Molecular Simulation Approach Research Articles

Identification of novel umami peptides from Boletus edulis and its mechanism via sensory analysis and molecular simulation approaches

The study aimed to identify umami peptides from Boletus edulis and explore their umami mechanism. 421, 713 and 616 peptides identified by LC-MS/MS from control sample (CS), enzymatically extracted sample (EES) and high-pressure cooking sample (HPCS), respectively. According to molecular docking study, three potential umami peptides (DGF, KCGQ and HHYE) were chemically synthesized for sensory evaluation. DGF/HHYE had the lowest umami recognition threshold values in the absence (0.37 mmol/L for DGF)/presence (0.21 mmol/L for HHYE) of monosodium l-glutamate. KCGQ exhibited the strongest synergistic umami effect. Molecular dynamic simulation revealed that hydrogen bonds and hydrophobic interactions were the major intermolecular interaction forces and the charged amino acid residues (D1, E4 and K1) in umami peptides were dominate in the molecular recognition of umami peptides and the receptor. This study lays the groundwork for the efficient screening of umami peptides from edible fungi and contributes to the umami peptides structure–activity relationship research.

Corrosion inhibition of carboxylate substituted amidrazone on mild steel in 3% NaCl medium: Electrochemical, DFT and molecular dynamics simulation studies

The inhibitive effect of three synthesized amidrazone inhibitorsC6H4(2-COOH)NHN = C(COCH3)-NHC6H4(2-COOH) (1), C6H4(2-COOH)NHN = C(COCH3)-NHC6H5(2) and C6H5NHN = C(COCH3)-NHC6H4(2-COOH) (3)on mild steel in 3% NaCl solution at 25 ºC were evaluated by means of electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization. The X-ray show that two molecules of (1) isdimerize based on hydrogen bonding interactions. All experimental results demonstrate that these compounds are efficient inhibitors. The inhibition efficiencies(ηP%) increase with inhibitors concentration. At 1 × 10−4 M, the (ηP%) was 94.80%, 92.80% and 90.40% for 1, 2 and 3, respectively. The efficiency of inhibition is directly proportional to the concentration and the number of COOH on the amidrazone and inversely proportional to the temperature. Analysis of polarization curves showed that these compounds behaved as mixed-type inhibitors and their adsorption obeyed Langmuir model. Molecular dynamics and Quantum mechanical simulation approaches were utilized to rationalize the inhibition-efficiency of the investigated compounds.

Deep inside molecules — digital twins at the nanoscale

BackgroundDigital twins offer rich potential for exploration in virtual reality (VR). Using interactive molecular simulation approaches, they enable a human operator to access the physical properties of molecular objects and to build, manipulate, and study their assemblies. Integrative modeling and drug design are important applications of this technology. MethodsIn this study, head-mounted virtual reality displays connected to molecular simulation engines were used to create interactive and immersive digital twins. They were used to perform tasks relevant to specific use cases. ResultsThree areas were investigated, including model building, rational design, and tangible models. Here, we report several membrane-embedded systems of ion channels, viral components, and artificial water channels. We were able to improve and create molecular designs based on digital twins. ConclusionsThe molecular application domain offers great opportunities, and most of the technical and technological aspects have been solved. Wider adoption is expected once the onboarding of VR is simplified and the technology gains wider acceptance.

Molecular and Artificial Neural Networks Modeling of Sorption and Diffusion of Small Alkanes, Alkenes and Their Ternary Mixtures in ZIF-8 at Different Temperatures.

Numerical computations comprising of Grand Canonical-Monte Carlo (GCMC) and Canonical Statistical Ensemble (NVT) Molecular Dynamics (MD) simulations were used to study the diffusion and sorption characteristics primarily for methane, ethane, and ethene molecules and for their ternary mixtures at different temperatures in ZIF-8 porous material. Methane as pure component or in mixture proved to be the sorbed hydrocarbon with the higher molecular mobility at the temperature range of 273-373 K among alkanes and alkenes. In addtion, alkenes were the hydrocarbons with the higher self-diffusion coefficients compared to the respective alkanes. In the ternary mixtures ethane was preferentially sorbed in ZIF-8 at all temperatures studied. Direct comparisons of the self-diffusivity data obtained from the NVT-MD simulations with recently reported Magic Angle Spinning Pulsed Field Gradient Nuclear Magnetic Resonance (MAS PFG NMR) measurements showed reasonable agreement. Furthermore, the NVT-MD self-diffusivity coefficients in conjunction with the aforementioned MAS PFG NMR experimental measurements, and sorption thermodynamic data obtained from the present GCMC simulations were utilized for the development of individual Artificial Neural Networks (ANNs) predictive modeling procedures in order to provide additional quantitative and qualitative information regarding the diffusion and sorption of small alkanes, alkenes in ZIF-8. The ANNs predictions were in good agreement with the experimental measurements and with the molecular simulation data. The modeling and analysis capabilities of ANNs along with their fast computations using moderate computer resources can significantly assist the irreplaceable molecular simulation and experimental approaches to cope with complicated problems at the molecular level.

Anti-Inflammatory and Anti-Rheumatic Potential of Selective Plant Compounds by Targeting TLR-4/AP-1 Signaling: A Comprehensive Molecular Docking and Simulation Approaches.

Plants are an important source of drug development and numerous plant derived molecules have been used in clinical practice for the ailment of various diseases. The Toll-like receptor-4 (TLR-4) signaling pathway plays a crucial role in inflammation including rheumatoid arthritis. The TLR-4 binds with pro-inflammatory ligands such as lipopolysaccharide (LPS) to induce the downstream signaling mechanism such as nuclear factor κappa B (NF-κB) and mitogen activated protein kinases (MAPKs). This signaling activation leads to the onset of various diseases including inflammation. In the present study, 22 natural compounds were studied against TLR-4/AP-1 signaling, which is implicated in the inflammatory process using a computational approach. These compounds belong to various classes such as methylxanthine, sesquiterpene lactone, alkaloid, flavone glycosides, lignan, phenolic acid, etc. The compounds exhibited different binding affinities with the TLR-4, JNK, NF-κB, and AP-1 protein due to the formation of multiple hydrophilic and hydrophobic interactions. With TLR-4, rutin had the highest binding energy (−10.4 kcal/mol), poncirin had the highest binding energy (−9.4 kcal/mol) with NF-κB and JNK (−9.5 kcal/mol), respectively, and icariin had the highest binding affinity (−9.1 kcal/mol) with the AP-1 protein. The root means square deviation (RMSD), root mean square fraction (RMSF), and radius of gyration (RoG) for 150 ns were calculated using molecular dynamic simulation (MD simulation) based on rutin’s greatest binding energy with TLR-4. The RMSD, RMSF, and RoG were all within acceptable limits in the MD simulation, and the complex remained stable for 150 ns. Furthermore, these compounds were assessed for the potential toxic effect on various organs such as the liver, heart, genotoxicity, and oral maximum toxic dose. Moreover, the blood–brain barrier permeability and intestinal absorption were also predicted using SwissADME software (Lausanne, Switzerland). These compounds exhibited promising physico-chemical as well as drug-likeness properties. Consequently, these selected compounds portray promising anti-inflammatory and drug-likeness properties.

Structural and dynamic investigation of non-synonymous variations in Renin-AGT complex revealed altered binding via hydrogen-bonding network reprogramming to accelerate the hypertension pathway.

Hypertension is one of the major issues worldwide and one of the main factors involved in heart and kidney failure. Angiotensinogen and renin are key components of the renin-angiotensin-aldosterone system, which plays an indispensable role in hypertension. The aim of this study was to find out the non-synonymous mutations and structure-based mutation-function correlation in the renin-AGT complex and reveal the most deleterious mutations to accelerated hypertension. In the current study, we employed computational modeling and molecular simulation approaches to demonstrate the impact of specific mutations in the REN-AGT interface in hypertension. Computational algorithms, that is, PhD-SNP, PolyPhen-1, MAPP, Sorting Intolerant from Tolerant, Screening of non-acceptable polymorphism, PredictSNP, PolyPhen-2, and Protein Analysis Through Evolutionary Relationships predicted 20 mutations as deleterious in AGT while only five mutations were confirmed as deleterious in the renin protein. Investigation of the bonding analysis revealed that two mutations S107L and V193F in renin altered the hydrogen-bonding paradigm at the interface site. Furthermore, exploration of structural-dynamic behaviors demonstrated by that these mutations also increases the structural stability to regulate the expression of disease pathway. The flexibility index of each residues and structural compactness analysis further validated the findings by portraying the difference in the dynamic behavior in contrast to the wild type. Binding energy calculations based on molecular mechanics/generalized Born surface area methods were used which further established the binding differences between the wild type, S107L, and V193F mutant variants. The total binding energy for wild type, S107L, and V193F was reported to be -27.79, -47.72, and -38.25, respectively. In conclusion, these two mutations increase the binding free energy alongside the docking score to enhance the binding between renin and AGT to overexpress this pathway in a hypertension disease condition. Patients with these mutations may be screened for potential therapeutic intervention.

Computational Investigations of Traditional Chinese Medicinal Compounds against the Omicron Variant of SARS-CoV-2 to Rescue the Host Immune System.

Macrodomain-I of the NSP3 (non-structural protein 3) is responsible for immune response hijacking in the SARS-CoV-2 infection known as COVID-19. In the omicron variant (B.1.1.529), this domain harbors a new mutation, V1069I, which may increase the binding of ADPr and consequently the infection severity. This macrodomain-I, due to its significant role in infection, is deemed to be an important drug target. Hence, using structural bioinformatics and molecular simulation approaches, we performed a virtual screening of the traditional Chinese medicines (TCM) database for potential anti-viral drugs. The screening of 57,000 compounds yielded the 10 best compounds with docking scores better than the control ADPr. Among the top ten, the best three hits—TCM42798, with a docking score of −13.70 kcal/mol, TCM47007 of −13.25 kcal/mol, and TCM30675 of −12.49 kcal/mol—were chosen as the best hits. Structural dynamic features were explored including stability, compactness, flexibility, and hydrogen bonding, further demonstrating the anti-viral potential of these hits. Using the MM/GBSA approach, the total binding free energy for each complex was reported to be −69.78 kcal/mol, −50.11 kcal/mol, and −47.64 kcal/mol, respectively, which consequently reflect the stronger binding and inhibitory potential of these compounds. These agents might suppress NSP3 directly, allowing the host immune system to recuperate. The current study lays the groundwork for the development of new drugs to combat SARS-CoV-2 and its variants.

An integrated approach reveals how lipo-chitooligosaccharides interact with the lysin motif receptor-like kinase MtLYR3.

N‐acetylglucosamine containing compounds acting as pathogenic or symbiotic signals are perceived by plant‐specific Lysin Motif Receptor‐Like Kinases (LysM‐RLKs). The molecular mechanisms of this perception are not fully understood, notably those of lipo‐chitooligosaccharides (LCOs) produced during root endosymbioses with nitrogen‐fixing bacteria or arbuscular mycorrhizal fungi. In Medicago truncatula, we previously identified the LysM‐RLK LYR3 (MtLYR3) as a specific LCO‐binding protein. We also showed that the absence of LCO binding to LYR3 of the non‐mycorrhizal Lupinus angustifolius, (LanLYR3), was related to LysM3, which differs from that of MtLYR3 by several amino acids and, particularly, by a critical tyrosine residue absent in LanLYR3. Here, we aimed to define the LCO binding site of MtLYR3 by using molecular modelling and simulation approaches, combined with site‐directed mutagenesis and LCO binding experiments. 3D models of MtLYR3 and LanLYR3 ectodomains were built, and homology modelling and molecular dynamics (MD) simulations were performed. Molecular docking and MD simulation on the LysM3 identified potential key residues for LCO binding. We highlighted by steered MD simulations that in addition to the critical tyrosine, two other residues were important for LCO binding in MtLYR3. Substitution of these residues in LanLYR3‐LysM3 by those of MtLYR3‐LysM3 allowed the recovery of high‐affinity LCO binding in experimental radioligand‐binding assays. An analysis of selective constraints revealed that the critical tyrosine has experienced positive selection pressure and is absent in some LYR3 proteins. These findings now pave the way to uncover the functional significance of this specific evolutionary pattern.

Effect of support hydrophobicity of halloysite‐based catalysts on the polyalphaolefin hydrofinishing performance

AbstractHydrogenation of polyalphaolefins (PAOs) is an industrial process catalyzed by supported precious metals. In this regard, halloysite (Hal) clay has been proven as an efficient support for the immobilization of Pd nanoparticles and development of high‐performance catalysts under mild reaction condition. In this research, the effect of Hal hydrophobicity on the PAO hydrofinishing efficiency is studied. In this line, cetrimonium bromide (CTAB) was used for adjusting the hydrophobicity of halloysite surface. Three catalysts, Hal/Pd, Hal/Pd/CTAB, and Hal/CTAB/Pd, were fabricated by palladation of Hal, treating palladated Hal with CTAB and palladation of CTAB‐treated Hal, respectively. The catalysts were characterized, and their activity for the hydrogenation of PAO was appraised. Moreover, a molecular simulation approach was employed to survey the effect of surface hydrophobicity of Hal on the alkene hydrogenation energy diagram and the steric maps of the main catalytic stages. Both experimental and computational studies approved that the presence of CTAB detracts the activity of the catalyst. Moreover, the order of introduction of Pd and CTAB affects the content of incorporated CTAB and Pd and Pd particle size, and the order of catalysts activity was as follows: Hal/Pd > Hal/Pd/CTAB > Hal/CTAB/Pd. In fact, 5 wt.% Hal/Pd promoted the hydrogenation at 130°C and hydrogen pressure of 8 bar to furnish 98% hydrogenated PAO.

Molecular Simulation Approaches to the Study of Thermotropic and Lyotropic Liquid Crystals

Over the last decade, the availability of computer time, together with new algorithms capable of exploiting parallel computer architectures, has opened up many possibilities in molecularly modelling liquid crystalline systems. This perspective article points to recent progress in modelling both thermotropic and lyotropic systems. For thermotropic nematics, the advent of improved molecular force fields can provide predictions for nematic clearing temperatures within a 10 K range. Such studies also provide valuable insights into the structure of more complex phases, where molecular organisation may be challenging to probe experimentally. Developments in coarse-grained models for thermotropics are discussed in the context of understanding the complex interplay of molecular packing, microphase separation and local interactions, and in developing methods for the calculation of material properties for thermotropics. We discuss progress towards the calculation of elastic constants, rotational viscosity coefficients, flexoelectric coefficients and helical twisting powers. The article also covers developments in modelling micelles, conventional lyotropic phases, lyotropic phase diagrams, and chromonic liquid crystals. For the latter, atomistic simulations have been particularly productive in clarifying the nature of the self-assembled aggregates in dilute solution. The development of effective coarse-grained models for chromonics is discussed in detail, including models that have demonstrated the formation of the chromonic N and M phases.

Conducting the RBD of SARS-CoV-2 Omicron Variant with Phytoconstituents from Euphorbia dendroides to Repudiate the Binding of Spike Glycoprotein Using Computational Molecular Search and Simulation Approach.

(1) Background: Natural constituents are still a preferred route for counteracting the outbreak of COVID-19. Essentially, flavonoids have been found to be among the most promising molecules identified as coronavirus inhibitors. Recently, a new SARS-CoV-2 B.1.1.529 variant has spread in many countries, which has raised awareness of the role of natural constituents in attempts to contribute to therapeutic protocols. (2) Methods: Using various chromatographic techniques, triterpenes (1–7), phenolics (8–11), and flavonoids (12–17) were isolated from Euphorbia dendroides and computationally screened against the receptor-binding domain (RBD) of the SARS-CoV-2 Omicron variant. As a first step, molecular docking calculations were performed for all investigated compounds. Promising compounds were subjected to molecular dynamics simulations (MD) for 200 ns, in addition to molecular mechanics Poisson–Boltzmann surface area calculations (MM/PBSA) to determine binding energy. (3) Results: MM/PBSA binding energy calculations showed that compound 14 (quercetin-3-O-β-D-glucuronopyranoside) and compound 15 (quercetin-3-O-glucuronide 6″-O-methyl ester) exhibited strong inhibition of Omicron, with ΔGbinding of −41.0 and −32.4 kcal/mol, respectively. Finally, drug likeness evaluations based on Lipinski’s rule of five also showed that the discovered compounds exhibited good oral bioavailability. (4) Conclusions: It is foreseeable that these results provide a novel intellectual contribution in light of the decreasing prevalence of SARS-CoV-2 B.1.1.529 and could be a good addition to the therapeutic protocol.

Computer Aided Drug Design of 1,2,3-Triazole Fused Bioactive Derivative Targeting Glucosamine-6-Phosphate Synthase (GlmS) – XRD, Computational Crystallography, and Molecular Simulation Approach

The crystal structure of a 1,2,3-triazole fused heterocyclic derivative 2-(1-Benzyl-5-methyl-1H-1,2,3-triazol-4-yl)-4-(2,4-dichlorophenyl)-6-phenyl pyridine (DICLPY; 4h) is reported. The structural characterization is done by single crystal X-ray technique. The Hirshfeld surfaces (HS) and 2D fingerprint graphs are generated to investigate the inter atomic contacts contribution for structure by CrystalExplorer 17.5 program. The pairwise interaction energies between neighboring molecules are computed at the B3LYP/6-31G(d,p) method. This interaction energy analysis showed that the total stability of the DICLPY structure is mainly contributed by the dispersion force factor followed by the coulomb potential force factor. The DFT-based HOMO, LUMO orbitals and molecular electrostatic potential map are studied to identify the reactivity of our molecule. In-silico molecular docking technique is used to inspect the DICLPY compound as a possible antibacterial agent by docking with Glucosamine-6-phosphate synthase protein (PDB ID: 2VF5) using PyRx and AutoDock Vina programs. The molecular dynamics simulation is performed to examine the physical movement of our molecule DICLPY with Glucosamine-6-phosphate synthase protein for 100 ns time period. MD simulation revealed the greater stability of DICLPY and Glucosamine-6-phosphate synthase protein complex during the simulation period.

Investigation of the binding and dynamic features of A.30 variant revealed higher binding of RBD for hACE2 and escapes the neutralizing antibody: A molecular simulation approach

With the emergence of Delta and Omicron variants, many other important variants of SARS-CoV-2, which cause Coronavirus disease-2019, including A.30, are reported to increase the concern created by the global pandemic. The A.30 variant, reported in Tanzania and other countries, harbors spike gene mutations that help this strain to bind more robustly and to escape neutralizing antibodies. The present study uses molecular modelling and simulation-based approaches to investigate the key features of this strain that result in greater infectivity. The protein-protein docking results for the spike protein demonstrated that additional interactions, particularly two salt-bridges formed by the mutated residue Lys484, increase binding affinity, while the loss of key residues at the N terminal domain (NTD) result in a change to binding conformation with monoclonal antibodies, thus escaping their neutralizing effects. Moreover, we deeply studied the atomic features of these binding complexes through molecular simulation, which revealed differential dynamics when compared to wild type. Analysis of the binding free energy using MM/GBSA revealed that the total binding free energy (TBE) for the wild type receptor-binding domain (RBD) complex was −58.25 kcal/mol in contrast to the A.30 RBD complex, which reported −65.59 kcal/mol. The higher TBE for the A.30 RBD complex signifies a more robust interaction between A.30 variant RBD with ACE2 than the wild type, allowing the variant to bind and spread more promptly. The BFE for the wild type NTD complex was calculated to be −65.76 kcal/mol, while the A.30 NTD complex was estimated to be −49.35 kcal/mol. This shows the impact of the reported substitutions and deletions in the NTD of A.30 variant, which consequently reduce the binding of mAb, allowing it to evade the immune response of the host. The reported results will aid the development of cross-protective drugs against SARS-CoV-2 and its variants.

A protein coupling and molecular simulation analysis of the clinical mutants of androgen receptor revealed a higher binding for Leupaxin, to increase the prostate cancer invasion and motility

Recently a novel coactivator, Leupaxin (LPXN), has been reported to interact with Androgen receptor (AR) and play a significant role in the invasion and progression of prostate cancer. The interaction between AR and LPXN occurs in a ligand-dependent manner and has been reported that the LIM domain in the Leupaxin interacts with the LDB (ligand-binding domain) domain AR. However, no detailed study is available on how the LPXN interacts with AR and increases the (prostate cancer) PCa progression. Considering the importance of the novel co-activator, LPXN, the current study also uses state-of-the-art methods to provide atomic-level insights into the binding of AR and LPXN and the impact of the most frequent clinical mutations H874Y, T877A, and T877S on the binding and function of LPXN. Protein coupling analysis revealed that the three mutants favour the robust binding of LPXN than the wild type by altering the hydrogen bonding network. Further understanding of the binding variations was explored through dissociation constant prediction which demonstrated similar reports as the docking results. A molecular simulation approaches further revealed the dynamic features which reported variations in the dynamics stability, protein packing, hydrogen bonding network, and residues flexibility index. Furthermore, we also assessed the protein motion and free energy landscape which also demonstrated variations in the internal dynamics. The binding free energy calculation revealed -32.95 ± 0.17 kcal/mol for the wild type, for H874Y the total binding energy (BFE) was -36.69 ± 0.11kcal/mol, for T877A the BFE was calculated to be -38.78 ± 0.17 kcal/mol while for T877S the BFE -41.16 ± 0.12 kcal/mol. This shows that the binding of LPXN is increased by these mutations which consequently increase the PCa invasion and motility. In conclusion, the current study helps in understanding the protein networks and particular the coupling of AR-LPXN in prostate cancer and is of great interest in deciphering the molecular mechanism of disease and therapeutics developments.

Immune epitopes identification and designing of a multi-epitope vaccine against bovine leukemia virus: a molecular dynamics and immune simulation approaches.

BackgroundBovine leukemia virus (BLV) is an oncogenic delta-retrovirus causing bovine leucosis. Studies on BLV have shown the association with human breast cancer. However, the exact molecular mechanism is neither known nor their appropriate preventative measure to halt the disease initiation and progression. In this study, we designed a multi-epitope vaccine against BLV using a computational analyses. MethodsFollowing a rigorous assessment, the vaccine was constructed using the T-cell epitopes from each BLV-derived protein with suitable adjuvant and linkers. Both physicochemistry and immunogenic potency as well as the safeness of the vaccine candidate were assessed. Population coverage was done to evaluate the vaccine probable efficiency in eliciting the immune response worldwide. After homology modeling, the three-dimensional structure was refined and validated to determine the quality of the designed vaccine. The vaccine protein was then subjected to molecular docking with Toll-like receptor 3 (TLR3) to evaluate the binding efficiency followed by dynamic simulation for stable interaction.ResultsOur vaccine construct has the potential immune response and good physicochemical properties. The vaccine is antigenic and immunogenic, and has no allergenic or toxic effect on the human body. This novel vaccine contains a significant interactions and binding affinity with the TLR3 receptor.ConclusionsThe proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat BLV infections. However, experimental evaluations are essential to validate the exact safety and immunogenic profiling of this vaccine.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00262-022-03181-w.

Efficacy of defensins as neutralizing agents against the deadly SARS-CoV-2

SARS-CoV-2 infection causes asymptomatic to severe human respiratory diseases. Vaccinations are effective only to a certain extent, and the disease recurs with milder symptoms even after booster doses. Hence, we hypothesize that antiviral therapy in conjunction with vaccination is the need of the hour for containing the disease. SARS-CoV-2 enters the host cell through interaction between viral spike (S) protein and human Angiotensin II converting enzyme2 (ACE2). So, any S-protein neutralizing molecule could be a potential antiviral moiety. The interaction-interface architecture indicates that cationic peptides effectively bind to anionic interface residues of S protein-receptor binding domain (S-RBD). Subsequently, we adopted molecular docking and simulation approaches to examine the binding affinity of cationic human α and β defensins, HNP1 and HBD2 with S-RBD. We observed strong hydrogen bonds, electrostatic, salt bridge, and hydrophobic interactions between these defensins and S-RBD with binding energy (BE) of −10.7 kcal/mol. Interestingly, defensins from Zea mays (ZmD32), Solanum lycopersicum (TPP3), and Sorghum bicolor (DEF1_SORBI) exhibited approximately similar BE of −11.1 kcal/mol, −11.9 kcal/mol, and −12.6 kcal/mol respectively, comparable to ACE2 (BE= −11.9 kcal/mol). Molecular dynamics simulation of S-RBD complexes formed with HBD2, ZmD32 and TPP3, showed stable associations for 100 ns. Results of in-silico studies demonstrated higher binding affinity of more positively-charged peptides with S-RBD, suggesting the potential of plant defensins to block ACE2 binding of S-RBD. These results warrant experimental validation. However these findings indicate the usefulness of plant defensin homologues as neutralizing antiviral agents for use as ideal prophylactic and therapeutic drugs for COVID-19. Communicated by Ramaswamy H. Sarma

Targeting the RBD of Omicron Variant (B.1.1.529) with Medicinal Phytocompounds to Abrogate the Binding of Spike Glycoprotein with the hACE2 Using Computational Molecular Search and Simulation Approach.

Simple SummaryThe current study based on virtual drugs screening and simulations identified novel drugs to target the RBD of the spike protein from Omicron variant of SARS-CoV-2. Using molecular modeling tools to search for a good binding drugs we identified SANC00944, SANC01032, SANC00992, and SANC00317 from South African natural compounds database as potential inhibitor of the Spike-ACE2 complex. In sum, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging Omicron variant of SARS-CoV-2.The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus continues to inflict chaos globally. The emergence of a novel Omicron variant (B.1.1.529) in South Africa harbors 30 mutations in the spike protein. The variant is distinguished from other variants of concern (VOCs) with an increased (15) number of mutations in the receptor-binding domain (RBD) and suggests higher chances of causing reinfections. Initial reports also claimed that this variant escapes all the neutralizing antibodies, thus demanding a novel strategy against it. Thus, in this study, we performed a computational molecular screening against the RBD of the Omicron (B.1.1.529) variant and assessed the binding affinity of potent drugs against the RBD. The multi-steps screening of the South African Natural Compounds Database (SANCDB) revealed four medicinal compounds as excellent (potential) anti-viral agents against the Omicron variant, namely SANC00944, SANC01032, SANC00992, and SANC00317. The simulation analysis of these compounds in complex with the RBD demonstrated stable dynamics and structural compactness. Moreover, the residual flexibility analysis revealed that the flexibility of three loops required for interaction with hACE2 has been reduced by the binding of these drugs. The post-simulation validation of these compounds such as binding free energy, in silico bioactivity, and dissociation constant prediction validated the anti-viral potency of these compounds. The total binding free energy (TBFE) for the SANC01032–RBD complex was reported to be −46.54 kcal/mol; for the SANC01032–RBD complex, the TBFE was −41.88 kcal/mol; for the SANC00992–RBD complex the TBFE was −29.05 kcal/mol, while for the SANC00317–RBD complex the TBFE was −31.03 kcal/mol. The results showed the inhibition potential of these compounds by targeting the RBD. In conclusion, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging Omicron variant of SARS-CoV-2.

Inhibition of SARS-Cov-2 proteases by medicinal plant bioactive constituents: Molecular docking simulation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus that has caused the corona pandemic since 2019 or known as Covid-19. The cleavage of its polyprotein started this viral replication into functional viral proteins by two proteases: 3-chymotrypsin-like protease (3CL protease), also known as main protease (Mpro), and Papain-like protease (PLpro). Medicinal plant bioactive constituents could potentially become protease inhibitor agents of this virus and prevent viral replication. Thus, further might be developed into drug candidates for diseases with no specific drug currently available. The first step of discovering the medicine is virtual screening with a molecular docking simulation approach. The stable conformation structure of the bioactive compounds was docked into the enzymes SARS-CoV-2 Main Protease (PDB ID: 6XMK) and SARS-CoV-2 Papain-Like Protease (PDB ID: 7CMD). Molecular docking simulations were operated using Molegro Virtual Docker (MVD) program after the validation process. In this study, analysis of the docking simulation was carried out of compounds in Andrographis paniculata, Phyllanthus niruri L., Aloe vera, and Sonchus arvensis. They are medicinal plants that have been used as a medicine for generations and may have potential as antivirals. A docking score with a more negative presentation binding energy value has a more significant potential to be a lead compound. Several potential compounds were evaluated for their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. This method can reduce the trial and error factor in the drug discovery stage, although it needs further proof by experimentation in a wet laboratory.

A multiscale molecular simulation approach for assessing the effects of mutations on functional activity and drug sensitivity in kinases

Recently, precision medicine based on an individual’s genomic background has been advanced for diverse diseases such as cancer. It has been reported that some of gene mutations identified from patients are closely associated with pathological conditions, however the functional effect of these mutations at the molecular level remains poorly understood. Here, we focus on four oncogenic kinases (EGFR, PI3Kα, ALK, and RET), and examine the effects of mutations on kinase activity and drug sensitivity by combining molecular dynamics (MD) simulation, protein-drug binding free energy computation, and quantum mechanical calculation.

Blocking key mutated hotspot residues in the RBD of the omicron variant (B.1.1.529) with medicinal compounds to disrupt the RBD-hACE2 complex using molecular screening and simulation approaches.

A new variant of SARS-CoV-2 known as the omicron variant (B.1.1.529) reported in South Africa with 30 mutations in the whole spike protein, among which 15 mutations are in the receptor-binding domain, is continuously spreading exponentially around the world. The omicron variant is reported to be highly contagious with antibody-escaping activity. The emergence of antibody-escaping variants is alarming, and thus the quick discovery of small molecule inhibitors is needed. Hence, the current study uses computational drug screening and molecular dynamics simulation approaches (replicated) to identify novel drugs that can inhibit the binding of the receptor-binding domain (RBD) with hACE2. Screening of the North African, East African and North-East African medicinal compound databases by employing a multi-step screening approach revealed four compounds, namely (−)-pipoxide (C1), 2-(p-hydroxybenzyl) benzofuran-6-ol (C2), 1-(4-hydroxy-3-methoxyphenyl)-2-{4-[(E)-3-hydroxy-1-propenyl]-2-methoxyphenoxy}-1,3-propanediol (C3), and Rhein (C4), with excellent anti-viral properties against the RBD of the omicron variant. Investigation of the dynamics demonstrates stable behavior, good residue flexibility profiles, and structural compactness. Validation of the top hits using computational bioactivity analysis, binding free energy calculations and dissociation constant (KD) analysis also indicated the anti-viral properties of these compounds. In conclusion, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging omicron variant of SARS-CoV-2.