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An Efficient Protein Structure Prediction Using Genetic Algorithm
Published in Abdel-Badeeh M. Salem, Innovative Smart Healthcare and Bio-Medical Systems, 2020
Mohamad Yousef, Tamer Abdelkader, Khaled El-Bahnasy
Formerly written in FORTRAN 90 and then re-implemented using Python, MODELLER runs on UNIX, windows, and MAC computers via scripts written in the Python. It does not provide any graphical user interface. MODELLER is a software used for creating homologous protein structure models for proteins that does not have experimentally determined three-dimensional (3D) structures yet. It utilizes the satisfaction of spatial restraints method assisted by nuclear magnetic resonance (NMR) spectroscopy data. Using the NMR data, a set of geometrical measures are used to produce probability density functions for each atom’s location in the protein [3, 4].
An object-oriented approach to modelling health care
Published in Peter Edwards, Stephen Jones, Dennis Shale, Mark Thursz, Shared Care, 2018
Peter Edwards, Stephen Jones, Dennis Shale, Mark Thursz
A common model is achieved through exclusion of fine detail and abstraction of critical concepts from all areas of the relevant domain. The process of abstraction has a drawback in that it takes the model a step further away from the real world that it strives to represent. In the model described below, in which the objective is to represent the entire domain of clinical care, there is inevitably a high degree of abstraction which means that some concepts, such as diagnosis, are not immediately perceived by the casual observer. In developing such a model there are two opposing pressures on the modellers: the need to represent all areas of the clinical domain demands a high level of abstractionthe need for the model to be comprehensible without extensive tuition demands a low level of abstraction.
Computational characterization and integrative analysis of proteins involved in spermatogenesis
Published in C. Yan Cheng, Spermatogenesis, 2018
Pranitha Jenardhanan, Manivel Panneerselvam, Premendu P. Mathur
With the identification of differentially expressed genes/proteins, it becomes necessary to understand their biological significance. Application of bioinformatics finds its place in this step, where several integrated bioinformatics tools are employed. The basic understanding of biological significance aims at understanding different aspects of gene products such as their cellular location, functional classification, structural classification, and analysis of their domain, structures, relationship to biological pathways, and diseases. Several integrated bioinformatics tools like the Database for Annotation, Visualization and Integrated Discovery (DAVID), gene ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) are being used for this purpose. DAVID tool performs gene-list-based annotations15,16 that takes gene list as the input and identifies data related to gene ontology17 and metabolic pathway analysis from KEGG.18 With identification of protein targets it becomes essential to understand their interaction partners, which can be achieved using web-based protein-protein interaction databases such as String.19 Later, structural analysis of predicted targets is achieved by three-dimensional structure prediction of proteins by the MODELLER suite20 and the Rosetta suite.21 With analysis of individual protein structures it becomes essential to understand how selected protein interacts with its targets using protein-protein docking software such as HADDOCK22 and protein-ligand docking such as Schrodinger Glide.23 Finally, the conformational changes induced by complex formation are evaluated using molecular dynamics simulation studies that use software such as the Gromacs suite.24
In vitro and in silico studies on clinically important enzymes inhibitory activities of flavonoids isolated from Euphorbia pulcherrima
Published in Annals of Medicine, 2022
Abdur Rauf, Muslim Raza, Muhammad Humayun Khan, Hassan A. Hemeg, Yahya S. Al-Awthan, Omar Bahattab, Sami Bawazeer, Saima Naz, Faika Basoglu, Muhammad Saleem, Majid Khan, Hosseini Seyyedamirhossein, Mohammad S. Mubarak, Ilkay Erdogan Orhan
Tyrosinase, PDB ID: 2Y9W, protein structures (urease, PDB ID: 4GY7, PDB ID:3VO3) and bovine serum albumin were downloaded from (PDB) protein data bank. The targeted sequence for the other enzymes, phosphodiesterase-I (PDE-1 from snake venom) was retrieved from the UniPort database [14], with the accession number of J3SEZ3. BLAST against PBD found the optimal template [15]. The optimal template was selected based on sequence similar to the PDE-1 enzyme structure from Mus musculus (PDB ID: 4GTW). With the help of Bio edit software and MODELLER 9.12, target template sequence alignment and 3-D model creation were completed. [16]. Swiss PDB viewer v4.1.0 software was employed to refine the projected models’ energy [17]. Similarly, ProSA 27 [18] and Procheck online servers [19] were used to assess the models, and the best predicted model was chosen for future docking investigations. The Swisspdb viewer v4.1.0 software was used to optimize the crystal structure’s geometry [20]. Chem sketch [21] and Avogadro’s program [22] were used to construct compounds 1 and 2 as well as standard structures for docking. We employed Autodockvina [23] to conduct docking experiments, and technique improvements of the docking software were done first, and Autodockvina [24] was linked with PyRex tools. Removal of solvent molecules, hydrogen addition, and computation of gasteiger charges were all completed [25]. Autodockvina was used to dock with all of the default settings [26,27]. LIGPLOT + version v.1.4.5 [28] and PyMOL version 1.7.2 [29] were employed to perform interaction studies on docked complexes.
Identification of novel cis-mutations in the GJA8 gene in a 3-generation Iranian family with autosomal dominant congenital nuclear cataract
Published in Ophthalmic Genetics, 2022
Neda Jabbarpour, Hassan Saei, Mohammad Hossein Jabbarpoor Bonyadi, Mortaza Bonyadi
To assess the impact of the identified mutations on the GJA8 protein dynamic and stability, the DynaMut tool was used (14). This tool implements the Normal Mode Analysis (NMA) computational method to produce potential movements of the conformation, providing vital insights on protein motions and their available conformational repertoires. Furthermore, DynaMut quickly investigates the impact of mutations on a protein’s dynamics and stability caused by changes in vibrational entropy. The integration of these two methods in this tool enables an accurate assessment of the mutation impact on protein. ELASPIC tool, an ensemble machine learning approach, was also utilized to compare predictions in the protein level (15). ELASPIC employs Modeller to build homology models of domains and domain–domain interactions (16). It also uses FoldX to optimize those models and introduce mutations.
A structure-based approach towards the identification of novel antichagasic compounds: Trypanosoma cruzi carbonic anhydrase inhibitors
Published in Journal of Enzyme Inhibition and Medicinal Chemistry, 2020
Manuel A. Llanos, María L. Sbaraglini, María L. Villalba, María D. Ruiz, Carolina Carrillo, Catalina Alba Soto, Alan Talevi, Andrea Angeli, Seppo Parkkila, Claudiu T. Supuran, Luciana Gavernet
TcCA has been recently cloned and characterised by Pan et al.24 As mentioned before, the three His residues coordinating the Zinc ion are conserved in the active site of TcCA, with the fourth coordination position occupied by a water molecule (or by a hydroxide ion, depending on the pH). Like human CA II, TcCA exerts a high catalytic activity, and the gatekeeping residues Glu106 and Thr199 are well conserved8–12. However, the proton shuttle His64 is absent in TcCA isoform. Despite several CA structures of many organisms have been crystallised so far, there is not a good template to perform a comparative modelling of TcCA. There are 924 structures of CAs deposited in the Protein Data Bank (PDB)75, but all of them have sequence identities lower than 30% with TcCA. In this situation, the combination of multiple templates generally increases the quality of the resultant model, but only when the correct templates are combined since there is a trade-off between the number of sequences included and the noise introduced in the restraints. One possible approach to address this challenge was recently proposed by Meier et al.31 and used in this investigation. They introduced a modification in the MODELLER algorithm, using probability theory to combine the density functions of individual template restraints76.