In-silico binding affinity of a phage display library screened novel peptide against various FABPs.

In accordance to the American Heart Association (AHA), cardiovascular diseases (CVDs) are the leading cause of death around the globe, causing more than 19.1 million deaths in 2020. Heart-type fatty acid binding protein (H-FABP) is required for the metabolism of fatty acids (FA) inside cardiomyocytes is reported as a biomarker for myocardial damage. As early as one hour after an Acute myocardial infarction (AMI), H-FABP can be used to detect myocardial ischemia. Thus, H-FABP based detection can reduce the burden on the emergency department. A peptide-based detection system can provide point-of-care diagnostics for CVDs. There is a lot of research being done on peptide-based detection, and it has a lot of potential to help with unmet medical diagnostic needs. A twelve (12) amino acid peptide has been discovered using Phage Display Library Screening. The affinity of peptide with H-FABP and other FABPs has been done using molecular docking and ADMET profile has been done. Molecular docking of small peptides against the target protein can play a crucial role in recognizing peptide binding sites and poses. The docking study was done using the HDOCK server and the visualization of the docked complex was done using Pymol and UCSF chimera. The molecular simulation study of three protein-peptide complexes were done which also validated the binding affinity of peptide with the proteins. The RMSD, RMSF and radius of gyration are also analyzed. The results indicate that H-FABP shows higher level of binding interaction with the peptide having bond length ranging from 2.3 to 3.4 Å. The screened peptide is suitable for H-FABP binding and can be used for prognosis purposes in the heart ischemic conditions.

Molecular Docking Approach for Biological Interaction of Green Synthesized Nanoparticles.

In recent years, significant progress has been made in the subject of nanotechnology, with a range of methods developed to synthesize precise-sized and shaped nanoparticles according to particular requirements. Often, the nanoparticles are created by employing dangerous reducing chemicals to reduce metal ions into uncharged nanoparticles. Green synthesis or biological approaches have been used recently to circumvent this issue because biological techniques are simple, inexpensive, safe, clean, and extremely productive. Nowadays, much research is being conducted on how different kinds of nanoparticles connect to proteins and nucleic acids using molecular docking models. Therefore, this review discusses the most recent advancements in molecular docking capacity to predict the interactions between various nanoparticles (NPs), such as ZnO, CuO, Ag, Au, and Fe3O4, and biological macromolecules.

A review of the principles and biotechnological applications of glycoside hydrolases from extreme environments.

It is apparent that Biocatalysts are shaping the future by providing a more sustainable approach to established chemical processes. Industrial processes rely heavily on the use of toxic compounds and high energy or pH reactions, factors that both contributes to the worsening climate crisis. Enzymes found in bacterial systems and other microorganisms, from the glaciers of the Arctic to the sandy deserts of Abu Dhabi, provide key tools and understanding as to how we can progress in the biotechnology sector. These extremophilic bacteria harness the adaptive enzymes capable of withstanding harsh reaction conditions in terms of stability and reactivity. Carbohydrate-active enzymes, including glycoside hydrolases or carbohydrate esterases, are extremely beneficial for the presence and future of biocatalysis. Their involvement in the industry spans from laundry detergents to paper and pulp treatment by degrading oligo/polysaccharides into their monomeric products in almost all detrimental environments. This includes exceedingly high temperatures, pHs or even in the absence of water. In this review, we discuss the structure and function of different glycoside hydrolases from extremophiles, and how they can be applied to industrial-scale reactions to replace the use of harsh chemicals, reduce waste, or decrease energy consumption.

PyProtif: a PyMol plugin to retrieve and visualize protein motifs for structural studies.

Proteins often possess several motifs and the ones with similar motifs were found to have similar biochemical properties and thus related biological functions. Thereby, multiple databases were developed to store information on such motifs in proteins. For instance, PDBsum stores the results of Promotif's generated structural motifs and Pfam stores pre-computed patterns of functional domains. In addition to the fact that all this stored information is extremely useful, we can further augment its importance if we ought to integrate these motifs into visualization software. In this work, we have developed PyProtif, a plugin for the PyMOL molecular visualization program, which automatically retrieves protein structural and functional motifs from different databases and integrates them in PyMOL for visualization and analyses. Through an expendable menu and a user-friendly interface, the plugin grants the users the ability to study simultaneously multiple proteins and to select and manipulate each motif separately. Thus, this plugin will be of great interest for structural, evolutionary and classification studies of proteins.

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.

Boosting the Full Potential of PyMOL with Structural Biology Plugins.

Over the past few decades, the number of available structural bioinformatics pipelines, libraries, plugins, web resources and software has increased exponentially and become accessible to the broad realm of life scientists. This expansion has shaped the field as a tangled network of methods, algorithms and user interfaces. In recent years PyMOL, widely used software for biomolecules visualization and analysis, has started to play a key role in providing an open platform for the successful implementation of expert knowledge into an easy-to-use molecular graphics tool. This review outlines the plugins and features that make PyMOL an eligible environment for supporting structural bioinformatics analyses.

Lectins from plants and algae act as anti-viral against HIV, influenza and coronaviruses.

BACKGROUND: Carbohydrate-lectin interactions are extremely specific as the lectin is capable of recognising monomeric and oligomeric sugars in a reversible manner. It has been known for a long time that lectins have antibacterial, antifungal, and insecticidal activities. Recently, it has been reported that many lectins can prevent the virus growth by interacting with the viral envelop surface glycoprotein. Spike protein, which is found on the surface of some enveloped viruses, is heavily mannosylated and will have strong affinity for mannose specific lectins. According to the findings, lectins have a high binding affinity for the glycans of the SARS-CoV-2 spike glycoprotein, which contains N-glycosylation sites. As a result, various lectins are being researched and developed as anti-viral agents. RESULTS: According to our in silico studies, the amino acid residues Asn487, Tyr489, Gln493, Lys417, and Tyr505 of the receptor binding domain (RBD) of SARS-CoV-2 formed an interaction with the model lectin Lablab purpureus lectin. Similar interaction for SARS-CoV-2 spike protein was observed with Griffithsin lectin (algal source) as well. These observations demonstrate that lectins could be one of the potential molecules for neutralising coronavirus infection. CONCLUSION: This review focuses on anti-viral lectins isolated and characterized from plants and algae (last 5 years) and showed anti-viral properties against HIV, Influenza, and coronaviruses.

Solvent accessibility of E1α and E1ß residues with known missense mutations causing pyruvate dehydrogenase complex (PDC) deficiency: Impact on PDC-E1 structure and function.

Pyruvate dehydrogenase complex deficiency is a major cause of primary lactic acidemia resulting in high morbidity and mortality, with limited therapeutic options. PDHA1 mutations are responsible for >82% of cases. The E1 component of PDC is a symmetric dimer of heterodimers (αß/α'ß') encoded by PDHA1 and PDHB. We measured solvent accessibility surface area (SASA), utilized nearest-neighbor analysis, incorporated sequence changes using mutagenesis tool in PyMOL, and performed molecular modeling with SWISS-MODEL, to investigate the impact of residues with disease-causing missense variants (DMVs) on E1 structure and function. We reviewed 166 and 13 genetically resolved cases due to PDHA1 and PDHB, respectively, from variant databases. We expanded on 102 E1α and 13 E1ß nonduplicate DMVs. DMVs of E1α Arg112-Arg224 stretch (exons 5-7) and of E1α Arg residues constituted 40% and 39% of cases, respectively, with invariant Arg349 accounting for 22% of arginine replacements. SASA analysis showed that 86% and 84% of residues with nonduplicate DMVs of E1α and E1ß, respectively, are solvent inaccessible ("buried"). Furthermore, 30% of E1α buried residues with DMVs are deleterious through perturbation of subunit-subunit interface contact (SSIC), with 73% located in the Arg112-Arg224 stretch. E1α Arg349 represented 74% of buried E1α Arg residues involved in SSIC. Structural perturbations resulting from residue replacements in some matched neighboring pairs of amino acids on different subunits involved in SSIC at 2.9-4.0 Å interatomic distance apart, exhibit similar clinical phenotype. Collectively, this work provides insight for future target-based advanced molecular modeling studies, with implications for development of novel therapeutics for specific recurrent DMVs of E1α.

Druggable hot spots in trypanothione reductase: novel insights and opportunities for drug discovery revealed by DRUGpy.

Assessment of target druggability guided by search and characterization of hot spots is a pivotal step in early stages of drug-discovery. The raw output of FTMap provides the data to perform this task, but it relies on manual intervention to properly combine different sets of consensus sites, therefore allowing identification of hot spots and evaluation of strength, shape and distance among them. Thus, the user's previous experience on the target and the software has a direct impact on how data generated by FTMap server can be explored. DRUGpy plugin was developed to overcome this limitation. By automatically assembling and scoring all possible combinations of consensus sites, DRUGpy plugin provides FTMap users a straight-forward method to identify and characterize hot spots in protein targets. DRUGpy is available in all operating systems that support PyMOL software. DRUGpy promptly identifies and characterizes pockets that are predicted by FTMap to bind druglike molecules with high-affinity (druggable sites) or low-affinity (borderline sites) and reveals how protein conformational flexibility impacts on the target's druggability. The use of DRUGpy on the analysis of trypanothione reductases (TR), a validated drug target against trypanosomatids, showcases the usefulness of the plugin, and led to the identification of a druggable pocket in the conserved dimer interface present in this class of proteins, opening new perspectives to the design of selective inhibitors.

Nicotinic cholinergic system and COVID-19: In silico evaluation of nicotinic acetylcholine receptor agonists as potential therapeutic interventions.

SARS-CoV-2 infection was announced as a pandemic in March 2020. Since then, several scientists have focused on the low prevalence of smokers among hospitalized COVID-19 patients. These findings led to our hypothesis that the Nicotinic Cholinergic System (NCS) plays a crucial role in the manifestation of COVID-19 and its severe symptoms. Molecular modeling revealed that the SARS-CoV-2 Spike glycoprotein might bind to nicotinic acetylcholine receptors (nAChRs) through a cryptic epitope homologous to snake toxins, substrates well documented and known for their affinity to the nAChRs. This binding model could provide logical explanations for the acute inflammatory disorder in patients with COVID-19, which may be linked to severe dysregulation of NCS. In this study, we present a series of complexes with cholinergic agonists that can potentially prevent SARS-CoV-2 Spike glycoprotein from binding to nAChRs, avoiding dysregulation of the NCS and moderating the symptoms and clinical manifestations of COVID-19. If our hypothesis is verified by in vitro and in vivo studies, repurposing agents currently approved for smoking cessation and neurological conditions could provide the scientific community with a therapeutic option in severe COVID-19.

PyVibMS: a PyMOL plugin for visualizing vibrations in molecules and solids.

Visualizing vibrational motions calculated with different ab initio packages requires dedicated post-processing tools. Here, we present a PyMOL plugin called PyVibMS for visualizing the vibrational motions for both molecular and solid systems calculated by mainstream quantum chemical computer programs including Gaussian, Q-Chem, VASP, and CRYSTAL. Benefiting from the continuing development of the PyMOL platform, PyVibMS provides powerful functionalities and user-friendly interface. PyVibMS was written in Python and its open-source nature makes it flexible and sustainable. As an example, the motions of the Konkoli-Cremer local vibrational modes are shown in this work for the first time. PyVibMS is freely available at https://github.com/smutao/PyVibMS . Graphical abstract In this work, a PyMOL plugin named PyVibMS is developed to visualize molecular and lattice vibrations.

PyXlinkViewer: A flexible tool for visualization of protein chemical crosslinking data within the PyMOL molecular graphics system.

Chemical crosslinking-mass spectrometry (XL-MS) is a valuable technique for gaining insights into protein structure and the organization of macromolecular complexes. XL-MS data yield inter-residue restraints that can be compared with high-resolution structural data. Distances greater than the crosslinker spacer-arm can reveal lowly populated "excited" states of proteins/protein assemblies, or crosslinks can be used as restraints to generate structural models in the absence of structural data. Despite increasing uptake of XL-MS, there are few tools to enable rapid and facile mapping of XL-MS data onto high-resolution structures or structural models. PyXlinkViewer is a user-friendly plugin for PyMOL v2 that maps intra-protein, inter-protein, and dead-end crosslinks onto protein structures/models and automates the calculation of inter-residue distances for the detected crosslinks. This enables rapid visualization of XL-MS data, assessment of whether a set of detected crosslinks is congruent with structural data, and easy production of high-quality images for publication.

Shortcuts for faster image creation in PyMOL.

PyMOL is often used to generate images of biomolecular structures. Hundreds of parameters in PyMOL provide precise control over the appearance of structures. We developed 241 Python functions-called "shortcuts"-that extend and ease the use of PyMOL. A user runs a shortcut by entering its name at the PyMOL prompt. We clustered the shortcuts by functionality into 25 groups for faster look-up. One set of shortcuts generates new styles of molecular representation. Another group saves files with time stamps in the file names; the unique filenames avoid overwriting files that have already been developed. A third group submits search terms in the user's web browser. The help function prints the function's documentation to the command history window. This documentation includes the PyMOL commands that the user can reuse by copying and pasting onto the command line or into a script file. The shortcuts should save the average PyMOL user many hours per year searching for code fragments in their computer or on-line. STATEMENT FOR LAY PUBLIC: Computer-generated images of protein structures are vital to the interpretation of and communication about the molecular structure of proteins. PyMOL is a popular computer program for generating such images. We made a large collection of macros or shortcuts that save time by executing complex operations with a few keystrokes.

Calculation of Thermodynamic Properties of Bound Water Molecules.

Water molecules in the binding site of a protein significantly influence protein structure and function, for example, by mediating protein-ligand interactions or in form of desolvation as driving force for ligand binding. The knowledge about location and thermodynamic properties of water molecules in the binding site is crucial to the understanding of protein function. This chapter describes the method of calculating the location and thermodynamic properties of bound water molecules from molecular dynamics (MD) simulation trajectories. Thermodynamic profiles of water molecules can be calculated either with or without the presence of a bound ligand based on the scientific problem. The location and thermodynamic profile of hydration sites mediating the protein-ligand interactions is important for understanding protein-ligand binding. The protein desolvation free energy can be estimated for any ligand by summation of the hydration site free energies of the displaced hydration sites. The WATsite program with an easy-to-use graphical user interface (GUI) based on PyMOL was developed for those calculations and is discussed in this chapter. The WATsite program and its PyMOL plugin are available free of charge from http://people.pharmacy.purdue.edu/~mlill/software/watsite/version3.shtml .

The disruptive effect of lysozyme on the bacterial cell wall explored by an in-silico structural outlook.

The bacterial cell wall, a structural unit of peptidoglycan polymer comprised of glycan strands consisting of a repeating disaccharide motif [N-acetylglucosamine (NAG) and N-acetylmuramylpentapeptide (NAM pentapeptide)], encases bacteria and provides structural integrity and protection. Lysozymes are enzymes that break down the bacterial cell wall and disrupt the bacterial life cycle by cleaving the linkage between the NAG and NAM carbohydrates. Lab exercises focused on the effects of lysozyme on the bacterial cell wall are frequently incorporated in biochemistry classes designed for undergraduate students in diverse fields as biology, microbiology, chemistry, agronomy, medicine, and veterinary medicine. Such exercises typically do not include structural data. We describe here a sequence of computer tasks designed to illustrate and reinforce both physiological and structural concepts involved in lysozyme effects on the bacterial cell-wall structure. This lab class usually lasts 3.5 hours. First, the instructor presents introductory concepts of the bacterial cell wall and the effect of lysozyme on its structure. Then, students are taught to use computer modeling to visualize the three-dimensional structure of a lysozyme in complex with bacterial cell-wall fragments. Finally, the lysozyme inhibitory effect on a bacterial culture is optionally proposed as a simple microbiological assay. The computer lab exercises described here give students a realistic understanding of the disruptive effect of lysozymes on the bacterial cell wall, a crucial component in bacterial survival. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):83-90, 2018.

PyMOL mControl: Manipulating molecular visualization with mobile devices.

Viewing and manipulating three-dimensional (3D) structures in molecular graphics software are essential tasks for researchers and students to understand the functions of molecules. Currently, the way to manipulate a 3D molecular object is mainly based on mouse-and-keyboard control that is usually difficult and tedious to learn. While gesture-based and touch-based interactions are increasingly popular in interactive software systems, their suitability in handling molecular graphics has not yet been sufficiently explored. Here, we designed the gesture-based and touch-based interaction methods to manipulate virtual objects in PyMOL utilizing the motion and touch sensors in a mobile device. Three fundamental viewing controls-zooming, translation and rotation-and frequently used functions were implemented. Results from a pilot user study reveal that task performances on viewing controls using a mobile device are slightly reduced as compared to mouse-and-keyboard method. However, it is considered to be more suitable for oral presentations and equally suitable for education scenarios such as school classes. Overall, PyMOL mControl provides an alternative way to manipulate objects in molecular graphic software with new user experiences. The software is freely available at http://cbbio.cis.umac.mo/mcontrol.html. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):76-83, 2017.

Ligand-based virtual screening interface between PyMOL and LiSiCA.

Ligand-based virtual screening of large small-molecule databases is an important step in the early stages of drug development. It is based on the similarity principle and is used to reduce the chemical space of large databases to a manageable size where chosen ligands can be experimentally tested. Ligand-based virtual screening can also be used to identify bioactive molecules with different basic scaffolds compared to already known bioactive molecules, thus having the potential to increase the structural variability of compounds. Here, we present an interface between the popular molecular graphics system PyMOL and the ligand-based virtual screening software LiSiCA available at http://insilab.org/lisica-plugin and demonstrate how this interface can be used in the early stages of drug discovery process.Graphical AbstractLigand-based virtual screening interface between PyMOL and LiSiCA.

PyMOL360: Multi-user gamepad control of molecular visualization software.

Interactive visualization of biomolecular structure is a powerful tool for scientists, students, and audiences from the laboratory to the classroom and beyond. However, existing platforms lack the ability to generate a collaborative environment to engage multiple users simultaneously. To address this need, PyMOL360 is described, which enables control of PyMOL molecular visualization software from multiple gamepad controllers. Extensive modularity enables user-defined configurations while default settings ease adoption by new users. A walkthrough of the software demonstrates its ability to select relevant molecules and modify viewing perspectives, molecular styles, colors, highlighted residues, or chains. Provision of source code encourages use and further development. © 2016 Wiley Periodicals, Inc.

Using the PyMOL application to reinforce visual understanding of protein structure.

Visualization of chemical concepts can be challenging for many students. This is arguably a critical skill for beginning students of biochemistry to develop, since new information is often presented visually in the form of textbook figures. It is recommended that visual literacy be explicitly taught in the classroom rather than assuming that students will develop this skill on their own.  The activity described here is designed to assist students in their development of understanding of basic representations of protein three-dimensional structure as well as various types of ligands (small molecules, ions) through the use of the iPad application PyMOL.  It has been used as a laboratory exercise but can also be used in a typical 50-minute class period with a portion of the activity assigned as homework. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(5):433-437, 2016.

Improvements in GROMACS plugin for PyMOL including implicit solvent simulations and displaying results of PCA analysis.

In order to get the dynamic molecule model from the static one, the molecular dynamics (MD) simulation needs to be performed. Some software sets such as GROMACS are used for that purpose. Unfortunately they lack GUI. The Dynamics PyMOL plugin allows researcher to perform MD simulations directly from the PyMOL software by GUI-based interface of GROMACS tools. This paper describes many improvements introduced into the Dynamics PyMOL plugin 2.0 including: an integration with ProDy library, possibility to use the implicit solvents, an ability to interpret the MD simulations, and implementation of some more GROMACS functionality.