Homology modeling, molecular docking and MD simulation studies to investigate role of cysteine protease from Xanthomonas campestris in degradation of Aβ peptide

In silico homology modeling of dengue virus non-structural 4B (NS4B) protein and its molecular docking studies using triterpenoids

BACKGROUND

Dengue fever has become a significant worldwide health concern, because of its high morbidity rate and the potential for an increase in mortality rates due to lack of adequate treatment. There is an immediate need for the development of effective medication for dengue fever.

METHODS

Homology modeling of dengue virus (DENV) non-structural 4B (NS4B) protein was performed by SWISS-MODEL to predict the 3D structure of the protein. Structure validation was conducted using PROSA, PROCHECK, Ramachandran plot, and VERIFY-3D. MOE software was used to find out the in-Silico inhibitory potential of the five triterpenoids against the DENV-NS4B protein.

RESULTS

The SWISS-MODEL was employed to predict the three-dimensional protein structure of the NS4B protein. Through molecular docking, it was found that the chosen triterpenoid NS4B protein had a high binding affinity interaction. It was observed that the NS4B protein binding energy for 15-oxoursolic acid, betulinic acid, ursolic acid, lupeol, and 3-o-acetylursolic acid were - 7.18, - 7.02, - 5.71, - 6.67 and - 8.00 kcal/mol, respectively.

CONCLUSIONS

NS4B protein could be a promising target which showed good interaction with tested triterpenoids which can be developed as a potential antiviral drug for controlling dengue virus pathogenesis by inhibiting viral replication. However, further investigations are necessary to validate and confirm their efficacy.

Structural insights into the potential binding sites of Cathepsin D using molecular modelling techniques

Alzheimer's disease (AD) is the most prevalent type of dementia caused by the accumulation of amyloid beta (Aβ) peptides. The extracellular deposition of Aβ peptides in human AD brain causes neuronal death. Therefore, it has been found that Aβ peptide degradation is a possible therapeutic target for AD. CathD has been known to breakdown amyloid beta peptides. However, the structural role of CathD is not yet clear. Hence, for the purpose of gaining a deeper comprehension of the structure of CathD, the present computational investigation was performed using virtual screening technique to predict CathD's active site residues and substrate binding mode. Ligand-based virtual screening was implemented on small molecules from ZINC database against crystal structure of CathD. Further, molecular docking was utilised to investigate the binding mechanism of CathD with substrates and virtually screened inhibitors. Localised compounds obtained through screening performed by PyRx and AutoDock 4.2 with CathD receptor and the compounds having highest binding affinities were picked as; ZINC00601317, ZINC04214975 and ZINCC12500925 as our top choices. The hydrophobic residues Viz. Gly35, Val31, Thr34, Gly128, Ile124 and Ala13 help stabilising the CathD-ligand complexes, which in turn emphasises substrate and inhibitor selectivity. Further, MM-GBSA approach has been used to calculate binding free energy between CathD and selected compounds. Therefore, it would be beneficial to understand the active site pocket of CathD with the assistance of these discoveries. Thus, the present study would be helpful to identify active site pocket of CathD, which could be beneficial to develop novel therapeutic strategies for the AD.

Amyloid-induced neurodegeneration: A comprehensive review through aggregomics perception of proteins in health and pathology

Amyloidosis of protein caused by fibrillation and aggregation are some of the most exciting new edges not only in protein sciences but also in molecular medicines. The present review discusses recent advancements in the field of neurodegenerative diseases and therapeutic applications with ongoing clinical trials, featuring new areas of protein misfolding resulting in aggregation. The endogenous accretion of protein fibrils having fibrillar morphology symbolizes the beginning of neuro-disorders. Prognostic amyloidosis is prominent in numerous degenerative infections such as Alzheimer's and Parkinson's disease, Amyotrophic lateral sclerosis (ALS), etc. However, the molecular basis determining the intracellular or extracellular evidence of aggregates, playing a significant role as a causative factor in neurodegeneration is still unclear. Structural conversions and protein self-assembly resulting in the formation of amyloid oligomers and fibrils are important events in the pathophysiology of the disease. This comprehensive review sheds light on the evolving landscape of potential treatment modalities, highlighting the ongoing clinical trials and the potential socio-economic impact of novel therapeutic interventions in the realm of neurodegenerative diseases. Furthermore, many drugs are undergoing different levels of clinical trials that would certainly help in treating these disorders and will surely improve the socio-impact of human life.

Anti-angiogenic Potential of Trans-chalcone in an In Vivo Chick Chorioallantoic Membrane Model: An ATP Antagonist to VEGFR with Predicted Blood-brain Barrier Permeability

BACKGROUND

Glioblastoma multiforme (GBM) is characterized by massive tumorinduced angiogenesis aiding tumorigenesis. Vascular endothelial growth factor A (VEGF-A) via VEGF receptor 2 (VEGFR-2) constitutes majorly to drive this process. Putting a halt to tumordriven angiogenesis is a major clinical challenge, and the blood-brain barrier (BBB) is the prime bottleneck in GBM treatment. Several phytochemicals show promising antiangiogenic activity across different models, but their ability to cross BBB remains unexplored.

METHODS

We screened over 99 phytochemicals having anti-angiogenic properties reported in the literature and evaluated them for their BBB permeability, molecular interaction with VEGFR-2 domains, ECD2-3 (extracellular domains 2-3) and TKD (tyrosine kinase domain) at VEGF-A and ATP binding site, cell membrane permeability, and hepatotoxicity using in silico tools. Furthermore, the anti-angiogenic activity of predicted lead Trans-Chalcone (TC) was evaluated in the chick chorioallantoic membrane.

RESULTS

Out of 99 phytochemicals, 35 showed an efficient ability to cross BBB with a probability score of > 0.8. Docking studies revealed 30 phytochemicals crossing benchmark binding affinity < -6.4 kcal/mol of TKD with the native ligand ATP alone. Out of 30 phytochemicals, 12 showed moderate to low hepatotoxicity, and 5 showed a violation of Lipinski's rule of five. Our in silico analysis predicted TC as a BBB permeable anti-angiogenic compound for use in GBM therapy. TC reduced vascularization in the CAM model, which was associated with the downregulation of VEGFR-2 transcript expression.

CONCLUSION

The present study showed TC to possess anti-angiogenic potential via the inhibition of VEGFR-2. In addition, the study predicted TC to cross BBB as well as a safe alternative for GBM therapy, which needs further investigation.

Molecular insights into the inhibition of early stage of Aβ peptide aggregation and destabilization of Alzheimer's Aβ protofibril by dipeptide D-Trp-Aib: A molecular modelling approach

Amyloid beta (Aβ) peptide aggregates rapidly into the soluble oligomers, protofibrils and fibrils to form senile plaques, a neurotoxic component and pathological hallmark of Alzheimer's disease (AD). Experimentally, it has been demonstrated the inhibition of an early stages of Aβ aggregation by a dipeptide D-Trp-Aib inhibitor, but its molecular mechanism is still unclear. Hence, in the present study, we used molecular docking and molecular dynamics (MD) simulations to explore the molecular mechanism of inhibition of an early oligomerization and destabilization of preformed Aβ protofibril by D-Trp-Aib. Molecular docking study showed that the D-Trp-Aib binds at the aromatic (Phe19, Phe20) region of Aβ monomer, Aβ fibril and hydrophobic core of Aβ protofibril. MD simulations revealed the binding of D-Trp-Aib at the aggregation prone region (Lys16-Glu22) resulted in the stabilization of Aβ monomer by π-π stacking interactions between Tyr10 and indol ring of D-Trp-Aib, which decreases the β-sheet content and increases the α-helices. The interaction between Lys28 of Aβ monomer to D-Trp-Aib could be responsible to block the initial nucleation and may impede the fibril growth and elongation. The loss of hydrophobic contacts between two β-sheets of Aβ protofibril upon binding of D-Trp-Aib at the hydrophobic cavity resulted in the partial opening of β-sheets. This also disrupts a salt bridge (Asp23-Lys28) leading to the destabilization of Aβ protofibril. Binding energy calculations revealed that van der Waals and electrostatic interactions maximally favours the binding of D-Trp-Aib to Aβ monomer and Aβ protofibril respectively. The residues Tyr10, Phe19, Phe20, Ala21, Glu22, Lys28 of Aβ monomer, whereas Leu17, Val18, Phe19, Val40, Ala42 of protofibril contributing for the interactions with D-Trp-Aib. Thus, the present study provides structural insights into the inhibition of an early oligomerization of Aβ peptides and destabilization of Aβ protofibril, which could be useful to design novel inhibitors for the treatment of AD.

Lipopolysaccharide induced neuroprotective effects of bacterial protease against Alzheimer's disease in male Wistar albino rats

Alzheimer's disease (AD) is a highly severe neurodegenerative condition that affects the hippocampus and is characterized by memory loss and dementia. This investigation aims to determine the potential of a bacterial protease enzyme produced by a new mutant strain of bacteria (Bacillus cereus S6-3/UM90) to influence the rat behavioural, biochemical, histological, and immuno-histochemical functions induced by lipopolysaccharides (LPS) experimentally. The administration of LPS exhibited a decline in memory performance via Morris' Water Maze test along with an elevation of IL-6, IL-17, amino acid neurotransmitters, Adenosine monophosphate (AMP), and 8-OHdG, whereas a decrease in ATP (Adenosine Triphosphate), monoamine transmitters, AChE (acetylcholinesterase) and PC (phosphatidylcholine). Additionally, there was a notable increase in GFAP (glial fibrillary acidic protein) and p-Tau protein immuno-expression levels along with obvious histological lesions in the hippocampal CA3 region. Moreover, the administration of protease or Donepezil restored the measured parameters to nearly normal levels and improved the histological architecture of the hippocampus and ameliorated memory impairments. In conclusion, the study provides evidence that the treatment with Bacterial protease can improve the memory and learning impairments of LPS-induced AD and may be used as a promising therapeutic agent to manage AD since it has anti-inflammatory and antioxidant effects.

Molecular modelling studies and identification of novel phytochemical inhibitor of DLL3

Prostate cancer has been recently considered the most diagnosed cancer in male. DLL3 is overexpressed in CRPC-NE but not in localised prostate cancer or BPH. There are no effective treatments for neuroendocrine differentiated prostate cancer due to a lack of understanding of DLL3 structure and function. The structure of DLL3 is not yet determined using any experimental techniques. Hence, the structure-based drug discovery approach against prostate cancer has not shown great success. In present study, molecular modelling techniques were employed to generate three-dimensional structure of DLL3 and performed its thorough structural analysis. Further, all-atom molecular dynamics simulation was performed to obtain energetically favourable conformation. Further, we used a virtual screening using a library of >13800 phytochemicals from the IMPPAT database and other literature to select the best possible phytochemical inhibitor for DLL3 and identified the top five compounds. Relative binding affinity was calculated using the MM-PBSA approach. ADMET properties of the screened compounds reveal the toxic effect of Gnemonol C. We believe these studied physicochemical properties, functional domain identification, and binding site identification would be very useful to gain more structural and functional insights of DLL3; also, it can be used to infer their pharmacodynamics properties of DLL3 which was recently reported as an important prostate cancer target. The current study also proposes that Ergosterol Peroxide, Dioslupecin A, Mulberrofuran K, and Caracurine V have strong affinities and could serve as plausible inhibitors against DLL3. We believe this study would further help develop better drug candidates against neuroendocrine prostate cancer.Communicated by Ramaswamy H. Sarma.

In Silico Molecular Docking and Simulation Studies of Protein HBx Involved in the Pathogenesis of Hepatitis B Virus-HBV

Current drug discovery involves finding leading drug candidates for further development. New scientific approaches include molecular docking, ADMET studies, and molecular dynamic simulation to determine targets and lead compounds. Hepatitis B is a disease of concern that is a life-threatening liver infection. The protein considered for the study was HBx. The hepatitis B X-interacting protein crystal structure was obtained from the PDB database (PDB ID-3MSH). Twenty ligands were chosen from the PubChem database for further in silico studies. The present study focused on in silico molecular docking studies using iGEMDOCK. The triethylene glycol monoethyl ether derivative showed an optimum binding affinity with the molecular target HBx, with a high negative affinity binding energy of -59.02 kcal/mol. Lipinski's rule of five, Veber, and Ghose were followed in subsequent ADMET studies. Molecular dynamic simulation was performed to confirm the docking studies and to analyze the stability of the structure. In these respects, the triethylene glycol monoethyl ether derivative may be a promising molecule to prepare future hepatitis B drug candidates. Substantial research effort to find a promising drug for hepatitis B is warranted in the future.

Structural significance of Neprylysin from Streptococcus suis GZ1 in the degradation of Aβ peptides, a causative agent in Alzheimer's disease

Alzheimer's disease (AD) is a progressive brain disorder. The accumulation of amyloid beta (Aβ) peptides in the human brain leads to AD. The cleavage of Aβ peptides by several enzymes is being considered as an essential aspect in the treatment of AD. Neprilysin (NEP) is an important enzyme that clears the Aβ plaques in the human brain. The human NEP activity has been found reduced due to mutations in NEP and the presence of inhibitors. However, the role of NEP in the degradation of Aβ peptides in detail at the molecular level is not yet clear. Hence, in the present study, we have investigated the structural significance of NEP from the bacterial source Streptococcus suis GZ1 using various bioinformatics approaches. The homology modelling technique was used to predict the three-dimensional structure of NEP. Further, molecular dynamic (MD) simulated model of NEP was docked with Aβ peptide. Analysis of MD simulated docked complex showed that the wild-type NEP-Aβ-peptide complex is more stable as compared to mutant complex. Hydrogen bonding interactions between NEP with Zn²⁺and Aβ peptide confirm the degradation of the Aβ peptide. The molecular docking and MD simulation results revealed that the active site residue Glu-538 of bacterial NEP along with Zn²⁺ interact with His-13 of Aβ peptide. This stable interaction confirms the involvement of NEP with Glu-538 in the degradation of the Aβ peptide. The other residues such as Glu203, Ser537, Gly140, Val587, and Val536 could also play an important role in the cleavage of Aβ peptide in between Asp1-Ala2, Arg5-His6, Val18-Phe19, Gly9-Tyr10, and Arg5-His6. Hence, the predicted model of the NEP enzyme of Streptococcus suis GZ1could be useful to understand the Aβ peptide degradation in detail at the molecular level. The information obtained from this study would be helpful in designing new lead molecules for the effective treatment of AD.

Structural insights and inhibition mechanism of TMPRSS2 by experimentally known inhibitors Camostat mesylate, Nafamostat and Bromhexine hydrochloride to control SARS-coronavirus-2: A molecular modeling approach

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has been responsible for the cause of global pandemic Covid-19 and to date, there is no effective treatment available. The spike ‘S’ protein of SARS-CoV-2 and ACE2 of the host cell are being targeted to design new drugs to control Covid-19. Similarly, a transmembrane serine protease, TMPRSS2 of the host cell plays a significant role in the proteolytic cleavage of viral ‘S’ protein helpful for the priming of ACE2 receptors and viral entry into human cells. However, three-dimensional structural information and the inhibition mechanism of TMPRSS2 is yet to be explored experimentally. Hence, we have used a molecular dynamics (MD) simulated homology model of TMPRSS2 to study the inhibition mechanism of experimentally known inhibitors Camostat mesylate, Nafamostat and Bromhexine hydrochloride (BHH) using molecular modeling techniques. Prior to docking, all three inhibitors were geometry optimized by semi-empirical quantum chemical RM1 method. Molecular docking analysis revealed that Camostat mesylate and its structural analogue Nafamostat interact strongly with residues His296 and Ser441 present in the catalytic triad of TMPRSS2, whereas BHH binds with Ala386 along with other residues. Comparative molecular dynamics simulations revealed the stable behavior of all the docked complexes. MM-PBSA calculations also revealed the stronger binding of Camostat mesylate to TMPRSS2 active site residues as compared to Nafamostat and BHH. Thus, this structural information could be useful to understand the mechanistic approach of TMPRSS2 inhibition, which may be helpful to design new lead compounds to prevent the entry of SARS-Coronavirus 2 in human cells.

Molecular Docking in Formulation and Development

BACKGROUND

In pharmaceutical research drug discovery and development process is timeconsuming and expensive. In many cases, it produces incompetent results due to the failure of in vitro and in vivo conventional approaches. Before any new drug is placed in the market it must undergo rigorous testing to get FDA approval. Due to the several limitations imposed by the drug discovery process, in recent times in silico approaches are widely applied in this field. The purpose of this review is to highlight the current molecular docking strategies used in drug discovery and to explore various advances in the field.

METHODS

In this review we have compiled database after an extensive literature search on docking studies which has found its applications relevant to the field of formulation and development. The papers retrieved were further screened to appraise the quality of work. In depth strategic analysis was carried out to confirm the credibility of the findings.

RESULTS

The papers included in this review highlight the promising role of docking studies to overcome the challenges in formulation and development by emphasizing it's applications to predict drug excipient interactions which in turn assist to increase protein stability; to determine enzyme peptide interactions which maybe further used in drug development studies; to determine the most stable drug inclusion complex; to analyze structure at molecular level that ascertain an increase in solubility, dissolution and in turn the bioavailability of the drug; to design a dosage form that amplify the drug discovery and development process.

CONCLUSION

This review summarizes recent findings of critical role played by molecular docking in the process of drug discovery and development. The application of docking approach will assist to design a dosage form in the most cost effective and time saving manner.

Structural and biochemical characterization of a novel thermophilic Coh01147 protease

Proteases play an essential role in living organisms and represent one of the largest groups of industrial enzymes. The aim of this work was recombinant production and characterization of a newly identified thermostable protease 1147 from thermophilum indigenous Cohnella sp. A01. Phylogenetic tree analysis showed that protease 1147 is closely related to the cysteine proteases from DJ-1/ThiJ/PfpI superfamily, with the conserved catalytic tetrad. Structural prediction using MODELLER 9v7 indicated that protease 1147 has an overall α/β sandwich tertiary structure. The gene of protease 1147 was cloned and expressed in Escherichia coli (E. coli) BL21. The recombinant protease 1147 appeared as a homogenous band of 18 kDa in SDS-PAGE, which was verified by western blot and zymography. The recombinant protein was purified with a yield of approximately 88% in a single step using Ni-NTA affinity chromatography. Furthermore, a rapid one-step thermal shock procedure was successfully implemented to purify the protein with a yield of 73%. Using casein as the substrate, K_m, and k_cat, k_cat/K_m values of 13.72 mM, 3.143 × 10⁻³ (s^-1), and 0.381 (M^-1 S^-1) were obtained, respectively. The maximum protease activity was detected at pH = 7 and 60°C with the inactivation rate constant (kin) of 2.10 × 10–3 (m^-1), and half-life (t_1/2) of 330.07 min. Protease 1147 exhibited excellent stability to organic solvent, metal ions, and 1% SDS. The protease activity was significantly enhanced by Tween 20 and Tween 80 and suppressed by cysteine protease specific inhibitors. Docking results and molecular dynamics (MD) simulation revealed that Tween 20 interacted with protease 1147 via hydrogen bonds and made the structure more stable. CD and fluorescence spectra indicated structural changes taking place at 100°C, very basic and acidic pH, and in the presence of Tween 20. These properties make this newly characterized protease a potential candidate for various biotechnological applications.

Amyloid beta peptide-degrading microbial enzymes and its implication in drug design

Alzheimer's disease (AD) is a chronic and progressive neurological brain disorder. AD pathophysiology is mainly represented by formation of neuritic plaques and neurofibrillary tangles (NFTs). Neuritic plaques are made up of amyloid beta (Aβ) peptides, which play a central role in AD pathogenesis. In AD brain, Aβ peptide accumulates due to overproduction, insufficient clearance and defective proteolytic degradation. The degradation and cleavage mechanism of Aβ peptides by several human enzymes have been discussed previously. In the mean time, numerous experimental and bioinformatics reports indicated the significance of microbial enzymes having potential to degrade Aβ peptides. Thus, there is a need to shift the focus toward the substrate specificity and structure-function relationship of Aβ peptide-degrading microbial enzymes. Hence, in this review, we discussed in vitro and in silico studies of microbial enzymes viz. cysteine protease and zinc metallopeptidases having ability to degrade Aβ peptides. In silico study showed that cysteine protease can cleave Aβ peptide between Lys16-Cys17; similarly, several other enzymes also showed capability to degrade Aβ peptide at different sites. Thus, this review paves the way to explore the role of microbial enzymes in Aβ peptide degradation and to design new lead compounds for AD treatment.

Rational drug repurposing for cancer by inclusion of the unbiased molecular dynamics simulation in the structure-based virtual screening approach: Challenges and breakthroughs

Managing cancer is now one of the biggest concerns of health organizations. Many strategies have been developed in drug discovery pipelines to help rectify this problem and two of the best ones are drug repurposing and computational methods. The combination of these approaches can have immense impact on the course of drug discovery. In silico drug repurposing can significantly reduce the time, the cost and the effort of drug development. Computational methods such as structure-based drug design (SBDD) and virtual screening can predict the potentials of small molecule binders, such as drugs, for having favorable effect on a particular molecular target. However, the demand for accuracy and efficiency of SBDD requires more sophisticated and complicated approaches such as unbiased molecular dynamics (UMD) simulation that has been recently introduced. As a complementary strategy, the knowledge acquired from UMD simulations can increase the chance of finding the right candidates and the pipeline of its administration is introduced and discussed in this review. An elaboration of this pipeline is also made by detailing an example, the binding and unbinding pathways of dasatinib-c-Src kinase complex, which shows that how influential this method can be in rational drug repurposing in cancer treatment.

Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets

The discovery of targeted drugs heavily relies on three-dimensional (3D) structures of target proteins. When the 3D structure of a protein target is unknown, it is very difficult to design its corresponding targeted drugs. Although the 3D structures of some proteins (the so-called undruggable targets) are known, their targeted drugs are still absent. As increasing crystal/cryogenic electron microscopy structures are deposited in Protein Data Bank, it is much more possible to discover the targeted drugs. Moreover, it is also highly probable to turn previous undruggable targets into druggable ones when we identify their hidden allosteric sites. In this review, we focus on the currently available advanced methods for the discovery of novel compounds targeting proteins without 3D structure and how to turn undruggable targets into druggable ones.

Theoretical and Experimental Approaches Aimed at Drug Design Targeting Neurodegenerative Diseases

In recent years, green chemistry has been strengthening, showing how basic and applied sciences advance globally, protecting the environment and human health. A clear example of this evolution is the synergy that now exists between theoretical and computational methods to design new drugs in the most efficient possible way, using the minimum of reagents and obtaining the maximum yield. The development of compounds with potential therapeutic activity against multiple targets associated with neurodegenerative diseases/disorders (NDD) such as Alzheimer’s disease is a hot topic in medical chemistry, where different scientists from various disciplines collaborate to find safe, active, and effective drugs. NDD are a public health problem, affecting mainly the population over 60 years old. To generate significant progress in the pharmacological treatment of NDD, it is necessary to employ different experimental strategies of green chemistry, medical chemistry, and molecular biology, coupled with computational and theoretical approaches such as molecular simulations and chemoinformatics, all framed in the rational drug design targeting NDD. Here, we review how green chemistry and computational approaches have been used to develop new compounds with the potential application against NDD, as well as the challenges and new directions of the drug development multidisciplinary process.

Combined approach of homology modeling, molecular dynamics, and docking: computer-aided drug discovery

With the continuous development in software, algorithms, and increase in computer speed, the field of computer-aided drug design has been witnessing reduction in the time and cost of the drug designing process. Structure based drug design (SBDD), which is based on the 3D structure of the enzyme, is helping in proposing novel inhibitors. Although a number of crystal structures are available in various repositories, there are various proteins whose experimental crystallization is difficult. In such cases, homology modeling, along with the combined application of MD and docking, helps in establishing a reliable 3D structure that can be used for SBDD. In this review, we have reported recent works, which have employed these three techniques for generating structures and further proposing novel inhibitors, for cytoplasmic proteins, membrane proteins, and metal containing proteins. Also, we have discussed these techniques in brief in terms of the theory involved and the various software employed. Hence, this review can give a brief idea about using these tools specifically for a particular problem.

The Potential of Serratiopetidase and Lumbrokinase for the Degradation of Prion Peptide 106-126 - an In Vitro and In Silico Perspective

BACKGROUND

PrPC is a host-encoded prion protein, which gets post translationally modified into a transmissible, β-sheet rich disease associated protein called PrPSc, responsible for the Prion disease including mad cow disease in cattle and CJD in humans. The PrP 106-126 region in PrPSc peptide initiates the conformational change in that protein leading to fibrillation. Any agent that can destabilize or disintegrate such proteins can be served as a potential drug candidate for Prion diseases.

METHODS

In the present study, an enzyme Lumbrokinase (LK) was isolated from earthworm and its activity was exploited towards PrP 106-126 amyloids in vitro along with another enzyme Serratiopeptidase (SP) taking Nattokinase (NK) as a standard.

RESULTS

The results showed that PrP 106-126 amyloid formation was inhibited by both LK and SP, as evidenced from Thioflavin T fluorescence assay. Further, the size of fibrils as estimated by dynamic light scattering, was also found to be lower at different time intervals after incubation of the prion amyloids with LK and SP. Additionally, the molecular dynamics simulation revealed the thermodynamically favorable interaction of PrP 106-126 with LK as well as with SP with high affinity.

CONCLUSION

Finally, the toxicity of the disintegrated amyloids was assessed using PC12 cell lines which showed higher cell viability in case of LK and SP treated amyloids compared to only PrP 106- 126 amyloid treatment. Altogether, the study concluded that the serine proteases like LK and SP have the potential to disintegrate PrP 106-126 amyloids with improved cell viability. The in vivo studies are needed to be executed in future.

Evaluation of drug candidature: In silico ADMET, binding interactions with CDK7 and normal cell line studies of potentially anti-breast cancer enamidines

We have recently explored novel class of potentially anti-breast cancer active enamidines in which four molecules 4a-c and 4h showed higher anticancer activity compared to standard drug doxorubicin. As a part of extension of this work, we have further evaluated in silico cheminformatic studies on bioactivity prediction of synthesized series of enamidines using mole information. The normal cell line study of four lead compounds 4a-c and 4h against African green monkey kidney vero strain further revealed that the compounds complemented good selectivity in inhibition of cancer cells. The in silico bioactivity and molecular docking studies also revealed that the compounds have significant interactions with the drug targets. The results reveal that enamidine moieties are vital for anti-breast cancer activity as they possess excellent drug-like characteristics, being potentially good inhibitors of cyclin dependent kinases7 (CDK7).

In Silico Studies in Drug Research Against Neurodegenerative Diseases

Background

Neurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis, Parkinson's disease (PD), spinal cerebellar ataxias, and spinal and bulbar muscular atrophy are described by slow and selective degeneration of neurons and axons in the central nervous system (CNS) and constitute one of the major challenges of modern medicine. Computer-aided or in silico drug design methods have matured into powerful tools for reducing the number of ligands that should be screened in experimental assays.

Methods

In the present review, the authors provide a basic background about neurodegenerative diseases and in silico techniques in the drug research. Furthermore, they review the various in silico studies reported against various targets in neurodegenerative diseases, including homology modeling, molecular docking, virtual high-throughput screening, quantitative structure activity relationship (QSAR), hologram quantitative structure activity relationship (HQSAR), 3D pharmacophore mapping, proteochemometrics modeling (PCM), fingerprints, fragment-based drug discovery, Monte Carlo simulation, molecular dynamic (MD) simulation, quantum-mechanical methods for drug design, support vector machines, and machine learning approaches.

Results

Detailed analysis of the recently reported case studies revealed that the majority of them use a sequential combination of ligand and structure-based virtual screening techniques, with particular focus on pharmacophore models and the docking approach.

Conclusion

Neurodegenerative diseases have a multifactorial pathoetiological origin, so scientists have become persuaded that a multi-target therapeutic strategy aimed at the simultaneous targeting of multiple proteins (and therefore etiologies) involved in the development of a disease is recommended in future.

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

Background

Neurodegenerative disorders (NDs) are diverse group of disorders characterized by escalating loss of neurons (structural and functional). The development of potential therapeutics for NDs presents an important challenge, as traditional treatments are inefficient and usually are unable to stop or retard the process of neurodegeneration. Computer-Aided Drug Design (CADD) has emerged as an efficient means of developing candidate drugs for the treatment of many disease types. Applications of CADD approach to drug discovery are progressing day by day. The recent tendency in drug design is to rationally design potent therapeutics with multi-targeting effects, higher efficacies, and fewer side effects, especially in terms of toxicity.

Methods

A wide literature search was performed for writing this review. An updated view on different types of NDs, their effect on human population and a brief introduction to CADD, various approaches involved in this technique, ranging from structural-based to ligand-based drug design has been discussed. The successful application of CADD approaches for the treatment of neurodegenerative disorders is also included in this review.

Results

In this review, we have briefly described about CADD and its use in the development of the therapeutic drug candidates against NDs. The successful applications, limitations and future prospects of this approach have also been discussed.

Conclusion

CADD can assist researchers studying interactions between drugs and receptors. We believe this review will be helpful for better understanding of CADD and its applications towards the discovery of new drug candidates against various fatal NDs.

Molecular Cloning and Docking of speB Gene Encoding Cysteine Protease With Antibiotic Interaction in Streptococcus pyogenes NBMKU12 From the Clinical Isolates

Streptococcus pyogenes causes a variety of diseases ranging from mild diseases to severe invasive infections which result in significant morbidity and mortality. This study focuses on the antibiotic resistance of S. pyogenes and their interaction with cysteine protease. Around 36 beta-hemolytic isolates were collected from the clinical lab, of which seven isolates (19.4%) were identified as Streptococcus pyogenes. One of the seven isolates was collected from a urinary tract infection, which was identified by antibody agglutination and MALTI-TOF-MS, and it is designated as S. pyogenes NBMKU12. Around 8.3 to 66.6 % of the isolates were found to be resistant to one or more antimicrobial agents, especially, penicillin-G resistance was exhibited by 29.1% of the isolates. In the NBMKU12 isolate, the beta lactem (TEM) gene was detected among the 13 antibiotic genes for which it was tested. Furthermore, when analysis for presence of 13 virulence genes were carried out in NBMKU12 isolate, only speJ and speB were detected. The speB (streptococcal pyrogenic exotoxin B) encoding cysteine protease gene was cloned. This was followed by performing DNA sequencing to understand the putative cysteine protease interaction with antibiotics, inhibitors, and substrate. The speB gene consists of 1197 nucleotides and encodes a protein with multiple domains, including a signal peptide (aa 1-22), an inhibitor region (aa 27-156), and a catalytic cysteine domain (aa 160-367). The signal peptide cleavage site is predicted between Ala22 and Asn23. The putative 398 amino acid residues were found to have a theoretical pI of 8.76 and a molecular mass of 43,204.36 Da. The tested culture supernatants of NBMKU12 isolate exhibited the proteolytic activity against casein, papaya and pineapple used as substrates. The proteolytic activity suggests the expression of speB gene. Molecular docking analysis of cysteine protease showed that erythromycin (bond length 2.41 Å), followed by chloramphenicol (2.51 Å), exhibited a strong interaction; while penicillin-G (3.24 Å) exhibited a weak interaction, and this factor could be considered as a cause for penicillin-G resistance. The present study contributes to a better understanding of speB gene encoding cysteine protease, antibiotic resistance, and their interaction in the isolate, S. pyogenes NBMKU12. The antibiotics and cysteine protease interaction study confirms the resistance or sensitivity of S. pyogenes. Hence, it could be hypothesized that the isolate NBMKU12 is resistant to most of the tested antibiotics, and this resistance might be a cause for mutation.

An insight to the molecular interactions of the FDA approved HIV PR drugs against L38L↑N↑L PR mutant

The aspartate protease of the human immune deficiency type-1 virus (HIV-1) has become a crucial antiviral target in which many useful antiretroviral inhibitors have been developed. However, it seems the emergence of new HIV-1 PR mutations enhances drug resistance, hence, the available FDA approved drugs show less activity towards the protease. A mutation and insertion designated L38L↑N↑L PR was recently reported from subtype of C-SA HIV-1. An integrated two-layered ONIOM (QM:MM) method was employed in this study to examine the binding affinities of the nine HIV PR inhibitors against this mutant. The computed binding free energies as well as experimental data revealed a reduced inhibitory activity towards the L38L↑N↑L PR in comparison with subtype C-SA HIV-1 PR. This observation suggests that the insertion and mutations significantly affect the binding affinities or characteristics of the HIV PIs and/or parent PR. The same trend for the computational binding free energies was observed for eight of the nine inhibitors with respect to the experimental binding free energies. The outcome of this study shows that ONIOM method can be used as a reliable computational approach to rationalize lead compounds against specific targets. The nature of the intermolecular interactions in terms of the host-guest hydrogen bond interactions is discussed using the atoms in molecules (AIM) analysis. Natural bond orbital analysis was also used to determine the extent of charge transfer between the QM region of the L38L↑N↑L PR enzyme and FDA approved drugs. AIM analysis showed that the interaction between the QM region of the L38L↑N↑L PR and FDA approved drugs are electrostatic dominant, the bond stability computed from the NBO analysis supports the results from the AIM application. Future studies will focus on the improvement of the computational model by considering explicit water molecules in the active pocket. We believe that this approach has the potential to provide information that will aid in the design of much improved HIV-1 PR antiviral drugs.

Molecular Docking Technique to Understand Enzyme-Ligand Interactions

Molecular docking has advanced to such an extent that one can rapidly and accurately identify pharmaceutically useful lead compounds. It is being used routinely to understand molecular interactions between enzyme and ligand molecules. Several computational approaches are combined with experimental work to investigate molecular mechanisms in detail at the atomic level. Molecular docking method is also useful to investigate proper orientation and interactions between receptor and ligand. In this chapter we have discussed protein-protein approach to understand interactions between enzyme and amyloid beta (Aß) peptide. The Aß peptide is a causative agent of Alzheimer's disease. The Aß peptides can be cleaved specifically by several enzymes. Their interactions with Aß peptide and specific enzyme can be investigated using molecular docking. Thus, the molecular information obtained from docking studies might be useful to design new therapeutic approaches in treatment of Alzheimer's as well as several other diseases.

Molecular modeling approach to explore the role of cathepsin B from Hordeum vulgare in the degradation of Aβ peptides

The pathological hallmark of Alzheimer's disease is the accumulation of Aβ peptides in human brains. These Aβ peptides can be degraded by several enzymes such as hACE, hECE, hIDE and cathepsin B. Out of which cathepsin B also belongs to the papain super family and has been found in human brains, it has a role in Aβ peptide degradation through limited proteolysis. The Aβ concentrations are maintained properly by its production and clearance via receptor-mediated cellular uptake and direct enzymatic degradation. However, the reduced production of Aβ degrading enzymes as well as their Aβ degrading activity in human brains initiate the process of accumulation of Aβ peptides. So it becomes essential to investigate the molecular interactions involved in the process of Aβ degradation in detail at the atomic level. Hence, homology modeling, molecular docking and molecular dynamics simulation techniques have been used to explore the possible role of cathepsin B from Hordeum vulgare in the degradation of amyloid beta (Aβ) peptides. The homology model of cathepsin B from Hordeum vulgare shows good similarity with human cathepsin B. Molecular docking and MD simulation results revealed that the active site residues Cys32, HIS112, HIS113 are involved in the catalytic activity of cathepsin B. The sulfhydryl group of the Cys32 residue of cathepsin B from Hordeum vulgare cleaves the Aβ peptide from the carboxylic end of Glu11. Hence, this structural study might be helpful in designing alternative strategies for the treatment of AD.

Binding Free Energy Calculations of Nine FDA-approved Protease Inhibitors Against HIV-1 Subtype C I36T↑T Containing 100 Amino Acids Per Monomer

In this work, have investigated the binding affinities of nine FDA-approved protease inhibitor drugs against a new HIV-1 subtype C mutated protease, I36T↑T. Without an X-ray crystal structure, homology modelling was used to generate a three-dimensional model of the protease. This and the inhibitor models were employed to generate the inhibitor/I36T↑T complexes, with the relative positions of the inhibitors being superimposed and aligned using the X-ray crystal structures of the inhibitors/HIV-1 subtype B complexes as a reference. Molecular dynamics simulations were carried out on the complexes to calculate the average binding free energies for each inhibitor using the molecular mechanics generalized Born surface area (MM-GBSA) method. When compared to the binding free energies of the HIV-1 subtype B and subtype C proteases (calculated previously by our group using the same method), it was clear that the I36T↑T proteases mutations and insertion had a significant negative effect on the binding energies of the non-pepditic inhibitors nelfinavir, darunavir and tipranavir. On the other hand, ritonavir, amprenavir and indinavir show improved calculated binding energies in comparison with the corresponding data for wild-type C-SA protease. The computational model used in this study can be used to investigate new mutations of the HIV protease and help in establishing effective HIV drug regimes and may also aid in future protease drug design.

Amyloid cascade hypothesis: Pathogenesis and therapeutic strategies in Alzheimer's disease

Alzheimer's disease is an irreversible, progressive neurodegenerative disorder. Various therapeutic approaches are being used to improve the cholinergic neurotransmission, but their role in AD pathogenesis is still unknown. Although, an increase in tau protein concentration in CSF has been described in AD, but several issues remains unclear. Extensive and accurate analysis of CSF could be helpful to define presence of tau proteins in physiological conditions, or released during the progression of neurodegenerative disease. The amyloid cascade hypothesis postulates that the neurodegeneration in AD caused by abnormal accumulation of amyloid beta (Aβ) plaques in various areas of the brain. The amyloid hypothesis has continued to gain support over the last two decades, particularly from genetic studies. Therefore, current research progress in several areas of therapies shall provide an effective treatment to cure this devastating disease. This review critically evaluates general biochemical and physiological functions of Aβ directed therapeutics and their relevance.

Evaluation of a possible role of Stigmatella aurantiaca ACE in Aβ peptide degradation: a molecular modeling approach

Amyloid-β (Aβ)-degrading enzymes are known to degrade Aβ peptides, a causative agent of Alzheimer's disease. These enzymes are responsible for maintaining Aβ concentration. However, loss of such enzymes or their Aβ-degrading activity because of certain genetic as well as nongenetic reasons initiates the accumulation of Aβ peptides in the human brain. Considering the limitations of the human enzymes in clearing Aβ peptide, the search for microbial enzymes that could cleave Aβ is necessary. Hence, we built a three-dimensional model of angiotensin-converting enzyme (ACE) from Stigmatella aurantiaca using homology modeling technique. Molecular docking and molecular dynamics simulation techniques were used to outline the possible cleavage mechanism of Aβ peptide. These findings suggest that catalytic residue Glu 434 of the model could play a crucial role to degrade Aβ peptide between Asp 7 and Ser 8. Thus, ACE from S. aurantiaca might cleave Aβ peptides similar to human ACE and could be used to design new therapeutic strategies against Alzheimer's disease.

Insight into molecular interactions of Aβ peptide and gelatinase from Enterococcus faecalis: a molecular modeling approach

Alzheimer's disease is characterized by the presence of extracellular deposition of amyloid beta (Aβ) peptides.

Lead discovery and in silico 3D structure modeling of tumorigenic FAM72A (p17)

FAM72A (p17) is a novel neuronal protein that has been linked to tumorigenic effects in non-neuronal tissue. Using state of the art in silico physicochemical analyses (e.g., I-TASSER, RaptorX, and Modeller), we determined the three-dimensional (3D) protein structure of FAM72A and further identified potential ligand-protein interactions. Our data indicate a Zn(2+)/Fe(3+)-containing 3D protein structure, based on a 3GA3_A model template, which potentially interacts with the organic molecule RSM ((2s)-2-(acetylamino)-N-methyl-4-[(R)-methylsulfinyl] butanamide). The discovery of RSM may serve as potential lead for further anti-FAM72A drug screening tests in the pharmaceutical industry because interference with FAM72A's activities via RSM-related molecules might be a novel option to influence the tumor suppressor protein p53 signaling pathways for the treatment of various types of cancers.