Aims: The surplus use of herbicide Dalapon® contains 2,2-dichloropropionic acid (2,2-DCP) poses great danger to human and ecosystem due to its toxicity. Hence, this study focused on the isolation and characterization of a dehalogenase producing bacteria from Sungai Skudai, Johor, capable of utilizing 2,2-DCP as a carbon source and in silico analysis of its putative dehalogenase. Methodology and results: Isolation of the target bacteria was done by using 2,2-DCP-enriched culture as the sole carbon source that allows a bacterium to grow in 20 mM of 2,2-DCP at 30 °C with the corresponding doubling time of 8.89 ± 0.03 h. The isolated bacterium was then designated as Klebsiella pneumoniae strain YZ based on biochemical tests and basic morphological examination. The full genome of K. pneumoniae strain KLPN_25 (accession number: RRE04903) which obtained from NCBI database was screened for the presence of dehalogenase gene, assuming both strains YZ and KLPN_25 were the same organisms. A putative dehalogenase gene was then identified as type II dehalogenase from the genome sequence of strain KLPN_25. The protein structure of the type II dehalogenase of KLPN_25 strain was then pairwise aligned with the crystal structure of L-2-haloacid dehalogenase (L-DEX) Pseudomonas sp. strain YL as the template, revealing the existence of conserved amino acids residues, uniquely known to participate in the dehalogenation mechanism. The finding thus implies that the amino acid residues of type II dehalogenase possibly shares similar catalytic functions with the L-DEX. Conclusion, significance and impact of the study In conclusion, this study confirmed the presence of new dehalogenase from the genus Klebsiella with potential to degrade 2,2-DCP from the river water. The structural information of type II dehalogenase provides insights for future work in designing haloacid dehalogenases.
Klebsiella pneumoniae--isolation & ; purification ; Computer Simulation ; Molecular Dynamics Simulation

More effective production of human insulin is important, because insulin is the main medication that is used to treat multiple types of diabetes and because many people are suffering from diabetes. The current system of insulin production is based on recombinant DNA technology, and the expression vector is composed of a preproinsulin sequence that is a fused form of an artificial leader peptide and the native proinsulin. It has been reported that the sequence of the leader peptide affects the production of insulin. To analyze how the leader peptide affects the maturation of insulin structurally, we adapted several in silico simulations using 13 artificial proinsulin sequences. Three-dimensional structures of models were predicted and compared. Although their sequences had few differences, the predicted structures were somewhat different. The structures were refined by molecular dynamics simulation, and the energy of each model was estimated. Then, protein-protein docking between the models and trypsin was carried out to compare how efficiently the protease could access the cleavage sites of the proinsulin models. The results showed some concordance with experimental results that have been reported; so, we expect our analysis will be used to predict the optimized sequence of artificial proinsulin for more effective production.
Computer Simulation ; DNA, Recombinant ; Humans* ; Insulin ; Molecular Dynamics Simulation* ; Proinsulin ; Protein Sorting Signals ; Trypsin

The disease tuberculosis, caused by Mycobacterium tuberculosis (MTB), remains a major cause of morbidity and mortality in developing countries. The evolution of drug-resistant tuberculosis causes a foremost threat to global health. Most drug-resistant MTB clinical strains are showing resistance to isoniazid and rifampicin (RIF), the frontline anti-tuberculosis drugs. Mutation in rpoB, the beta subunit of DNA-directed RNA polymerase of MTB, is reported to be a major cause of RIF resistance. Amongst mutations in the well-defined 81-base-pair central region of the rpoB gene, mutation at codon 450 (S450L) and 445 (H445Y) is mainly associated with RIF resistance. In this study, we modeled two resistant mutants of rpoB (S450L and H445Y) using Modeller9v10 and performed a docking analysis with RIF using AutoDock4.2 and compared the docking results of these mutants with the wild-type rpoB. The docking results revealed that RIF more effectively inhibited the wild-type rpoB with low binding energy than rpoB mutants. The rpoB mutants interacted with RIF with positive binding energy, revealing the incapableness of RIF inhibition and thus showing resistance. Subsequently, this was verified by molecular dynamics simulations. This in silico evidence may help us understand RIF resistance in rpoB mutant strains.
Codon ; Computer Simulation ; Developing Countries ; DNA-Directed RNA Polymerases ; Drug Resistance ; Isoniazid ; Molecular Dynamics Simulation ; Mortality ; Mycobacterium tuberculosis ; Rifampin* ; Tuberculosis* ; Tuberculosis, Multidrug-Resistant

OBJECTIVE: To study the binding target of photosensitizer and bacteria in antimicrobial photodynamic therapy with computer-simulated target prediction and molecular docking research methods and to calculate the binding energy. METHODS: The protein names of Porphyromonas gingivalis (Pg) were obtained and summarized in Uniprot database and RCSB PDB database; the structure diagrams of methy-lene blue were screened in SciFinder database, PubChem database, ChemSpider database, and Chemical Book, and ChemBioDraw software was used to draw and confirm the three-dimensional structure for target prediction and Cytoscape software was used to build a visual network diagram; a protein interaction network was searched and built between the methylene blue target and the common target of Pg in the String database; then we selected FimA, Mfa4, RgpB, and Kgp K1 proteins, used AutoDock software to calculate the docking energy of methylene blue and the above-mentioned proteins and performed molecular docking. RESULTS: The target prediction results showed that there were 19 common targets between the 268 potential targets of methylene blue and 1 865 Pg proteins. The 19 targets were: groS, radA, rplA, dps, fabH, pyrG, thyA, panC, RHO, frdA, ileS, bioA, def, ddl, TPR, murA, lepB, cobT, and gyrB. The results of the molecular docking showed that methylene blue could bind to 9 sites of FimA protein, with a binding energy of -6.26 kcal/mol; with 4 sites of Mfa4 protein and hydrogen bond formation site GLU47, and the binding energy of -5.91 kcal/mol, the binding energy of LYS80, the hydrogen bond forming site of RgpB protein, was -5.14 kcal/mol, and the binding energy of 6 sites of Kgp K1 protein and the hydrogen bond forming site GLY1114 of -5.07 kcal/mol. CONCLUSION Computer simulation of target prediction and molecular docking technology can initially reveal the binding, degree of binding and binding sites of methylene blue and Pg proteins. This method provides a reference for future research on the screening of binding sites of photosensitizers to cells and bacteria.
Computer Simulation ; Methylene Blue ; Molecular Docking Simulation ; Photosensitizing Agents ; Porphyromonas gingivalis

Objectives: This study aims to assess the drug-likeness and binding of nucleobase-substituted ponatinib analogues towards wild-type and T315I mutant BCR-ABL tyrosine kinases. Methodology: A total of 415 ponatinib analogues, encompassing single and combinatorial modifications on five parts of the drug were generated, profiled in SwissADME, and subjected to molecular docking using AutoDock4. Complexes formed by the top analogues then underwent a 100-ns molecular dynamics simulation with GROMACS. Results: Analogues featuring the replacement of the imidazo[1,2b]pyridazine with adenine and cytosine exhibited promising binding free energies, attributed to the presence of primary amines that facilitate crucial hydrogen bond interactions in the hinge region. RMSD, RMSF, and atomic distance analyses of the MD trajectories revealed that the six top analogues formed stable complexes in their inactive DFG-out conformations. Changes in the MMPBSA and MMGBSA-calculated free energies were mainly driven by changes in hydrogen bonds. Furthermore, drug-likeness predictions supported the formulation of most analogues for oral administration. Conclusion Among the top analogues, VP10004 and VP81014 exhibited the most favorable binding free energies and interactions with the target models, while VP10312 was identified as the most feasible candidate for synthesis.
Hydrogen Bonding ; Molecular Dynamics Simulation ; Molecular Docking Simulation

Small molecules with physiological or pharmacological activities need to interact with biological macromolecules in order to function in the body. As the protein with the highest proportion of plasma protein,serum albumin is the main protein binding to various endogenous or exogenous small molecules. Serum albumin interacts with small molecules in a reversible non-covalent manner and transports small molecules to target sites. Bovine serum albumin( BSA) is an ideal target protein for drug research because of its low cost and high homology with human serum albumin. The research on the interaction between drugs and BSA has become a hotspot in the fields of pharmacy,medicine,biology and chemistry. In this research,molecular docking method was used to study the interaction between three small ginsenosides with high pharmacological value( Rg_1,Rb_1,Ro) and bovine serum albumin( BSA),and the binding mode information of three ginsenosides interacting with BSA was obtained. The results of molecular docking showed that ginsenosides and amino acid residues in the active pocket of proteins could be combined by hydrophobic action,hydrogen bonding and electrostatic action. The interaction between small ginsenosides and bovine serum albumin is not the only form,and their interaction has many forms of force. The interaction between these molecules and various weak forces is the key factor for the stability of the complex. The results of this study can provide the structural information of computer simulation for the determination of the interaction patterns between active components and proteins of ginseng.
Animals ; Binding Sites ; Cattle ; Computer Simulation ; Ginsenosides ; chemistry ; Molecular Docking Simulation ; Protein Binding ; Serum Albumin, Bovine ; chemistry ; Spectrometry, Fluorescence ; Thermodynamics

OBJECTIVE: To seek potential Chinese herbal medicine (CHM) for the treatment of coronavirus disease 2019 (COVID-19) through the molecular docking of the medicine with SARS-CoV-2 3CL hydrolytic enzyme and the angiotensin converting enzyme II(ACE2) as receptors, using computer virtual screening technique, so as to provide a basis for combination forecasting. METHODS: The molecular docking of CHM with the SARS-Cov-2 3CL hydrolase and the ACE2 converting enzyme, which were taken as the targets, was achieved by the Autodock Vina software. The CHM monomers acting on 3CLpro and ACE2 receptors were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, the active ingredients were selected, and the key CHMs and compounds were speculated. Based on the perspective of network pharmacology, the chemical-target network was constructed, and the functional enrichment analysis of gene ontology and the pathway enrichment analysis of Kyoto encyclopedia of genes and genomes were carried out by DAVID to speculate about the mechanism of action of the core drug pairs. RESULTS: There are 6 small molecule compounds that have the optimal binding energy with the two target proteins. Among 238 potential anti-COVID-19 herbs screened in total, 16 kinds of CHM containing the most active ingredients, and 5 candidate anti-COVID-19 herbs that had been used in high frequency, as well as a core drug pair, namely, Forsythiae Fructus-Lonicerae Japonicae Flos were selected. CONCLUSION The core drug pair of Forsythiae Fructus-Lonicerae Japonicae Flos containing multiple components and targets is easy to combine with 3CLpro and ACE2, and exerts an anti-COVID-19 pneumonia effect through multi-component and multi-target, and plays the role of anti-COVID-19 pneumonia in multi-pathway.
Betacoronavirus ; metabolism ; Computer Simulation ; Coronavirus Infections ; drug therapy ; Drugs, Chinese Herbal ; therapeutic use ; Gene Ontology ; Humans ; Molecular Docking Simulation ; Pandemics ; Peptidyl-Dipeptidase A ; metabolism ; Pneumonia, Viral ; drug therapy ; Thermodynamics

In this tutorial, we introduce a differential equation simulation model for use in pharmacometrics involving NONMEM, Berkeley Madonna, and R. We report components of the simulation code and similarities/differences between software, rather than how to use each software. Depending on the purpose of the simulation, an appropriate tool can be selected for effective communication.
Computer Simulation ; Software

OBJECTIVE: To study some thermal problems in invasive microwave coagulation (IMC) therapy. METHODS: Temperature fields predicts, limitation and remedy methods of the Pennes bioheat transfer equation during the temperature distribution analyses and how to kill a large anomalistic tumor for only once were discussed. RESULTS: The coagulation area between the simulations and actual measured results showed good correspondence. Blood flow influenced the rise in temperature significantly. CONCLUSIONS: Thermal distribution with computer simulation in invasive microwave coagulation therapy is an accurate and reliable method.
Computer Simulation ; Microwaves*

No abstract available.
Computer Simulation* ; Orthognathic Surgery*