QSAR and DFT Studies of Some Tacrine-Hydroxamate Derivatives as Inhibitors of Cholinesterase (AChEs) in the Treatment of Alzheimer's Disease

Introduction: This work was devoted to an in silico investigation conducted on twenty-eight Tacrine-hydroxamate derivatives as a potential treatment for Alzheimer's disease using DFT and QSAR modeling techniques. Method(s): The data set was randomly partitioned into a training set (22 compounds) and a test set (6 compounds). Then, fourteen models were built and were used to compute the predicted pIC50 of compounds belonging to the test set. Result(s): Al built models were individualy validated using both internal and external validation methods, including the Y-Randomization test and Golbraikh and Tropsha's model acceptance criteria. Then, one model was selected for its higher R2, R2test, and Q2cv values (R2 = 0.768, R2adj = 0.713, MSE = 0.304, R2test=0.973, Q2cv = 0.615). From these outcomes, the activity of the studied compounds toward the main protease of Cholinesterase (AChEs) seems to be influenced by 4 descriptors, i.e., the total dipole moment of the molecule (mu), number of rotatable bonds (RB), molecular topology radius (MTR) and molecular topology polar surface area (MTPSA). The effect of these descriptors on the activity was studied, in particular, the increase in the total dipole moment and the topological radius of the molecule and the reduction of the rotatable bond and topology polar surface area increase the activity. Conclusion(s): Some newly designed compounds with higher AChEs inhibitory activity have been designed based on the best-proposed QSAR model. In addition, ADMET pharmacokinetic properties were carried out for the proposed compounds, the toxicity results indicate that 7 molecules are nontoxic.Copyright © 2023 Bentham Science Publishers.

Assembling a structural model of the SARS-CoV-2 replication and transcription complex from 60+ subunits

The SARS-CoV-2 replication and transcription complex (RTC) is made up of nine distinct non-structural viral proteins encoded by the ORF1ab gene. These proteins house seven enzymatic sites that synthesize new viral genomic and subgenomic RNA, proofread and correct errors in the synthesis, add a 5'-cap to the nascent RNA, and truncate the intermediate negative sense 5'-poly-U tail. While x-ray crystallography and cryo-EM have provided high resolution structures of each of the individual proteins of the RTC and have shed light on how subsets of the proteins associate, a full picture of the RTC has remained elusive. Using molecular modeling tools, including protein-protein docking, we have generated a model of the RTC centered around hexameric nsp15, which is capped on two faces by trimers of nsp14/nsp16/(nsp10)2. A conformational change of nsp14, necessary to facilitate binding to nsp15, then recruits six nsp12/nsp7/(nsp8)2 polymerase subunits. To this, six nsp13 subunits are distributed around the complex. The resulting superstructure is composed of 60 subunits total and positions the nsp14 exonuclease and nsp15 endonuclease sites in line with the dsRNA exiting the nsp12 polymerase site. Nsp10 acts to separate the RNA strands, directing the nascent strand to the nsp12 NiRAN site, where a transiently associated nsp9 facilitates the first step in mRNA capping. The RNA is then directed to the nsp14 N7-methyltransferase site and the nsp16 2'O-methyltransferase site to complete the capping. Additionally, template switching during transcription is proposed to be facilitated by positioning of the TRS-L RNA-bound N-protein above the polymerase active site, between two subunits of nsp13. The model, while constructed based on structural considerations, offers a unifying set of hypotheses to explain the diverse set of processes involved in coronavirus genome replication and transcription. All work presented was funded by Gilead Sciences.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Visualization and functional annotation of coronavirus spike protein glycoshields

Spike proteins of coronaviruses are highly glycosylated and responsible for host recognition and viral entry. The glycans provide a camouflaging shield to help coronaviruses evade host immunity and, in some cases, modulate functional domain structures and dynamics pertinent to host recognition. However, the glycans are chemically and conformationally heterogeneous, making it challenging to determine the chemical compositions and conformations quantitatively. Combining cryo-electron microscopy, mass spectrometry, and molecular modeling, we systematically characterize a panel of spike protein variants of human and animal coronaviruses, including those of the variants of concern of SARS-CoV-2. We have established a robust workflow to quantify the heterogeneity of individual N-glycans by mass spectrometry. We also demonstrated the ability to visualize long glycan structures directly in regions where the dynamics are restricted. In places where the N-glycans are too dynamic, their structural information is generally lost after extended cryo-EM data processing that aims to achieve high resolution. To address this issue, we developed a computational tool called GlycoSHIELD to generate ensembles of glycan conformers to recapitulate the fuzzy structures that are in quantitative agreement with the experimental cryo-EM data. The ability to generate fully glycosylated spike protein models enables the prediction of hitherto unknown receptor and antibody binding sites. This work was supported by Academia Sinica intramural fund, an Academia Sinica Career Development Award, Academia Sinica to STDH (AS-CDA-109- L08), an Infectious Disease Research Supporting Grant to STDH (AS-IDR- 110-08), and the Ministry of Science and Technology (MOST), Taiwan (MOST 109-3114-Y-001-001, MOST 110-2113-M-001- 050-MY3 and MOST 110-2311-B-001-013-MY3) to STDH.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Herbal medicines in the treatment of coronavirus disease 2019 (Covid-19)

Coronavirus disease 2019 (COVID-19), caused by a novel coronavirus, started in livestock within the markets of Wuhan, China and was consequently spread around the world. The virus has been rapidly spread worldwide due to the outbreak. COVID-19 is the third serious coronavirus outbreak in less than 20 years after Severe Acute Respiratory Syndrome (SARS) in 2003 and Middle East Respiratory Syndrome (MERS) in 2012. The novel virus has a nucleotide identity closer to that of the SARS coronavirus than that of the MERS coronavirus. Since there is still no vaccine, the main ways to improve personal immunity against this disease are prophylactic care and self-resistance including an increased personal hygiene, a healthy lifestyle, an adequate nutritional intake, a sufficient rest, and wearing medical masks and increasing time spent in well ventilated areas. There is a need for novel antivirals that are highly efficient and economical for the management and control of viral infections when vaccines and standard therapies are absent. Herbal medicines and purified natural products have the potential to offer some measure of resistance as the development of novel antiviral drugs continues. In this review, we evaluated 41 articles related to herbal products which seemed to be effective in the prevention or treatment of COVID-19.Copyright © 2021 The Author(s).

The emerging Omicron variant spike mutation: the relative receptor-binding domain affinity and molecular dynamics

This study aims to fill a knowledge gap in our understanding of Omicron variant receptor-binding domain (RBD) interactions with host cell receptor, angiotensin-converting enzyme 2 (ACE2). Protein-protein docking, scoring, and filtration were all performed using the HDOCK server. A coarse-grained prediction of the changes in binding free energy caused by point mutations in Omicron RBD was requested from the Binding Affinity Changes upon Mutation (BeAtMuSiC) tools. GROMACS was utilized to perform molecular dynamics simulations (MD). Within the 15 mutations in Omicron RBD, several mutations have been linked to increased receptor affinity, immunological evasion, and inadequate antibody response. Wild-type (wt) SARS-CoV-2 and its Omicron variant have 92.27% identity. Nonetheless, Omicron RBD mutations resulted in a slight increase in the route mean square deviations (RMSD) of the Omicron structural model during protein-protein docking, as evidenced by RMSDs of 0.47 and 0.85 A for the wt SARS-CoV-2 and Omicron RBD-ACE2 complexes, respectively. About five-point mutations had essentially an influence on binding free energy, namely G6D, S38L, N107K, E151A, and N158Y. The rest of the mutations were expected to reduce the binding affinity of Omicron RBD and ACE2. The MD simulation supports the hypothesis that Omicron RBD is more stably bound to ACE2 than wt SARS-CoV-2 RBD. Lower RMSD and greater radius of gyration (Rg) imply appropriate Omicron structure 3D folding and stability. However, the increased solvent accessible surface area (SASA) with a greater Omicron shape may have a different interaction with receptor binding and regulate virus entrance. Omicron RBD's mutations help it maintain its structural stability, compactness, ACE2 binding, and immune evasion.Copyright © 2022 AEPress, s.r.o.. All rights reserved.

A Computational Framework for Determining the Breadth of Antibodies Against Highly Mutable Pathogens

Highly mutable pathogens pose daunting challenges for antibody design. The usual criteria of high potency and specificity are often insufficient to design antibodies that provide long-lasting protection. This is due, in part, to the ability of the pathogen to rapidly acquire mutations that permit them to evade the designed antibodies. To overcome these limitations, design of antibodies with a larger neutralizing breadth can be pursued. Such broadly neutralizing antibodies (bnAbs) should remain targeted to a specific epitope, yet show robustness against pathogen mutability, thereby neutralizing a higher number of antigens. This is particularly important for highly mutable pathogens, like the influenza virus and the human immunodeficiency virus (HIV). The protocol describes a method for computing the "breadth” of a given antibody, an essential aspect of antibody design. © 2023, Springer Science+Business Media, LLC, part of Springer Nature.

Computational tools for aptamer identification and optimization

Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamer selections against SARS-CoV-2 are discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively. Copyright © 2022 Elsevier B.V.

Study of Marine Natural Products as Anti-SARS-CoV-2 Agents Using Molecular Modeling

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a global pandemic. Viral entry into host cells is mediated by spike glycoprotein (SGP) interactions with angiotensin-converting enzyme 2 (ACE2) and heparan sulfate glycosaminoglycans on the cell surface. Carbohydrate small molecules were found to bind to the receptor binding domain (RBD) of SGP, which also interacts with ACE2, forming a ternary complex. Moreover, glycans isolated from sea cucumber and red alga species exhibited anti-SARS-CoV-2 activities, presumably by blocking viral entry mediated through SGP-heparan sulfate interactions. Here we report a collection of computational studies conducted as part of a collaborative effort to investigate the effects of marine natural products (NPs) on the wild-type and N501Y mutant SGP RBD. Starting from an X-ray crystal structure of the RBD-ACE2 complex, a model of SGP RBD was built. To investigate the static and dynamic behavior of RBD-NP interactions, blind and site-targeted molecular docking using diverse docking programs (Glide, AutoDock Vina or ClusPro) was carried out, followed by extensive molecular dynamics simulations with two force fields (CHARMM36 or Glycam06) and binding free energy calculations. Predicted conformations of the NPs varied considerably when modeled in water or in complex with RBD. Five NP binding sites on the RBD were studied. NP binding specificities towards SARS-CoV-2 variants were explained and important RBD residues were identified. Statistical analyses of the stability of various protein-NP complexes during molecular dynamics simulations helped to differentiate pseudo-vs. real-binding sites. Our results provide significant insights into the importance of extensive molecular dynamics calculations in order to move beyond the limitations of molecular docking.

Repurposing FDA-approved Drugs Targeting SARS-CoV2 3CLpro: A Study by Applying Virtual Screening, Molecular Dynamics, MM-PBSA Calculations and Covalent Docking

Background: Since the end of 2019, the etiologic agent SAR-CoV-2 responsible for one of the most significant epidemics in history has caused severe global economic, social, and health damages. The drug repurposing approach and application of Structure-based Drug Discovery (SBDD) using in silico techniques are increasingly frequent, leading to the identification of several molecules that may represent promising potential. Methods: In this context, here we use in silico methods of virtual screening (VS), pharmacophore modeling (PM), and fragment-based drug design (FBDD), in addition to molecular dynamics (MD), molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) calculations, and covalent docking (CD) for the identification of potential treatments against SARS-CoV-2. We initially validated the docking protocol followed by VS in 1,613 FDA-approved drugs obtained from the ZINC database. Thus, we identified 15 top hits, of which three of them were selected for further simulations. In parallel, for the compounds with a fit score value ≤ of 30, we performed the FBDD protocol, where we designed 12 compounds. Results: By applying a PM protocol in the ZINC database, we identified three promising drug candidates. Then, the 9 top hits were evaluated in simulations of MD, MM-PBSA, and CD. Subsequently, MD showed that all identified hits showed stability at the active site without significant changes in the pro-tein's structural integrity, as evidenced by the RMSD, RMSF, Rg, SASA graphics. They also showed interactions with the catalytic dyad (His41 and Cys145) and other essential residues for activity (Glu166 and Gln189) and high affinity for MM-PBSA, with possible covalent inhibition mechanism. Conclusion: Finally, our protocol helped identify potential compounds wherein ZINC896717 (Zafir-lukast), ZINC1546066 (Erlotinib), and ZINC1554274 (Rilpivirine) were more promising and could be explored in vitro, in vivo, and clinical trials to prove their potential as antiviral agents.

Evaluation of the inhibitory activities of thyme compounds against coronavirus disease-19 (COVID-19) by molecular docking and molecular dynamic simulation

We have explored the inhibitory capability of Thymus vulgaris compounds against ACE2 protein -the host receptor for SARS-CoV-2, papain-like and main protease of the SARS-CoV-2 through molecular simulations. The docking results showed that the compounds had a greater capability to inhibit ACE2 and papain-like protease in comparison to the main protease. The majority of compounds (61.7%) bind to the S2 active pocket of ACE2. The most powerful anticoronavirus activity is expressed in the order: Terpinolene > Thymol > Bicyclogermacrene. Pi interactions play key roles in the binding of three compounds to the active sites of ACE2 enzyme. 34 out of these 60 compounds were fitted in the PLpro active site. α-humulene followed by (+)-Spathulenol, and (-)-β-Bourbonene showed strong capacity to inhibit PLpro binding site. Except for (+)-Spathulenol which also formed H-bond with Asp165 and Tyr274 amino acids, α-humulene and (-)-β-Bourbonene conjugate with PLpro were stabilized mainly through alkyl and pi interactions. According to the Mpro docking results, 58.3% of thyme compounds could block the active site. The binding energy order was (-)-Spathulenol at highest, then Bicyclogermacrene, (+)-δ-cadinene, (+)-Spathulenol, and Viridiflorol, followed by (-)-β-Caryophyllene oxide. Cys145, His41, Met49, and Met165 are key residues in the interaction of these ligands with the enzyme binding site. The weakest interaction with all three enzymes was observed for (R)-(-)-1-Octen-3-ol and (3S)-Oct-1-en-3-ol. Based on the molecular dynamics simulation lowest conformational change was detected for ACE2 in the present of Terpinolene. (-)-Spathulenol and α-Humulene had the least and most displacement compared to its initial positions, respectively.

Exploration of Luteolin as Potential Anti-COVID-19 Agent: Molecular Docking, Molecular Dynamic Simulation, ADMET and DFT Analysis

Background: Coronavirus disease-2019 (COVID-19) has recently emerged as a pandemic respiratory disease with mild to severe pneumonia symptoms. No clinical antiviral agent is available so far. However, several repurposing drugs and vaccines are being given to individuals or in clinical trials against SARS-CoV-2 Objective: The aim of this study is to uncover the potential effects of Luteolin (Lut) as an inhibitor of SARS-CoV2 encoded proteins via utilizing computational tools. Methods: Molecular modelling to unfold the anti-SARS-CoV2 potential of Lut along with reference drugs namely remdesivir and nafamostat was performed by the use of molecular docking, molecular dynamic (MD) simulation, absorption, distribution, metabolism, excretion, toxicity (ADMET) and density functional theory (DFT) methods against the five different SARS-CoV-2 encoded key proteins and one human receptor protein. The chemical reactivity of Luteolin is done through prediction of HOMO-LUMO gap energy and other chemical descriptors analysis. Results: In the present study, Lut binds effectively in the binding pockets of spike glycoprotein (6VSB), ADP phosphatase of NSP3 (6W02), and RNA dependent RNA polymerase (7AAP) protein receptors with significant values of docking scores-7.00,-7.25, and-6.46 respectively as compared to reference drugs remdesivir and nafamostat. Conclusion: Thus, Lut can act as a therapeutic agent and is orally safe for human consumption as predicted by molecular modelling against SARS-CoV-2 in the treatment of COVID-19.

Hydroxychloroquine (HCQ) Exhibits Better Binding to the Main Protease (Mpro) Compared to Spike Protein (S protein) of SARS-CoV-2: An In-silico Analysis

Background: Despite various efforts in preventing and treating SARS-CoV-2 infec-tions;transmission and mortality have been increasing at alarming rates globally. Since its first oc-currence in Wuhan, China, in December 2019, the number of cases and deaths due to SARS-CoV--2 infection continues to increase across 220 countries. Currently, there are about 228 million cases and 4.6 million deaths recorded globally. Although several vaccines/drugs have been reported to prevent or treat SARS-CoV-2, their efficacy to protect against emerging variants and duration of protection are not fully known. Hence, more emphasis is given to repurpose the existing pharmacological agents to manage the infected individuals. One such agent is hydroxychloroquine (HCQ), which is a more soluble derivative of antimalarial drug chloroquine. HCQ has been tested in clinical trials to mitigate SARS-CoV-2 infection-induced complications while reducing the time to clinical recovery (TTCR). However, several concerns and questions about the utility and efficacy of HCQ for treating SARS-CoV-2 infected individuals still persist. Identifying key proteins regulated by HCQ is likely to provide vital clues required to address these concerns. Objective: The objective of this study is to identify the ability of HCQ for binding to the most wide-ly studied molecular targets of SARS-CoV-2 viz., spike glycoprotein (S protein), and main pro-tease (Mpro, also referred as chymotrypsin like protease) using molecular docking approaches and correlate the results with reported mechanisms of actions of HCQ. Methods: X-ray crystallographic structures of spike glycoprotein and main protease of SARS-CoV-2 were retrieved from Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (PDB). The structure of Hydroxychloroquine was retrieved from the PubChem compound database. The binding interactions of the HCQ with target proteins were predicted using C-Docker algorithm, and visualized using Discovery studio visualizer. Results: Data from molecular docking studies showed very strong binding of HCQ to the main pro-tease compared to spike glycoprotein. Conclusion: The antiviral activity of HCQ is attributed to its ability to bind to the main protease compared to surface glycoprotein. Therefore, future studies should focus more on developing a combination agent/strategy for targeting surface glycoprotein and main protease together.

Molecular modelling and docking analysis of SARSCoV-2 helicase (yp-009725308) as drug target

Introduction: The ongoing outbreak of COVID-19 has become a global health emergency. The SARS-CoV-2 helicase (nsp13) play an important role in SARS-CoV-2 replication and could be serve as a target for antivirals to develop potential COVID-19 treatment. Objective: Homology modelling and docking analysis of SARSCoV-2 helicase (YP-009725308) as drug target. Methodology: The structure and function of SARSCoV-2 helicase (YP-009725308) predicted by in silico modelling studies. The SWISS-MODEL Structure Assessment tool was used for homology modelling and visual analysis of crystal structure of protein. The validation for structure models was performed by using PROCHECK. Model quality estimates based on the QMEAN and ProSA. The MCULE-1-Click docking, and InterEvDock-2.0 server were used for protein-ligand docking. Results: The SARS-CoV-2 helicase (YP-009725308) model corresponding to probability conformation with 90.9% residue of core section that specifies accuracy of predicted model. The ProSA Z-score score -9.17;indicates the good quality of the model. Inhibitor N-[3-(carbamoylamino) phenyl] acetamide exhibited effective binding affinity against helicase (YP-009725308). Docking studies revealed that Lys-146, Leu-147, Ile-151, Tyr-185, Lys-195, Tyr224, Val-226, Leu-227, Ser-229 are important residues for receptor-ligand interaction. Conclusion: Hence, the proposed inhibitor could potently inhibit SARS-CoV-2 helicase (YP-009725308) that recognized to play key roles during replication of viral RNAs. Overall findings demonstrate the SARS-CoV-2 helicase (nsp13) serve as a target for antivirals to cure COVID-19.