Molecular Visualization Research Articles

Moliverse: Contextually embedding the microcosm into the universe

We present Moliverse, an integration of the molecular visualization framework VIAMD into the astronomical visualization software OpenSpace, allowing us to bridge the two extreme ends of the scale spectrum to show, for example, the gas composition in a planet’s atmosphere or molecular structures in comet trails and can empower the creation of educational exhibitions. For that purpose we do not use a linear scale traversal but break the scale continuity and show molecular simulations as focus in the context of celestial bodies. We demonstrate the application of our concept in two storytelling scenarios and envision the application both for science presentations to lay audiences and for dedicated exploration, potentially also in a molecule-only environment.

Study on the cytochrome B protein of Culex quinquefasciatus with Malic acid using automated Insilico docking protocols

Culex quinquefasciatus is a major threat faced by people in India. The nematode worm, Wuchereria bancrofti causes Lymphatic filariasis which is transmitted by Culex quinquefasciatus acting as a vector. The aim of the present Insilico research work is to validate how malic acid interacts with the protein of the mosquito species, Culex quinquefasciatus using Bioinformatic tools. The target protein molecule is Cytochrome b mitochondrion protein of the mosquito species. The structure of Malic acid is retrieved from the generalized database, NCBI (National Center for Biotechnology Information). Drug docking studies are performed using an automated drug docking server. The chemical molecule is converted from 2D to 3D using an advanced molecular visualization software. The result obtained from docking clearly shows that Malic acid binds with the functional domain region of Cytochrome b protein of the mosquito sps. All the results were clearly elucidated using 3D visualization techniques on the binding interaction between malic acid and the protein of the mosquito sps. It was thus proved that Malic acid is an efficient agent for controlling Culex quinquefasciatus.

State of the Art of Molecular Visualization in Immersive Virtual Environments

AbstractVisualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head‐mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.

Molecular Screening of Bioactive Compounds of Garlic for Therapeutic Effects against COVID-19.

An outbreak of pneumonia occurred on December 2019 in Wuhan, China, which caused a serious public health emergency by spreading around the globe. Globally, natural products are being focused on more than synthetic ones. So, keeping that in view, the current study was conducted to discover potential antiviral compounds from Allium sativum. Twenty-five phytocompounds of this plant were selected from the literature and databases including 3-(Allylsulphinyl)-L-alanine, Allicin, Diallyl sulfide, Diallyl disulfide, Diallyl trisulfide, Glutathione, L-Cysteine, S-allyl-mercapto-glutathione, Quercetin, Myricetin, Thiocysteine, Gamma-glutamyl-Lcysteine, Gamma-glutamylallyl-cysteine, Fructan, Lauricacid, Linoleicacid, Allixin, Ajoene, Diazinon Kaempferol, Levamisole, Caffeicacid, Ethyl linoleate, Scutellarein, and S-allylcysteine methyl-ester. Virtual screening of these selected ligands was carried out against drug target 3CL protease by CB-dock. Pharmacokinetic and pharmacodynamic properties defined the final destiny of compounds as drug or non-drug molecules. The best five compounds screened were Allicin, Diallyl Sulfide, Diallyl Disulfide, Diallyl Trisulfide, Ajoene, and Levamisole, which showed themselves as hit compounds. Further refining by screening filters represented Levamisole as a lead compound. All the interaction visualization analysis studies were performed using the PyMol molecular visualization tool and LigPlot+. Conclusively, Levamisole was screened as a likely antiviral compound which might be a drug candidate to treat SARS-CoV-2 in the future. Nevertheless, further research needs to be carried out to study their potential medicinal use.

In Silico Analysis Effect of Potential Antidiabetic from Dandang Gendis Extract on Aldose Reductase, Glucokinase, and GSK3β for Type 2 Diabetes Mellitus

Introduction: Diabetes mellitus is a metabolic disease characterized by hyperglycemia. Various epidemiological studies have shown a trend of increasing incidence and prevalence of diabetes mellitus in various parts of the world. Therefore, diabetes mellitus is currently a global health threat. Dandang gendis (Clinacanthus nutans) is a widely used plant as a traditional herbal treatment in Indonesia, and it has been proven that the ethanol extract of dandang gendis leaves shows an antidiabetic effect. This research aims to determine the compatibility among the flavonoid compounds in C. nutans with Aldose reductase, glucokinase, and GSK3β target drugs for type 2 diabetes mellitus using in silico method.Methods: 45 compounds were obtained from multiple sources. The screening method used Lipinski’s rule of five and Pyrx until 8 compounds were selected. Avogadro, AutoDock 4.2, and Biovia Discovery Studio 2016 were used for molecular docking and visualization analysis.Results: Molecular docking results demonstrate that the ligand-protein interaction’s binding energy was -7.31 to 35.25 kcal/mol for 1AH3, -7.55 to 0.15 kcal/mol for 1V4S, and -7.99 to -2.85 kcal/mol for 3D0E.Conclusion: We can conclude that flavonoid compounds Apigenin, Vitexin, 3,3-di-O-Methylellagic Acid, and Clinacoside C show a high binding affinity with Aldose Reductase, Glucokinase, and GSK3β proteins and have the potential to be oral antidiabetic drug compounds for Diabetes Mellitus. However, its binding affinity has not been able to exceed that of the native ligand of the protein. Further research is needed to determine the significant efficacy and potential as an antidiabetic.

Exploration and comparison of molecular mechanisms across diseases using MINERVA Net.

Protein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories containing manually constructed systems biology diagrams. Disease maps hosted on the Molecular Interaction Network VisuAlization (MINERVA) Platform are individually accessible through a REST API interface of each instance, making it challenging to systematically explore their contents. To address this challenge, we introduce the MINERVA Net web service, a repository of open-access disease maps allowing users to publicly share minimal information about their maps. The MINERVA Net repository provides REST API endpoints of particular disease maps, which then can be individually queried for content. In this article, we describe the concept of MINERVA Net and illustrate its use by comparing proteins and their interactions in three different disease maps.

Equity analysis of an augmented reality‐mediated group activity in a college biochemistry classroom

AbstractThe use of two‐dimensional images to teach students about three‐dimensional molecules continues to be a prevalent issue in many classrooms. As affordable visualization technologies continue to advance, there has been an increasing interest to utilize novel technology, such as augmented reality (AR), in the development of molecular visualization tools. Existing evaluations of these visual–spatial learning tools focus primarily on student performance and attitude, with little attention toward potential inequity in student participation. Our study adds to the current literature on introducing molecular visualization technology in biochemistry classrooms by examining the potential inequity in a group activity mediated by AR technology. Adapting the participatory equity framework to our specific context, we view equity and inequity in terms of access to the technological conversational floor, a social space created when people enter technology‐mediated joint endeavors. We explore three questions: What are the different ways students interact with an AR model of the potassium channel? What are salient patterns of participation that may signify inequity in classroom technology use? What is the interplay between group social dynamics and the introduction of AR technology in the context of a technology‐mediated group activity? Pairing qualitative analysis with quantitative metrics, our mixed‐methods approach produced a complex story of student participation in an AR‐mediated group activity. The patterns of student participation showed that equity and inequity in an AR‐mediated biochemistry group learning activity are fluid and multifaceted. It was observed that students who gave more explanations during group discussion also had more interactions with the AR model (i.e., they had greater access to the technological conversational floor), and their opinion of the AR model may have greater influence on how their group engage with the AR model. This study provides more nuanced ways of conceptualizing equity and inequity in biochemistry learning settings.

LongBondEliminator: A Molecular Simulation Tool to Remove Ring Penetrations in Biomolecular Simulation Systems.

We develop a workflow, implemented as a plugin to the molecular visualization program VMD, that can fix ring penetrations with minimal user input. LongBondEliminator, detects ring piercing artifacts by the long, strained bonds that are the local minimum energy conformation during minimization for some assembled simulation system. The LongBondEliminator tool then automatically treats regions near these long bonds using multiple biases applied through NAMD. By combining biases implemented through the collective variables module, density-based forces, and alchemical techniques in NAMD, LongBondEliminator will iteratively alleviate long bonds found within molecular simulation systems. Through three concrete examples with increasing complexity, a lignin polymer, an viral capsid assembly, and a large, highly glycosylated protein aggrecan, we demonstrate the utility for this method in eliminating ring penetrations from classical MD simulation systems. The tool is available via gitlab as a VMD plugin, and has been developed to be generically useful across a variety of biomolecular simulations.

Correlative Light and Electron Cryo-Microscopy Workflow Combining Micropatterning, Ice Shield, and an In-Chamber Fluorescence Light Microscope.

In situ cryo-electron tomography (cryo-ET) is the most current, state-of-the-art technique to study cell machinery in its hydrated near-native state. The method provides ultrastructural details at sub-nanometer resolution for many components within the cellular context. Making use of recent advances in sample preparation techniques and combining this method with correlative light and electron microscopy (CLEM) approaches have enabled targeted molecular visualization. Nevertheless, the implementation has also added to the complexity of the workflow and introduced new obstacles in the way of streamlining and achieving high throughput, sample yield, and sample quality. Here, we report a detailed protocol by combining multiple newly available technologies to establish an integrated, high-throughput, optimized, and streamlined cryo-CLEM workflow for improved sample yield. Key features • PRIMO micropatterning allows precise cell positioning and maximum number of cell targets amenable to thinning with cryo focused-ion-beam-scanning electron microscopy. • CERES ice shield ensures that the lamellae remain free of ice contamination during the batch milling process. • METEOR in-chamber fluorescence microscope facilitates the targeted cryo focused-ion-beam (cryo FIB) milling of these targets. • Combining the three technologies into one cryo-CLEM workflow maximizes sample yield, throughput, and efficiency. Graphical overview.

Carotenoids from female Grapsus albolineatus as potential anti-ageing compounds

Introduction: Grapsus albolineatus is thought to have a high concentration of carotenoid pigments. Although studies on male G. albolineatus have been conducted, no studies on pigment extraction from female G. albolineatus have been carried out. Carotenoids have a high ability to fight free radicals. Previous research has shown that carotenoids can fight free radicals that cause premature skin-aging. The purpose of this research was to find out what kinds of carotenoids are found in G. albolineatus and whether they can act as natural inhibitors of proteins that cause premature aging, such as glucogenase, elastase, and hyaluronidase enzymes. Methods: Carotenoids were extracted from G. albolineatus using column chromatography and high-performance liquid chromatography (HPLC); molecular docking and visualization were done with Autodock 4.2 and Discovery Studio/Biovia, respectively. Results: According to HPLC data, there are carotenoid pigments such as didehydroastaxanthin, tetrahydroastaxanthin, dihydroastaxanthin, diatoxanthin, astaxanthin, and adonixanthin. According to molecular docking experiments, pigment carotenoids from G. albolineatus are efficient inhibitors of protein elastase and hyaluronidase. Conclusions: G. albolineatus carotenoids have the potential to be anti-aging since they are more effective as protein elastase and hyaluronidase inhibitors than their native inhibitors.

In Silico Analysis of Protein of Milk, Soybean, and Kefir as Anti- Thrombotic Bioactive Peptide

Currently, Cardiovascular Diseases (CVDs) cases are increasing significantly in Indonesia and the world. WHO reported that in 2019-related CVD patients accounted for 85%, which increased to 87% in 2021. The cases increased significantly by 2%, which is a significant number as it covered the world population. Stroke is a disease affected by platelets undergoing thrombolysis by the α-thrombin (IIa) receptor with coagulation factors on the heart blood vessel. Chemical or synthesis drugs to treat thrombolytics such as heparin are already available, but they would be harmful if misused. In this study, we focused on the activity, interaction, and prediction of the physicochemical of anti-thrombotic peptides. We found that k-casein from kefir has the highest activity of 0.037 A based on BIOPEP analysis with 17 peptide libraries and molecular docking visualization analysis using PyMol, PyRx, and Discovery Studio for screening the best peptide. ToxinPred and AlgPred showed there are no potentially harmful peptides, but the protein variant of β-conglycinin subunit can be an allergen known to the immune system IgE. In conclusion, the GPR peptide has the highest binding affinity, with a total energy of -6.8 kcal/mol.

A Semester-Long Learning Path Teaching Computational Skills via Molecular Graphics in PyMOL

ABSTRACT Structural biology describes biological processes at the molecular level and is an integral part of undergraduate study programs in molecular biosciences. Students are often fascinated by the visualizations created by molecular graphics software, which allow them to see the molecular world for the first time. Today, molecular visualization and structural analysis do not require expensive high-end computers but can be performed on the students' own laptops and are therefore highly suited for active learning approaches. We have designed a semester-long learning path that integrates molecular graphics and structural analysis using PyMOL into an undergraduate course in biomolecular structure and function. Compared to stand-alone PyMOL introductions, the semester-long learning path allows for an improved pedagogical design. The path progressively introduces more advanced functions in relevant scientific contexts and allows for spaced repetition. Advanced analysis functions in PyMOL are available only via the command line, so the learning path also teaches basic scripting and serves as an accessible introduction to computational thinking because a few lines of code can produce stunning results. Student surveys carried out at the end of the course suggest that the learning path supported the ability to perform structural analysis to a high degree. Moreover, a simulated exam showed that almost all students were able to carry out basic visualization tasks using PyMOL scripts, while three-quarters could undertake advanced structural analysis after following the course. In summary, integration of molecular graphics software with teaching of structural biochemistry allows a hands-on approach to analyzing molecular mechanisms and introduces biologically oriented students to computational thinking.

Water-soluble Self-assembled {Pd84 }Ac Polyoxopalladate Nano-wheel as a Supramolecular Host.

Polyoxopalladates (POPs) are a class of self-assembling palladium-oxide clusters that span a variety of sizes, shapes and compositions. The largest of this family, {Pd84 }Ac , is constructed from 14 building units of {Pd6 } and lined on the inner and outer torus by 28 acetate ligands. Due to its high water solubility, large hydrophobic cavity and distinct 1 H NMR fingerprint {Pd84 }Ac is an ideal molecule for exploring supramolecular behaviour with small organic molecules in aqueous media. Molecular visualisation studies highlighted potential binding sites between {Pd84 }Ac and these species. Nuclear Magnetic Resonance (NMR) techniques, including 1 H NMR, 1 H Diffusion Ordered Spectroscopy (DOSY) and Nuclear Overhauser Spectroscopy (NOESY), were employed to study the supramolecular chemistry of this system. Here, we provide conclusive evidence that {Pd84 }Ac forms a 1 : 7 host-guest complex with benzyl viologen (BV2+ ) in aqueous solution.

Water‐soluble Self‐assembled {Pd84}Ac Polyoxopalladate Nano‐wheel as a Supramolecular Host

AbstractPolyoxopalladates (POPs) are a class of self‐assembling palladium‐oxide clusters that span a variety of sizes, shapes and compositions. The largest of this family, {Pd84}Ac, is constructed from 14 building units of {Pd6} and lined on the inner and outer torus by 28 acetate ligands. Due to its high water solubility, large hydrophobic cavity and distinct 1H NMR fingerprint {Pd84}Ac is an ideal molecule for exploring supramolecular behaviour with small organic molecules in aqueous media. Molecular visualisation studies highlighted potential binding sites between {Pd84}Ac and these species. Nuclear Magnetic Resonance (NMR) techniques, including 1H NMR, 1H Diffusion Ordered Spectroscopy (DOSY) and Nuclear Overhauser Spectroscopy (NOESY), were employed to study the supramolecular chemistry of this system. Here, we provide conclusive evidence that {Pd84}Ac forms a 1 : 7 host‐guest complex with benzyl viologen (BV2+) in aqueous solution.

Fast and Interactive Positioning of Proteins within Membranes

(1) Background: We developed an algorithm to perform interactive molecular simulations (IMS) of protein alignment in membranes, allowing on-the-fly monitoring and manipulation of such molecular systems at various scales. (2) Methods: UnityMol, an advanced molecular visualization software; MDDriver, a socket for data communication; and BioSpring, a Spring network simulation engine, were extended to perform IMS. These components are designed to easily communicate with each other, adapt to other molecular simulation software, and provide a development framework for adding new interaction models to simulate biological phenomena such as protein alignment in the membrane at a fast enough rate for real-time experiments. (3) Results: We describe in detail the integration of an implicit membrane model for Integral Membrane Protein And Lipid Association (IMPALA) into our IMS framework. Our implementation can cover multiple levels of representation, and the degrees of freedom can be tuned to optimize the experience. We explain the validation of this model in an interactive and exhaustive search mode. (4) Conclusions: Protein positioning in model membranes can now be performed interactively in real time.

Antibacterial activity of Stachytarpheta jamaicensis (L.) Vahl roots extract on some bacteria proteins: An in silico and in vitro study

Context: Stachytarpheta jamaicensis (L.) Vahl plant is used for traditional therapy because of its content, including flavonoids, alkaloids, tannins, saponins, terpenoids, and coumarins. Aims: To determine the antibacterial ability of S. jamaicensis roots extract (SJRE) on some selected mouth bacteria through in vitro and in silico studies. Methods: Phytochemical analysis and liquid chromatography-high resolution mass spectrometry (LC-HRMS) were done to explore the active compounds on SJRE. Absorption, distribution, metabolism, excretion and toxicity prediction, molecular docking simulation and visualization of luvangetin, and xanthyletin as anti-inflammatory and antibacterial were investigated in silico. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of SJRE against Aggregatibacter actinomycetemcomitans, Enterococcus faecalis, and Actinomyces spp. were calculated. Results: Luvangetin and xanthyletin are good candidate drug molecules with low toxicity. Xanthyletin has higher binding activity than luvangetin to TNF-α, IL-6, IL-10, peptidoglycan, flagellin, and dectin protein. SJRE exhibited a high antibacterial ability, and MIC. This extract inhibits the growth of A. actinomycetemcomitans, E. faecalis and Actinomyces spp. at various concentrations 2000, 8000, and 8000 µg/mL, respectively, with statistically significant differences (p = 0.0001; p<0.05). Conclusions: SJRE has an antibacterial ability, and 2000 µg/mL SJRE may act as an antibacterial agent in vitro. In addition, xanthyletin in SJRE has a potential role as an antibacterial and anti-inflammatory in silico.

Molecular simulation of compounds from n-hexane fraction of Sonchus arvensis L. leaves as SARS-CoV-2 antiviral through inhibitor activity targeting strategic viral protein

Context: COVID-19 was caused by the spread and transmission of SARS-CoV-2 at the end of 2019 until now. The problem comes when antiviral drugs have not yet been found and patients infected with SARS-CoV-2 can trigger a cytokine storm condition due to the effects of viral replication. Indonesia has various kinds of medicinal plants, such as Sonchus arvensis L., which are used as medicinal plants. Aims: To analyze the activity of the inhibitor as SARS-CoV-2 antiviral agents from n-hexane fractions of S. arvensis leaves. Methods: The sample was collected from GC-MS analysis, PubChem, and Protein Databank database, then drug-likeness identification using Lipinski Rule of Five server and bioactive prediction of bioactive compounds as inhibitor activity was conducted by Molinspiration server. Furthermore, the docking simulation was performed using PyRx 0.9.9 software to determine the binding activity, molecular interaction by Discovery Studio software to identify position and interaction type, 3D molecular visualization by PyMol 2.5. software, and dynamic by CABS-flex 2.0 server to predict interaction stability. Results: α-Amyrin and β-amyrin from n-hexane fractions of S. arvensis leaves had activity as SARS-CoV-2 inhibitors through interactions on helicase, RdRp, Mpro, and RBD-Spike, both compounds had more negative binding affinity than control drug and can produce stable chemical bond interactions in the ligand-protein complexes. However, the results were merely computational, so they must be validated through an in vivo and in vitro research approach. Conclusions: Sonchus arvensis L. leaves were predicted to have SARS-CoV-2 antiviral through inhibitor activity by α-amyrin and β-amyrin.

PacDOCK: A Web Server for Positional Distance-Based and Interaction-Based Analysis of Docking Results.

Molecular docking is a key method for structure-based drug design used to predict the conformations assumed by small drug-like ligands when bound to their target. However, the evaluation of molecular docking studies can be hampered by the lack of a free and easy to use platform for the complete analysis of results obtained by the principal docking programs. To this aim, we developed PacDOCK, a freely available and user-friendly web server that comprises a collection of tools for positional distance-based and interaction-based analysis of docking results, which can be provided in several file formats. PacDOCK allows a complete analysis of molecular docking results through root mean square deviation (RMSD) calculation, molecular visualization, and cluster analysis of docked poses. The RMSD calculation compares docked structures with a reference structure, also when atoms are randomly labelled, and their conformational and positional differences can be visualised. In addition, it is possible to visualise a ligand into the target binding pocket and investigate the key receptor–ligand interactions. Moreover, PacDOCK enables the clustering of docking results by identifying a restrained number of clusters from many docked poses. We believe that PacDOCK will contribute to facilitating the analysis of docking results to improve the efficiency of computer-aided drug design.

Identification of compelling inhibitors of human norovirus 3CL protease to combat gastroenteritis: A structure-based virtual screening and molecular dynamics study.

Human noroviruses (NV) are the most prevalent cause of sporadic and pandemic acute gastroenteritis. NV infections cause substantial morbidity and death globally, especially amongst the aged, immunocompromised individuals, and children. There are presently no authorized NV vaccines, small-molecule therapies, or prophylactics for humans. NV 3 C L protease (3CLP) has been identified as a promising therapeutic target for anti-NV drug development. Herein, we employed a structure-based virtual screening method to screen a library of 700 antiviral compounds against the active site residues of 3CLP. We report three compounds, Sorafenib, YM201636, and LDC4297, that were revealed to have a higher binding energy (BE) value with 3CLP than the control (Dipeptidyl inhibitor 7) following a sequential screening, in-depth molecular docking and visualization, physicochemical and pharmacological property analysis, and molecular dynamics (MD) study. Sorafenib, YM201636, and LDC4297 had BEs of -11.67, -10.34, and -9.78 kcal/mol with 3CLP, respectively, while control had a BE of -6.38 kcal/mol. Furthermore, MD simulations of the two best compounds and control were used to further optimize the interactions, and a 100 ns MD simulation revealed that they form stable complexes with 3CLP. The estimated physicochemical, drug-like, and ADMET properties of these hits suggest that they might be employed as 3CLP inhibitors in the management of gastroenteritis. However, wet lab tests are a prerequisite to optimize them as NV 3CLP inhibitors.

Stmol: A component for building interactive molecular visualizations within streamlit web-applications.

Streamlit is an open-source Python coding framework for building web-applications or “web-apps” and is now being used by researchers to share large data sets from published studies and other resources. Here we present Stmol, an easy-to-use component for rendering interactive 3D molecular visualizations of protein and ligand structures within Streamlit web-apps. Stmol can render protein and ligand structures with just a few lines of Python code by utilizing popular visualization libraries, currently Py3DMol and Speck. On the user-end, Stmol does not require expertise to interactively navigate. On the developer-end, Stmol can be easily integrated within structural bioinformatic and cheminformatic pipelines to provide a simple means for user-end researchers to advance biological studies and drug discovery efforts. In this paper, we highlight a few examples of how Stmol has already been utilized by scientific communities to share interactive molecular visualizations of protein and ligand structures from known open databases. We hope Stmol will be used by researchers to build additional open-sourced web-apps to benefit current and future generations of scientists.