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Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro).

Polysaccharide monooxygenases (PMOs) use a type-2 copper center to activate O

SARS-CoV-2 rapidly infects millions of people worldwide since December 2019. There is still no effective treatment for the virus, resulting in the death of more than one million of patients. Inhibiting the activity of SARS-CoV-2 main protease (Mpro), 3C-like protease (3CLP), is able to block the viral replication and proliferation. Although the dimer was shown to be the biologically active form of the SARS-CoV-2 Mpro, in this context, our study has revealed that in silico screening for inhibitors of SARS-CoV-2 Mpro can be reliably done using the monomeric structure of the receptor. Docking and fast pulling of ligand (FPL) simulations for both monomeric and dimeric forms correlate well with the corresponding experimental binding affinity data of 30 compounds. In particular, the correlation coefficients between computational and experimental binding free energy of the monomeric SARS-CoV-2 Mpro are approximately similar to the dimeric target. Moreover, the correlation coefficient between the rupture forces to binding free energy are roughly the same. Furthermore, the correlation coefficient between calculated metrics of the monomeric and dimeric SARS-CoV-2 Mpro is R = 0.74. Our study results show that it is possible to speed up computer-aided drug design for SARS-CoV-2 Mpro by focusing on the monomeric form instead of the larger dimeric one.

Inhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of

AutoDock Vina (Vina) achieved a very high docking-success rate, p ̂, but give a rather low correlation coefficient, R, for binding affinity with respect to experiments. This low correlation can be an obstacle for ranking of ligand-binding affinity, which is the main objective of docking simulations. In this context, we evaluated the dependence of Vina R coefficient upon its empirical parameters. R is affected more by changing the gauss2 and rotation than other terms. The docking-success rate p ̂ is sensitive to the alterations of the gauss1, gauss2, repulsion, and hydrogen bond parameters. Based on our benchmarks, parameter set1 has been suggested to be the most optimal. The testing study over 800 complexes indicated that the modified Vina provided higher correlation with experiment R_set1=0.556±0.025 compared with R_Default=0.493±0.028 obtained by the original Vina and R_(Vina 1.2)=0.503±0.029 by Vina version 1.2. Besides, the modified Vina can be also applied more widely, giving R≥0.500 for 32/48 targets, compared with the default package, giving R≥0.500 for 31/48 targets. In addition, validation calculations for 1036 complexes obtained from version 2019 of PDBbind refined structures showed that the set1 of parameters gave higher correlation coefficient (R_set1=0.621±0.016) than the default package (R_Default=0.552±0.018) and Vina version 1.2 (R_(Vina 1.2)=0.549±0.017). The version of Vina with set1 of parameters can be downloaded at https://github.com/sontungngo/mvina. The outcomes would enhance the ranking of ligand-binding affinity using Autodock Vina.

Amyloid β (Aβ) peptides are considered the major causative agents of Alzheimer's disease (AD). In a widely accepted mechanism for AD pathogenesis, Aβ peptides are proposed to play multiple roles in damaging brain cells and their synaptic communications. Due to the heterogeneous nature of Aβ oligomers, their in vivo structures have not been understood. Most experimental and computational studies favored β-rich structures of Aβ as observed in Aβ fibrils. In this in silico study, we investigated an alternative perspective on the structures and function of Aβ oligomers in the cell membrane. Transmembrane α-helix bundles of the Aβ17-42 tetramer and trimer were observed in extensive temperature replica exchange molecular dynamics (REMD) simulations. We observed three minima on the free-energy landscape of each oligomer, namely, A, B, and C for the tetramer and D, E, and F for the trimer. Except for F, the minima consist of 4 or 3 parallel helices spanning across the membrane model dipalmitoylphosphatidylcholine. Replica exchange molecular dynamics-umbrella sampling (REMD-US) simulation was applied to study the process of a Ca2+ crossing the pore formed by the α-helix bundles in A-E in comparison to that in a calcium channel and a proton channel. REMD-US reveals that A, C, and D allow Ca2+ to cross their pore with a free-energy barrier comparable to that found for the calcium channel. In contrast, the free-energy barrier of a Ca2+ ion crossing B, E, and the proton channel is significantly higher. This result suggests that Aβ peptide oligomers could form transmembrane α-helix bundles that provide feasible pathways for Ca2+ transport. This is an intriguing observation that will stimulate further studies.

According to the previous benchmark, Autodock Vina (Vina) achieved a very high successful-docking rate, p ̂, but give a rather a low correlation coefficient, R, for binding affinity with respect to experiment. This low correlation can be an obstacle for ranking of ligand-binding affinity, which is a main objective of docking simulations. The accuracy of Vina likely depends on the empirical parameters, which include the Gaussian steric interaction, repulsion, hydrophobic, hydrogen bond, and rotation metrics. In this context, we evaluated the dependence of Vina accuracy upon empirical parameters. Although changing of six parameters alters the obtained R values, the gauss2 and rotation terms form more effects. The p ̂ terms are sensitive to the alterations of the gauss1, gauss2, repulsion, and hydrogen bond parameters. Therefore, three sets of empirical parameters were proposed as well as more to modestly focus on R (set1), modestly focus on p ̂ (set3), and keep a tradeoff between R and p ̂. The testing study over 800 complexes indicated that the Vina with proposed sets of parameters can provide more accurate results since forming the larger R value (R_set1=0.556±0.025) compared with the original one (R_Default=0.493±0.028) and Vina version 1.2 (R_(Vina 1.2)=0.503±0.029). Besides, the testing study over 48 biological targets indicated that the modified Vina can be applied more widely compared with the default package. These newly proposed parameters achieved a higher correlation coefficient and reasonable correlation coefficients (R>0.500) for at least 32 targets, whereas the default parameters provided by the original Vina gave only 31 targets with at least 0.500 correlation. In addition, validation calculations for 1315 complexes obtained from the version 2019 of PDBbind refined structures suggested that set1 of parameters are more appropriate than the other parameters (R_set1=0.621±0.016) compared with the default package (R_Default=0.552±0.018) and Vina version 1.2 (R_(Vina 1.2)=0.549±0.017). The version of Vina with set1 of parameters can be downloaded at https://github.com/sontungngo/mvina. The outcomes probably enhance the ranking of ligand-binding affinity using Autodock Vina.

By 2030, global rice production will need to increase to meet the demand of the growing world population. However, rice is severely affected by blast disease caused by the fungus Pyricularia oryzae, which accounts for 10–30% yield losses per year globally, thus posing a threat to the world’s most important food crop. The fungus can infect all parts of the rice plant, including leaves, nodes and panicles. In the early stages of the infection process, P. oryzae forms an infection structure called appressorium to break the plant cuticle. After an initial biotrophic phase, the fungus kills plant cells thus leading to visible symptoms. Currently, several methods for the management of rice blast disease, such as agronomic practices, use of resistant cultivars and synthetic fungicides, are available and can be exploited in an integrated management approach. However, despite some resistant rice varieties that have been developed by breeding programs, P. oryzae is able to rapidly develop new races that overcome resistance genes. Furthermore, the continuous use of fungicides may be harmful to humans and environment and can increase the risk of appearance of resistant fungal races. Biological control using microbial agents or plant extracts with antimicrobial activity is therefore considered a possible alternative and sustainable approach to control rice blast disease. However, biological protection is difficult to achieve in the field as its effectiveness is variable, highly depending on formulations and climatic conditions. Because of these drawbacks, durable control of rice blast still represents a substantial challenge. Innovative strategies for the identification of new molecules for the sustainable protection of rice are thus highly desirable.

The main protease (Mpro) of the novel coronavirus SARS-CoV-2, which causes the COVID-19 pandemic, is responsible for the maturation of its key proteins. Thus, inhibiting SARS-CoV-2 Mpro could prevent SARS-CoV-2 from multiplying. Because new inhibitors require thorough validation, repurposing current drugs could help reduce the validation process. Many recent studies used molecular docking to screen large databases for potential inhibitors of SARS-CoV-2 Mpro. However, molecular docking does not consider molecular dynamics and thus can be prone to error. In this work, we developed a protocol using free energy perturbation (FEP) to assess the potential inhibitors of SARS-CoV-2 Mpro. We first tested both molecular docking and FEP on a set of 11 inhibitors of SARS-CoV-2 Mpro with experimentally determined inhibitory data. The experimentally deduced binding free energy exhibits significantly stronger correlation with that predicted by FEP (R = 0.94 ± 0.04) than with that predicted by molecular docking (R = 0.82 ± 0.08). This result clearly shows that FEP is the most accurate method available to estimate the binding affinity of a ligand to SARS-CoV-2 Mpro. We subsequently used FEP to validate the top 33 compounds screened with molecular docking from the ZINC15 database. Thirteen of these compounds were predicted to have strong binding affinity for SARS-CoV-2 Mpro, most of which are currently used as drugs for various diseases in humans. Notably, delamanid, an anti-tuberculosis drug, was predicted to inhibit SARS-CoV-2 Mpro in the nanomolar range. Because both COVID-19 and tuberculosis are lung diseases, delamanid has higher probability to be suitable for treating COVID-19 than other predicted compounds. Analysis of the interactions between SARS-CoV-2 Mpro and the top inhibitors revealed the key residues involved in the binding, including the catalytic dyad His14 and Cys145, which is consistent with the structural studies reported recently.

African swine fever (ASF) is a highly infectious viral disease with high mortality. The most recent ASF outbreak in Vietnam began in 2019, posing a threat to spread to the neighbouring Asian countries. Without a commercial vaccine or efficient chemotherapeutics, rapid diagnosis and necessary biosecurity procedures are required to control the disease. While the diagnostic method of ASF recommended by the World Organization of Animal Health is real-time PCR, the ideal diagnosis procedure including master mix setup, template extraction and a high-cost qPCR equipment for many samples being tested simultaneously is not portable. In this study, a colorimetric loop-mediated isothermal amplification (LAMP) assay was modified and evaluated for ASF virus detection using crude serum samples collected from domestic pigs in Vietnam during the 2019 outbreak. The LAMP results can be readily visualized to the naked eye within 30 min without the requirement of DNA extraction and sophisticated equipment. The sensitivity, specificity and limit of detection of direct colorimetric LAMP assay were comparable to a commercial diagnostic real-time PCR kit. Results strongly indicate that the adapted colorimetric LAMP assay has a remarkable potential for the in-field diagnosis of ASF.

The main protease (Mpro) of the novel coronavirus SARS-CoV-2, which has caused the COVID-19 pandemic, is responsible for the maturation of its key proteins. Thus, inhibiting SARS-CoV-2 Mpro could prevent SARS-CoV-2 from multiplying. Because new inhibitors require thorough validation, repurposing current drugs could help reduce the validation process. Many recent studies used molecular docking to screen large databases for potential inhibitors of SARS-CoV-2 Mpro. However, molecular docking does not consider molecular dynamics and thus can be prone to error. In this work, we developed a protocol using free energy perturbation (FEP) to assess the potential inhibitors of SARS-CoV-2 Mpro. First, we validated both molecular docking and FEP on a set of 11 inhibitors of SARS-CoV-2 Mpro with experimentally determined inhibitory data. The experimentally deduced binding free energy exhibits significantly stronger correlation with that predicted by FEP (R = 0.94 ± 0.04) than with that predicted by molecular docking (R = 0.82 ± 0.08). This result clearly shows that FEP is the most accurate method available to predict the binding affinity of SARS-CoV-2 Mpro + ligand complexes. We subsequently used FEP to validate the top 33 compounds screened with molecular docking from the ZINC15 database. Thirteen of these compounds were predicted to bind strongly to SARS-CoV-2 Mpro, most of which are currently used as drugs for various diseases in humans. Notably, delamanid, an anti-tuberculosis drug, was predicted to inhibit SARS-CoV-2 Mpro in the nanomolar range. Because both COVID-19 and tuberculosis are lung diseases, delamanid has higher probability to be suitable for treating COVID-19 than other predicted compounds. Analysis of the complexes of SARS-CoV-2 Mpro and the top inhibitors revealed the key residues involved in the binding, including the catalytic dyad His14 and Cys145, which is consistent with the structural studies reported recently.

Originating for the first time in Wuhan, China, the outbreak of SARS-CoV-2 has caused a serious global health issue. An effective treatment for SARS-CoV-2 is still unavailable. Therefore, in this study, we have tried to predict a list of potential inhibitors for SARS-CoV-2 main protease (Mpro) using a combination of molecular docking and fast pulling of ligand (FPL) simulations. The approaches were initially validated over a set of eleven available inhibitors. Both Autodock Vina and FPL calculations produced consistent results with the experiments with correlation coefficients of RDock = 0.72 ± 0.14 and RW = −0.76 ± 0.10, respectively. The combined approaches were then utilized to predict possible inhibitors that were selected from a ZINC15 sub-database for SARS-CoV-2 Mpro. Twenty compounds were suggested to be able to bind well to SARS-CoV-2 Mpro. Among them, five top-leads are periandrin V, penimocycline, cis-p-Coumaroylcorosolic acid, glycyrrhizin, and uralsaponin B. The obtained results could probably lead to enhance the COVID-19 therapy.

African Swine Fever (ASF) is a highly infectious viral disease with high mortality. The most recent ASF outbreak in Vietnam occurred in 2019, posing a threat to spread to the neighboring Asian countries. Without a commercial vaccine or efficient chemotherapeutics successfully developed, rapid diagnosis and necessary biosecurity procedures are required to control the disease. While the diagnosis method of ASF recommended by the World Organization of Animal Health is real-time PCR, it is not suitable for in-field detection of the disease. In this study, a colorimetric Loop-Mediated Isothermal Amplification (LAMP) assay was developed and evaluated for ASF virus detection using crude serum samples collected from domestic pigs in Vietnam during the 2019 outbreak. The LAMP results can be readily visualized to naked eyes within 30 minutes without the requirement of DNA extraction and sophisticated equipment. The sensitivity, specificity, and limit of detection of colorimetric LAMP assay were comparable to a commercial diagnostic real-time PCR kit. Results strongly indicate that the developed colorimetric LAMP assay is highly recommended for the in-field diagnosis of ASF.

The COVID-19, caused by the novel coronavirus SARS-CoV-2, has broken out of control all over the globe and put the majority of the world under lockdown. There have been no specific antiviral medications for SARS-CoV-2 while vaccines are still under development. Thus, rapid diagnosis and necessary public health measures are currently key parts to contain the pandemic. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is the gold standard method for SARS-CoV-2 detection. However, this method is not suitable for point-of-care (POC) diagnosis because of the timeconsuming procedure, the requirements of biosafety conditions and expensive equipment. In this study, the colorimetric isothermal nucleic acid amplification tests (iNAATs) for SARS-CoV-2 based on loop-mediated isothermal amplification (LAMP), cross-priming amplification (CPA), and polymerase spiral reaction (PSR) were developed and compared. The three methods exhibited similar performance with the limit of detection (LOD) as low as just 1 copy per reaction when evaluated on the synthetic DNA fragments. The results can be read with naked eyes within 30 minutes without crossreactivity to closely related coronaviruses. When tested with SARS-CoV-2 extracted genomic-RNA, LAMP outperformed both CPA and PSR assays. Moreover, the direct detection of SARS-CoV-2 in simulated patient samples (oropharyngeal and nasopharyngeal swabs) by colorimetric iNAATs was also successful. Further preparation of the lyophilized reagents for LAMP reactions revealed that the freeze-dried, ready-to-use kit maintained the sensitivity and LOD value of the liquid assays. These results strongly indicate that the colorimetric lyophilized LAMP test kit developed herein is highly suitable for detecting SARS-CoV-2 at POC.

The search for efficient inhibitors targeting Aβ oligomers and fibrils is an important issue in Alzheimer's disease treatment. As a consequence, an accurate and computationally cheap approach to estimate the binding affinity for many ligands interacting with Aβ peptides is very important. Here, the calculated binding free energies of 30 ligands interacting with 12Aβ11–40 peptides using the linear interaction energy (LIE) approach are found to be in good correlation with experimental data (R = 0.79). The binding affinities of these complexes are also calculated by using free energy perturbation (FEP) and molecular mechanic/Poisson–Boltzmann surface area (MM/PBSA) methods. The time-consuming FEP method provides results with similar correlation (R = 0.72), whereas MM/PBSA calculations show very low correlation with experimental data (R = 0.27). In all complexes, van der Waals interactions contribute much more than electrostatic interactions. The LIE model, which is much less time-consuming than both the FEP and MM/PBSA methods, opens the door to accurate and rapid affinity prediction of ligands with Aβ peptides and the design of new ligands.

There is experimental evidence that the astaxanthin, betanin, and epigallocatechin-3-gallate (EGCG) compounds slow down the aggregation kinetics and the toxicity of the amyloid-β (Aβ) peptide. How these inhibitors affect the self-assembly at the atomic level remains elusive. To address this issue, we have performed for each ligand atomistic replica exchange molecular dynamic (REMD) simulations in an explicit solvent of the Aβ11-40 trimer from the U-shape conformation and MD simulations starting from Aβ1-40 dimer and tetramer structures characterized by different intra- and interpeptide conformations. We find that the three ligands have similar binding free energies on small Aβ40 oligomers but very distinct transient binding sites that will affect the aggregation of larger assemblies and fibril elongation of the Aβ40 peptide.

There is experimental evidence that the astaxanthin, betanin, and epigallocatechin-3-gallate (EGCG) compounds slow down the aggregation kinetics and the toxicity of the amyloid-β (Aβ) peptide. How these inhibitors affect the self-assembly at the atomic level remains elusive. To address this issue, we have performed for each ligand atomistic replica exchange molecular dynamic (REMD) simulations in an explicit solvent of the Aβ

Ten conjugated polymers (polypyrrole, polyfuran, polythiophene, polyborole, polycyclopentadiene, polysilole, polyphosphole, polycyclopentadienethione, polycyclopentadieneone, poly(p-phenylene)) have been investigated using density functional theory (DFT) and semi-empirical method. BP86-30% HF hybrid functional with CEP-31G* basis set combined with the quadratic regression provides bandgaps of polymers that are consistent with their optical experiment bandgaps. The higher contribution of quinoid character in polymer results in lower bandgap, and this observation is supported by shorter carbon – carbon bondlength of inter-rings of polymer with prefered quinoid character. The averaged crystal orbital overlap population (COOP) between carbon – carbon of inter-rings shows that polymer with higher orbital overlap population leads to lower bandgap. The resonance energies of polymers calculated using natural bond orbital method (NBO) show two opposite observations: very low bandgap polymer (≤0.19 eV) has highest resonance energy; however, with polymer having bandgap larger than 1 eV, higher resonance energy results in higher bandgap. This observation is due to the fact that resonance energy may be associated with electron delocalization over entire polymer backbone or within the rings. Band structures of polymers typically present direct bandgap at gamma point, and lower bandgap polymers do not essentially show higher carrier mobility.

X-ray absorption spectroscopy (XAS) was utilized to gain insights into the structure and electronic properties of the reduced copper active site in NCU08746, a polysaccharide monooxygenase (PMO) from Neurospora crassa that activates O2 to cleave glycosidic linkages in starch. The reaction of NCU08746 likely starts with binding of O2 to the copper(I) center. However, the solution structure of the reduced active site in NCU08746 has not been properly elucidated. In this study, we prepared Cu(I)-NCU08746 in solution, which was snap-frozen to preserve the solution structure of the copper(I) active site prior to XAS analysis. Results show that the copper(I) center in Cu(I)-NCU08746 exhibits a 4-coordinate geometry, which is different from the 3-coordinate geometry observed for some other PMOs. This difference likely arises from the coordination of the active site tyrosine residue and could contribute to the difference in activity between NCU08746 and other PMOs.

The increasing demand for the next generation of renewable fuels has driven extensive research in carbohydrate-active enzymes involved in converting plant biomass to fermentable sugars. Standing out of new enzymes discovered recently are polysaccharide monooxygenases (PMOs) that activate O2 with a Type 2 mono copper active site for the regioselective hydroxylation of the glycosidc linkages. This hydroxylation leads to the cleavage of glycosidic linkage on the substrate surfaces, creating new chain ends on the substrate surface that can be further processed by canonical glycoside hydrolases. PMOs can thus significantly boost the activity of industrial cellulases and have great potentials in the biofuel industry. Extensive research in the last 8 years have shed lights into the nature of the copper active site and how it activates O2. While other aspects of PMOs have been thoroughly discussed in recent outstanding reviews, the coordination chemistry aspects of the copper active site have not been reviewed in details. This article will provide in-depth analysis of the copper active site and surrounding residues, including structure, electronic and spectroscopic properties, copper-binding affinity, redox properties, modulation of geometry and activity by second-sphere residues, substrate binding affinity, O2 intermediates, and initial mechanistic insights, as well as some relevant model complexes. This review will also identify some key areas that need further work and predict the trend in PMOs research in the coming years.

Acetylcholinesterase (AChE) is considered as one of the most favored drug targets for Alzheimer’s disease. The effects of different force fields (FFs) on ranking affinity of acetylcholinesterase inhibitors were obtained using the fast pulling of ligand (FPL) method in steered-molecular dynamics (SMD) simulations. GROMOS, AMBER, CHARMM, and OPLS-AA FFs were investigated in this work. The pulling work derived with GROMOS FF has the strongest correlation and smallest error compared with experimental binding affinity. Moreover, the CPU consumption in the calculations using GROMOS FF is the lowest, which could allow us to rank affinity of a large number of AChE ligands.

Correction for ‘Rapid prediction of possible inhibitors for SARS-CoV-2 main protease using docking and FPL simulations’ by Minh Quan Pham et al., RSC Adv., 2020, 10, 31991–31996, https://doi.org/10.1039/D0RA06212J.

The self-assembly of Amyloid beta (Aβ) peptides are widely accepted to associate with Alzheimer's disease (AD) via several proposed mechanisms. Because Aβ oligomers exist in a complicated environment consisting of various forms of Aβ, including oligomers, protofibrils, and fibrils, their structure has not been well understood. The negatively charged residue D23 is one of the critical residues of the Aβ peptide as it is located in the central hydrophobic domain of the Aβ N-terminal and forms a salt-bridge D23-K28, which helps stabilize the loop domain. In the familial Iowa (D23N) mutant, the total net charge of Aβ oligomers decreases, resulting in the decrease of electrostatic repulsion between D23N Aβ monomers and thus the increase in their self-aggregation rate. In this work, the impact of the D23N mutation on 3Aβ11–40 trimer was characterized utilizing temperature replica exchange molecular dynamics (REMD) simulations. Our simulation reveals that D23N mutation significantly enhances the affinity between the constituting chains in the trimer, increases the β-content (especially in the sequence 21–23), and shifts the β-strand hydrophobic core from crossing arrangement to parallel arrangement, which is consistent with the increase in self-aggregation rate. Molecular docking indicates that the Aβ fibril-binding ligands bind to the D23N and WT forms at different poses. These compounds prefer to bind to the N-terminal β-strand of the D23N mutant trimer, while they mostly bind to the N-terminal loop region of the WT. It is important to take into account the difference in the binding of ligands to mutant and wild type Aβ peptides in designing efficient inhibitors for various types of AD.

The fast pulling of ligand (FPL) method, which evaluates the relative ligand-protein binding affinity with low CPU usage and high accuracy, was applied for the first time to determine the affinity of β-secretase 1 (BACE1) and its inhibitors using steered-molecular dynamics simulations. The total non-bonded interaction energy difference Δ E total is a highly appropriate criterion to predict the relative BACE1-inhibitor binding affinity with strong correlation to experimental data ( R = 0.92 ) and small deviation ( δ E total = 7 % ). The van der Waals interaction and electrostatic interaction contribute 56% and 44% to the total non-bonded interaction energy between BACE1 and its inhibitors.

Type 2 copper active sites, one of the several important copper active sites in biology, were recently found in the novel superfamily of polysaccharide monooxygenases (PMOs) that cleave recalcitrant polysaccharides via an unprecedented oxidative mechanism. The copper center in PMOs is ligated by the bidentate N-terminal histidine residue and another conserved histidine residue, forming a unique T-shaped core termed as

The binding pose and affinity between a ligand and enzyme are very important pieces of information for computer-aided drug design. In the initial stage of a drug discovery project, this information is often obtained by using molecular docking methods. Autodock4 and Autodock Vina are two commonly used open-source and free software tools to perform this task, and each has been cited more than 6000 times in the last ten years. It is of great interest to compare the success rate of the two docking software programs for a large and diverse set of protein-ligand complexes. In this study, we selected 800 protein-ligand complexes for which both PDB structures and experimental binding affinity are available. Docking calculations were performed for these complexes using both Autodock4 and Autodock Vina with different docking options related to computing resource consumption and accuracy. Our calculation results are in good agreement with a previous study that the Vina approach converges much faster than AD4 one. However, interestingly, AD4 shows a better performance than Vina over 21 considered targets, whereas the Vina protocol is better than the AD4 package for 10 other targets. There are 16 complexes for which both the AD4 and Vina protocols fail to produce a reasonable correlation with respected experiments so both are not suitable to use to estimate binding free energies for these cases. In addition, the best docking option for performing the AD4 approach is the long option. However, the short option is the best solution for carrying out Vina docking. The obtained results probably will be useful for future docking studies in deciding which program to use.

Polymer contamination is a major pollutant in all waterways and a significant concern of the 21st Century, gaining extensive research, media, and public attention. The polymer pollution problem is so vast; plastics are now observed in some of the Earth's most remote regions such as the Mariana trench. These polymers enter the waterways, migrate, breakdown; albeit slowly, and then interact with the environment and the surrounding biodiversity. It is these biodiversity and ecosystem interactions that are causing the most nervousness, where health researchers have demonstrated that plastics have entered the human food chain, also showing that plastics are damaging organisms, animals, and plants. Many researchers have focused on reviewing the macro and micro-forms of these polymer contaminants, demonstrating a lack of scientific data and also a lack of investigation regarding nano-sized polymers. It is these nano-polymers that have the greatest potential to cause the most harm to our oceans, waterways, and wildlife. This review has been especially ruthless in discussing nano-sized polymers, their ability to interact with organisms, and the potential for these nano-polymers to cause environmental damage in the marine environment. This review details the breakdown of macro-, micro-, and nano-polymer contamination, examining the sources, the interactions, and the fates of all of these polymer sizes in the environment. The main focus of this review is to perform a comprehensive examination of the literature of the interaction of nanoplastics with organisms, soils, and waters; followed by the discussion of toxicological issues. A significant focus of the review is also on current analytical characterisation techniques for nanoplastics, which will enable researchers to develop protocols for nanopolymer analysis and enhance understanding of nanoplastics in the marine environment.

Determination of the ligand-binding affinity is an extremely interesting problem. Normally, the free energy perturbation (FEP) method provides an appropriate result. However, it is of great interest to improve the accuracy and precision of this method. In this context, temperature replica exchange molecular dynamics implementation of the FEP computational approach, which we call replica exchange free energy perturbation (REP) was proposed. In particular, during REP simulations, the system can easily escape from being trapped in local minima by exchanging configurations with high temperatures, resulting in significant improvement in the accuracy and precision of protein-ligand binding affinity calculations. The distribution of the decoupling free energy was enlarged, and its mean values were decreased. This results in changes in the magnitude of the calculated binding free energies as well as in alteration in the binding mechanism. Moreover, the REP correlation coefficient with respect to experiment ( RREP = 0.85 ± 0.15) is significantly boosted in comparison with the FEP one ( RFEP = 0.64 ± 0.30). Furthermore, the root-mean-square error (RMSE) of REP is also smaller than FEP, RMSEREP = 4.28 ± 0.69 versus RMSEFEP = 5.80 ± 1.11 kcal/mol, respectively. © 2019 Wiley Periodicals, Inc.

Degradation of polysaccharides is central to numerous biological and industrial processes. Starch-active polysaccharide monooxygenases (AA13 PMOs) oxidatively degrade starch and can potentially be used with industrial amylases to convert starch into a fermentable carbohydrate. The oxidative activities of the starch-active PMOs from the fungi Neurospora crassa and Myceliophthora thermophila, NcAA13 and MtAA13, respectively, on three different starch substrates are reported here. Using high-performance anion-exchange chromatography coupled with pulsed amperometry detection, we observed that both enzymes have significantly higher oxidative activity on amylose than on amylopectin and cornstarch. Analysis of the product distribution revealed that NcAA13 and MtAA13 more frequently oxidize glycosidic linkages separated by multiples of a helical turn consisting of six glucose units on the same amylose helix. Docking studies identified important residues that are involved in amylose binding and suggest that the shallow groove that spans the active-site surface of AA13 PMOs favors the binding of helical amylose substrates over nonhelical substrates. Truncations of NcAA13 that removed its native carbohydrate-binding module resulted in diminished binding to amylose, but truncated NcAA13 still favored amylose oxidation over other starch substrates. These findings establish that AA13 PMOs preferentially bind and oxidize the helical starch substrate amylose. Moreover, the product distributions of these two enzymes suggest a unique interaction with starch substrates.

CBM20s are starch-binding domains found in many amylolytic enzymes, including glucoamylase, alpha-amylase, beta-amylases, and a new family of starch-active polysaccharide monooxygenases (AA13 PMOs). Previous studies of CBM20–substrate interaction only concerned relatively small or soluble amylose molecules, while amylolytic enzymes often work on extended chains of insoluble starch molecules. In this study, we utilized molecular simulation techniques to gain further insights into the interaction of CBM20 with substrates of various sizes via its two separate binding sites, termed as BdS1 and BdS2. Results show that substrate binding at BdS1 involving two conserved tryptophan residues is about 2–4 kcal mol−1 stronger than that at BdS2. CBM20 exhibits about two-fold higher affinity for helical substrates than for the amylose random coils. The affinity for amylose individual double helices does not depend on the helices' length. At least three parallel double helices are required for optimal binding. The binding affinity for a substrate containing 3 or more double helices is ∼−15 kcal mol−1, which is 2–3 kcal mol−1 larger than that for individual double helices. 100 ns molecular dynamics simulations were carried out for the binding of CBM20 to an extended substrate containing 3 layers of 9 60-unit double helices (A3L). A stable conformation of CBM20–A3L was found at BdS1. However, when CBM20 binds A3L via BdS2, it moves across the surface of the substrate and does not form a stable complex. MD simulations show that small amylose helices are quickly disrupted upon binding to CBM20. Our results provide some important molecular insights into the interactions of CBM20 with starch substrates, which will serve as the basis for further studies of CBM20-containing enzymes, including AA13 PMOs.

Alzheimer's disease (AD) is associated with the oligomerization and/or fibrillation of amyloid beta (Aβ) peptides, which cause damage to brain cells. Aβ oligomers and fibrils contain hydrophobic cores formed with parallel beta sheets. Mutations of F19, a residue in the hydrophobic core of Aβ peptides, slow down their aggregation process but do not alter the overall structure of the resulting fibrils. However, the effects of F19 mutations on the toxic Aβ oligomers have not been elucidated. We studied the F19W mutant of the 11–40 truncated Aβ trimer (F19W 3Aβ11–40) using replica exchange molecular dynamics (REMD) simulations. While most structural terms do not change significantly, critical polar contacts decrease by 20%, and notably, RMSD almost doubles upon F19W mutation. Six minima were found in the free energy surface of F19W 3Aβ11–40, which have lower energy barriers (by ∼1 kJ mol−1) and significantly lower total population (∼20%) compared to those of the three minima found for 3Aβ11–40 (∼60%). The binding free energy between constituting chains of the mutant trimer increases by ∼28 kcal mol−1 but fluctuates significantly (±27.1 kcal mol−1). Our results indicate that while the hydrophobic core of amyloid beta peptide is capable of adapting to structural changes, F19W mutation results in a significantly more flexible trimer. The more flexible F19W mutant oligomers would require more time to self-assemble into fibrils. Our results contribute to a better understanding of the behavior of Aβ peptides and their oligomerization/aggregation process, which is necessary to understand AD pathogenesis.

The fabrication techniques of hydrophobic and superhydrophobic surfaces have received attention from many researchers. In this study, the change of water contact angle of the glass surface modified with chlorosilane or trichlorosilane compound was investigated. The microscope glass with water contact angle of 88° and 107° were obtained by treating with trimethylchlorosilane (TMCS) and octadecyltrichlorosilane (OTS), respectively. The chemical resistance of hydrophobic layer was evaluated by immersing the treated samples into an acidic or a basic solution. The result showed that OTS bonded to the glass surface more strongly than TMCS. The superhydrophobic state with the highest contact angle of 154° (sliding angle 17°) could be achieved with the glass microfiber filter by using OTS. The similar phenomenon could not be observed with TMCS because the TMCS-treated glass filter remained completely wetted with all investigated concentrations. The hydrophobic layer on the glass slides was strongly affected by abrasive force while the contact angle value of more than 154° was detected in the treated glass filter after 50 cycles of abrasion test on a sandpaper. The scanning electron microscope (SEM) images had revealed the aggregation of the OTS molecules on the glass filter surface. The chemically-treated filter performed both superhydrophobic and superoleophilic properties. The OTS coating showed strong resistance to the organic solvent. Separation of mixture n-hexane and water was successfully demonstrated using the modified filter.

The purpose of our study is to theoretically calculate the HOMO – LUMO gaps and aromaticity indices (HOMA, PDI, FLU, MCBO, PLR, Shannon, and NICS) for graphene quantum dot molecule and its seventeen derivatives. The correlation between the HOMO – LUMO gap and each aromaticity index was established for the core and petal rings. The linear correlation coefficient for the petal ring is: NICS(1) (0.7181) > PLR (0.6910) > PDI (0.6740) > FLU (0.6098) > MCBO (0.5294) > HOMA (0.3846) > Shannon (0.1498); and that for the core ring is: Shannon (0.4846) > MCBO (0.3765) > PLR (0.3334) > PDI (0.2647) > FLU (0.2356) > NICS (1) (0.2072) > HOMA (0.0529). All calculated aromaticity indices show that the petal ring is more aromatic than the core ring. A better correlation between the HOMO – LUMO gap and the energetic or electronic delocalization criterion than the structural criterion was observed for the investigated molecules.

Polysaccharide monooxygenases (PMOs), also known as lytic PMOs (LPMOs), enhance the depolymerization of recalcitrant polysaccharides by hydrolytic enzymes and are found in the majority of cellulolytic fungi and actinomycete bacteria. For more than a decade, PMOs were incorrectly annotated as family 61 glycoside hydrolases (GH61s) or family 33 carbohydrate-binding modules (CBM33s). PMOs have an unusual surface-exposed active site with a tightly bound Cu(II) ion that catalyzes the regioselective hydroxylation of crystalline cellulose, leading to glycosidic bond cleavage. The genomes of some cellulolytic fungi contain more than 20 genes encoding cellulose-active PMOs, suggesting a diversity of biological activities. PMOs show great promise in reducing the cost of conversion of lignocellulosic biomass to fermentable sugars; however, many questions remain about their reaction mechanism and biological function. This review addresses, in depth, the structural and mechanistic aspects of oxidative depolymerization of cellulose by PMOs and considers their biological function and phylogenetic diversity.

Oligomerization of amyloid beta (Aβ) peptides has been considered as the crucially causative agent in the development of Alzheimer's disease. Etersalate, a nonsteroidal anti-inflammatory oral drug (United State Food and Drug Administration-Unique Ingredient Identifier: 653GN04T2G) was previously suggested to bind well to proto-fibrils of Aβ peptides in silico. Here, the effect of etersalate on the oligomerization of soluble Aβ16-22 hexamer (6Aβ16-22) were extensively investigated using temperature replica exchange molecular dynamics (REMD) simulations over ~16.8 μs in total for 48 replicas (350 ns per replica). The results reveal that etersalate can enter the inner space or bind on the surface of 6Aβ16-22 conformations, which destabilizes the hexamer. Etersalate was predicted to able to cross the blood brain barrier using prediction of absorption, distribution, metabolism, and excretion-toxicity (preADMET) tools. Overall, although the investigation was performed with the low concentration of trial inhibitor, the obtained results indicate that etersalate is a potential drug candidate for AD through inhibiting formation of Aβ oligomers with the average binding free energy of -11.7 kcal/mol.