PDB Format Research Articles

Efficient protein structure archiving using ProteStAr.

The introduction of Deep Minds' Alpha Fold 2 enabled the prediction of protein structures at an unprecedented scale. AlphaFold Protein Structure Database and ESM Metagenomic Atlas contain hundreds of millions of structures stored in CIF and/or PDB formats. When compressed with a general-purpose utility like gzip, this translates to tens of terabytes of data, which hinders the effective use of predicted structures in large-scale analyses. Here, we present ProteStAr, a compressor dedicated to CIF/PDB, as well as supplementary PAE files. Its main contribution is a novel approach to predicting atom coordinates on the basis of the previously analyzed atoms. This allows efficient encoding of the coordinates, the largest component of the protein structure files. The compression is lossless by default, though the lossy mode with a controlled maximum error of coordinates reconstruction is also present. Compared to the competing packages, i.e. BinaryCIF, Foldcomp, PDC, our approach offers a superior compression ratio at established reconstruction accuracy. By the efficient use of threads at both compression and decompression stages, the algorithm takes advantage of the multicore architecture of current central processing units and operates with speeds of about 1 GB/s. The presence of Python and C++ API further increases the usability of the presented method. The source code of ProteStAr is available at https://github.com/refresh-bio/protestar.

Describing and Sharing Molecular Visualizations Using the MolViewSpec Toolkit.

With the ever-expanding toolkit of molecular viewers, the ability to visualize macromolecular structures has never been more accessible. Yet, the idiosyncratic technical intricacies across tools and the integration complexities associated with handling structure annotation data present significant barriers to seamless interoperability and steep learning curves for many users. The necessity for reproducible data visualizations is at the forefront of the current challenges. Recently, we introduced MolViewSpec (homepage: https://molstar.org/mol-view-spec/, GitHub project: https://github.com/molstar/mol-view-spec), a specification approach that defines molecular visualizations, decoupling them from the varying implementation details of different molecular viewers. Through the protocols presented herein, we demonstrate how to use MolViewSpec and its 3D view-building Python library for creating sophisticated, customized 3D views covering all standard molecular visualizations. MolViewSpec supports representations like cartoon and ball-and-stick with coloring, labeling, and applying complex transformations such as superposition to any macromolecular structure file in mmCIF, BinaryCIF, and PDB formats. These examples showcase progress towards reusability and interoperability of molecular 3D visualization in an era when handling molecular structures at scale is a timely and pressing matter in structural bioinformatics as well as research and education across the life sciences. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating a MolViewSpec view using the MolViewSpec Python package Basic Protocol 2: Creating a MolViewSpec view with reference to MolViewSpec annotation files Basic Protocol 3: Creating a MolViewSpec view with labels and other advanced features Support Protocol 1: Computing rotation and translation vectors Support Protocol 2: Creating a MolViewSpec annotation file.

DeepKa Web Server: High-Throughput Protein pKa Prediction.

DeepKa is a deep-learning-based protein pKa predictor proposed in our previous work. In this study, a web server was developed that enables online protein pKa prediction driven by DeepKa. The web server provides a user-friendly interface where a single step of entering a valid PDB code or uploading a PDB format file is required to submit a job. Two case studies have been attached in order to explain how pKa's calculated by the web server could be utilized by users. Finally, combining the web server with post processing as described in case studies, this work suggests a quick workflow of investigating the relationship between protein structure and function that are pH dependent. The web server of DeepKa is freely available at http://www.computbiophys.com/DeepKa/main.

A Insilico Study on Structural aspects of Caffeine by ArgusLab 4 software

In this study, the quasi-experimental molecular computational studies of the caffeine compound found in many herbal and the binding properties of the 4QHO protein to the active site were investigated by molecular docking method. For molecular docking, first of all, caffeine molecule, geometry optimization was done in ArgusLab program with semi-experimental PM3 method. The HOMO, LUMO, HOMO-LUMO energy differences and potential energy surface of all optimized molecules were calculated. The selected 4QHO protein crystal structure was obtained from the protein database in *.pdb format and optimized ligand interaction with this crystal structure was studied using ArgusLab. As a result of molecular docking studies, ligand-protein binding energies, hydrogen bond sites and number that can occur between ligand-protein were determined and evaluated.

Molecular Docking Studies for Evaluation of Amaranth Grain Squalene for Treatment of Melanoma Skin Cancer in Human Beings

Abstract: The main purpose of the present study is to check the therapeutic role of Amaranth squalene against skin cancer by performing docking studies with TGF-β, MIA and Raf which are important target proteins of signal transduction pathways leading to skin cancer development in human beings. In accordance with the World Health Organization, one of the leading causes of death worldwide is cancer. Discovering alternative, economical, and effective cancer treatment options is essential due to the high cost of the currently existing cancer therapies and other treatment-related constraints. Grains of Amaranth, a nutritionally important pseudocereal, are rich in squalene which possess important pharmacological properties. Due to the presence of squalene, Amaranth grain can be used as food based therapy for many dreadful diseases including cancer. Melanoma type of skin cancer is a serious form of skin cancer which is responsible for high mortality rate world wide. At present, Vemurafenib, which binds Braf and commonly used as drug for treatment of skin cancer has various adverse effects. Therefore, in the current investigation, the interaction of squalene a terpenoid compound from Amaranth, with proteins of skin cancer signalling pathway such as TGF-beta, Braf, and M.I.A was studied through molecular docking conducted by using Autodock vina software. To check the therapeutic role of Amaranth squalene against skin cancer by performing docking studies with TGF-β, MIA and Raf which are important target proteins of signal transduction pathway leading to skin cancer development in human beings. The 3D crystal structures of the proteins examined in this investigation were queried from The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) Web server (https:// www. rcsb. org/). For the present study, three proteins were taken, TGF-Beta (PDB ID:3tzm. MIA (PDB ID: 5ixb, BRAF (PDB ID:5jrq. The structure of squalene was taken from the PubChem database and was converted from .sdf format to .pdb format using Open- Babel. pkCSM (http:// structure. bioc.cam. ac.uk/pkcsm) along with SwissADME (http:// www. swiss adme.ch/ index. php) websites were used for Drug-likeliness properties of the compound. Anticancerous behaviour of Squalene was predicted with support of software PASS. Active Site of target Protein was projected by Biovia Drug Discovery Studio Visualizer 2020 (PDB ID: (TGF-β: 3tzm), (MIA: 5ixb), (BRAF: 5jrq). Protein-ligand docking studies were performed using the AutoDock v4.2.6 program. On the basis of the docking score, it was revealed that Amaranth squalene strongly interacted with Braf (5jrq) with binding energy of -14.4 followed by TGF-beta (3tzm) and MIA (5ixb) as compared to well-known drug Vemurafenib which has a binding energy of -4.9 only. Moreover, squalene ligand satisfied Lipinski’s rule of 5. Squalene may have enzyme-inhibitory action according to docking results and also be useful in in-vivo anti-cancerous screenings on model organisms. The present study demonstrated the therapeutic potential of Amaranth Squalene in the prevention of skin cancer as revealed by it’s stronger interaction with BRAF, TGF-β and MIA proteins as compared to Vemurafanib, a well-known drug used to treat skin cancer. The studies paved the way for Squalene to have a potential drug. Since Amaranth grains possess are enriched with squalene, the nutraceuticals/ food prepared from them has high prospectus to be used as a food based therapy for skin cancer treatment.

Acteoside (Verbascoside): A Prospective Therapeutic Alternative against Hepatocellular Carcinoma by Inhibiting the Expression of AXL, FGFR, BRAF, TIE2 and RAF1 Targets.

Hepatocellular carcinoma (HCC) is the world's second leading cause of cancerrelated mortality and the fifth most prevalent cancer overall. Several synthetic and plant-based remedies are in practice to treat diverse liver disorders. Because of their minimal side effects and protective characteristics, plant phenolics have the potential to become alternative therapeutics, replacing currently existing HCC medications. The present study identifies the plant phenolics as having the capacity to inhibit HCC with low side effects and cost efficiency. Hepatocellular carcinoma (HCC) is the leading cause of cancer-related mortality, despite the proven effectiveness of screening programs for at-risk individuals, the majority of patients have disease progression or tumor characteristics that preclude curative therapies at the time of diagnosis. Acteoside (Verbascoside) is a naturally occurring phenylethanoid glycoside found throughout the plant kingdom. Acteoside is a physiologically active chemical with the number of pharmacological and protective effects against various liver illnesses. Currently used HCC medications have a variety of side effects. Plant-based chemicals offer the possibility of treating HCC with minimal side effects. The work is targeted to find the best phytochemical (plant phenolic) lead molecule for future drug development research against Hepatocellular carcinoma. The targets were selected based on an analysis of relevant literature, and the 3D structures of the selected receptors were obtained in. pdb format from the RCSB-Protein data bank (PDB, http://www.rscb.org/pdb). Based on a review of the literature, sixty plant secondary metabolites, or plant phenolics, were selected. The ligand structures were obtained and downloaded in.sdf format from the NCBI PubChem chemicals database (https://pubchem.ncbi.nlm.nih.gov/). Molecular docking between the receptor and ligands was accomplished using the Molegro Virtual Docker 6.0 (MVD) software. The target RAF1, BRAF chain 1, TIE2 chain 2 FGFR1, FGFR2, AXL, and FGFR4 showed the best binding effectiveness with acteoside compared to their respective positive control. RET chain 1 and BRAF chain 2 acteoside showed prominent binding efficacy after Curcumin, and Epigallocatechingallate, respectively, against positive control. Present findings clearly point towards the potentiality of acteoside in inhibiting various HCC targets. Acteoside may be used as a prominent lead molecule in the future treatment of hepatic cancer with its multifaceted binding efficiencies against various target proteins.

Beneficial effects of flavonoids on cardiovascular diseases by influencing NLRP3 inflammasome.

Cardiovascular diseases (CVDs) are a leading cause of global mortality and have a high incidence rate worldwide. The function of inflammasomes in CVDs has received a lot of attention recently, and the nucleotide-binding domain and leucine-rich repeat protein 3 (NLRP3) inflammasome may be a new target for the prevention and treatment of CVDs. Flavonoids, which are found in food and plant extracts, inhibited inflammation in CVDs by regulating the NLRP3 inflammasome. CB-Dock was used to investigate whether 34 flavonoids from natural products acted on NLRP3 inflammasome. In brief, the PDB format of NLRP3 was selected as a protein file, and 34 flavonoids in SDF format were selected as the ligand file, and then input to CB-Dock for molecular docking. The docking results showed that epigallocatechin-3-gallate (EGCG), amentoflavone, baicalin, scutellarin, vitexin, silibinin, and puerarin had good binding affinities to NLRP3, which could be used as NLRP3 inhibitors, and aid in the discovery of lead compounds for the design and development of CVDs.

Virtual prediction of Brown Rice Gamma Oryzanol as anti-inflammation via COX-1 and COX-2 inhibitions

Brown rice gamma oryzanol (GO) is an important bioactive compound with numerous potential health functions, such as anti-inflammatory and anti-diabetic. Cyclooxygenase (COX) is the enzyme that mediates the biological transformation of arachidonic acid (ARA) into prostaglandins (PGs) in the mechanism of inflammation. This study purposed to identify the potency of gamma oryzanol of brown rice as an anti-inflammatory compound via COX-1 and COX-2 inhibition. The three-dimensional structure of COX-1 and COX-2 was determined by binding affinity calculations from virtual molecular docking with gamma oryzanol ligand through in silico study. Arachidonic acid as native ligand of COX-1/COX-2 was performed as a control in this study. Gamma oryzanol (CIS 5282164) and arachidonic acid (CIS 444899) were downloaded in 3D-SDF format from the PubChem database. The three-dimensional model of COX-1 and COX-2 was acquired from the protein data bank (www.rscb.org) in PDB format. The molecular docking was performed by Vina Wizard integrated on PyRx version 0.8. The interaction between GO and COX-1/COX-2 was visualized using the Discovery Studio version 2022 software. Molecular dynamics (MD) simulation also used to analyze the stability of the protein-ligand complex. The results showed that brown rice gamma oryzanol binds to COX-1 and COX-2 at many active sites with strongest binding affinity compared to arachidonic acid, with energy binding -7.8 kcal/mol and -6.2 kcal/mol, respectively. This in silico study concluded that brown rice gamma oryzanol has potential function as an anti-inflammatory activity through COX-1 and COX-2 catalysis reduction.

Bestsel: Updated webserver for secondary structure and fold prediction for protein CD spectroscopy.

Circular dichroism (CD) spectroscopy is widely used to characterize the secondary structure of proteins. Recently, we have developed the Beta Structure Selection (BeStSel) method to derive accurate and detailed structural information from the CD spectra which handles the spectral diversity of β-structured proteins. The BeStSel webserver provides a user-friendly and intelligent interface for the analysis of single or multiple CD spectra. Uniquely, BeStSel provides information on eight secondary structure components including parallel β-structure and antiparallel β-sheets with three different groups of twist. It overperforms any available methods in accuracy and information content, moreover, it is capable of predicting the protein fold down to the topology/homology level of the CATH classification. With the new versions of the DSSP and CATH databases, even more accurate estimates can be obtained using re-optimised basis spectra. A new module of the updated webserver helps to distinguish intrinsically disordered proteins by their CD spectrum. Users can also enter PDB IDs or upload structure files in PDB format as input to determine the corresponding secondary structure contents and fold classification, which help the experimental verification of protein MD and in silico modelling using CD spectroscopy. To aid correct concentration determination, extinction coefficients at 205 and 214 nm can be calculated from the primary sequence of the protein. The BeStSel server can be freely accessed at https://bestsel.elte.hu. This work was supported by National Research, Development and Innovation Fund of Hungary (K120391, KH125597, 2017-1.2.1-NKP-2017-00002, FIEK_16-1-2016-0005, TÉT_16-1-2016-0134, TÉT_16-1-2016-0197); SOLEIL Synchrotron, France (proposals 20171582, 20160916, 20151300, 20150515).

In-silico investigation and drug likeliness studies of benzimidazole congeners: The new face of innovation

BackgroundThe primary driving force behind the development of several small molecules for the treatment of tuberculosis is multi-drug resistance. A new fluorinated heterocyclic benzimidazole derivative gives extensive pharmacological activity against the FtsZ protein. FtsZ is a new validated target for tuberculosis drug design. It is a cell division filament protein present in Mycobacterium tuberculosis and other bacteria. MethodsLigand preparation- The ligand molecules were selected from the previously published paper and analyzed for reliability with the FtsZ protein. The 3D structure of the ligand was prepared using Chem-Draw Pro (version 12.0). Protein preparation- The PDB format FtsZ protein was downloaded from RCSB (https://www.rcsb.org/). The FtsZ protein of PDBID 2q1y was taken for the docking studies. The binding pocket was determined using the Castp server (http://sts.bioe.uic.edu/castp/index.html?201l). Thereafter, the in-silico docking was performed using PyRx 1.0 software. ResultThe docking result explains the importance of benzimidazole derivatives as potential FtsZ inhibitors. This study was focused on the in-silico development of new inhibitors and their chances to develop the candidate for oral delivery. The binding free energy, ADMET properties, and druglikeness characteristic of benzimidazole derivatives make them a perfect candidate for FtsZ inhibitors. Compound A-21 and A-20 had the best binding energy of −9.0 kcal/mol and −8.9 kcal/mol respectively. Molecular docking study revealed that Asn41, Thr42, Gly69, and Ala70 are required for conventional hydrogen bonding. The majority of the compounds (A-1, A-23 to A-32) are substrates for P-gp, which implies that their concentration inside the cell remain low due to P-efflux mechanism. ConclusionCompound A-20 formed five H-bond with target proteins (Gln30, Thr200, Gly226, Asp296, Val305). Almost all the molecules fulfil the criteria of drug likeliness. From this result, it can be concluded that benzimidazole derivatives can be developed as a new anti-Tb agent.

Computational investigation of quinazoline derivatives as Keap1 inhibitors for Alzheimer's disease

The Keap1-Nrf2-ARE pathway is crucial in the antioxidant defense mechanism. The Keap1-Nrf2-ARE pathway has become an important target for the development of potent therapeutic agents for numerous diseases. Keap1-Nrf2 protein inhibitors are electrophilic species that covalently bind with the sulfhydryl group of a cysteine residue of Keap1, which results in modification in cysteine residue. In this in-silico research, we investigated the Keap1 inhibitory potential of 99 quinazoline derivatives by molecular docking investigation. The ligand molecules were extracted from the ZINC15 database in sdf format. The pdb format Keap1 protein with PDBID: 4ZY3 was downloaded from RCSB (https://www.rcsb.org/). Resveratrol was chosen as a standard drug molecule for molecular docking studies to compare the results of test ligands. The in-silico docking study was performed by using AutoDock Vina 1.5.7 software. Out of 99 quinazoline derivatives, 12 derivatives showed the best binding energy towards Keap1. Thus, the top 12 quinazoline derivatives were further screened for their ADME profiling, and bioactivity assessment. The molecular docking study revealed that trifluoromethyl substituted quinazoline derivatives S91 and S44 had the best binding energy of −9.1 kcal/mol and −9.0 kcal/mol respectively (better than reference drug Resveratrol, ΔG = −8.1 kcal/mol) at the KELCH binding pocket of Keap1. Compound S91 formed a conventional hydrogen bond with Val (418, 464,512), Ala (366, 466, 607), and Gly (419,511). All 12 derivatives were found to possess drug likeliness properties. For this result, it can be concluded that quinazoline derivatives can be developed as new potent Keap1-Nrf2 inhibitors. The in-vivo/in-vitro study is necessary to validate the in-silico results.

MOLECULAR DOCKING STUDY OF HENTRIACONTANE FOR ANTICANCER AND ANTITUBERCULAR ACTIVITY

Objective: The present study discusses the molecular docking study of Hentriacontane for its Anti-tubercular and Anti-cancer activity. Methods: Two protein targets were selected for the study and their structures were taken from RCSB Protein Data Bank in PDB format. Preparation of proteins was done using Discovery Studio 2021 Client. The structure of Hentriacontane was drawn using ChemDraw 20.0 and saved in Mol format. Molecular docking was performed using PyRx software. 3D and 2D docking interactions were visualized by Discovery Studio 2021 Client. Results: Hentriacontane has docked against the selected proteins, namely Extra-cellular regulated kinase–2 (ERK-2; PDB ID: 3QYW) and Shikimate kinase (PDB ID: 1ZYU). The compound has shown the best binding score against Shikimate kinase (-10.4 kcal/mol), and Extra-cellular regulated kinase–2 (-7.4 kcal/mol) than the standard drugs. Conclusion: Molecular Docking study indicates that Hentriacontane could be an effective inhibitor for the proteins under study. Hence, the compound may be considered a lead molecule and further investigation of its analogues may help in the development of novel drugs for the treatment of breast cancer and tuberculosis.

MOLECULAR DOCKING AND COMPUTATIONAL PHARMACOKINETIC STUDY OF SOME NOVEL COUMARIN–BENZOTHIAZOLE SCHIFF’S BASE FOR ANTIMICROBIAL ACTIVITY

Objective: The present study discusses molecular docking of some novel coumarin–benzothiazole Schiff bases and the prediction of pharmacokinetic properties of potent molecules by the computational method. Methods: Five protein targets were selected for the study and their structures were taken from RCSB Protein Data Bank in PDB format. Preparation of proteins was done using Discovery Studio 2021 Client. A total of twenty derivatives were drawn using ChemDraw 20.0 and saved in Mol format. Molecular docking was performed using PyRx software. Docking results were visualized by Discovery Studio 2021 Client. The pharmacokinetic properties of the best compounds were determined using the pkCSM tool. Results: All twenty derivatives were docked against the five proteins, namely DNA Ligase (PDB ID: 3PN1), Topoisomerase (PDB ID: 3TTZ), Sterol demethylase (PDB ID: 5FSA), Enoyl-acyl-carrier protein (PDB ID: 1BVR) and Glutamate racemase (PDB ID: 5HJ7). The compound JJB18 has shown the best binding score against DNA ligase (-10.7 kcal/mol), Glutamate racemase (-8.4 kcal/mol), and Enoyl-acyl-carrier protein (-10.8 kcal/mol). Further, compound JJB19 has shown the best score for fungal sterol demethylase (-10.6 kcal/mol) and compound JJB20 towards topoisomerase (-9.4 kcal/mol) than the standard drugs. The physicochemical properties of potent derivatives were also reported. Conclusion: Molecular Docking study indicates that coumarin–benzothiazole Schiff bases may be effective inhibitors for the different microbial proteins. Additionally, in silico ADMET studies predicts drug-like features. Hence, these compounds may be considered lead molecules and further investigation of their analogues may help in the development of novel drugs for the treatment of microbial diseases.

Study of Anti-inflammatory Activity of New Derivative of Indomethacin: A Computational Study

This article presents the synthesis of new derivative from thiodaizole, based on the reaction of Thiosemicarbazide with Indomethacin in the presence of Phosphorus (V) oxychloride as catalyst. COX enzyme is divided to two isoforms COX-1 and COX-2 with similar structure and high sequence identity. The novel Inhibitor used a thiodaizole ring in combination with Indomethacin to reduce the risk of analogs interfering with COX-1’s small hydrophobic tunnel. Furthermore, the absence of a carboxylic group in the new Inhibitor reduces the Inhibitor’s ability to form a salt bridge with Arg120 (Figure 2), preventing the inhibition of the COX-1 enzyme. The aim of this study is to investigate the Anti-inflammatory activity of Indomethacin against the human second isoform of prostaglandin synthase (cyclooxygenase, COX-2). COX-2 enzyme 3D structures (PDB ID: 1CVU) were extracted from the protein databank. The PDB format of Indomethacin and its derivative were prepared by use Discovery Studio 2016 Client. Molecular docking study appeared that the new derivative exhibited better binding energy (-10.9 kcal/mol) compared with Indomethacin that have binding energy (-10.09 kcal/mol) and it’s have high selectivity towered COX-2 enzyme in the other hand In the present study, the predicted Pharmacokinetic (PK) values of Inhibitor (1) and Indomethacin (NSAID) deduce that Inhibitor (1) satisfies all PK parameters and has qualified as best lead candidate as an Anti-inflammatory agent compared to Indomethacin

MetBP: a software tool for detection of interaction between metal ion-RNA base pairs.

The role of metals in shaping and functioning of RNA is a well-established fact, and the understanding of that through the analysis of structural data has biological relevance. Often metal ions bind to one or more atoms of the nucleobase of an RNA. This fact becomes more interesting when such bases form a base pair with any other base. Furthermore, when metal ions bind to any residue of an RNA, the secondary structural features of the residue (helix, loop, unpaired, etc.) are also biologically important. The available metal-binding-related software tools cannot address such type-specific queries. To fill this limitation, we have designed a software tool, called MetBP that meets the goal. This tool is a stand-alone command-line-based tool and has no dependency on the other existing software. It accepts a structure file in mmCIF or PDB format and computes the base pairs and thereafter reports all metals that bind to one or more nucleotides that form pairs with another. It reports binding distance, angles along with base pair stability. It also reports several other important aspects, e.g. secondary structure of the residue in the RNA. MetBP can be used as a generalized metal-binding site detection tool for Proteins and DNA as well. https://github.com/computational-biology/metbp. Supplementary data are available at Bioinformatics online.

In Silico Investigation of Gastroprotective Compounds from n‐Butanol Fraction of Costus igneus on Antiulcer Druggable Targets

Gastric ulcer is a common gastrointestinal tract disorder characterized by discontinuation in the stomach mucosal lining and forming a painful lesion. Costus igneus is an ethnobotanical plant used in the management of gastrointestinal disturbances. This study characterized the gastroprotective bioactive compounds from n‐butanol fraction of C. igneus leaf (CIBF) and investigated their druggability effects on selected antiulcer targets using in silico approach.CIBF compounds were identified and characterized using gas chromatography‐mass spectrometry (GC‐MS) method. The 3D structures of CIBF compounds were downloaded in SDF format from Pubchem National Library of Medicine compound database and used as ligands to dock H+K+ATPase receptor (PDB ID: 5YLV), muscarinic receptor (PDB ID: 5ZHP), urease (PDB ID: 6ZJA) and histamine receptor (using Beta‐1‐adrenergic receptor [PDB ID: 2YCW] as a template). The 3D structures of the proteins were downloaded from the Protein Data Bank. Omeprazole, cimetidine and vonoprazan were used as reference drugs. The ligands and target proteins were processed and prepared for docking in pdb formats by using Chimera 1.14 and OpenBabel GUI version 2.3.2a, respectively. Multi‐targeted molecular docking was done using PyRx – Python Prescription 0.8. Physicochemical and pharmacokinetic properties were analyzed using Osiris DataWarrior version 5.5.0. Bioavailability and drug‐likeness analyses were done using the SwissADME web tool.GC‐MS analysis detected 15 suspected bioactive compounds in CIBF. Molecular docking study showed that 10‐11, (6ʹ,7ʹ) naphthoquinono [3.2] paracyclophane (NQP) had the highest ligand binding affinity for H+K+ATPase, muscarinic receptor, urease and histamine receptor when compared with the others 14 compounds, omeprazole, cimetidine and vonoprazan. Physicochemical properties of NQP did not violate the Lipinski, verber and lead likeness rules. Pharmacokinetic predictive analysis indicated that NQP possesses good oral bioavailability, high gastrointestinal absorption, blood‐brain barrier permeability and no inhibitory effect on cytochrome P450s.Findings from this study showed that NQP exhibited substantial inhibitory effects on proton pump, urease activity, muscarinic and histamine receptors. It also showed good physicochemical and pharmacokinetic properties. It is recommended that n‐butanol fraction of C. igneusleaves should be further explored as a potential source of drug lead candidate for the management of gastric ulcer disease.

DSB and SSB damages by 0.1–20 MeV protons enhanced by high-Z nanoparticles computed using Geant4-DNA

The interaction of protons in the energy range of 0.1 to 20 MeV with water sphere, as the target volume, containing DNA molecules has been simulated using Geant4-DNA toolkit. PDB format of DNA was used as DNA molecules were distributed randomly inside the target volume. The number of DNA damage is calculated in the absence of nanoparticles. Then the simulation has been repeated in the presence of 3 different nanoparticles (gold, gadolinium and iodine), in the identical physical and geometric conditions. The number of DNA damages without nanoparticles was in agreement with previous studies. Simulations results demonstrate that adding gold nanoparticles leads to increase damage yields in DNA. Increase of the yield between 10% to 50% were observed for SSB and DSB. Enhancement of the yield damage in the case of gadolinium and iodine nanoparticles was observed to be 4% and 9% less than that of gold nanoparticles.

STRIDER: Steric hindrance and metal coordination identifier

Biomolecular structural knowledge is important to understand the biological processes and the mechanisms underlying human diseases. In silico modeling plays a vital role in de novo design and docking of biomacromolecules as well as in exploring their conformational dynamics. Additionally, it has a major role in acquiring the structural insights using the parameters derived from experimental techniques such as cryo-electron microscopy. Steric hindrance is one of the important measures to validate the accuracy of the modeled biomolecular structures. A web user interface (WUI), namely, STRIDER (steric hindrance and metal coordination identifier) (www.iith.ac.in/strider/) estimates and reports pairwise inter- and intra- molecular steric hindrances using the van der Waals radius of 117 elements. STRIDER identifies and reports the coordination pattern of 64 metals in an interactive mode. It can provide conformer wise interaction pattern(s) of an ensemble of conformers which is needed in circumventing sampling issue in flexible docking, protein folding and structure based virtual screening. Further, it generates a pymol session file which highlights the aforementioned interaction for an offline analysis. Since STRIDER simply requires the Cartesian coordinates of a molecule in PDB format, any chemical structure can be given as an input. Functionality of STRIDER is illustrated here by considering several examples.

Pharmacokinetics and Molecular Docking Studies of Sinapaldehyde and MCM7 Protein against Meier-Gorlin Syndrome

Objective: The objective of this study to investigate the MCM7 protein in contrast to Meier-Gorlin Syndrome which contains most of the ORC1, ORC4, ORC6, CDT1, and CDC6 causative genes in the preinitiation complex disruptions. Methods: Sinapaldehyde and MCM7 were retrieved from Protein Data bank and PubChem database in the format of PDB and SDF format. Further, SDF format was converted to PDB format using Biovia Discovery Studio visualizer. Sinapaldehyde was subjected to pharmacoinformatics study as well as Molecular Docking analysis to find out the best anti-Gorlin potential. Results: Sinapaldehyde showed the -5.9kcal/mol binding affinity against MCM7 protein which considers to be a better candidate drug molecule against Meier-Gorlin Syndrome and validated using Pharmacokinetics mechanism. Conclusion: Molecular Docking studies and ADMET analysis showed the inhibitory activity of Sinapaldehyde with respect to Meier-Gorlin Syndrome and related pathway analysis and can be better compound for in vitro studies for future perspectives.

Pharmacokinetics and Molecular Docking Studies of Sinapaldehyde and MCM7 Protein against Meier-Gorlin Syndrome

Objective: The objective of this study to investigate the MCM7 protein in contrast to Meier-Gorlin Syndrome which contains most of the ORC1, ORC4, ORC6, CDT1, and CDC6 causative genes in the preinitiation complex disruptions. Methods: Sinapaldehyde and MCM7 were retrieved from Protein Data bank and PubChem database in the format of PDB and SDF format. Further, SDF format was converted to PDB format using Biovia Discovery Studio visualizer. Sinapaldehyde was subjected to pharmacoinformatics study as well as Molecular Docking analysis to find out the best anti-Gorlin potential. Results: Sinapaldehyde showed the -5.9kcal/mol binding affinity against MCM7 protein which considers to be a better candidate drug molecule against Meier-Gorlin Syndrome and validated using Pharmacokinetics mechanism. Conclusion: Molecular Docking studies and ADMET analysis showed the inhibitory activity of Sinapaldehyde with respect to Meier-Gorlin Syndrome and related pathway analysis and can be better compound for in vitro studies for future perspectives.