Potential bioactive compound and hub gene identification of endometrial carcinoma using systems biology

Endometrial carcinoma is a frequent cancer of the female genital tract. Endometrial carcinoma accounts for 97% of all uterine malignancies and 3 % of sarcomas that develop from the endometrium's glands. Endometrial cancer is frequently found in its early stages since most women quickly report postmenopausal vaginal hemorrhage. The need for more advanced medications to improve survival in such situations is still unfulfilled. As a result, there is growing interest in employing an herbal treatment to treat endometriosis, which seems to be an effective strategy. We have discovered a few unintended targets (ligands) in our investigation that are active components of common therapeutic herbs. The differentially expressed genes (DEG - target protein) for endometrial cancer were found using the NCBI and CIViC databases. In our investigation, the protein used for docking and simulation was PDB ID: 3THW. Using the Cytoscape server, the gene-encoding protein network has been identified. It was discovered that the Protein 3THW's binding energy to the bioactive substance (Asarone) was -7.15 Kcal/mol. It was discovered that the crucial interacting amino acid residues were ILE648, PHE650, ILE651, VAL802, TYR815, VAL817. The properties of the pharmaceutical target are further investigated by employing a molecular simulation study for 100 ns with NAMD software. Low RMSD and SASA (Solvent accessible surface area), high RMSF, High hydrogen bonds, between Asarone and MSH2 demonstrated their potency as endometrial cancer inhibitor compounds. Based on these analyses we infer that the bioactive substances originating from medicinal plants may be an effective treatment for endometrial cancer.Communicated by Ramaswamy H. Sarma.

Structural dynamics of moonlighting intrinsically disordered proteins - A black box in multiple sclerosis

Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system that disturbs the flow of brain signals to other parts of the body. The actual cause of the disease is still not apparent. The intrinsically disordered proteins (IDP) play a crucial role in neurodegenerative diseases like Alzheimer's, Lewy bodies, Parkinson's, Amyotrophic Lateral Sclerosis, Multiple Sclerosis, etc. In MS, it was known that the immune system attacks the proteins like Myelin Basic Protein (MBP), Myelin-associated Oligodendrocyte Basic protein (MOBP), Myelin-Associated Protein (MAG), and Myelin Proteolipid Protein (PLP) and this leads to demyelination causing MS. Here the proteins MBP and MOBP are both moonlighting intrinsically disordered proteins and exist between the myelin sheath, unlike MAG which is a transmembrane protein. The main focus of the article was to examine the significant role of proteins intrinsically disordered regions (IDR) in maintaining their function. Molecular dynamics simulation studies were performed to study the conformational dynamics of these protein IDRs both in water and near the myelin sheath. The results suggest that the IDR dominates the structural dynamics of these proteins and IDR in both proteins was responsible for their interaction with the myelin sheath. Interestingly, it was noted that the known epitopes MBP83-96 and MOBP65-87 in the IDR have no interaction with the myelin sheath. Thus when the protein remains intrinsically disordered it maintains the proper function and myelin integrity and if it adopts folds the region was identified as an epitope by the immune system leading to demyelination causing MS.

Molecular dynamics simulation of ssDNA and cationic polythiophene

In this work, molecular dynamics simulations of complexes composed of single strand DNA (ssDNA) sequences and cationic oligothiophenes are performed to understand experimental findings and the sensing ability of polythiophene electrolytes toward ssDNA. The simulation results exhibit no significant structural effect for replacing the cationic amine moiety with imidazole derivative on the side group of the oligomer. Adding a homopurine strand elongates the oligomer backbone; on the contrary, mixing up the homopyrimidine strand causes compression. On the other hand, these ssDNAs do not notably affect the compactness of the oligomer backbones. The anion-cation interactions play an essential role in the structural and spectroscopic change of cationic polythiophenes (CPTs) upon complexation with ssDNAs. The red shift of CPTs in the UV-VIS spectra with the addition of homopurine strands might be explained by the strong anion-cation, weak π -cation interactions, and high binding affinities. Nonpolar interactions (vdW and SA) and complex solvation energies dominate binding free energies. Hydrogen interaction analyses show that oligomers most likely approach the ssDNAs from their backbone upon complexation except for the duplex containing homopyrimidine strand and oligothiophene possessing imidazole derivative side chain.

MDBuilder: a PyMOL plugin for the preparation of molecular dynamics simulations

The preprocessed initial files that feed the molecular dynamics (MD) simulation packages dramatically influence the outcome of the simulations. However, the popular MD simulation packages depend, to a great extent, on the user's experience in the preparation of MD simulation systems. In this work, we present an easy-to-use tool called MDBuilder, a PyMOL plugin that assists researchers in building the starting structures for multiple popular MD simulation packages. MDBuilder is not only designed to assist MD beginners to overcome the steep learning curve by providing a menu-oriented, point-and-click user graphic interface (GUI), but also to provide an alternative way to prepare the input files for some highly scalable CHARMM force field-based MD simulation packages. The platform-independent GUI is implemented as a PyMOL plugin using the Python language, and it has been tested on Windows and Linux platforms. The source code and documentation of MDBuilder can be downloaded freely from https://github.com/HuiLiuCode/MDBuilder under the GNU General Public License.

Molecular Dynamics Simulation of Protein Cages

Molecular dynamics (MD) simulations enable the description of the physical movement of the system over time based on classical mechanics at various scales depending on the models. Protein cages are a particular group of different-size proteins with hollow, spherical structures and are widely found in nature, which have vast applications in numerous fields. The MD simulation of cage proteins is particularly important as a powerful tool to unveil their structures and dynamics for various properties, assembly behavior, and molecular transport mechanisms. Here, we describe how to conduct MD simulations for cage proteins, especially technical details, and analyze some of the properties of interest using GROMACS/NAMD packages.

Molecular Dynamics Simulations of RNA Motifs to Guide the Architectural Parameters and Design Principles of RNA Nanostructures

Molecular dynamics (MD) simulations can be used to investigate the stability and conformational characteristics of RNA nanostructures. However, MD simulations of an RNA nanostructure is computationally expensive due to the size of nanostructure and the number of atoms. Alternatively, MD simulations of RNA motifs can be used to estimate the conformational stability of constructed RNA nanostructure due to their small sizes. In this chapter, we introduce the preparation and MD simulations of two RNA kissing loop (KL) motifs, a linear KL complex and a bent KL complex, and an RNA nanoring. The initial solvated system and topology files of each system will be prepared by two major force fields, AMBER and CHARMM force fields. MD simulations will be performed by NAMD simulation package, which can accept both force fields. In addition, we will introduce the use of the AMBER cpptraj program and visual molecular dynamics (VMD) for data analysis. We will also discuss how MD simulations of two KL motifs can be used to estimate the conformation and stability of RNA nanoring as well as to explain the vibrational characteristics of RNA nanoring.

Non-bonding energy directed designing of HDAC2 inhibitors through molecular dynamics simulation

Designing an inhibitor having strong affinity in the active site pocket is the cherished goal of structure based drug designing. To achieve this, it is considerably important to predict which structural scaffold is better suited for change to increase affinity. We have explored five HDAC2 co-crystals having PDB ligand code-SHH (vorinostat), LLX, 20Y, IWX (BRD4884) and 6EZ (BRD7232). For analyzing protein-ligand interaction at an atomistic level, we have employed the NAMD molecular dynamics (MD) package. The obtained 100 ns long MD trajectories were subjected to quantitative estimations of non-bonding energies (NBEs) for inferring their interactions with the whole protein or its composite active site (CAS). In addition, relative ΔG_bind was calculated to rank the inhibitors. These inhibitors' NBEs reveal that the phenyl moieties are the major structural scaffold where modifications should be attempted. We designed new compounds (NCs) via introducing hydroxyl groups at 4,5 position of the phenyl moiety of 6EZ, called NC1. Improvement in NC1 further encouraged us for CAP modification by isochromane and isoindoline moieties in place of oxabicyclooctane in NC1, resulting in NC2 and NC3. We also explored trifluoromethyl oxadiazole in 6EZ (NC4 and NC5) and SHH (NC6 and NC7). This moiety acts as a ZBG in NC4 while acting as a part of the foot-pocket in the rest. NC2 and NC6 have highest favorable NBEs among all studied ligands due increased favorable electrostatic contribution. We expect these NBEs data will provide atomistic level insights and benefit in designing new and improved HDAC2 inhibitors. Communicated by Ramaswamy H. Sarma.

Interference of Chaga mushroom terpenoids with the attachment of SARS-CoV-2; in silico perspective

Finding a potent inhibitor to the pandemic SARS-CoV-2 is indispensable nowadays. Currently, in-silico methods work as expeditious investigators to screen drugs for possible repurposing or design new ones. Targeting one of the possible SARS-CoV-2 attachment and entry receptors, Glucose-regulated protein 78 (GRP78), is an approach of major interest. Recently, GRP78 was reported as a recognized representative in recognition of the latest variants of SARS-CoV-2. In this work, molecular docking and molecular dynamics simulations were performed on the host cell receptor GRP78. With its many terpenoid compounds, Chaga mushroom was tested as a potential therapeutic against the SARS-CoV-2 receptor, GRP78. Results revealed low binding energies (high affinities) toward the GRP78 substrate-binding domain β (SBDβ) of Chaga mushroom terpenoids. Even the highly specific cyclic peptide Pep42, which selectively targeted GRP78 over cancer cells in vivo, showed lower binding affinity against GRP78 SBDβ compared to the binding affinities of terpenoids. These are auspicious results that need to be tested experimentally. Intriguingly, terpenoids work as a double sword as they can be used to interfere with VUI 202,012/01, 501.V2, and B.1.1.248 variants of SARS-CoV-2 spike recognition.

Inhibition constant and stability of tripeptide inhibitors of gut trypsin-like enzyme of the soybean pest Anticarsia gemmatalis

Insects overcome the action of natural protease inhibitors (PIs) due to evolutionary adaptations through endogenous proteolysis and reprogramming proteases. Insect adaptations complicate the formulation of IP-based crop protection products. However, small peptides designed based on the active site of enzymes have shown promising results that could change this scenario. GORE1 and GORE2 are designed tripeptides that reduce the survival of Anticarsia gemmatalis when ingested orally. In this article, the stability and ability of the peptides to bind trypsin-like enzymes of A. gemmatalis were evaluated by molecular dynamics (MD) simulations. The ability of the peptides to inhibit trypsin-like enzymes in vivo was compared with the SKTI protein by feeding A. gemmatalis larvae at different concentrations, followed by an inhibition persistence assay. During the MD simulation of enzyme-ligand complexes, both peptides showed a small variation of root-mean-square deviation and root-mean-square fluctuation, suggesting that these molecules reach equilibrium when forming a complex with the trypsin-like enzyme. Furthermore, both peptides form hydrogen bonds with substrate recognition sites of A. gemmatalis trypsin-like enzyme, with GORE2 having more interactions than GORE1. Larvae of A. gemmatalis exposed to the peptides and SKTI showed a similar reduction in proteolytic activity, but the persistence of inhibition of trypsin-like enzyme was longer in peptide-fed insects. Despite their size, the peptides exhibit important active and substrate binding site interactions, stability during complex formation, and steadiness effects in vivo. The results provide fundamental information for the development of mimetic molecules and help in decision-making for the selection of delivery methods for larger-scale experiments regarding similar molecules.

Experiences Porting NAMD to the Data Parallel C++ Programming Model

HPC applications have a growing need to leverage heterogeneous computing resources with a vendor-neutral programming paradigm. Data Parallel C++ is a programming language based on open standards SYCL, providing a vendor-neutral solution. We describe our experiences porting the NAMD molecular dynamics application with its GPU-offload force kernels to SYCL/DPC++. Results are shown that demonstrate correctness of the porting effort.

Aqueous Molecular Dynamics for Understanding Glycosaminoglycan Recognition by Proteins

Glycosaminoglycans (GAGs) are biopolymers that exist in most organisms. GAGs are known to bind to hundreds of proteins and partake in multiple biological processes such as growth, morphogenesis, inflammation, infection, and others. Their intrinsic structural heterogeneity and conformational variability introduce major challenges in experimental studies. On the other hand, recent advances in force field development and computational technology have yielded phenomenal opportunity to study thousands of GAG sequences simultaneously to understand recognition of target protein(s). Here, we describe experimental setup for conventional molecular dynamics simulations of GAGs to position an experimental biologist favorably in performance, analysis and interpretation of stability, specificity, and conformational properties of GAGs, while also elucidating their interactions with amino acid residues of a protein at an atomistic level in presence of water.

Large-Scale Molecular Dynamics Simulations of Cellular Compartments

Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.

Exploring Covalent Docking Mechanisms of Boron-Based Inhibitors to Class A, C and D β-Lactamases Using Time-dependent Hybrid QM/MM Simulations

Recently, molecular covalent docking has been extensively developed to design new classes of inhibitors that form chemical bonds with their biological targets. This strategy for the design of such inhibitors, in particular boron-based inhibitors, holds great promise for the vast family of β-lactamases produced, inter alia, by Gram-negative antibiotic-resistant bacteria. However, the description of covalent docking processes requires a quantum-mechanical approach, and so far, only a few studies of this type have been presented. This study accurately describes the covalent docking process between two model inhibitors - representing two large families of inhibitors based on boronic-acid and bicyclic boronate scaffolds, and three β-lactamases which belong to the A, C, and D classes. Molecular fragments containing boron can be converted from a neutral, trigonal, planar state with sp2 hybridization to the anionic, tetrahedral sp3 state in a process sometimes referred to as morphing. This study applies multi-scale modeling methods, in particular, the hybrid QM/MM approach which has predictive power reaching well beyond conventional molecular modeling. Time-dependent QM/MM simulations indicated several structural changes and geometric preferences, ultimately leading to covalent docking processes. With current computing technologies, this approach is not computationally expensive, can be used in standard molecular modeling and molecular design works, and can effectively support experimental research which should allow for a detailed understanding of complex processes important to molecular medicine. In particular, it can support the rational design of covalent boron-based inhibitors for β-lactamases as well as for many other enzyme systems of clinical relevance, including SARS-CoV-2 proteins.

The impact of curcumin derived polyphenols on the structure and flexibility COVID-19 main protease binding pocket: a molecular dynamics simulation study

The newly occurred SARS-CoV-2 caused a leading pandemic of coronavirus disease (COVID-19). Up to now it has infected more than one hundred sixty million and killed more than three million people according to 14 May 2021 World Health Organization report. So far, different types of studies have been conducted to develop an anti-viral drug for COVID-19 with no success yet. As part of this, silico were studied to discover and introduce COVID-19 antiviral drugs and results showed that protease inhibitors could be very effective in controlling. This study aims to investigate the binding affinity of three curcumin derived polyphenols against COVID-19 the main protease (Mpro), binding pocket, and identification of important residues for interaction. In this study, molecular modeling, auto-dock coupled with molecular dynamics simulations were performed to analyze the conformational, and stability of COVID-19 binding pocket with diferuloylmethane, demethoxycurcumin, and bisdemethoxycurcumin. All three compounds have shown binding affinity −39, −89 and −169.7, respectively. Demethoxycurcumin and bisdemethoxycurcumin showed an optimum binding affinity with target molecule and these could be one of potential ligands for COVID-19 therapy. And also, COVID-19 main protease binding pocket binds with the interface region by one hydrogen bond. Moreover, the MD simulation parameters indicated that demethoxycurcumin and bisdemethoxycurcumin were stable during the simulation run. These findings can be used as a baseline to develop therapeutics with curcumin derived polyphenols against COVID-19.

Identifying and elucidating the roles of Y198N and Y204F mutations in the PAH enzyme through molecular dynamic simulations

Phenylketonuria is an autosomal recessive disorder caused by mutations in the phenylalanine hydroxylase gene. In phenylketonuria causes various symptoms including severe mental retardation. PAH gene of a classical Phenylketonuria patient was sequenced, and two novel heterozygous mutations, p.Y198N and p.Y204F, were found. This study aimed to reveal the impacts of these variants on the structural stability of the PAH enzyme. In-silico analyses using prediction tools and molecular dynamics simulations were performed. Mutations were introduced to the wild type catalytic monomer and full length tetramer crystal structures. Variant pathogenicity analyses predicted p.Y198N to be damaging, and p.Y204F to be benign by some prediction tools and damaging by others. Simulations suggested p.Y198N mutation cause significant fluctuations in the spatial organization of two catalytic residues in the temperature accelerated MD simulations with the monomer and increased root-mean-square deviations in the tetramer structure. p.Y204F causes noticeable changes in the spatial positioning of T278 suggesting a possible segregation from the catalytic site in temperature accelerated MD simulations with the monomer. This mutation also leads to increased root-mean-square fluctuations in the regulatory domain which may lead to conformational change resulting in inhibition of dimerization and enzyme activation. Our study reports two novel mutations in the PAH gene and gives insight to their effects on the PAH activity. MD simulations did not yield conclusive results that explains the phenotype but gave plausible insight to possible effects which should be investigated further with in-silico and in-vitro studies to assess the roles of these mutations in etiology of PKU. Communicated by Ramaswamy H. Sarma.

Molecular Dynamics Flexible Fitting: All You Want to Know About Resolution Exchange

In recent years, owing to the advances in instrumentation, cryo-EM has emerged as the go-to tool for obtaining high-resolution structures of biomolecular systems. However, building three-dimensional atomic structures of biomolecules from these high-resolution maps remains a concern for the traditional map-guided structure-determination schemes. Recently, we developed a computational tool, Resolution Exchange Molecular Dynamics Flexible Fitting (ReMDFF) to address this problem by re-refining a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution (Wang et al., J Struct Biol 204(2):319-328, 2018). In this chapter, we present a step-by-step outline for preparing, executing, and analyzing ReMDFF refinements of simple proteins and multimeric complexes. The structure determination of carbon monoxide dehydrogenase and Mg²⁺-channel CorA are employed as case studies. All scripts are provided via GitHub (Vant, Resolution exchange molecular dynamics flexible fitting (ReMDFF) all you want to know about flexible fitting, 2019, https://github.com/jvant/ReMDFF_Singharoy_Group.git ).

Implementation of magnetic field force in molecular dynamics algorithm: NAMD source code version 2.12

The external fields, such as the magnetic force, have made advances in many industrial and biotechnology applications during the past century, although the changes in the structure of materials under the impact of the electromagnetic fields have not entirely been clear yet. The molecular simulation technique by providing extensive data from the configuration and orientations of the atoms is becoming the effective useful tool for scientists in a wide range of research areas. This paper presents an extended velocity Verlet algorithm inside the Nanoscale Molecular Dynamics (NAMD) package that enhances the NAMD features with the capability to compute the magnetic field force. We described how this novel feature has been implemented inside the package. Moreover, the results are reported for the rotation of a charged particle, and the thermo-physical properties of water in the presence of a magnetic field confirming how this developed NAMD source code provides accurate measurements compared with other available data.

Study of the Binding Pattern of HLA Class I Alleles of Indian Frequency and cTAP Binding Peptide for Chikungunya Vaccine Development

Chikungunya is a mosquito-borne disease, caused by the member of the Togaviridae family belongs to the genus alphavirus, making it a major threat in all developing countries as well as some developed countries. The mosquito acts as a vector for the disease and carries the CHIK-Virus. To date there is no direct treatment available and that demands the development of more effective vaccines. In this study author employed Immune Epitope Database and Analysis Resource, a machine learning-based algorithm principally working on the Artificial Neural Network (ANN) algorithm, also known as (IEDB-ANN) for the prediction and analysis of Epitopes. A total of 173 epitopes were identified on the basis of IC50 values, among them 40 epitopes were found, sharing part with the linear B-cell epitopes and exposed to the cTAP1protein, and out of 40, 6 epitopes were noticed to show interactions with the cTAP with their binding energy ranging from - 3.61 to - 1.22 kcal/mol. The six epitopes identified were exposed to the HLA class I alleles and from this all revealed interaction with the HLA alleles and minimum binding energy that ranges from - 4.12 to - 5.88 kcal/mol. Besides, two T cell epitopes i.e. 145KVFTGVYPE153 and 395STVPVAPPR403 were found most promiscuous candidates. These promiscuous epitopes-HLA complexes were further analyzed by the molecular dynamics simulation to check the stability of the complex. Results obtained from this study suggest that the identified epitopes i.e. and 395 STVPVAPPR 403 , are likely to be capable of passing through the lumen of ER to bind withthe HLA class I allele and provide new insights and potential application in the designing and development of peptide-based vaccine candidate for the treatment of chikungunya.

A comparative study for the intermediate states of myelin oligodendrocyte glycoprotein in the absence and presence of glycan - A computational approach

Myelin Oligodendrocyte glycoprotein (MOG) is found to play an important role in providing structural integrity to myelin sheath at the same time it acts as an auto-antigen which might lead to Multiple Sclerosis (MS). What causes this specific property of being an auto-antigen is still not known. Here we present molecular dynamics simulation studies of unfolding and folding of the protein MOG in both the absence and presence of N-glycan in order to understand the role of glycosylation in the stability and flexibility of the protein. The main results from these studies show that the glycosylation increases the stability of the protein MOG and inhibits the complete unfolding of MOG in the SMD. From the folding studies using TMD, it was observed that the glycan helps the protein to attain the near-native folded conformation. However, it was also observed from the direct TMD studies that the pathway of protein folding was enhanced by the trace-back of intermediate states in the presence of glycan.

Design of fluorinated sialic acid analog inhibitor to H5 hemagglutinin of H5N1 influenza virus through molecular dynamics simulation study

Influenza epidemics and pandemics are caused by influenza A virus. The cell surface protein of hemagglutinin and neuraminidase is responsible for viral infection and release of progeny virus on the host cell membrane. Now 18 hemagglutinin and 11 neuraminidase subtypes are identified. The avian influenza virus of H5N1 is an emergent threat to public health issues. To control the influenza viral infection it is necessary to develop antiviral inhibitors and vaccination. In the present investigation we carried out 50 ns Molecular Dynamics simulation on H5 hemagglutinin of Influenza A virus H5N1 complexed with fluorinated sialic acid by substituting fluorine atoms at any two hydroxyls of sialic acid by considering combinatorial combination. The binding affinity between the protein-ligand complex system is investigated by calculating pair interaction energy and MM-PBSA binding free energy. All the complex structures are stabilized by hydrogen bonding interactions between the H5 protein and the ligand fluorinated sialic acid. It is concluded from all the analyses that the fluorinated complexes enhance the inhibiting potency against H5 hemagglutinin and the order of inhibiting potency is SIA-F9 ≫ SIA-F2 ≈ SIA-F7 ≈ SIA-F2F4 ≈ SIA-F2F9 ≈ SIA-F7F9 > SIA-F7F8 ≈ SIA-F2F8 ≈ SIA-F8F9 > SIA-F4 ≈ SIA-F4F7 ≈ SIA-F4F8 ≈ SIA-F8 ≈ SIA-F2F7 ≈ SIA > SIA-F4F9. This study suggests that one can design the inhibitor by using the mono fluorinated models SIA-F9, SIA-F2 and SIA-F7 and difluorinated models SIA-F2F4, SIA-F2F9 and SIA-F7F9 to inhibit H5 of H5N1 to avoid Influenza A viral infection.Communicated by Ramaswamy H. Sarma.

Stability of β-turn in LaR2C-N7 peptide for its translation-inhibitory activity against hepatitis C viral infection: A molecular dynamics study

Hepatitis C virus (HCV) requires an essential host factor, human La protein, for its translation and replication activity. Earlier, it was demonstrated that a 24-mer synthetic peptide (LaR2C) encompassing residues 112 to 184 of the natural human La protein interacts with the HCV internal ribosome entry site (IRES) and inhibits translation. Interestingly, a shorter version of the same LaR2C peptide, LaR2C-N7, containing residues 174 to 180 (KYKETDL), with a unique β-turn secondary structure, is sufficient to inhibit IRES mediated translation of HCV. Hence, it is imperative to understand the role of each amino acid of this heptapeptide towards β-turn formation which will then help in designing potential drugs against HCV infection. Here, we use Nanoscale Molecular Dynamics (NAMD) simulation to investigate the factors modulating its β-turn formation and stability. Using 100 ns simulation paradigms, we find that the peptide populated the type 1 β-turn conformation in its free form in solution. However, simulation of the single-site mutants of the heptapeptide revealed that none of the 7 mutants retained the β-turn conformation with sufficient stability. We observed that the β-turn was stabilized mainly by the side chain interaction, salt-bridge and weak hydrogen bonds between K3 and D6 residues. Y2, K1 and K3 sites upon mutation heavily destabilized the β-turn when compared to alteration at the E4 and T5 sites which would then drastically reduce its HCV RNA IRES binding capabilities. Taken together, our results provide a basis for designing peptidomimetics as potential anti-HCV drug candidates.

Adsorption of Fibronectin Fragment on Surfaces Using Fully Atomistic Molecular Dynamics Simulations

The effect of surface chemistry on the adsorption characteristics of a fibronectin fragment (FNIII^8⁻10) was investigated using fully atomistic molecular dynamics simulations. Model surfaces were constructed to replicate self-assembled monolayers terminated with methyl, hydroxyl, amine, and carboxyl moieties. It was found that adsorption of FNIII^8⁻10 on charged surfaces is rapid, specific, and driven by electrostatic interactions, and that the anchoring residues are either polar uncharged or of opposing charge to that of the targeted surfaces. On charged surfaces the presence of a strongly bound layer of water molecules and ions hinders FNIII^8⁻10 adsorption. In contrast, adsorption kinetics on uncharged surfaces are slow and non-specific, as they are driven by van der Waals interactions, and the anchoring residues are polar uncharged. Due to existence of a positively charged area around its cell-binding region, FNIII^8⁻10 is available for subsequent cell binding when adsorbed on a positively charged surface, but not when adsorbed on a negatively charged surface. On uncharged surfaces, the availability of the fibronectin fragment's cell-binding region is not clearly distinguished because adsorption is much less specific.

Molecular dynamics studies of polysaccharide carrier based on starch in dental cavities

Health is an important element that influences the level of development in a community. Studies show that tooth decay has been prevalent recently. Starch incorporating curcumin can serve as an alternative approach in preventing the activity of Streptococcus mutans attributed to biofilm and plaque formation on teeth. In this research, the performance of starch nanoparticle as a carrier for curcumin, a natural anti-inflammatory and a strong antioxidant agent, in decreasing dental caries was simulated. In the first stage, the conformational rearrangements of molecules and their interactions with other molecular species in a range of environments were examined via computational techniques and molecular dynamics (MD) simulation. The charts of energy, temperature, density, cell size and the radial distribution function (RDF) derived from the simulation, confirmed that during 5 initial steps there was a stable binding between the curcumin and starch in the presence of bacteria. The energy released in the starch formed nanosphere is very high, and this indicates a full reaction in the system. However, the density-decreasing trend of nanosystem suggests that it can effectively inhibit the activity of microorganism.

A QSAR model of Olanzapine derivatives as potential inhibitors for 5-HT2A Receptor

Schizophrenia is a complex, chronic mental disorder, affecting about 21 million people worldwide. It is characterized by symptoms, including distortions in thinking, perception, emotions, disorganized speech, sense of self and behavior. Recently, a numbers of marketed drugs for Schizophrenia are available against dopamine D2 and serotonin 5-HT2A receptors. Here, we docked Olanzapine derivatives (collected from literature) with 5-HT2A Receptor using the program AutoDock 4.2. The docked protein inhibitor complex structure was optimized using molecular dynamics simulation for 5ps with the CHARMM-22 force field using NAMD (NAnoscale Molecular Dynamics program) incorporated in visual molecular dynamics (VMD 1.9.2) and then evaluating the stability of complex structure by calculating RMSD values. NAMD is a parallel, object-oriented molecular dynamics code designed for high-performance simulation of large biomolecular systems. A quantitative structure activity relationship (QSAR) model was built using energy-based descriptors as independent variable and pKi value as dependent variable of eleven known Olanzapine derivatives with 5-HT2A Receptor, yielding correlation coefficient r2 of 0.63861. The predictive performance of QSAR model was assessed using different crossvalidation procedures. Our results suggest that a ligand-receptor binding interaction for 5-HT2A receptor using a QSAR model is promising approach to design more potent 5-HT2A receptor inhibitors prior to their synthesis.

Rosetta Broker for membrane protein structure prediction: concentrative nucleoside transporter 3 and corticotropin-releasing factor receptor 1 test cases

Background

Membrane proteins are difficult targets for structure prediction due to the limited structural data deposited in Protein Data Bank. Most computational methods for membrane protein structure prediction are based on the comparative modeling. There are only few de novo methods targeting that distinct protein family. In this work an example of such de novo method was used to structurally and functionally characterize two representatives of distinct membrane proteins families of solute carrier transporters and G protein-coupled receptors. The well-known Rosetta program and one of its protocols named Broker was used in two test cases. The first case was de novo structure prediction of three N-terminal transmembrane helices of the human concentrative nucleoside transporter 3 (hCNT3) homotrimer belonging to the solute carrier 28 family of transporters (SLC28). The second case concerned the large scale refinement of transmembrane helices of a homology model of the corticotropin-releasing factor receptor 1 (CRFR1) belonging to the G protein-coupled receptors family.

Results

The inward-facing model of the hCNT3 homotrimer was used to propose the functional impact of its single nucleotide polymorphisms. Additionally, the 100 ns molecular dynamics simulation of the unliganded hCNT3 model confirmed its validity and revealed mobility of the selected binding site and homotrimer interface residues. The large scale refinement of transmembrane helices of the CRFR1 homology model resulted in the significant improvement of its accuracy with respect to the crystal structure of CRFR1, especially in the binding site area. Consequently, the antagonist CP-376395 could be docked with Autodock VINA to the CRFR1 model without any steric clashes.

Conclusions

The presented work demonstrated that Rosetta Broker can be a versatile tool for solving various issues referring to protein biology. Two distinct examples of de novo membrane protein structure prediction presented here provided important insights into three major areas of protein biology. Namely, the dynamics of the inward-facing hCNT3 homotrimer system, the structural changes of the CRFR1 receptor upon the antagonist binding and finally, the role of single nucleotide polymorphisms in both, hCNT3 and CRFR1 proteins, were investigated.

Electronic supplementary material

The online version of this article (doi:10.1186/s12900-017-0078-8) contains supplementary material, which is available to authorized users.

Demographics of patients receiving Intravitreal anti-VEGF treatment in real-world practice: healthcare research data versus randomized controlled trials

BACKGROUND

While randomized controlled trials (RCTs) are based on strict inclusion/exclusion criteria, non-interventional studies (NISs) might provide additional information to guide management in patients more representative to the real-world setting. The aim of this study was to compare baseline characteristics of patients receiving intravitreal treatment in the NIS OCEAN with those from published RCTs.

METHODS

The ongoing OCEAN study enrolled patients treated with ranibizumab for neovascular age-related macular degeneration (nAMD), diabetic macular oedema (DME) or branch/central retinal vein occlusion (B/CRVO). Baseline patient characteristics were compared by indication within the OCEAN cohort. Furthermore, the characteristics were set in reference to those of published RCTs in the same indications. Confidence intervals (CIs) were calculated and assessed for statistically significant differences as indicated by non-overlapping CIs.

RESULTS

Patient characteristics in the NIS OCEAN were evaluated for 3,614 patients with nAMD, 1,211 with DME, 204 with BRVO and 121 with CRVO. Between these groups, significant differences in mean age, gender distributions, and mean baseline VA were seen, reflecting known differences between the indications. Compared to the patient characteristics of published RCTs (trials selected by literature search: nAMD: 13 RCTs, DME: 9, RVO: 5), the OCEAN patients' mean age was significantly higher in every indication. The gender distributions across the trials were comparable, with only few differences between OCEAN and the RCTs. Regarding the mean baseline VA, notable differences were found in nAMD and in DME, with VA significantly higher in some RCTs and lower in others.

CONCLUSIONS

The described differences underline the complementarity of NISs and RCTs. OCEAN covers a broader spectrum and more variability of patients than do RCTs. As baseline values may have impact on the treatment response (ceiling effect), there is an ongoing need for research in all patient subgroups. Country-specific assessments of patient populations can better reflect the real-world situation. NISs can deliver insights that RCTs may not, as NISs can include non-typical patients, patients with comorbidities, a broader age spectrum and patients of various disease stages.

TRIAL REGISTRATION

The NIS OCEAN was registered on www.clinicaltrials.gov (identifier: NCT02194803 ).

Mutation-based structural modification and dynamics study of amyloid beta peptide (1-42): An in-silico-based analysis to cognize the mechanism of aggregation

Alzheimer's disease is the prevalent cause of premature senility, a progressive mental disorder due to degeneration in brain and deposition of amyloid β peptide (1-42, a misfolded protein) in the form of aggregation that prevails for a prolonged time and obstructs every aspect of life. One of the primary hallmarks of the neuropathological disease is the accretion of amyloid β peptide in the brain that leads to Alzheimer's disease, but the mechanism is still a mystery. Several investigations have shown that mutations at specific positions have a significant impact in stability of the peptide as predicted from aggregation profiles. Here in our study, we have analyzed the mutations by substituting residues at position A22G, E22G, E22K, E22Q, D23N, L34V and molecular dynamics have been performed to check the deviation in stability and conformation of the peptide. The results validated that the mutations at specific positions lead to instability and the proline substitution at E22P and L34P stalled the aggregation of the peptide.

Computational Methods for Structural and Functional Studies of Alzheimer's Amyloid Ion Channels

Aggregation can be studied by a range of methods, experimental and computational. Aggregates form in solution, across solid surfaces, and on and in the membrane, where they may assemble into unregulated leaking ion channels. Experimental probes of ion channel conformations and dynamics are challenging. Atomistic molecular dynamics (MD) simulations are capable of providing insight into structural details of amyloid ion channels in the membrane at a resolution not achievable experimentally. Since data suggest that late stage Alzheimer's disease involves formation of toxic ion channels, MD simulations have been used aiming to gain insight into the channel shapes, morphologies, pore dimensions, conformational heterogeneity, and activity. These can be exploited for drug discovery. Here we describe computational methods to model amyloid ion channels containing the β-sheet motif at atomic scale and to calculate toxic pore activity in the membrane.

Generalized Scalable Multiple Copy Algorithms for Molecular Dynamics Simulations in NAMD

Computational methodologies that couple the dynamical evolution of a set of replicated copies of a system of interest offer powerful and flexible approaches to characterize complex molecular processes. Such multiple copy algorithms (MCAs) can be used to enhance sampling, compute reversible work and free energies, as well as refine transition pathways. Widely used examples of MCAs include temperature and Hamiltonian-tempering replica-exchange molecular dynamics (T-REMD and H-REMD), alchemical free energy perturbation with lambda replica-exchange (FEP/λ-REMD), umbrella sampling with Hamiltonian replica exchange (US/H-REMD), and string method with swarms-of-trajectories conformational transition pathways. Here, we report a robust and general implementation of MCAs for molecular dynamics (MD) simulations in the highly scalable program NAMD built upon the parallel programming system Charm++. Multiple concurrent NAMD instances are launched with internal partitions of Charm++ and located continuously within a single communication world. Messages between NAMD instances are passed by low-level point-to-point communication functions, which are accessible through NAMD's Tcl scripting interface. The communication-enabled Tcl scripting provides a sustainable application interface for end users to realize generalized MCAs without modifying the source code. Illustrative applications of MCAs with fine-grained inter-copy communication structure, including global lambda exchange in FEP/λ-REMD, window swapping US/H-REMD in multidimensional order parameter space, and string method with swarms-of-trajectories were carried out on IBM Blue Gene/Q to demonstrate the versatility and massive scalability of the present implementation.

Reduced HIV-1 integrase flexibility as a mechanism for raltegravir resistance

HIV-1 integrase is an essential enzyme necessary for the replication of the HIV virus as it catalyzes the insertion of the viral genome into the host chromosome. Raltegravir was the first integrase inhibitor approved by the FDA for antiretroviral treatment. HIV patients on raltegravir containing regimens often develop drug resistance mutations at residue 140 and 148 in the catalytic 140's loop resulting in a 5-10 fold decrease in susceptibility to raltegravir. Obtaining crystallographic structure information on the Q148H/R, G140S/A primary and secondary mutations has been elusive. Using 10 ns molecular dynamics simulations, we present a detailed analysis of the structural changes induced by these mutations. The formation frequency of a transient helix in the catalytic 140's loop is increased and the length of this helix is extended from 3-residues to 4 in the mutants relative to the wild type. This helix causes reduced flexibility in the protein active site and therefore serves as a gating mechanism restricting the access of raltegravir to the integrase binding pocket. These results suggest that resistance to raltegravir occurs through a common mechanism of altering the formation frequency of transient secondary structures such as α2 and β5 in addition to the conformational changes in the 140's loop therefore decreasing the flexibility of the HIV-1 integrase protein. The reduced integrase flexibility serves as a mechanism of resistance to raltegravir.