set, the correlation coefficient r² was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.     

Design, synthesis and preliminary evaluation of new cinnamoyl pyrrolidine derivatives as potent gelatinase inhibitors

A series of new cinnamoyl pyrrolidine derivatives have been synthesized based on the l-hydroxyproline scaffold and inhibiting activities on gelatinase (MMP-2 and -9) and APN were tested. Structure–activity relationship studies showed that the side chain with aromatic ring at C4in pyrrolidine ring showed better inhibitory activities on gelatinase than aliphatic side chain. Most compounds exhibited poor activities on APN compared with MMP-2. Within this series, three compounds, A8, B9 and C10, have the good potency (IC₅₀ = 5.2–9.7 nM) and could be used as lead compounds in the future.     

In silico studies of urease inhibitors to explore ligand-enzyme interactions

In continuation of our previous study on the urease inhibition by a number of chalcones, 2,3-dihydro-1,5-benzothiazepines and 2,3,4,5-tetrahydro-1,5-benzothiazepines, FlexX docking has been exploited to get a deeper insight into the mechanism of their inhibitory action. A comparison of the IC(50) values of the active compounds reveals that, of the three classes of compounds studied, 2,3-dihydro-1,5-benzothiazepines were the most potent urease inhibitors. An in silico examination of these compounds showed that the activity is related to the interaction of ligand with the nickel metallocentre, its interaction with two amino acid residues, Asp224 and Cys322, in addition to the orientation of rings A and B in the catalytic core of the enzyme. The most active compound 2,3-dihydro-1,5-benzothiazepine (4) anchor tightly through a network of interactions with Ni701 and Ni702. This includes a number of hydrogen bonds and hydrophobic contacts with the amino acid residues in its vicinity. For their reduced analogs, the difference in the activity of different diastereomers has been observed to be configuration-dependent. This may be ascribed mainly to the difference in the orientation of ring B of the two stereoisomers and the extent of their interaction with Asp224 and Cys322 present in the catalytic core of the enzyme.     

In silico studies of urease inhibitors to explore ligand-enzyme interactions

In continuation of our previous study on the urease inhibition by a number of chalcones, 2,3-dihydro-1,5-benzothiazepines and 2,3,4,5-tetrahydro-1,5-benzothiazepines, FlexX docking has been exploited to get a deeper insight into the mechanism of their inhibitory action. A comparison of the IC₅₀ values of the active compounds reveals that, of the three classes of compounds studied, 2,3-dihydro-1,5-benzothiazepines were the most potent urease inhibitors. An in silico examination of these compounds showed that the activity is related to the interaction of ligand with the nickel metallocentre, its interaction with two amino acid residues, Asp224 and Cys322, in addition to the orientation of rings A and B in the catalytic core of the enzyme. The most active compound 2,3-dihydro-1,5-benzothiazepine (4) anchor tightly through a network of interactions with Ni701 and Ni702. This includes a number of hydrogen bonds and hydrophobic contacts with the amino acid residues in its vicinity. For their reduced analogs, the difference in the activity of different diastereomers has been observed to be configuration-dependent. This may be ascribed mainly to the difference in the orientation of ring B of the two stereoisomers and the extent of their interaction with Asp224 and Cys322 present in the catalytic core of the enzyme.     

Focused screening to identify new adenosine kinase inhibitors

Adenosine kinase (AdK) is a key player in controlling intra- and extracellular concentrations of the signaling molecule adenosine. Extensive evidence points to an important role of AdK in several diseases, and suggests that AdK inhibition might be a promising therapeutic strategy.The development of a new AdK assay and subsequent screening of part of our focused compound library led to the identification of 12 hit compounds (hit rate of 6%) representing six new classes of non-nucleoside human AdK inhibitors. The most potent inhibitor 1 displayed a K_i value of 184 nM. Compound screening with a newly developed assay was useful and efficient for discovering novel AdK inhibitors which may serve as lead structures for developing drugs for adenosine augmentation therapy.     

In silico approach to quantify nucleus self-deformation on micropillared substrates

Biomechanics and Modeling in Mechanobiology - Considering the major role of confined cell migration in biological processes and diseases, such as embryogenesis or metastatic cancer, it has become...     

Virtual screening and biochemical evaluation to identify new inhibitors of mammalian target of rapamycin (mTOR)

Mammalian target of rapamycin (mTOR) is a promising target for the development of anticancer medicines. Here, we report the first example for a successful application of the structure-based virtual screening to identify new mTOR inhibitors. Using the scoring function improved by implementing the ligand solvation effects on protein–ligand association, six novel mTOR inhibitors are found with IC₅₀ values ranging from 8 to 60 μM. Because these new inhibitors are also computationally screened for having desirable physicochemical properties as a drug candidate, they deserve consideration for further development by structure–activity relationship studies to optimize the inhibitory and anticancer activities. Structural features relevant to the stabilization of the inhibitors in the ATP-binding site of mTOR are addressed in detail.     

A novel in silico approach to identify potential therapeutic targets in human bacterial pathogens

In recent years, genome-sequencing projects of pathogens and humans have revolutionized microbial drug target identification. Of the several known genomic strategies, subtractive genomics has been successfully utilized for identifying microbial drug targets. The present work demonstrates a novel genomics approach in which codon adaptation index (CAI), a measure used to predict the translational efficiency of a gene based on synonymous codon usage, is coupled with subtractive genomics approach for mining potential drug targets. The strategy adopted is demonstrated using respiratory pathogens, namely, Streptococcus pneumoniae and Haemophilus influenzae as examples. Our approach identified 8 potent target genes (Streptococcus pneumoniae?C2, H. influenzae?C6), which are functionally significant and also play key role in host-pathogen interactions. This approach facilitates swift identification of potential drug targets, thereby enabling the search for new inhibitors. These results underscore the utility of CAI for enhanced in silico drug target identification.     

Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors

Mesenchymal epithelial transition factor (c-Met) is an attractive target for cancer therapy. Three-dimensional pharmacophore hypotheses were built based on a set of known structurally diverse c-Met inhibitors. The best pharmacophore model, which identified inhibitors with an associated correlation coefficient of 0.983 between their experimental and estimated IC(50) values, consisted of two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic feature. The highly predictive power of the model was rigorously validated by test set prediction and Fischer's randomization method. The high values of enrichment factor and receiver operating characteristic (ROC) score indicated the model performed fairly well at distinguishing active from inactive compounds. The model was then applied to screen compound database for potential c-Met inhibitors. A filtering protocol, including druggability and molecular docking, were also applied in hits selection. The final 38 molecules, which exhibited good estimated activities, desired binding mode and favorable drug likeness were identified as potential c-Met inhibitors. Their novel backbone structures could be served as scaffolds for further study, which may facilitate the discovery and rational design of potent c-Met kinase inhibitors.     

In silico screening of drug databases for TSE inhibitors

Today, thousands of different chemical compounds are used as drugs for a wealth of different indications. Here, we demonstrate the use of a novel conformational drug database for the search of compounds with a positive influence on Transmissible Spongiform Encephalopathies (TSEs) by using two- and three-dimensional structural similarity to compounds with known effect. Both methods are combined to deduce a list of 16 candidate drugs. The proposal of a small number of putative inhibitors out of about 2300 approved essential drugs allows testing by expensive or time-consuming methods with the advantage that all agents are well known and suitable for use in humans.     

In silico study of peptide inhibitors against BACE 1

Peptides are increasingly used as inhibitors of various disease specific targets. Several naturally occurring and synthetically developed peptides are undergoing clinical trials. Our work explores the possibility of reusing the non-expressing DNA sequences to predict potential drug-target specific peptides. Recently, we experimentally demonstrated the artificial synthesis of novel proteins from non-coding regions of Escherichia coli genome. In this study, a library of synthetic peptides (Synpeps) was constructed from 2500 intergenic E. coli sequences and screened against Beta-secretase 1 protein, a known drug target for Alzheimer’s disease (AD). Secondary and tertiary protein structure predictions followed by protein–protein docking studies were performed to identify the most promising enzyme inhibitors. Interacting residues and favorable binding poses of lead peptide inhibitors were studied. Though initial results are encouraging, experimental validation is required in future to develop efficient target specific inhibitors against AD.