In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of Mycobacterium tuberculosis

With tuberculosis still being one of leading causes of death in the world and the emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb), researchers have been seeking to find further therapeutic strategies or more specific molecular targets. PknB is one of the 11 Ser/Thr protein kinases of Mtb and is responsible for phosphorylation-mediated signaling, mainly involved in cell wall synthesis, cell division and metabolism. With the amount of structural information available and the great interest in protein kinases, PknB has become an attractive target for drug development. This work describes the optimization and application of an in silico computational protocol to find new PknB inhibitors. This multi-level computational approach combines protein–ligand docking, structure-based virtual screening, molecular dynamics simulations and free energy calculations. The optimized protocol was applied to screen a large dataset containing 129,650 molecules, obtained from the ZINC/FDA-Approved database, Mu.Ta.Lig Virtual Chemotheca and Chimiothèque Nationale. It was observed that the most promising compounds selected occupy the adenine-binding pocket in PknB, and the main interacting residues are Leu17, Val26, Tyr94 and Met155. Only one of the compounds was able to move the active site residues into an open conformation. It was also observed that the P-loop and magnesium position loops change according to the characteristics of the ligand. This protocol led to the identification of six compounds for further experimental testing while also providing additional structural information for the design of more specific and more effective derivatives.     

Identification of Flavonoids as Putative ROS-1 Kinase Inhibitors Using Pharmacophore Modeling for NSCLC Therapeutics

Non-small cell lung cancer (NSCLC) is a lethal non-immunogenic malignancy and proto-oncogene ROS-1 tyrosine kinase is one of its clinically relevant oncogenic markers. The ROS-1 inhibitor, crizotinib, demonstrated resistance due to the Gly2032Arg mutation. To curtail this resistance, researchers developed lorlatinib against the mutated kinase. In the present study, a receptor-ligand pharmacophore model exploiting the key features of lorlatinib binding with ROS-1 was exploited to identify inhibitors against the wild-type (WT) and the mutant (MT) kinase domain. The developed model was utilized to virtually screen the TimTec flavonoids database and the retrieved drug-like hits were subjected for docking with the WT and MT ROS-1 kinase. A total of 10 flavonoids displayed higher docking scores than lorlatinib. Subsequent molecular dynamics simulations of the acquired flavonoids with WT and MT ROS-1 revealed no steric clashes with the Arg2032 (MT ROS-1). The binding free energy calculations computed via molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) demonstrated one flavonoid (Hit) with better energy than lorlatinib in binding with WT and MT ROS-1. The Hit compound was observed to bind in the ROS-1 selectivity pocket comprised of residues from the β-3 sheet and DFG-motif. The identified Hit from this investigation could act as a potent WT and MT ROS-1 inhibitor.     

The Derived Components of Gnaphalium hypoleucum DC. Reduce Quorum Sensing of Chromobacterium violaceum

Gnaphalium hypoleucum DC. was first recorded in the Chinese National Pharmacopoeia “Yi Plant Medicine”. There is no detailed report on its main components’ activity in suppressing the quorum sensing activity (QS) of bacteria. Our study aimed to screen the main components in extracts of G. hypoleucum DC. in order to measure their effects on bacterial QS activity and to explore specific quorum sensing mechanisms that are affected by G. hypoleucum DC. extracts. Crude extracts of G. hypoleucum DC. contained significant amounts of two compounds shown to inhibit bacterial QS activity, namely apigenin and luteolin. Apigenin and luteolin in crude extracts of G. hypoleucum DC. showed substantial inhibition of pigment formation, biofilm production, and motility in Chromobacterium violaceum ATCC 12472 compared to the effects of other phytochemicals from G. hypoleucum DC. Apigenin and luteolin exhibited a strong QS inhibitory effect on C. violaceum, interfering with the violacein pigment biosynthesis by downregulating the vioB, vioC, and vioD genes. In the presence of signal molecules, the QS effect is prevented, and the selected compounds can still inhibit the production of the characteristic purple pigment in C. violaceum. Based on qualitative and quantitative research using genomics and bioinformatics, we concluded that apigenin and luteolin in crude extracts of G. hypoleucum DC can interfere with the generation of QS in C. violaceum by downregulating the vioB, vioC, and vioD genes. Indeed, G. hypoleucum DC. is used for the treatment of bacterial infections, and this research provides new ideas and potential alternative uses for medicinal plants.     

Identification of Mtb GlmU Uridyltransferase Domain Inhibitors by Ligand-Based and Structure-Based Drug Design Approaches

Targeting enzymes that play a role in the biosynthesis of the bacterial cell wall has long been a strategy for antibacterial discovery. In particular, the cell wall of Mycobacterium tuberculosis (Mtb) is a complex of three layers, one of which is Peptidoglycan, an essential component providing rigidity and strength. UDP-GlcNAc, a precursor for the synthesis of peptidoglycan, is formed by GlmU, a bi-functional enzyme. Inhibiting GlmU Uridyltransferase activity has been proven to be an effective anti-bacterial, but its similarity with human enzymes has been a deterrent to drug development. To develop Mtb selective hits, the Mtb GlmU substrate binding pocket was compared with structurally similar human enzymes to identify selectivity determining factors. Substrate binding pockets and conformational changes upon substrate binding were analyzed and MD simulations with substrates were performed to quantify crucial interactions to develop critical pharmacophore features. Thereafter, two strategies were applied to propose potent and selective bacterial GlmU Uridyltransferase domain inhibitors: (i) optimization of existing inhibitors, and (ii) identification by virtual screening. The binding modes of hits identified from virtual screening and ligand growing approaches were evaluated further for their ability to retain stable contacts within the pocket during 20 ns MD simulations. Hits that are predicted to be more potent than existing inhibitors and selective against human homologues could be of great interest for rejuvenating drug discovery efforts towards targeting the Mtb cell wall for antibacterial discovery.     

Insight into the Inhibitory Mechanism of Aryl Formyl Piperidine Derivatives on Monoacylglycerol Lipase through Molecular Dynamics Simulations

Monoacylglycerol lipase (MAGL) can regulate the endocannabinoid system and thus becomes a target of antidepressant drugs. In this paper, molecular docking and molecular dynamics simulations, combined with binding free energy calculation, were employed to investigate the inhibitory mechanism and binding modes of four aryl formyl piperidine derivative inhibitors with different 1-substituents to MAGL. The results showed that in the four systems, the main four regions where the enzyme bound to the inhibitor included around the head aromatic ring, the head carbonyl oxygen, the tail amide bond, and the tail benzene ring. The significant conformational changes in the more flexible lid domain of the enzyme were caused by 1-substituted group differences of inhibitors and resulted in different degrees of flipping in the tail of the inhibitor. The flipping led to a different direction of the tail amide bond and made a greater variation in its interaction with some of the charged residues in the enzyme, which further contributed to a different swing of the tail benzene ring. If the swing is large enough, it can weaken the binding strength of the head carbonyl oxygen to its nearby residues, and even the whole inhibitor with the enzyme so that the inhibition decreases.     

Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking

In molecular docking, it is challenging to develop a scoring function that is accurate to conduct high-throughput screenings. Most scoring functions implemented in popular docking software packages were developed with many approximations for computational efficiency, which sacrifices the accuracy of prediction. With advanced technology and powerful computational hardware nowadays, it is feasible to use rigorous scoring functions, such as molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) in molecular docking studies. Here, we systematically investigated the performance of MM/PBSA and MM/GBSA to identify the correct binding conformations and predict the binding free energies for 98 protein-ligand complexes. Comparison studies showed that MM/GBSA (69.4%) outperformed MM/PBSA (45.5%) and many popular scoring functions to identify the correct binding conformations. Moreover, we found that molecular dynamics simulations are necessary for some systems to identify the correct binding conformations. Based on our results, we proposed the guideline for MM/GBSA to predict the binding conformations. We then tested the performance of MM/GBSA and MM/PBSA to reproduce the binding free energies of the 98 protein-ligand complexes. The best prediction of MM/GBSA model with internal dielectric constant 2.0, produced a Spearman's correlation coefficient of 0.66, which is better than MM/PBSA (0.49) and almost all scoring functions used in molecular docking. In summary, MM/GBSA performs well for both binding pose predictions and binding free-energy estimations and is efficient to re-score the top-hit poses produced by other less-accurate scoring functions.     

A Computational Approach Applied to the Study of Potential Allosteric Inhibitors Protease NS2B/NS3 from Dengue Virus

Dengue virus (DENV) is a danger to more than 400 million people in the world, and there is no specific treatment. Thus, there is an urgent need to develop an effective method to combat this pathology. NS2B/NS3 protease is an important biological target due it being necessary for viral replication and the fact that it promotes the spread of the infection. Thus, this study aimed to design DENV NS2B/NS3pro allosteric inhibitors from a matrix compound. The search was conducted using the Swiss Similarity tool. The compounds were subjected to molecular docking calculations, molecular dynamics simulations (MD) and free energy calculations. The molecular docking results showed that two compounds, ZINC000001680989 and ZINC000001679427, were promising and performed important hydrogen interactions with the Asn152, Leu149 and Ala164 residues, showing the same interactions obtained in the literature. In the MD, the results indicated that five residues, Lys74, Leu76, Asn152, Leu149 and Ala166, contribute to the stability of the ligand at the allosteric site for all of the simulated systems. Hydrophobic, electrostatic and van der Waals interactions had significant effects on binding affinity. Physicochemical properties, lipophilicity, water solubility, pharmacokinetics, druglikeness and medicinal chemistry were evaluated for four compounds that were more promising, showed negative indices for the potential penetration of the Blood Brain Barrier and expressed high human intestinal absorption, indicating a low risk of central nervous system depression or drowsiness as the the side effects. The compound ZINC000006694490 exhibited an alert with a plausible level of toxicity for the purine base chemical moiety, indicating hepatotoxicity and chromosome damage in vivo in mouse, rat and human organisms. All of the compounds selected in this study showed a synthetic accessibility (SA) score lower than 4, suggesting the ease of new syntheses. The results corroborate with other studies in the literature, and the computational approach used here can contribute to the discovery of new and potent anti-dengue agents.     

Identification of Potential Inhibitors of MurD Enzyme of Staphylococcus aureus from a Marine Natural Product Library

Staphylococcus aureus is an opportunistic pathogen that can cause fatal bacterial infections. MurD catalyzes the formation of peptide bond between UDP-N-acetylehyl-l-alanine and d-glutamic acid, which plays an important role in the synthesis of peptidoglycan and the formation of cell wall by S. aureus. Because S. aureus is resistant to most existing antibiotics, it is necessary to develop new inhibitors. In this study, Schrodinger 11.5 Prime homology modeling was selected to prepare the protein model of MurD enzyme, and its structure was optimized. We used a virtual screening program and similarity screening to screen 47163 compounds from three marine natural product libraries to explore new inhibitors of S. aureus. ADME provides analysis of the physicochemical properties of the best performing compounds during the screening process. To determine the stability of the docking effect, a 100 ns molecular dynamics was performed to verify how tightly the compound was bound to the protein. By docking analysis and molecular dynamics analysis, both 46604 and 46608 have strong interaction with the docking pocket, have good pharmacological properties, and maintain stable conformation with the target protein, so they have a chance to become drugs for S. aureus. Through virtual screening, similarity screening, ADME study and molecular dynamics simulation, 46604 and 46608 were selected as potential drug candidates for S. aureus.     

Discovery of Potential Antiviral Compounds against Hendra Virus by Targeting Its Receptor-Binding Protein (G) Using Computational Approaches

Hendra virus (HeV) belongs to the paramyxoviridae family of viruses which is associated with the respiratory distress, neurological illness, and potential fatality of the affected individuals. So far, no competitive approved therapeutic substance is available for HeV. For that reason, the current research work was conducted to propose some novel compounds, by adopting a Computer Aided Drug Discovery approach, which could be used to combat HeV. The G attachment Glycoprotein (Ggp) of HeV was selected to achieve the primary objective of this study, as this protein makes the entry of HeV possible in the host cells. Briefly, a library of 6000 antiviral compounds was screened for potential drug-like properties, followed by the molecular docking of short-listed compounds with the Protein Data Bank (PDB) structure of Ggp. Docked complexes of top two hits, having maximum binding affinities with the active sites of Ggp, were further considered for molecular dynamic simulations of 200 ns to elucidate the results of molecular docking analysis. MD simulations and Molecular Mechanics Energies combined with the Generalized Born and Surface Area (MMGBSA) or Poisson–Boltzmann and Surface Area (MMPBSA) revealed that both docked complexes are stable in nature. Furthermore, the same methodology was used between lead compounds and HeV Ggp in complex with its functional receptor in human, Ephrin-B2. Surprisingly, no major differences were found in the results, which demonstrates that our identified compounds can also perform their action even when the Ggp is attached to the Ephrin-B2 ligand. Therefore, in light of all of these results, we strongly suggest that compounds (S)-5-(benzylcarbamoyl)-1-(2-(4-methyl-2-phenylpiperazin-1-yl)-2-oxoethyl)-6-oxo-3,6-dihydropyridin-1-ium-3-ide and 5-(cyclohexylcarbamoyl)-1-(2-((2-(3-fluorophenyl)-2-methylpropyl)amino)-2-oxoethyl)-6-oxo-3,6-dihydropyridin-1-ium-3-ide could be considered as potential therapeutic agents against HeV; however, further in vitro and in vivo experiments are required to validate this study.     

Finding the First Potential Inhibitors of Shikimate Kinase from Methicillin Resistant Staphylococcus aureus through Computer-Assisted Drug Design

Methicillin-resistant Staphylococcus aureus (MRSA) is an important threat as it causes serious hospital and community acquired infections with deathly outcomes oftentimes, therefore, development of new treatments against this bacterium is a priority. Shikimate kinase, an enzyme in the shikimate pathway, is considered a good target for developing antimicrobial drugs; this is given because of its pathway, which is essential in bacteria whereas it is absent in mammals. In this work, a computer-assisted drug design strategy was used to report the first potentials inhibitors for Shikimate kinase from methicillin-resistant Staphylococcus aureus (SaSK), employing approximately 5 million compounds from ZINC15 database. Diverse filtering criteria, related to druglike characteristics and virtual docking screening in the shikimate binding site, were performed to select structurally diverse potential inhibitors from SaSK. Molecular dynamics simulations were performed to elucidate the dynamic behavior of each SaSK–ligand complex. The potential inhibitors formed important interactions with residues that are crucial for enzyme catalysis, such as Asp37, Arg61, Gly82, and Arg138. Therefore, the compounds reported provide valuable information and can be seen as the first step toward developing SaSK inhibitors in the search of new drugs against MRSA.     

Unveiling of Pyrimidindinones as Potential Anti-Norovirus Agents—A Pharmacoinformatic-Based Approach

The RNA-dependent RNA polymerase (RdRp) receptor is an attractive target for treating human norovirus (HNV). A computer-aided approach like e-pharmacophore, molecular docking, and single point energy calculations were performed on the compounds retrieved from the Development Therapeutics Program (DTP) AIDS Antiviral Screen Database to identify the antiviral agent that could target the HNV RdRp receptor. Induced-fit docking (IFD) results showed that compounds ZINC1617939, ZINC1642549, ZINC6425208, ZINC5887658 and ZINC32068149 bind with the residues in the active site-B of HNV RdRp receptor via hydrogen bonds, salt bridge, and electrostatic interactions. During the molecular dynamic simulations, compounds ZINC6425208, ZINC5887658 and ZINC32068149 displayed an unbalanced backbone conformation with HNV RdRp protein, while ZINC1617939 and ZINC1642549 maintained stability with the protein backbone when interacting with the residues. Hence, the two new concluding compounds discovered by the computational approach can be used as a chemotype to design promising antiviral agents aimed at HNV RdRp.     

Marine Brominated Tyrosine Alkaloids as Promising Inhibitors of SARS-CoV-2

There have been more than 150 million confirmed cases of SARS-CoV-2 since the beginning of the pandemic in 2019. By June 2021, the mortality from such infections approached 3.9 million people. Despite the availability of a number of vaccines which provide protection against this virus, the evolution of new viral variants, inconsistent availability of the vaccine around the world, and vaccine hesitancy, in some countries, makes it unreasonable to rely on mass vaccination alone to combat this pandemic. Consequently, much effort is directed to identifying potential antiviral treatments. Marine brominated tyrosine alkaloids are recognized to have antiviral potential. We test here the antiviral capacity of fourteen marine brominated tyrosine alkaloids against five different target proteins from SARS-CoV-2, including main protease (M^pro) (PDB ID: 6lu7), spike glycoprotein (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), membrane glycoprotein (PDB ID: 6M17), and non-structural protein 10 (nsp10) (PDB ID: 6W4H). These marine alkaloids, particularly the hexabrominated compound, fistularin-3, shows promising docking interactions with predicted binding affinities (S-score = −7.78, −7.65, −6.39, −6.28, −8.84 Kcal/mol) for the main protease (M^pro) (PDB ID: 6lu7), spike glycoprotein (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), membrane glycoprotein (PDB ID: 6M17), and non-structural protein 10 (nsp10) (PDB ID: 6W4H), respectively, where it forms better interactions with the protein pockets than the native interaction. It also shows promising molecular dynamics, pharmacokinetics, and toxicity profiles. As such, further exploration of the antiviral properties of fistularin-3 against SARS-CoV-2 is merited.     

新型二氟甲基磷酸类酪氨酸蛋白磷酸酯酶1B抑制剂的分子动力学模拟和结合自由能计算

通过分子对接建立了一系列含二氟甲基磷酸基团(DFMP)或二氟甲基硫酸基团(DFMS)的抑制剂与酪氨酸蛋白磷酸酯酶1B(PTP1B)的相互作用模式, 并通过1 ns的分子动力学模拟和molecular mechanics/generalized Born surface area (MM/GBSA)方法计算了其结合自由能. 计算获得的结合自由能排序和抑制剂与靶酶间结合能力排序一致; 通过基于主方程的自由能计算方法, 获得了抑制剂与靶酶残基间相互作用的信息, 这些信息显示DFMP/DFMS基团的负电荷中心与PTP1B的221位精氨酸正电荷中心之间的静电相互作用强弱决定了此类抑制剂的活性, 进一步的分析还显示位于DFMP/DFMS基团中的氟原子或其他具有适当原子半径的氢键供体原子会增进此类抑制剂与PTP1B活性位点的结合能力.     

Conformational dependence of charges in protein simulations

We have studied the conformational dependence of molecular mechanics atomic charges for proteins by calculating the charges fitted to the quantum mechanical (QM) electrostatic potential (ESP) for all atoms in complexes between avidin and seven biotin analogues for 20 snapshots from molecular dynamics simulations. We have studied how various other charge sets reproduce those charges. The QM charges, even if averaged over all snapshots or all residues, in general have a larger magnitude than standard Amber charges, indicating that the restraint toward zero in the restrained ESP method is too strong. This has a significant influence on the electrostatic conformational energies and the interaction energy between the biotin ligand and the protein, giving a difference between the QM and Amber charges of 43 and 8 kJ/mol for the negatively charged and neutral biotin analogues, respectively (3-4%). However, this energy difference is strongly reduced if the solvation energy (calculated by the Poisson-Boltzmann or Generalized Born methods) is added, viz., to 7 kJ/mol for charged and 3 kJ/mol for uncharged ligand. In fact, charges need to be recalculated with a QM method only for residues within 7 or 4 A of the ligand, if the error should be less than 4 kJ/mol. Unfortunately, the QM charges do not give significantly better MM/PBSA estimates of ligand-binding affinities than standard Amber charges.     

Identification of SARS-CoV-2 Papain-like Protease (PLpro) Inhibitors Using Combined Computational Approach**

In the current pandemic, finding an effective drug to prevent or treat the infection is the highest priority. A rapid and safe approach to counteract COVID-19 is in silico drug repurposing. The SARS-CoV-2 PLpro promotes viral replication and modulates the host immune system, resulting in inhibition of the host antiviral innate immune response, and therefore is an attractive drug target. In this study, we used a combined in silico virtual screening for candidates for SARS-CoV-2 PLpro protease inhibitors. We used the Informational spectrum method applied for Small Molecules for searching the Drugbank database followed by molecular docking. After in silico screening of drug space, we identified 44 drugs as potential SARS-CoV-2 PLpro inhibitors that we propose for further experimental testing.     

Identification of Kaurane-Type Diterpenes as Inhibitors of Leishmania Pteridine Reductase I

The current treatments against Leishmania parasites present high toxicity and multiple side effects, which makes the control and elimination of leishmaniasis challenging. Natural products constitute an interesting and diverse chemical space for the identification of new antileishmanial drugs. To identify new drug options, an in-house database of 360 kauranes (tetracyclic diterpenes) was generated, and a combined ligand- and structure-based virtual screening (VS) approach was performed to select potential inhibitors of Leishmania major (Lm) pteridine reductase I (PTR1). The best-ranked kauranes were employed to verify the validity of the VS approach through LmPTR1 enzyme inhibition assay. The half-maximal inhibitory concentration (IC₅₀) values of selected bioactive compounds were examined using the random forest (RF) model (i.e., 2β-hydroxy-menth-6-en-5β-yl ent-kaurenoate (135) and 3α-cinnamoyloxy-ent-kaur-16-en-19-oic acid (302)) were below 10 μM. A compound similar to 302, 3α-p-coumaroyloxy-ent-kaur-16-en-19-oic acid (302a), was also synthesized and showed the highest activity against LmPTR1. Finally, molecular docking calculations and molecular dynamics simulations were performed for the VS-selected, most-active kauranes within the active sites of PTR1 hybrid models, generated from three Leishmania species that are known to cause cutaneous leishmaniasis in the new world (i.e., L. braziliensis, L. panamensis, and L. amazonensis) to explore the targeting potential of these kauranes to other species-dependent variants of this enzyme.     

Virtual Screening of Natural Chemical Databases to Search for Potential ACE2 Inhibitors

The angiotensin-converting enzyme II (ACE2) is a multifunctional protein in both health and disease conditions, which serves as a counterregulatory component of RAS function in a cardioprotective role. ACE2 modulation may also have relevance to ovarian cancer, diabetes, acute lung injury, fibrotic diseases, etc. Furthermore, since the outbreak of the coronavirus disease in 2019 (COVID-19), ACE2 has been recognized as the host receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The receptor binding domain of the SARS-CoV-2 S-protein has a strong interaction with ACE2, so ACE2 may be a potent drug target to prevent the virus from invading host cells for anti-COVID-19 drug discovery. In this study, structure- and property-based virtual screening methods were combined to filter natural product databases from ChemDiv, TargetMol, and InterBioScreen to find potential ACE2 inhibitors. The binding affinity between protein and ligands was predicted using both Glide SP and XP scoring functions and the MM-GBSA method. ADME properties were also calculated to evaluate chemical drug-likeness. Then, molecular dynamics (MD) simulations were performed to further explore the binding modes between the highest-potential compounds and ACE2. Results showed that the compounds 154-23-4 and STOCK1N-07141 possess potential ACE2 inhibition activities and deserve further study.     

Virtual Screening and Molecular Dynamics Simulation Study of Influenza Polymerase PB2 Inhibitors

Influenza A virus is the main cause of worldwide epidemics and annual influenza outbreaks in humans. In this study, a virtual screen was performed to identify compounds that interact with the PB2 cap-binding domain (CBD) of influenza A polymerase. A virtual screening workflow based on Glide docking was used to screen an internal database containing 8417 molecules, and then the output compounds were selected based on solubility, absorbance, and structural fingerprints. Of the 16 compounds selected for biological evaluation, six compounds were identified that rescued cells from H1N1 virus-mediated death at non-cytotoxic concentrations, with EC50 values ranging from 2.5–55.43 μM, and that could bind to the PB2 CBD of H1N1, with Kd values ranging from 0.081–1.53 μM. Molecular dynamics (MD) simulations of the docking complexes of our active compounds revealed that each compound had its own binding characteristics that differed from those of VX-787. Our active compounds have novel structures and unique binding modes with PB2 proteins, and are suitable to serve as lead compounds for the development of PB2 inhibitors. An analysis of the MD simulation also helped us to identify the dominant amino acid residues that play a key role in binding the ligand to PB2, suggesting that we should focus on increasing and enhancing the interaction between inhibitors and these major amino acids during lead compound optimization to obtain more active PB2 inhibitors.     

In Silico Identification of Potential Sites for a Plastic-Degrading Enzyme by a Reverse Screening through the Protein Sequence Space and Molecular Dynamics Simulations

The accumulation of polyethylene terephthalate (PET) seriously harms the environment because of its high resistance to degradation. The recent discovery of the bacteria-secreted biodegradation enzyme, PETase, sheds light on PET recycling; however, the degradation efficiency is far from practical use. Here, in silico alanine scanning mutagenesis (ASM) and site-saturation mutagenesis (SSM) were employed to construct the protein sequence space from binding energy of the PETase–PET interaction to identify the number and position of mutation sites and their appropriate side-chain properties that could improve the PETase–PET interaction. The binding mechanisms of the potential PETase variant were investigated through atomistic molecular dynamics simulations. The results show that up to two mutation sites of PETase are preferable for use in protein engineering to enhance the PETase activity, and the proper side chain property depends on the mutation sites. The predicted variants agree well with prior experimental studies. Particularly, the PETase variants with S238C or Q119F could be a potential candidate for improving PETase. Our combination of in silico ASM and SSM could serve as an alternative protocol for protein engineering because of its simplicity and reliability. In addition, our findings could lead to PETase improvement, offering an important contribution towards a sustainable future.     

Identification of potential HIV-1 integrase strand transfer inhibitors: In silico virtual screening and QM/MM docking studies

HIV-1 integrase (IN) is a retroviral enzyme that catalyses integration of the reverse-transcribed viral DNA into the host genome, which is necessary for efficient viral replication. In this study, we have performed an in silico virtual screening for the identification of potential HIV-1 IN strand transfer (ST) inhibitors. Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to 3-Hydroxypyrimidine-2,4-diones. Based on the ligand-based pharmacophore model, we obtained a five-point pharmacophore with two hydrogen bond acceptors (A), one hydrogen bond donor (D), one hydrophobic group (H) and one aromatic ring (R) as pharmacophoric features. The pharmacophore hypothesis AADHR was used as a 3D query in a sequential virtual screening study to filter small molecule databases Maybridge, ChemBridge and Asinex. Hits matching with pharmacophore hypothesis AADHR were retrieved and passed progressively through Lipinski’s rule of five filtering, molecular docking and hierarchical clustering. The five compounds with best hits with novel and diverse chemotypes were subjected to QM/MM docking, which showed improved docking accuracy. We further performed molecular dynamics simulation and found three compounds that form stable interactions with key residues. These compounds could be used as a leads for further drug development and rational design of HIV-1 IN inhibitors.