scholarly journals Cyanide Hydratase Modification Using Computational Design and Docking Analysis for Improved Binding Affinity in Cyanide Detoxification

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1799
Author(s):  
Narges Malmir ◽  
Najaf Allahyari Fard ◽  
Yamkela Mgwatyu ◽  
Lukhanyo Mekuto
Keyword(s):  
Trichoderma Harzianum ◽  
Homology Modelling ◽  
3D Structure ◽  
Design Procedure ◽  
Computational Design ◽  
Ligand Docking ◽  
Nucleophilic Attack ◽  
Total Charge ◽  
Ligand Complex ◽  
Cyanide Hydratase

Cyanide is a hazardous and detrimental chemical that causes the inactivation of the respiration system through the inactivation of cytochrome c oxidase. Because of the limitation in the number of cyanide-degrading enzymes, there is a great demand to design and introduce new enzymes with better functionality. This study developed an integrated method of protein-homology-modelling and ligand-docking protein-design approaches that reconstructs a better active site from cyanide hydratase (CHT) structure. Designing a mutant CHT (mCHT) can improve the CHT performance. A computational design procedure that focuses on mutation for constructing a new model of cyanide hydratase with better activity was used. In fact, this study predicted the three-dimensional (3D) structure of CHT for subsequent analysis. Inducing mutation on CHT of Trichoderma harzianum was performed and molecular docking was used to compare protein interaction with cyanide as a ligand in both CHT and mCHT. By combining multiple designed mutations, a significant improvement in docking for CHT was obtained. The results demonstrate computational capabilities for enhancing and accelerating enzyme activity. The result of sequence alignment and homology modeling show that catalytic triad (Cys-Glu-Lys) was conserved in CHT of Trichoderma harzianum. By inducing mutation in CHT structure, MolDock score enhanced from −18.1752 to −23.8575, thus the nucleophilic attack can occur rapidly by adding Cys in the catalytic cavity and the total charge of protein in pH 6.5 is increased from −6.0004 to −5.0004. Also, molecular dynamic simulation shows a stable protein-ligand complex model. These changes would help in the cyanide degradation process by mCHT.

Novel drug design and bioinformatics: an introduction

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohammad Kalim Ahmad Khan ◽  
Salman Akhtar
Keyword(s):  
Drug Design ◽  
Target Identification ◽  
Homology Modelling ◽  
3D Structure ◽  
Cost Effective ◽  
Biological Data ◽  
Combinatorial Design ◽  
Ligand Docking ◽  
Structure Based Drug Design ◽  
Biological Targets

Abstract In the current era of high-throughput technology, where enormous amounts of biological data are generated day by day via various sequencing projects, thereby the staggering volume of biological targets deciphered. The discovery of new chemical entities and bioisosteres of relatively low molecular weight has been gaining high momentum in the pharmacopoeia, and traditional combinatorial design wherein chemical structure is used as an initial template for enhancing efficacy pharmacokinetic selectivity properties. Once the compound is identified, it undergoes ADMET filtration to ensure whether it has toxic and mutagenic properties or not. If the compound has no toxicity and mutagenicity is either considered a potential lead molecule. Understanding the mechanism of lead molecules with various biological targets is imperative to advance related functions for drug discovery and development. Notwithstanding, a tedious and costly process, taking around 10–15 years and costing around $4 billion, cascaded approached of Bioinformatics and Computational biology viz., structure-based drug design (SBDD) and cognate ligand-based drug design (LBDD) respectively rely on the availability of 3D structure of target biomacromolecules and vice versa has made this process easy and approachable. SBDD encompasses homology modelling, ligand docking, fragment-based drug design and molecular dynamics, while LBDD deals with pharmacophore mapping, QSAR, and similarity search. All the computational methods discussed herein, whether for target identification or novel ligand discovery, continuously evolve and facilitate cost-effective and reliable outcomes in an era of overwhelming data.

scholarly journals Structure of SPH (self-incompatibility protein homologue) proteins: a widespread family of small, highly stable, secreted proteins

2019 ◽  
Vol 476 (5) ◽  
pp. 809-826
Author(s):  
Karthik V. Rajasekar ◽  
Shuangxi Ji ◽  
Rachel J. Coulthard ◽  
Jon P. Ride ◽  
Gillian L. Reynolds ◽  
...  
Keyword(s):  
Fusion Protein ◽  
Analytical Ultracentrifugation ◽  
De Novo ◽  
Learning Algorithm ◽  
Sequence Similarity ◽  
Homology Modelling ◽  
3D Structure ◽  
Large Family ◽  
Secreted Proteins ◽  
Self Incompatibility

Abstract SPH (self-incompatibility protein homologue) proteins are a large family of small, disulfide-bonded, secreted proteins, initially found in the self-incompatibility response in the field poppy (Papaver rhoeas), but now known to be widely distributed in plants, many containing multiple members of this protein family. Using the Origami strain of Escherichia coli, we expressed one member of this family, SPH15 from Arabidopsis thaliana, as a folded thioredoxin fusion protein and purified it from the cytosol. The fusion protein was cleaved and characterised by analytical ultracentrifugation, circular dichroism and nuclear magnetic resonance (NMR) spectroscopy. This showed that SPH15 is monomeric and temperature stable, with a β-sandwich structure. The four strands in each sheet have the same topology as the unrelated proteins: human transthyretin, bacterial TssJ and pneumolysin, with no discernible sequence similarity. The NMR-derived structure was compared with a de novo model, made using a new deep learning algorithm based on co-evolution/correlated mutations, DeepCDPred, validating the method. The DeepCDPred de novo method and homology modelling to SPH15 were then both used to derive models of the 3D structure of the three known PrsS proteins from P. rhoeas, which have only 15–18% sequence homology to SPH15. The DeepCDPred method gave models with lower discreet optimised protein energy scores than the homology models. Three loops at one end of the poppy structures are postulated to interact with their respective pollen receptors to instigate programmed cell death in pollen tubes.

scholarly journals Off-pathway 3D-structure provides protection against spontaneous Asn/Asp isomerization: shielding proteins Achilles heel

2020 ◽  
Vol 53 ◽  
Author(s):  
András Láng ◽  
Imre Jákli ◽  
Kata Nóra Enyedi ◽  
Gábor Mező ◽  
Dóra K. Menyhárd ◽  
...  
Keyword(s):  
Protective Factor ◽  
Structural Integrity ◽  
3D Structure ◽  
Nucleophilic Attack ◽  
Structural Element ◽  
Backbone Conformation ◽  
Peptide Models ◽  
Geometric Descriptors ◽  
Restricted Mobility ◽  
Methylene Group

Abstract Spontaneous deamidation prompted backbone isomerization of Asn/Asp residues resulting in – most cases – the insertion of an extra methylene group into the backbone poses a threat to the structural integrity of proteins. Here we present a systematical analysis of how temperature, pH, presence of charged residues, but most importantly backbone conformation and dynamics affect isomerization rates as determined by nuclear magnetic resonance in the case of designed peptide-models. We demonstrate that restricted mobility (such as being part of a secondary structural element) may safeguard against isomerization, but this protective factor is most effective in the case of off-pathway folds which can slow the reaction by several magnitudes compared to their on-pathway counterparts. We show that the geometric descriptors of the initial nucleophilic attack of the isomerization can be used to classify local conformation and contribute to the design of stable protein drugs, antibodies or the assessment of the severity of mutations.

scholarly journals Homology Modelling and Molecular Docking Studies of Selected Substituted Benzo[d]imidazol-1-yl)methyl)benzimidamide Scaffolds on Plasmodium falciparum Adenylosuccinate Lyase Receptor

2019 ◽  
Vol 13 ◽  
pp. 117793221986553 ◽  
Author(s):  
Gbolahan O Oduselu ◽  
Olayinka O Ajani ◽  
Yvonne U Ajamma ◽  
Benedikt Brors ◽  
Ezekiel Adebiyi
Keyword(s):  
Plasmodium Falciparum ◽  
Molecular Docking ◽  
In Silico ◽  
Homology Modelling ◽  
3D Structure ◽  
Docking Studies ◽  
Binding Energies ◽  
Benzimidazole Derivatives ◽  
Adenylosuccinate Lyase ◽  
In Silico Admet

Plasmodium falciparum adenylosuccinate lyase ( PfADSL) is an important enzyme in purine metabolism. Although several benzimidazole derivatives have been commercially developed into drugs, the template design as inhibitor against PfADSL has not been fully explored. This study aims to model the 3-dimensional (3D) structure of PfADSL, design and predict in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) of 8 substituted benzo[ d]imidazol-1-yl)methyl)benzimidamide compounds as well as predict the potential interaction modes and binding affinities of the designed ligands with the modelled PfADSL. PfADSL 3D structure was modelled using SWISS-MODEL, whereas the compounds were designed using ChemDraw Professional. ADMET predictions were done using OSIRIS Property Explorer and Swiss ADME, whereas molecular docking was done with AutoDock Tools. All designed compounds exhibited good in silico ADMET properties, hence can be considered safe for drug development. Binding energies ranged from −6.85 to −8.75 kcal/mol. Thus, they could be further synthesised and developed into active commercial antimalarial drugs.

Toward the Computational Design of Artificial Metalloenzymes: From Protein–Ligand Docking to Multiscale Approaches

ACS Catalysis ◽  
2015 ◽  
Vol 5 (4) ◽  
pp. 2469-2480 ◽  
Author(s):  
Victor Muñoz Robles ◽  
Elisabeth Ortega-Carrasco ◽  
Lur Alonso-Cotchico ◽  
Jaime Rodriguez-Guerra ◽  
Agustí Lledós ◽  
...  
Keyword(s):  
Computational Design ◽  
Ligand Docking ◽  
Artificial Metalloenzymes

A Design Procedure for Electric Inductive Capacitive Resonators with Negative Permittivity

2013 ◽  
Vol 448-453 ◽  
pp. 2199-2202
Author(s):  
Shi Wei Zhou ◽  
Yi Min Xie ◽  
Qing Li ◽  
Xiao Dong Huang
Keyword(s):  
Ring Resonator ◽  
Design Procedure ◽  
Computational Design ◽  
Split Ring Resonator ◽  
Index Of Refraction ◽  
Negative Permittivity ◽  
Electromagnetic Properties ◽  
Optimization Approach ◽  
Split Ring ◽  
Negative Index Of Refraction

Permittivity signifies a key component to metamaterial which can achieve negative index of refraction, but it has not been sufficiently addressed in computational design. This paper aims to attain negative permittivity through a topology optimization approach and provides an example equivalent to electric inductive-capacitive resonator. Similar to split ring resonator, this locally self-contained (without the demand for inter-cell connection) resonator allows keeping bulk electromagnetic properties homogeneously, facilitating mass fabrication, and realizing single sampling test.

scholarly journals Computational Design and Analysis of a Magic Snake

2020 ◽  
Vol 12 (5) ◽  
Author(s):  
Zilong Li ◽  
Songming Hou ◽  
Thomas C. Bishop
Keyword(s):  
3D Structure ◽  
Three Dimensional ◽  
Computational Design ◽  
Space Curve ◽  
One Dimensional ◽  
3D Structures ◽  
Multi Scale ◽  
3D Space ◽  
Slender Bodies ◽  
Self Similar

Abstract The Magic Snake (Rubik’s Snake) is a toy that was invented decades ago. It draws much less attention than Rubik’s Cube, which was invented by the same professor, Erno Rubik. The number of configurations of a Magic Snake, determined by the number of discrete rotations about the elementary wedges in a typical snake, is far less than the possible configurations of a typical cube. However, a cube has only a single three-dimensional (3D) structure while the number of sterically allowed 3D conformations of the snake is unknown. Here, we demonstrate how to represent a Magic Snake as a one-dimensional (1D) sequence that can be converted into a 3D structure. We then provide two strategies for designing Magic Snakes to have specified 3D structures. The first enables the folding of a Magic Snake onto any 3D space curve. The second introduces the idea of “embedding” to expand an existing Magic Snake into a longer, more complex, self-similar Magic Snake. Collectively, these ideas allow us to rapidly list and then compute all possible 3D conformations of a Magic Snake. They also form the basis for multidimensional, multi-scale representations of chain-like structures and other slender bodies including certain types of robots, polymers, proteins, and DNA.

scholarly journals ProfKin: A Comprehensive Web Server for Structure-based Kinase Selectivity Profiling

2020 ◽  
Author(s):  
Zihao Shen ◽  
Yu-Hang Yan ◽  
Shuo Yang ◽  
Sang Zhu ◽  
Yuan Yuan ◽  
...  
Keyword(s):  
Binding Site ◽  
Drug Targets ◽  
Kinase Inhibitor ◽  
3D Structure ◽  
Web Server ◽  
Binding Modes ◽  
Ligand Complex ◽  
Site Type ◽  
Ligand Type ◽  
Inhibitor Selectivity

Abstract Protein kinases are central mediators of signal-transduction cascades and attractive drug targets for therapeutic intervention. Since kinases are structurally and mechanistically related to each other, kinase inhibitor selectivity is often investigated by kinase profiling and considered as an important index for drug discovery. We here describe a versatile web server termed ProfKin for structure-based kinase selectivity profiling, which is based on a kinase-ligand focused database (KinLigDB). It provides all ready-to-use 3D structure coordinates of 4,219 kinase-ligand complex structures covering 297 human kinases and the associated information, particularly including binding site type, binding ligand type, interaction fingerprints, downstream molecules and related human diseases. The web server works via predicting possible binding modes for the query molecule, prioritizing the binding modes guided by an interaction fingerprint analysis method, and giving a list of ranked kinases by a comprehensive index. Users can freely select entire or part of the KinLigDB database, e.g. via subfamily and binding site type, to customize the profiling contents. The superimpositions of the predicted binding poses of the query molecule with reference binding modes can be visually inspected on the website. For each top-ranked kinase, the additional classification attributes and the phylogenetic tree are given simultaneously.

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