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Photodynamic therapy (PDT) is a rapidly evolving area of cancer management against solid tumors. PDT is either administrated by injecting photosensitizer (porphyrins) or by accumulation of intracellular protoporphyrin IX via the inhibition of human Protoporphyrinogen Oxidase IX (hPPO). In this study, novel inhibitors of hPPO have been investigated by integrating virtual screening, molecular docking, and molecular dynamics (MD) simulation. A ligand-based pharmacophore was generated from a training set of 22 inhibitors of hPPO. The selected pharmacophore had four chemical features including three hydrogen bond acceptors and one hydrophobic. The pharmacophore was characterized by highest correlation coefficient of 0.96, cost difference of 53.20, and lowest root mean square deviation of 0.73. The resultant pharmacophore was validated by Fischer’s Randomization and Test Set Validation methods. The validated pharmacophore was used as a 3D query to screen chemical databases including NCI, Asinex, Chembridge, and Maybridge. The screening of chemical databases and the subsequent application of Lipinski’s Rule of Five, and ADMET Assessment Test, retrieved 1176 drug-like compounds. The drug-like compounds were subjected to molecular docking studies in the active site of hPPO to eliminate false positive hits and to elucidate their true binding orientation. Top three candidate molecules with high docking scores and hydrogen bond interactions with catalytic active residues were selected as best candidate inhibitors against hPPO. The binding stability of selected candidate inhibitors was evaluated by MD simulation. The MD simulation of hits portrayed strong hydrogen bonds and key hydrophobic interactions with catalytic active residues of hPPO including R59, R97, G159, G332 and flavin moiety of FAD (coenzyme of hPPO). Our study predicts three hit compounds against hPPO, which could possibly accumulate high concentration of protoporphyrinogen-IX, and thereby acting as an intracellular photosensitizer against tumor cells through photodynamic therapy. Keywords: Photodynamic therapy (PDT), hPPO Inhibition, Virtual screening, Pharmacophore modeling, Molecular docking simulation, Molecular dynamics (MD) simulation

Progeria is a globally noticed rare genetic disorder manifested by premature aging with no effective treatment. Under these circumstances, farnesyltransferase inhibitors (FTIs) are marked as promising drug candidates. Correspondingly, a pharmacophore model was generated exploiting the features of lonafarnib. The selected pharmacophore model was allowed to screen the InterBioScreen natural compound database to retrieve the potential lead candidates. A series of filtering steps were applied to assess the drug-likeness of the compounds. The obtained compounds were advanced to molecular docking employing the CDOCKER module available with Discovery Studio (DS). Subsequently, three compounds (Hits) have displayed a higher dock score and demonstrated key residue interactions with stable molecular dynamics simulation results compared to the reference compound. Taken together, we therefore put forth three identified Hits as FTIs that may further serve as chemical spaces in designing new compounds.

Prolyl oligopeptidase (POP) is a potential therapeutic target for treatment of several neurological disorders and α-synucleinopathies including Parkinson's disease. Most of the known POP inhibitors failed in the clinical trials due to poor pharmacokinetic properties and blood-brain impermeability. Therefore, a training set of 30 structurally diverse compounds with a wide range of inhibitory activity against POP was used to generate a quantitative pharmacophore model, Hypo 3, to identify potential POP inhibitors with desirable drug-like properties. Validations through test set, cost analysis, and Fisher's randomization methods proved that Hypo 3 accurately predicted the known inhibitors among inactive compounds. Hypo 3 was employed as 3D query for virtual screening on an in-house drug-like chemical database containing compounds with good brain permeability and ADMET parameters. Database screening with Hypo 3 resulted in 99 compounds that were narrowed down to 21 compounds through molecular docking. Among them, five compounds were identified in our earlier studies, while two compounds showed in vitro POP inhibition. The current study proposed new 16 virtually screened compounds as potential inhibitors against POP that possess Gold docking score in the range of 64.61–75.74 and Chemscore of −32.25 to −38.35. Furthermore, the top scoring four hit compounds were subjected to molecular dynamics simulations to reveal their appropriate binding modes and assessing binding free energies. The hit compounds interacted with POP effectively via hydrogen bonds with important active site residues along with hydrophobic interactions. Moreover, the hit compounds had key inter-molecular interactions and better binding free energies as compared to the reference inhibitor. A potential new hydrogen bond interaction was discovered between Hit 2 with the Arg252 residue of POP. To conclude, we propose four hit compounds with new structural scaffolds against POP for the lead development of POP-based therapeutics for neurological disorders.

Breast cancer (BC) is the leading cause of death among women worldwide devoid of effective treatment. It is therefore important to develop agents that can reverse, reduce, or slow the growth of BC. The use of natural products as chemopreventive agents provides enormous advantages. The aim of the current investigation is to determine the efficacy of the phytochemicals against BC along with the approved drugs to screen the most desirable and effective phytocompound. In the current study, 36 phytochemicals have been evaluated against aromatase to identify the potential candidate drug along with the approved drugs employing the Cdocker module accessible on the Discovery Studio (DS) v4.5 and thereafter analysing the stability of the protein ligand complex using GROningen MAchine for Chemical Simulations v5.0.6 (GROMACS). Additionally, these compounds were assessed for the inhibitory features employing the structure-based pharmacophore (SBP). The Cdocker protocol available with the DS has computed higher dock scores for the phytochemicals complemented by lower binding energies. The top-ranked compounds that have anchored with key residues located at the binding pocket of the protein were subjected to molecular dynamics (MD) simulations employing GROMACS. The resultant findings reveal the stability of the protein backbone and further guide to comprehend on the involvement of key residues Phe134, Val370, and Met374 that mechanistically inhibit BC. Among 36 compounds, curcumin, capsaicin, rosmarinic acid, and 6-shogaol have emerged as promising phytochemicals conferred with the highest Cdocker interaction energy, key residue interactions, stable MD results than reference drugs, and imbibing the key inhibitory features. Taken together, the current study illuminates the use of natural compounds as potential drugs against BC. Additionally, these compounds could also serve as scaffolds in designing and development of new drugs.

Globally, breast cancer is one of the primary reasons of death noticed in women. Despite continuous efforts to formulate effective treatments, search to identify promising therapeutics is underway. Consequently, a drug with low toxicity, high efficacy, and which can escape resistance mechanism is in a high demand. Natural compounds are bestowed with several medicinal properties demonstrating low toxicity. Therefore, the current research focuses on the use of several plant- derived chemical compounds against aromatase, a validated drug target for breast cancer. Correspondingly, employing the known inhibitors, a 3D QSAR pharmacophore model was generated and was subsequently validated. Using the three-featured pharmacophore as the 3D query, the alkaloids, flavonoids, coumarins and the AfroDB were scrupulously examined to retrieve the compounds with inhibitory activities complemented by the pharmacophore model. The obtained compounds were subjected to molecular docking studies executed employing the Cdocker accessible on discovery studio v4.5. The resultant ideal poses from the largest cluster conferred with key reside interactions and higher dock scores than the reference and the Food and Drug Administration (FDA) approved drugs were escalated to molecular dynamics simulation studies conducted employing GROMACS v5.0.6 for 30 ns. Correspondingly, the Hits (ZINC95486358, ZINC95486354, and ZINC90711737) have displayed stable root mean square deviations, coupled by appropriate positioning at the active site displaying greater number of hydrogen bonds. Moreover, the Hits (ZINC95486358, ZINC95486354, and ZINC90711737) were noticed to anchor with various key residues essential for clamping the ligand at the binding pocket. Therefore, these findings guide us to determine that the identified Hits can act effectively against breast cancer, thereby increasing the life expectancy. Furthermore, they can assist as scaffolds for designing novel drugs that aid in curing the cancer.

The prevalence of a novel β-coronavirus (SARS-CoV-2) was declared as a public health emergency of international concern on 30 January 2020 and a global pandemic on 11 March 2020 by WHO. The spike glycoprotein of SARS-CoV-2 is regarded as a key target for the development of vaccines and therapeutic antibodies. In order to develop anti-viral therapeutics for SARS-CoV-2, it is crucial to find amino acid pairs that strongly attract each other at the interface of the spike glycoprotein and the human angiotensin-converting enzyme 2 (hACE2) complex. In order to find hot spot residues, the strongly attracting amino acid pairs at the protein–protein interaction (PPI) interface, we introduce a reliable inter-residue interaction energy calculation method, FMO-DFTB3/D/PCM/3D-SPIEs. In addition to the SARS-CoV-2 spike glycoprotein/hACE2 complex, the hot spot residues of SARS-CoV-1 spike glycoprotein/hACE2 complex, SARS-CoV-1 spike glycoprotein/antibody complex, and HCoV-NL63 spike glycoprotein/hACE2 complex were obtained using the same FMO method. Following this, a 3D-SPIEs-based interaction map was constructed with hot spot residues for the hACE2/SARS-CoV-1 spike glycoprotein, hACE2/HCoV-NL63 spike glycoprotein, and hACE2/SARS-CoV-2 spike glycoprotein complexes. Finally, the three 3D-SPIEs-based interaction maps were combined and analyzed to find the consensus hot spots among the three complexes. As a result of the analysis, two hot spots were identified between hACE2 and the three spike proteins. In particular, E37, K353, G354, and D355 of the hACE2 receptor strongly interact with the spike proteins of coronaviruses. The 3D-SPIEs-based map would provide valuable information to develop anti-viral therapeutics that inhibit PPIs between the spike protein of SARS-CoV-2 and hACE2.

DDX3 belongs to RNA helicase family that demonstrates oncogenic properties and has gained wider attention due to its role in cancer progression, proliferation and transformation. Mounting reports have evidenced the role of DDX3 in cancers making it a promising target to abrogate DDX3 triggered cancers. Dual pharmacophore models were generated and were subsequently validated. They were used as 3D queries to screen the InterBioScreen database, resulting in the selection of curcumin that was escalated to molecular dynamics simulation studies. In vitro anti-cancer analysis was conducted on three cell lines such as MCF-7, MDA-MB-231 and HeLa, which were evaluated along with exemestane. Curcumin was docked into the active site of the protein target (PDB code 2I4I) to estimate the binding affinity. The compound has interacted with two key residues and has displayed stable molecular dynamics simulation results. In vitro analysis has demonstrated that both the candidate compounds have reduced the expression of DDX3 in three cell lines. However, upon combinatorial treatment of curcumin (10 and 20 &mu, M) and exemestane (50 &mu, M) a synergism was exhibited, strikingly downregulating the DDX3 expression and has enhanced apoptosis in three cell lines. The obtained results illuminate the use of curcumin as an alternative DDX3 inhibitor and can serve as a chemical scaffold to design new small molecules.

Human epidermal growth factor receptors are implicated in several types of cancers characterized by aberrant signal transduction. This family comprises of EGFR (ErbB1), HER2 (ErbB2, HER2/neu), HER3 (ErbB3), and HER4 (ErbB4). Amongst them, HER2 is associated with breast cancer and is one of the most valuable targets in addressing the breast cancer incidences. For the current investigation, we have performed 3D-QSAR based pharmacophore search for the identification of potential inhibitors against the kinase domain of HER2 protein. Correspondingly, a pharmacophore model, Hypo1, with four features was generated and was validated employing Fischer's randomization, test set method and the decoy test method. The validated pharmacophore was allowed to screen the colossal natural compounds database (UNPD). Subsequently, the identified 33 compounds were docked into the proteins active site along with the reference after subjecting them to ADMET and Lipinski's Rule of Five (RoF) employing the CDOCKER implemented on the Discovery Studio. The compounds that have displayed higher dock scores than the reference compound were scrutinized for interactions with the key residues and were escalated to MD simulations. Additionally, molecular dynamics simulations performed by GROMACS have rendered stable root mean square deviation values, radius of gyration and potential energy values. Eventually, based upon the molecular dock score, interactions between the ligands and the active site residues and the stable MD results, the number of Hits was culled to two identifying Hit1 and Hit2 has potential leads against HER2 breast cancers.

Dihydrofolate reductase (DHFR) is an essential cellular enzyme and thereby catalyzes the reduction of dihydrofolate to tetrahydrofolate (THF). In cancer medication, inhibition of human DHFR (hDHFR) remains a promising strategy, as it depletes THF and slows DNA synthesis and cell proliferation. In the current study, ligand-based pharmacophore modeling identified and evaluated the critical chemical features of hDHFR inhibitors. A pharmacophore model (Hypo1) was generated from known inhibitors of DHFR with a correlation coefficient (0.94), root mean square (RMS) deviation (0.99), and total cost value (125.28). Hypo1 was comprised of four chemical features, including two hydrogen bond donors (HDB), one hydrogen bond acceptor (HBA), and one hydrophobic (HYP). Hypo1 was validated using Fischer’s randomization, test set, and decoy set validations, employed as a 3D query in a virtual screening at Maybridge, Chembridge, Asinex, National Cancer Institute (NCI), and Zinc databases. Hypo1-retrieved compounds were filtered by an absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment test and Lipinski’s rule of five, where the drug-like hit compounds were identified. The hit compounds were docked in the active site of hDHFR and compounds with Goldfitness score was greater than 44.67 (docking score for the reference compound), clustering analysis, and hydrogen bond interactions were identified. Furthermore, molecular dynamics (MD) simulation identified three compounds as the best inhibitors of hDHFR with the lowest root mean square deviation (1.2 Å to 1.8 Å), hydrogen bond interactions with hDHFR, and low binding free energy (−127 kJ/mol to −178 kJ/mol). Finally, the toxicity prediction by computer (TOPKAT) affirmed the safety of the novel inhibitors of hDHFR in human body. Overall, we recommend novel hit compounds of hDHFR for cancer and rheumatoid arthritis chemotherapeutics.

Additional file 9. Active sites comparison. Comparison of the active site residues of 4AG8 and 1URW.

Plant phytochromes are photoreceptors that mediate a variety of photomorphogenic responses. There are two spectral photoisomers, the red light-absorbing Pr and far-red light-absorbing Pfr forms, and the photoreversible transformation between the two forms is important for the functioning of phytochromes. In this study, we isolated a Tyr-268-to-Val mutant of Avena sativa phytochrome A (AsYVA) that displayed little photoconversion. Interestingly, transgenic plants of AsYVA showed light-independent phytochrome signaling with a constitutive photomorphogenic (cop) phenotype that is characterized by shortened hypocotyls and open cotyledons in the dark. In addition, the corresponding Tyr-303-to-Val mutant of Arabidopsis (Arabidopsis thaliana) phytochrome B (AtYVB) exhibited nuclear localization and interaction with phytochrome-interacting factor 3 (PIF3) independently of light, conferring a constitutive photomorphogenic development to its transgenic plants, which is comparable to the first constitutively active version of phytochrome B (YHB; Tyr-276-to-His mutant). We also found that chromophore ligation was required for the light-independent interaction of AtYVB with PIF3. Moreover, we demonstrated that AtYVB did not exhibit phytochrome B activity when it was localized in the cytosol by fusion with the nuclear export signal and that AsYVA exhibited the full activity of phytochrome A when localized in the nucleus by fusion with the nuclear localization signal. Furthermore, the corresponding Tyr-269-to-Val mutant of Arabidopsis phytochrome A (AtYVA) exhibited similar cop phenotypes in transgenic plants to AsYVA. Collectively, these results suggest that the conserved Tyr residues in the chromophore-binding pocket play an important role during the Pr-to-Pfr photoconversion of phytochromes, providing new constitutively active alleles of phytochromes by the Tyr-to-Val mutation.

It has been suggested that plant phytochromes are autophosphorylating serine/threonine kinases. However, the biochemical properties and functional roles of putative phytochrome kinase activity in plant light signalling are largely unknown. Here, we describe the biochemical and functional characterization of Avena sativa phytochrome A (AsphyA) as a potential protein kinase. We provide evidence that phytochrome-interacting factors (PIFs) are phosphorylated by phytochromes in vitro. Domain mapping of AsphyA shows that the photosensory core region consisting of PAS-GAF-PHY domains in the N-terminal is required for the observed kinase activity. Moreover, we demonstrate that transgenic plants expressing mutant versions of AsphyA, which display reduced activity in in vitro kinase assays, show hyposensitive responses to far-red light. Further analysis reveals that far-red light-induced phosphorylation and degradation of PIF3 are significantly reduced in these transgenic plants. Collectively, these results suggest a positive relationship between phytochrome kinase activity and photoresponses in plants., Phytochromes regulate plant responses to environmental light conditions but despite extensive research the initial events in phytochrome signaling remain uncertain. Here, Shin et al. provide evidence that phytochrome phosphorylates target proteins via kinase activity in the N-terminal core domain.

Aromatase inhibitors with an $\mathrm{IC}_{50}$ IC 50 value ranging from 1.4 to 49.7 µM are known to act as antiepileptic drugs besides being potential breast cancer inhibitors. The aim of the present study is to identify novel antiepileptic aromatase inhibitors with higher activity exploiting the ligand-based pharmacophore approach utilizing the experimentally known inhibitors. The resultant Hypo1 consists of four features and was further validated by using three different strategies. Hypo1 was allowed to screen different databases to identify lead molecules and were further subjected to Lipinski's Rule of Five and ADMET to establish their drug-like properties. Consequently, the obtained 68-screened molecules were subjected to molecular docking by GOLD v5.2.2. Furthermore, the compounds with the highest dock scores were assessed for molecular interactions. Later, the MD simulation was applied to evaluate the protein backbone stabilities and binding energies adapting GROMACS v5.0.6 and MM/PBSA which was followed by the density functional theory (DFT), to analyze their orbital energies, and further the energy gap between them. Eventually, the number of Hit molecules was culled to three projecting Hit1, Hit2, and Hit3 as the potential lead compounds based on their highest dock scores, hydrogen bond interaction, lowest energy gap, and the least binding energies and stable MD results.

Chagas disease is one of the primary causes of heart diseases accounting to 50,000 lives annually and is listed as the neglected tropical disease. Because the currently available therapies have greater toxic effects with higher resistance, there is a dire need to develop new drugs to combat the disease. In this pursuit, the 3D QSAR ligand-pharmacophore (pharm 1) and receptor-based pharmacophore (pharm 2) search was initiated to retrieve the candidate compounds from universal natural compounds database. The validated models were allowed to map the universal natural compounds database. The obtained lead candidates were subjected to molecular docking against cysteine protease (PDB code: 1ME3) employing -Cdocker available on the discovery studio. Subsequently, two Hits have satisfied the selection criteria and were escalated to molecular dynamics simulation and binding free energy calculations. These Hits have demonstrated higher dock scores, displayed interactions with the key residues portraying an ideal binding mode complemented by mapping to all the features of pharm 1 and pharm 2. Additionally, they have rendered stable root mean square deviation (RMSD) and potential energy profiles illuminating their potentiality as the prospective antichagastic agents. The study further demonstrates the mechanism of inhibition by tetrad residues compromising of Gly23 and Asn70 holding the ligand at each ends and the residues Gly65 and Gly160 clamping the Hits at the center. The notable feature is that the Hits lie in close proximity with the residues Glu66 and Leu67, accommodating within the S1, S2 and S3 subsites. Considering these findings, the study suggests that the Hits may be regarded as effective therapeutics against Chagas disease.

Background Antibiotic resistance is a defense mechanism, harbored by pathogens to survive under unfavorable conditions. Among several antibiotic resistant microbial consortium, Staphylococcus aureus is one of the most havoc microorganisms. Staphylococcus aureus encodes a unique enzyme 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (SaHPPK), against which, none of existing antibiotics have been reported. Methods Computational approaches have been instrumental in designing and discovering new drugs for several diseases. The present study highlights the impact of ginger phytochemicals on Staphylococcus aureus SaHPPK. Herein, we have retrieved eight ginger phytochemicals from published literature and investigated their inhibitory interactions with SaHPPK. To authenticate our work, the investigation proceeds considering the known antibiotics alongside the phytochemicals. Molecular docking was performed employing GOLD and CDOCKER. The compounds with the highest dock score from both the docking programmes were tested for their inhibitory capability in vitro. The binding conformations that were seated within the binding pocket showing strong interactions with the active sites residues rendered by highest dock score were forwarded towards the molecular dynamic (MD) simulation analysis. Results Based on molecular dock scores, molecular interaction with catalytic active residues and MD simulations studies, two ginger phytochemicals, gingerenone-A and shogaol have been proposed as candidate inhibitors against Staphylococcus aureus. They have demonstrated higher dock scores than the known antibiotics and have represented interactions with the key residues within the active site. Furthermore, these compounds have rendered considerable inhibitory activity when tested in vitro. Additionally, their superiority was corroborated by stable MD results conducted for 100 ns employing GROMACS package. Conclusions Finally, we suggest that gingerenone-A and shogaol may either be potential SaHPPK inhibitors or can be used as fundamental platforms for novel SaHPPK inhibitor development. Electronic supplementary material The online version of this article (10.1186/s12941-018-0266-9) contains supplementary material, which is available to authorized users.

Background Angiogenesis is a process of formation of new blood vessels and is an important criteria demonstrated by cancer cells. Over a period of time, these cancer cells infect the other parts of the healthy body by a process called progression. The objective of the present article is to identify a drug molecule that inhibits angiogenesis and progression. Methods In this pursuit, ligand based pharmacophore virtual screening was employed, generating a pharmacophore model, Hypo1 consisting of four features. Furthermore, this Hypo1 was validated recruiting, Fischer’s randomization, test set method and decoy set method. Later, Hypo1 was allowed to screen databases such as Maybridge, Chembridge, Asinex and NCI and were further filtered by ADMET filters and Lipinski’s Rule of Five. A total of 699 molecules that passed the above criteria, were challenged against 4AG8, an angiogenic drug target employing GOLD v5.2.2. Results The results rendered by molecular docking, DFT and the MD simulations showed only one molecule (Hit) obeyed the back-to-front approach. This molecule displayed a dock score of 89.77, involving the amino acids, Glu885 and Cys919, Asp1046, respectively and additionally formed several important hydrophobic interactions. Furthermore, the identified lead molecule showed interactions with key residues when challenged with CDK2 protein, 1URW. Conclusion The lead candidate showed several interactions with the crucial residues of both the targets. Furthermore, we speculate that the residues Cys919 and Leu83 are important in the development of dual inhibitor. Therefore, the identified lead molecule can act as a potential inhibitor for angiogenesis and progression.

2D interaction representation of the Hit compound and 4AG8. Detailed molecular interactions of the Hit compound. (DOCX 424Â kb)

2D interaction representation of the co-crystal and 1URW. Detailed molecular interactions of the co-crystal compound. (DOCX 229Â kb)

Test set assessment. Assessing the test set values for estimated and the experimental activities by Hypo1. (DOCX 18Â kb)

Cocrystal re-dock results of 4AG8. Overlapping of the co-crystal (cyan) onto the docked pose (orange). The binding pattern was found to be similar. (DOCX 181Â kb)

2D interaction representation of the Hit compound and 1URW. Molecular interaction details of the Hit compound. (DOCX 264Â kb)

Active sites comparison. Comparison of the active site residues of 4AG8 and 1UMR. (DOCX 13Â kb)

2D interaction representation of the reference compound and 1URW. Molecular interaction details of the reference compound. (DOCX 204Â kb)

2D interaction representation of the the reference compound and 4AG8. Detailed molecular interactions of the reference compound. (DOCX 420Â kb)

Docking of the co-crystal within the binding pocket of 1URW. Docking of the co-crystal within the binding pocket. Pink is the docked pose and green represents the co-crystal position. (DOCX 142Â kb)

Additional file 1: Table S1. Ginger phytochemicals with their respective dock scores. Table S2. Antibiotics and their dock score. Figure S1. RMSD cluster of eight systems. Figure S2. Interaction of cofactor and Mg2+ with the protein.

Prolyl oligopeptidase (POP) is a serine protease that is responsible for the maturation and degradation of short neuropeptides and peptide hormones. The inhibition of POP has been demonstrated in the treatment of α-synucleinopathies and several neurological conditions. Therefore, ligand-based and structure-based pharmacophore models were generated and validated in order to identify potent POP inhibitors. Pharmacophore-based and docking-based virtual screening of a drug-like database resulted in 20 compounds. The in vitro POP assays indicated that the top scoring compounds obtained from virtual screening, Hit 1 and Hit 2 inhibit POP activity at a wide range of concentrations from 0.1 to 10 µM. Moreover, treatment of the hit compounds significantly reduced the α-synuclein expression in SH-SY5Y human neuroblastoma cells, that is implicated in Parkinson’s disease. Binding modes of Hit 1 and Hit 2 compounds were explored through molecular dynamics simulations. A detailed investigation of the binding interactions revealed that the hit compounds exhibited hydrogen bond interactions with important active site residues and greater electrostatic and hydrophobic interactions compared to those of the reference inhibitors. Finally, our findings indicated the potential of the identified compounds for the treatment of synucleinopathies and CNS related disorders.

Progeria is a rare genetic disorder characterized by premature aging that eventually leads to death and is noticed globally. Despite alarming conditions, this disease lacks effective medications; however, the farnesyltransferase inhibitors (FTIs) are a hope in the dark. Therefore, the objective of the present article is to identify new compounds from the databases employing pharmacophore based virtual screening. Utilizing nine training set compounds along with lonafarnib, a common feature pharmacophore was constructed consisting of four features. The validated Hypo1 was subsequently allowed to screen Maybridge, Chembridge, and Asinex databases to retrieve the novel lead candidates, which were then subjected to Lipinski’s rule of 5 and ADMET for drug-like assessment. The obtained 3,372 compounds were forwarded to docking simulations and were manually examined for the key interactions with the crucial residues. Two compounds that have demonstrated a higher dock score than the reference compounds and showed interactions with the crucial residues were subjected to MD simulations and binding free energy calculations to assess the stability of docked conformation and to investigate the binding interactions in detail. Furthermore, this study suggests that the Hits may be more effective against progeria and further the DFT studies were executed to understand their orbital energies.

Breast cancer is one of the major impediments affecting women globally. The ATP-dependant heat shock protein 90 (Hsp90) forms the central component of molecular chaperone machinery that predominantly governs the folding of newly synthesized peptides and their conformational maturation. It regulates the stability and function of numerous client proteins that are frequently upregulated and/or mutated in cancer cells, therefore, making Hsp90 inhibition a promising therapeutic strategy for the development of new efficacious drugs to treat breast cancer. In the present in silico investigation, a structure-based pharmacophore model was generated with hydrogen bond donor, hydrogen bond acceptor and hydrophobic features complementary to crucial residues Ala55, Lys58, Asp93, Ile96, Met98 and Thr184 directed at inhibiting the ATP-binding activity of Hsp90. Subsequently, the phytochemical dataset of 3210 natural compounds was screened to retrieve the prospective inhibitors after rigorous validation of the model pharmacophore. The retrieved 135 phytocompounds were further filtered by drug-likeness parameters including Lipinski's rule of five and ADMET properties, then investigated via molecular docking-based scoring. Molecular interactions were assessed using Genetic Optimisation for Ligand Docking program for 95 drug-like natural compounds against Hsp90 along with two clinical drugs as reference compounds - Geldanamycin and Radicicol. Docking studies revealed three phytochemicals are better than the investigated clinical drugs. The reference and hit compounds with dock scores of 48.27 (Geldanamycin), 40.90 (Radicicol), 73.04 (Hit1), 72.92 (Hit2) and 68.12 (Hit3) were further validated for their binding stability through molecular dynamics simulations. We propose that the non-macrocyclic scaffolds of three identified phytochemicals might aid in the development of novel therapeutic candidates against Hsp90-driven cancers.

Sirtuin 2 (SIRT2) is one of the emerging targets in chemotherapy field and mainly associated with many diseases such as cancer and Parkinson's. Hence, quantitative hypothesis was developed using Discovery Studio v2.5. Top ten resultant hypotheses were generated, among them Hypo1 was selected as a best hypothesis based on the statistical parameters like high cost difference (52), lowest RMS (0.71), and good correlation coefficient (0.96). Hypo1 has been validated by using well known methodologies such as Fischer's randomization method (95% confidence level), test set which has shown the correlation coeffi- cient of 0.93 as well as the goodness of hit (0.65), and enrichment factor (8.80). All the above statistical validations confirm that the chemical features in Hypo1 (1 hydrogen bond acceptor, 1 hydrophobic, and 2 ring aromatic features) was able to inhibit the function of SIRT2. Hence, Hypo1 was used as a query in virtual screening to find a novel scaffolds by screening the various chemical databases. The screened mol- ecules from the databases were checked for the ADMET as well as the drug-like properties. Due to the lack of SIRT2-ligand complex structure in PDB, molecular docking and molecular dynamics (MD) simu- lation was carried out to find the suitable orientation of ligand in the active site. The representative struc- ture from MD simulations was used as a receptor to dock the molecules which passed the drug-like properties from the virtual screening. Finally, 29 compounds were selected as a potent candidate leads based on the interactions with the active site residues of SIRT2. Thus, the resultant pharmacophore can be used to discover and design the SIRT2 inhibitors with desired biological activity.

The acetylcholinesterase (AChE) is important to terminate acetylcholine-mediated neurotransmission at cholinergic synapses. The pivotal role of AChE in apoptosome formation through the interactions with cytochrome c (Cyt c) was demonstrated in recent study. In order to investigate the proper binding conformation between the human AChE (hAChE) and human Cyt c (hCyt c), macro-molecular docking simulation was performed using DOT 2.0 program. The hCyt c was bound to peripheral anionic site (PAS) on hAChE and binding mode of the docked conformation was very similar to the reported crystal structure of the AChE and fasciculin-II (Fas-II) complex. Two 10 ns molecular dynamics (MD) simulations were carried out to refine the binding mode of docked structure and to observe the differences of the binding conformations between the absent (Apo) and presence (Holo) of heme group. The key hydrogen bonding residues between hAChE and hCyt c proteins were found in Apo and Holo systems, as well as each Tyr341 and Trp286 residue of hAChE was participated in cation-pi (π) interactions with Lys79 of hCyt c in Apo and Holo systems, respectively. From the present study, although the final structures of the Apo and Holo systems have similar binding pattern, several differences were investigated in flexibilities, interface interactions, and interface accessible surface areas. Based on these results, we were able to predict the reasonable binding conformation which is indispensable for apoptosome formation.

Peroxisome proliferator-activated receptors (PPARs) are members of nuclear receptors and their activation induces regulation of fatty acid storage and glucose metabolism. Therefore, the PPARγ is a major target for the treatment of type 2 diabetes mellitus. In order to generate pharmacophore model, 1080 known agonists database was constructed and a training set was selected. The Hypo7, selected from 10 hypotheses, contains four features: three hydrogen-bond acceptors (HBA) and one general hydrophobic (HY). This pharmacophore model was validated by using 862 test set compounds with a correlation coefficient of 0.903 between actual and estimated activity. Secondly, CatScramble method was used to verify the model. Hence, the validated Hypo7 was utilized for searching new lead compounds over 238,819 and 54,620 chemical structures in NCI and Maybridge database, respectively. Then the leads were selected by screening based on the pharmacophore model, predictive activity, and Lipinski’s rules. Candidates were obtained and subsequently the binding affinities to PPARγ were investigated by the molecular docking simulations. Finally the best two compounds were presented and would be useful to treat type 2 diabetes.