Targeting SARS-CoV-2 Nsp12/Nsp8 interaction interface with approved and investigational drugs: anin silicostructure-based approach

In this study, the Nsp12-Nsp8 complex of SARS-CoV-2 was targeted with structure-based and computer-aided drug design approach because of its vital role in viral replication. Sequence analysis of RNA-dependent RNA polymerase (Nsp12) sequences from 30,366 different isolates were analysed for possible mutations. FDA-approved and investigational drugs were screened for interaction with both mutant and wild-type Nsp12-Nsp8 interfaces. Sequence analysis revealed that 70.42% of Nsp12 sequences showed conserved P323L mutation, located in the Nsp8 binding cleft. Compounds were screened for interface interaction, any with XP GScores lower than -7.0 kcal/mol were considered as possible interface inhibitors. RX-3117 (fluorocyclopentenyl cytosine) and Nebivolol had the highest binding affinities in both mutant and wild-type enzymes, therefore they were selected and resultant protein-ligand complexes were simulated for analysis of stability over 100 ns. Although the selected ligands had partial mobility in the binding cavity, they were not removed from the binding pocket after 100 ns. The ligand RX-3117 remained in the same position in the binding pocket of the mutant and wild-type enzyme after 100 ns MD simulation. However, the ligand Nebivolol folded and embedded in the binding pocket of mutant Nsp12 protein. Overall, FDA-approved and investigational drugs are able to bind to the Nsp12-Nsp8 interaction interface and prevent the formation of the Nsp12-Nsp8 complex. Interruption of viral replication by drugs proposed in this study should be further tested to pave the way forin vivostudies towards the treatment of COVID-19

Evaluation of the potency of FDA-approved drugs on wild type and mutant SARS-CoV-2 helicase (Nsp13)

SARS-CoV-2 has caused COVID-19 outbreak with nearly 2 M infected people and over 100K death worldwide, until middle of April 2020. There is no confirmed drug for the treatment of COVID-19 yet. As the disease spread fast and threaten human life, repositioning of FDA approved drugs may provide fast options for treatment. In this aspect, structure-based drug design could be applied as a powerful approach in distinguishing the viral drug target regions from the host. Evaluation of variations in SARS-CoV-2 genome may ease finding specific drug targets in the viral genome. In this study, 3458 SARS-CoV-2 genome sequences isolated from all around the world were analyzed. Incidence of C17747T and A17858G mutations were observed to be much higher than others and they were on Nsp13, a vital enzyme of SARS-CoV-2. Effect of these mutations was evaluated on protein-drug interactions using in silico methods. The most potent drugs were found to interact with the key and neighbor residues of the active site responsible from ATP hydrolysis. As result, cangrelor, fludarabine, folic acid and polydatin were determined to be the most potent drugs which have potency to inhibit both the wild type and mutant SARS-CoV-2 helicase. Clinical data supporting these findings would be important towards overcoming COVID-19

Targeting SARS-CoV-2 Nsp12/Nsp8 interactioninterface with approved and investigational drugs:an in silico structure-based approach

In this study, the Nsp12–Nsp8 complex of SARS-CoV-2 was targeted with structure-based and com-puter-aided drug design approach because of its vital role in viral replication. Sequence analysis ofRNA-dependent RNA polymerase (Nsp12) sequences from 30,366 different isolates were analysed forpossible mutations. FDA-approved and investigational drugs were screened for interaction with bothmutant and wild-type Nsp12–Nsp8 interfaces. Sequence analysis revealed that 70.42% of Nsp12sequences showed conserved P323L mutation, located in the Nsp8 binding cleft. Compounds werescreened for interface interaction, any with XP GScores lower than 7.0kcal/mol were considered aspossible interface inhibitors. RX-3117 (fluorocyclopentenyl cytosine) and Nebivolol had the highestbinding affinities in both mutant and wild-type enzymes, therefore they were selected and resultantprotein–ligand complexes were simulated for analysis of stability over 100ns. Although the selectedligands had partial mobility in the binding cavity, they were not removed from the binding pocketafter 100ns. The ligand RX-3117 remained in the same position in the binding pocket of the mutantand wild-type enzyme after 100ns MD simulation. However, the ligand Nebivolol folded andembedded in the binding pocket of mutant Nsp12 protein. Overall, FDA-approved and investigationaldrugs are able to bind to the Nsp12–Nsp8 interaction interface and prevent the formation of theNsp12–Nsp8 complex. Interruption of viral replication by drugs proposed in this study should be fur-ther tested to pave the way forin vivostudies towards the treatment of COVID-19

The Use of Total Artificial Heart With Example of Cases for End-Stage Heart Failure Therapy

29th Turkish Cardiology Congress of the Turkish-Society-of-Cardiology (TSC) with International Participation -- OCT 26-29, 2013 -- Antalya, TURKEYWOS: 000329858400098Turkish Soc Cardio

Florid cemento osseous dysplasia and dentygerous cyst in a patient with apert syndrome: A case report

Apert syndrome is a rare congenital malformation characterized by craniocinocytosis, craniofacial anomalies and symmetric syndactyly of the feet and hands. Oral manifestations of Apert syndrome usually represents bifid uvula, malposition of the teeth, severe open bite, tooth decay and periodontal diseases. Fluorid cemento-osseous dysplasia is usually asymptomatic slow-growing non-neoplastic fibro-osseous lesions. Lesions are detected by routine radiographic examination. The aim of this case report is to present dentigerous cyst and florid cemento-osseous displasia in a patient with Apert syndrome. A 38-year-old female patient with a history of Apert syndrome referred to Marmara University, Faculty of Dentistry, Clinic of Oral and Dentomaxillofacial Radiology due to pain and swelling. On panoramic radiography, unilocular, hyperdense lesion with regular borders was observed in the anterior region of the mandible. Cone-beam computed tomography (CBCT) was performed for further examination of the lesion and perforation of buccal bone cortex was seen. Additionally, a regular monolocular hypodense lesion was observed in the anterior region of maxilla. A biopsy was performed to examine the lesion histopathologically. Histopathologic examination was performed to evaluate the lesions and the lesion in the mandible was diagnosed as cemento-osseous dysplasia. Because the lesion was multifocal, it was considered and compatible with fluoride cemento-osseous dysplasia. The lesion in the maxilla was diagnosed as dentigerous cyst on histopathologic examination. The diagnosis of fluoride cemento-osseous dysplasia is established by definite radiological and histopathological evaluation. In asymptomatic cases of fluorid cemento-osseous dysplasia, treatment is not required but patients should be followed up regularly. Practitioners should take into consideration the oral and dental findings in patients with Apert syndrome which rarely appear.KEYWORDS Apert Syndrome, florid cementoosseous dysplasia, dentigerous cys

Active shrinkage protects neurons following axonal transection

Trauma, vascular events, or neurodegenerative processes can lead to axonal injury and eventual transection (axotomy). Neurons can survive axotomy, yet the underlying mechanisms are not fully understood. Excessive water entry into injured neurons poses a particular risk due to swelling and subsequent death. Using in vitro and in vivo neurotrauma model systems based on laser transection and surgical nerve cut, we demonstrated that axotomy triggers actomyosin contraction coupled with calpain activity. As a consequence, neurons shrink acutely to force water out through aquaporin channels preventing swelling and bursting. Inhibiting shrinkage increased the probability of neuronal cell death by about 3-fold. These studies reveal a previously unrecognized cytoprotective response mechanism to neurotrauma and offer a fresh perspective on pathophysiological processes in the nervous system.Yüzüncü Yıl Universit

Solving time-dependent heat conduction problems using metaheuristic algorithms extended with a novel local search strategy

This study proposes a novel and dexterous local search scheme for improving the exploitation phase of a generic metaheuristic algorithm. The proposed local search considers a twofold probing mechanism, which takes advantage of a chaotic number generated by the hybrid chaotic map composed of Logistic map and Kent map to move around the so-far-obtained global best solutions to reach feasible candidate solutions. Also, an iterative local search scheme inspired by a variant of the differential evolution algorithm is incorporated into the proposed manipulation scheme to enhance intensification on the promising regions. The proposed scheme is included in the well-reputed metaheuristics of differential evolution, crow search, whale optimization, and sine-cosine algorithms to assess the resulting improvements made on the optimization accuracy. Forty optimization benchmark functions composed of unimodal and multimodal test problems have been solved by the local search improved and basic forms of these optimizers to identify the amelioration in terms of solution accuracy and robustness. Two different real-world constrained optimization problems have been solved by these algorithms to analyze the improvement in solution qualities maintained by the utilization of the proposed local search method. Furthermore, these mentioned optimization algorithms along with their improved forms have been applied to one-dimensional transient heat conduction problems to obtain accurate temperature distribution across the heat transfer medium. Optimization results reveal that utilizing local search enhanced metaheuristic algorithms can be considered a favorable alternative to conventional solution methods for solving transient heat conduction problems

A novel chaotic manta-ray foraging optimization algorithm for thermo-economic design optimization of an air-fin cooler

This research study aims to introduce chaos theory into the Manta Ray Foraging Optimization (MRFO) Algorithm and optimize a real-world design problem through the chaos-enhanced versions of this method. Manta Ray Foraging Optimization algorithm is a bio-inspired swarm intelligence-based metaheuristic algorithm simulating the distinctive food search behaviors of the manta rays. However, MRFO suffers from some intrinsic algorithmic inefficiencies such as slow and premature convergence and unexpected entrapment to the local optimum points in the search domain like most of the metaheuristic algorithms in the literature. Recently, random numbers generated by chaos theory have been incorporated into the metaheuristic algorithms to solve these problems. More than twenty chaotic maps are applied to the base algorithm and ten best performing methods are considered for performance evaluation on high-dimensional optimization test problems. Forty test problems comprising unimodal and multimodal functions have been solved by chaotic variants of MRFO and extensive statistical analysis is performed. Furthermore, thermo-economic design optimization of an air-fin cooler is maintained by the chaotic MRFO variants to assess their optimization capabilities over complex engineering design problems. Ten decisive design variables of an air fin cooler are optimized in terms of total annual cost rates and optimum solutions obtained by five best chaotic MRFO algorithms are compared to the preliminary design. A significant improvement is observed in the objective function values when MRFO with chaotic operators is applied to this considered thermal design problem

Improved artificial cooperative search algorithm for solving non- convex economic dispatch problems with valve-point effects

This paper presents Improved Artificial Cooperative Search (IACS) algorithm for solving economic dispatch problemsconsidering the valve point effects, ramp rate limits, transmission losses and prohibited operation zones. In order to improve the solutionquality and increase the search efficiency, a novel perturbation scheme called “Global best guided chaotic local search” is proposed andincorporated into ACS algorithm. The effectiveness of the proposed IACS algorithm has been benchmarked with twelve widely knownoptimization test problems. In order to assess the performance of the proposed algorithm on non-convex optimization problems, four casestudies related to highly nonlinear economic dispatch problems have been solved . Results retrieved from IACS algorithm have beencompared with literature approaches in terms of minimum, maximum and average generation cost values. Comparison results indicate thatIACS produces more economical power load than those of other optimizers available in the literature