Advances and Applications in Bioinformatics and Chemistry最新文献

Introduction: Amorphous drug dispersion is frequently used to enhance the solubility and dissolution of poorly water-soluble drugs, thereby improving their oral bioavailability. The dispersion of these drugs into polymer matrix can inhibit their recrystallization. The inter-molecular interactions between drug and polymer plays a role in the improvement of the dissolution rate, solubility, and physical stability of drug.

Aim: This study aims to investigate the formation and interactions of ritonavir (RTV)/poloxamer (PLX) amorphous formulation using a computational approach via molecular dynamics (MD) simulations, which mimicked solvent evaporation and melt-quenching method.

Methods: TheRoot Mean Square Deviation (RMSD) value, Root Mean Square Fluctuation (RMSF), Radial Distribution Function (RDF), Radius of Gyration (Rg), Solvent Accessible Surface Area (SASA), and hydrogen bond interactions were analyzed to determine interaction mechanisms between RTV and PLX in amorphous solid dispersion.

Results: The pi-alkyl bonds between RTV and PLX were formed after simulations of solvent evaporation, while the hydrogen bond interactions of RTV-PLX was observed during melt method simulations. These results indicate the successful formulation of amorphous solid dispersion (ASD) from RTV and PLX. The RMSD values obtained from the solvent evaporation, melt-cooling-A, melt-cooling-B, and melt-cooling-C methods were 3.33 Å, 1.97 Å, 1.30 Å, and 1.29 Å, respectively, while the average RMSF values were 2.65 Å, 1.04 Å, 1.05 Å, and 1.07 Å, respectively. This indicates that the suppression of translational motion of RTV from the melt method can be stronger than solvent evaporation caused by the intermolecular interactions of RTV-PLX.

Conclusion: MD simulations helped in understanding the formation and interaction mechanisms of ASD formulations that were difficult to detect by experimental approaches.

Background: Cyphostemma cyphopetalum is a medicinal plant traditionally used to treat various ailments. Limited studies on C. cyphopetalum inspired us to investigate the chemical nature and therapeutic potential of the plant.

Methods: Silica gel column chromatographic separation was used for isolation. 1D and 2D NMR spectroscopic analysis and literature data were used for structural elucidation. Agar well diffusion assay was used for evaluation of antibacterial activity against E. coli, P. aeruginosa, and S. aureus. DPPH assay was used to evaluate radical scavenging activities. Molecular docking was done by AutoDock Vina 4.2 open-source program. DFT calculations were performed using the Gaussian 16 program package.

Results: Dichloromethane/methanol (1:1) roots extract afforded a new hydroxyl-spongiane diterpenoid lactone derivative, 3-hydroxyisoagatholactone (1), along with β-sitosterol (2) and ε-viniferin (3) whereas methanol extract afforded trans-resveratrol (4), gnetin H (5), tricuspidatol A (6), ε-viniferin-diol (7) and parthenostilbenin B (8). At 50 μg/mL, compound 3 recorded the highest inhibition against E. coli (8.55 ± 0.45 mm) and S. aureus (9.30 ±1.39 mm). Against P. aeruginosa, compound 5 consistently outperformed chloramphenicol (11.76 ± 0.77 mm, at 30 g/mL). Maximum binding affinity were observed by compound 3 against DNA gyrase B (-7.6 kcal/mol) where as compound 5 displayed maximum binding against PqsA (-8.8 kcal/mol) and S. aureus PK (-5.8 kcal/mol). Compounds 1, 3 and 4 satisfy Lipinski's rule of five. Trans-resveratrol (4) demonstrated strong DPPH scavenging activity at 12.5 g/mL, with IC₅₀ values of 0.052 µg/mL, compared to ascorbic acid (IC₅₀ value of 0.0012 µg/mL).

Conclusion: In this work, eight compounds were identified from the roots extracts of C. cyphopetalum including a new hydroxyl-spongiane diterpenoid lactone, 3-hydroxyisoagatholactone (1). Compounds 3 and 5 exhibited good antibacterial activity and binding affinities. The docking result is in agreement with the in vitro antibacterial study. Overall, the study result suggests that the isolated compounds have the potential to be used as therapeutic agents, which supports the traditional uses of C. cyphpetalum roots.

Background: Since the last COVID-19 outbreak, several approaches have been given a try to quickly tackle this global calamity. One of the well-established strategies is the drug repurposing, which consists in finding new therapeutic uses for approved drugs. Following the same paradigm, we report in the present study, an investigation of the potential inhibitory activity of 5-FU and nineteen of its analogues against the SARS-CoV-2 main protease (3CLpro).

Material and methods: Molecular docking calculations were performed to investigate the binding affinity of the ligands within the active site of 3CLpro. The best binding candidates were further considered for molecular dynamics simulations for 100 ns to gain a time-resolved understanding of the behavior of the guest-host complexes. Furthermore, the profile of druggability of the best binding ligands was assessed based on ADMET predictions. Finally, their chemical reactivity was elucidated using different reactivity descriptors, namely the molecular electrostatic potential (MEP), Fukui functions and frontier molecular orbitals.

Results and discussion: From the calculations performed, four candidates (compounds 14, 15, 16 and 18) show promising results with respect to the binding affinity to the target protease, 3CLpro, the therapeutic profile of druggability and safety. These compounds are maintained inside the active site of 3CLpro thanks to a variety of noncovalent interactions, especially hydrogen bonds, involving important amino acids such as GLU166, HIS163, GLY143, ASN142, HIS172, CYS145. Molecular dynamics simulations suggest that the four ligands are well trapped within the active site of the protein over a time gap of 100 ns, ligand 18 being the most retained.

Conclusion: In line with the findings reported herein, we recommend that further in-vitro and in-vivo investigations are carried out to shed light on the possible mechanism of pharmacological action of the proposed ligands.

Background: A prophylactic and immunotherapeutic vaccine for Mycobacterium tuberculosis (MTB) and SARS-CoV-2 coinfection needs to be developed for a proactive and effective therapeutic approach. Therefore, this study aims to use immunoinformatics to design a multi-epitope vaccine for protection against MTB and SARS-CoV-2 coinfection.

Methods: The bioinformatic techniques were used to screen and construct potential epitopes from outer membrane protein A Rv0899 of MTB and spike glycoprotein of SARS-CoV-2 for B and T cells. The antigenicity, allergenicity, and several physiochemical properties of the developed multi-epitope vaccination were then evaluated. Additionally, molecular docking and normal mode analysis (NMA) were utilized in evaluating the vaccine's immunogenicity and complex stability.

Results: Selected proteins and predicted epitopes suggest that the vaccine prediction can be helpful in the protection against both SARS-CoV-2 and MTB coinfection. Through docking molecular and NMA, the vaccine-TLR4 protein interaction was predicted to be efficient with a high level of IgG, T-helper cells, T-cytotoxic cells, andIFN-γ.

Conclusion: This epitope-based vaccine is a potentially attractive tool for SARS-CoV-2 and MTB coinfection vaccine development.

Background: Schistosomiasis is the world's second most devastating disease after malaria and the leading cause of disease and mortality for more than 200 million people in developing countries. Cysteine proteases, in particular SmCB1, are the most well-researched biological targets for this disorder.

Objective: To apply computational techniques to design new antischistosomal agents against SmCB1 protein with favorable pharmacokinetic properties.

Methods: The smCB1 receptor-based pharmacophore model was created and used to screen 567,000 fragments from the Enamine library. The best scoring fragments have been linked to build novel compounds that were subjected to molecular docking, MM-GBSA free energy estimation, ADME prediction, and molecular dynamics.

Results: A seven-point pharmacophore hypothesis ADDDRRR was created. The developed hypothesis was used to screen 1.3 M fragment conformations. Among them, 23,732 fragments matched the hypothesis and screened against the protein. The top 50 fragments were used to design new 7745 compounds using the Breed ligand panel which were subjected to docking and MMGBSA binding energy. This led to the identification of 10 compounds with better docking scores (-8.033- -7.483 kcal/mol) and lower-bound free energies (-58.49 - -40.02 kcal/mol) compared to the reference bound ligand. Most of the designed compounds demonstrated good drug-like properties. Concerning Molecular dynamics (MD) simulation results, a low root mean square deviation (RMSD) range (0.25-1.2 Å) was found for the top 3 complexes which indicated their stability.

Conclusion: We identified compounds that could be potential candidates in the search for novel Schistosoma mansoni inhibitors by targeting SmCB1 utilizing various computational tools. Three newly designed compounds namely breed 1, 2, and 3 showed promising affinity to the target as well as favorable drug-like properties which might be considered potential anti-schistosomal agents.

Purpose: Spike protein on SARS-CoV-2 virus plays an integral part during infection as cell entry depends on binding of this protein to human ACE2 receptor. Understanding of infectivity by these variants necessitates a comparative structural analysis of complexes of spike protein-receptor binding domain (RBD) of these variants to receptor.

Methodology: Wild type SARS-CoV-2 spike protein sequence was retrieved from the UniProt database, and mutations of five variants at receptor binding domain were manually incorporated and aligned using Clustal Omega. Crystal structure complexes of human ACE2 receptor with spike protein RBD domain of SARS-CoV-2 variants of wild type, α, β, and δ were extracted from the RCSB database. Wild type SARS-CoV-2 complex with receptor was used as template to generate model complexes of receptor with spike protein RBD of γ and omicron variants through WinCoot program. These were energy minimized and validated and molecular dynamic simulation was performed using Desmond simulation program.

Results: Mutations are distributed across the entire length of RBD, but the maximum number of mutations are seen at 11 positions within binding interface motifs of six variant sequences. Interface of spike protein RBDs with human ACE2-receptor shows different mix of hydrogen bonded and ionic interactions. Alpha and β variants have few interactions, while γ and δ variants have higher number of interactions compared to wild type variant. Omicron variant, with 10 polar interactions including two ionic bonds, has the highest binding energy.

Conclusion: Different mutations on RBD of spike protein results in varying quantity and quality of interactions, thereby affecting potency of each variant. Variations in binding are due to interactions of mutant residues and induced conformational changes on loops of RBDs. Variants α and β have a low potency, while, γ, δ, and omicron have a higher potency. These results correlate with viral infectivity and place clinical observations in the right perspective.

Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes at an atomistic level, which provides valuable understandings of the mechanisms of biomolecular recognition. However, the rather slow biomolecular binding events often present challenges for conventional MD (cMD), due to limited simulation timescales (typically over hundreds of nanoseconds to tens of microseconds). In this regard, enhanced sampling methods, particularly accelerated MD (aMD), have proven useful to bridge the gap and enable all-atom simulations of biomolecular binding events. Here, we will review the recent method developments of Gaussian aMD (GaMD), ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD), which have greatly expanded our capabilities to simulate biomolecular binding processes. Spontaneous binding of various biomolecules to their receptors has been successfully simulated by GaMD. Microsecond LiGaMD and Pep-GaMD simulations have captured repetitive binding and dissociation of small-molecule ligands and highly flexible peptides, and thus enabled ligand/peptide binding thermodynamics and kinetics calculations. We will also present relevant application studies in simulations of important drug targets and future perspectives for rational computer-aided drug design.

Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.

Shwachman-Bodian-Diamond syndrome (SBDS) is linked to a mutation in a single gene. The SBDS proinvolved in RNA metabolism and ribosome-associated functions, but SBDS mutation is primarily linked to a defect in polymorphonuclear leukocytes unable to orient correctly in a spatial gradient of chemoattractants. Results of data mining and comparative genomic approaches undertaken in this study suggest that SBDS protein is also linked to tRNA metabolism and translation initiation. Analysis of crosstalk between translation machinery and cytoskeletal dynamics provides new insights into the cellular chemotactic defects caused by SBDS protein malfunction. The proposed functional interactions provide a new approach to exploit potential targets in the treatment and monitoring of this disease.