MM-GBSA Method Research Articles

New Thiazole Carboxamide Derivatives as COX Inhibitors: Design, Synthesis, Anticancer Screening, In Silico Molecular Docking, and ADME Profile Studies.

The goal of this work was to create and test a new series of thiazole carboxamide derivatives for their cyclooxygenase (COX) suppressor and anticancer effects. The compounds were characterized using 1H, 13C NMR, and HRMS spectrum analysis, and their selectivity toward COX-1 and COX-2 was assessed using an in vitro COX inhibition assay kit. Cytotoxicity was assessed using an MTS assay against a panel of cancer and normal cell lines. The docking studies were aided by the Prime MM-GBSA method for estimating binding affinities. The density functional theory (DFT) analysis was performed to assess compound chemical reactivity, which was calculated by computing the border orbital energy of both HOMO and LUMO orbitals, as well as the HOMO-LUMO energy gap. For ADME-T analysis, the QiKProp module was employed. Furthermore, using human X-ray crystal structures, molecular docking studies were carried out to discover the probable binding patterns of these drugs within both COX-1 and COX-2 isozymes. The results demonstrated that the most effective compound against the COX-1 enzyme was 2b with an IC50 of 0.239 μM. It also showed potent activity against COX-2 with an IC50 value of 0.191 μM and a selectivity ratio of 1.251. The highest selectivity ratio was 2.766 for compound 2a against COX-2 with an IC50 dose of 0.958 μM relating to the celecoxib ratio of 23.8 and its IC50 against COX-2 of 0.002 μM. Compound 2j also showed good selectivity toward COX-2 (1.507) with an IC50 value of 0.957 μM. All compounds showed negligible cytotoxic activity against the evaluated normal cell lines, and the IC50 values were more than 300 μM, except for compound 2b, whose IC50 values were 203.71 ± 1.89 and 116.96 ± 2.05 μM against LX-2 and Hek293t cell lines, respectively. Moreover, compound 2b showed moderate anticancer activity against COLO205 and B16F1 cancer cell lines with IC50 values of 30.79 and 74.15 μM, respectively.

Computer-aided drug design approaches applied to screen natural product’s structural analogs targeting arginase in Leishmania spp

Introduction: Leishmaniasis is a disease with high mortality rates and approximately 1.5 million new cases each year. Despite the new approaches and advances to fight the disease, there are no effective therapies. Methods: Hence, this study aims to screen for natural products' structural analogs as new drug candidates against leishmaniasis. We applied Computer-aided drug design (CADD) approaches, such as virtual screening, molecular docking, molecular dynamics simulation, molecular mechanics–generalized Born surface area (MM–GBSA) binding free estimation, and free energy perturbation (FEP) aiming to select structural analogs from natural products that have shown anti-leishmanial and anti-arginase activities and that could bind selectively against the Leishmania arginase enzyme. Results: The compounds 2H-1-benzopyran, 3,4-dihydro-2-(2-methylphenyl)-(9CI), echioidinin, and malvidin showed good results against arginase targets from three parasite species and negative results for potential toxicities. The echioidinin and malvidin ligands generated interactions in the active center at pH 2.0 conditions by MM-GBSA and FEP methods. Conclusions: This work suggests the potential anti-leishmanial activity of the compounds and thus can be further in vitro and in vivo experimentally validated.

Identification of IL-2 inducible tyrosine kinase inhibitors by quantum mechanics and ligand based virtual screening approaches

Interleukin-2-inducible T-cell kinase (ITK) is a crucial intracellular signaling mediator in normal and malignant T-cells and natural killer cells. Selective inhibition of ITK might be useful for treating a variety of disorders including; autoimmune, inflammatory, and neoplastic disorders. Over the past two decades, the clinical management of ITK inhibitors has progressed dramatically. So far, specific inhibitor with no off-target effects against ITK is available. Herein, we aim to discover potential virtual hits to fasten the process of drug design and development against ITK. In this regard, the key chemical characteristics of ITK inhibitors were identified using ligand-based pharmacophore modeling. The validated pharmacophore comprises one hydrogen bond donor and three hydrogen bond acceptors and was utilized as a 3D query in virtual screening using ZINC, Covalent, and in-house databases. A total of 12 hit compounds were chosen on the basis of their critical interactions with the significant amino acids of ITK. The orbital energies such as HOMO and LUMO of the hit compounds were calculated to evaluate the inhibitor’s potencies. Further, molecular dynamics simulation demonstrated the stability of ITK upon binding of selected virtual hits. Binding energy using the MMGBSA method showed the potential binding affinity of all the hits with ITK. The research identifies key chemical characteristics with geometric restrictions that lead to ITK inhibition. Communicated by Ramaswamy H. Sarma

Identification of RdRp inhibitors against SARS-CoV-2 through E-pharmacophore-based virtual screening, molecular docking and MD simulations approaches

The outbreak of novel Coronavirus, an enduring pandemic declared by WHO, has consequences to an alarming ongoing public health menace which has already claimed several million human lives. In addition to numerous vaccinations and medications for mild to moderate COVID-19 infection, lack of promising medication or therapeutic pharmaceuticals remains a serious concern to counter the ongoing coronavirus infections and to hinder its dreadful spread. Global health emergencies have called for urgency for potential drug discovery and time is the biggest constraint apart from the financial and human resources required for the high throughput drug screening. However, computational screening or in-silico approaches appeared to be an effective and faster approach to discover potential molecules without sacrificing the model animals. Accumulated shreds of evidence on computational studies against viral diseases have revealed significance of in-silico drug discovery approaches especially in the time of urgency. The central role of RdRp in SARS-CoV-2 replication makes it promising drug target to curtain on going infection and its spread. The present study aimed to employ E-pharmacophore-based virtual screening to reveal potent inhibitors of RdRp as potential leads to block the viral replication. An energy-optimised pharmacophore model was generated to screen the Enamine REAL DataBase (RDB). Then, ADME/T profiles were determined to validate the pharmacokinetics and pharmacodynamics properties of the hit compounds. Moreover, High Throughput Virtual Screening (HTVS) and molecular docking (SP & XP) were employed to screen the top hits from pharmacophore-based virtual screening and ADME/T screen. The binding free energies of the top hits were calculated by conducting MM-GBSA analysis followed by MD simulations to determine the stability of molecular interactions between top hits and RdRp protein. These virtual investigations revealed six compounds having binding free energies of −57.498, −45.776, −46.248, −35.67, −25.15 and −24.90 kcal/mol respectively as calculated by the MM-GBSA method. The MD simulation studies confirmed the stability of protein ligand complexes, hence, indicating as potent RdRp inhibitors and are promising candidate drugs to be further validated and translated into clinics in future.

Insights into the binding mechanism between α‐TOH and CYP4F2: A homology modeling, molecular docking, and molecular dynamics simulation study

α-Tocopherol (α-TOH) is a potent antioxidant. The concentrations of α-TOH in plasma are closely related to human health. α-TOH can be regulated by the metabolism of cytochrome P450 4F2 (CYP4F2). However, the atomic-level basis for this regulation process remains elusive. Here, we successfully constructed the structure of CYP4F2 by homology modeling and obtained the α-TOH-CYP4F2 complex models using molecular docking. Three parallel 500 ns molecular dynamics simulations were performed on each complex model to investigate the details of the interaction between α-TOH and CYP4F2. MM-GBSA method combined with principal component analysis shows that 8 key residues establish a hydrophobic cavity stabilizing α-TOH in the pocket of CYP4F2 and S423 forms an important hydrogen bond with α-TOH anchoring α-TOH in the favorable position for ω-hydroxylation. Based on our simulation results and the experimental facts, we designed mutation simulation experiments to clarify the important role of two key residues (S423 and V433) in the binding of α-TOH with CYP4F2. The results show that the mutations directly or indirectly change the binding mode of α-TOH and decrease its binding affinity with CYP4F2, which is unfavorable for ω-hydroxylation. Our results could enrich the information on structure-function relationships of CYP4F2 and provide valuable insights into the regulatory mechanism of CYP4F2 on the metabolism of α-TOH.

Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

BRD9 and TAF1(2) have been regarded as significant targets of drug design for clinically treating acute myeloid leukemia, malignancies, and inflammatory diseases. In this study, multiple short molecular dynamics simulations combined with the molecular mechanics generalized Born surface area method were employed to investigate the binding selectivity of three ligands, 67B, 67C, and 69G, to BRD9/TAF1(2) with IC50 values of 230/59 nM, 1400/46 nM, and 160/410 nM, respectively. The computed binding free energies from the MM-GBSA method displayed good correlations with that provided by the experimental data. The results indicate that the enthalpic contributions played a critical factor in the selectivity recognition of inhibitors toward BRD9 and TAF1(2), indicating that 67B and 67C could more favorably bind to TAF1(2) than BRD9, while 69G had better selectivity toward BRD9 over TAF1(2). In addition, the residue-based free energy decomposition approach was adopted to calculate the inhibitor-residue interaction spectrum, and the results determined the gatekeeper (Y106 in BRD9 and Y1589 in TAF1(2)) and lipophilic shelf (G43, F44, and F45 in BRD9 and W1526, P1527, and F1528 in TAF1(2)), which could be identified as hotspots for designing efficient selective inhibitors toward BRD9 and TAF1(2). This work is also expected to provide significant theoretical guidance and insightful molecular mechanisms for the rational designs of efficient selective inhibitors targeting BRD9 and TAF1(2).

STRUCTURAL BIOINFORMATICS STUDY OF THE STRUCTURAL BASIS OF SUBSTRATE SPECIFICITY OF PURINE NUCLEOSIDE PHOSPHORYLASE FROM THERMUS THERMOPHILUS

Molecular dynamics simulations were performed for wild-type purine nucleoside phosphorylase in complexes with two substrates (adenosine and guanosine). The MD simulations were also performed for the mutant form of the enzyme with the same substrates. The free energy changes upon the formation of the complexes were evaluated from the molecular dynamics trajectories by the MM-GBSA method.

Integrative network pharmacology and in silico analyses identify the anti-omicron SARS-CoV-2 potential of eugenol

Eugenol as a natural product is the source of isoniazid, and purified eugenol is extensively used in the cosmetics industry and the productive processes of edible spices. Accumulating evidence suggested that eugenol exerted potent anti-microorganism and anti-inflammation effects. Application of eugenol effectively reduced the risk of atherosclerosis, arterial embolism, and Type 2 diabetes. A previous study confirmed that treatment with eugenol attenuated lung inflammation and improved heart functions in SARS-CoV-2 spike S1-intoxicated mice. In addition to the study, based on a series of public datasets, computational analyses were conducted to characterize the acting targets of eugenol and the functional roles of these targets in COVID-19. The binding capacities of eugenol to conservative sites of SARS-CoV-2 like RNA-dependent RNA polymerase (RdRp) and mutable site as spike (S) protein, were calculated by using molecular docking following the molecular dynamics simulation with RMSD, RMSF, and MM-GBSA methods. The results of network pharmacology indicated that six targets, including PLAT, HMOX1, NUP88, CTSL, ITGB1 andTMPRSS2 were eugenol-SARS-CoV-2 interacting proteins. The omics results of in-silico study further implicated that eugenol increased the expression of SCARB1, HMOX1 and GDF15, especially HMOX1, which were confirmed the potential interacting targets between eugenol and SARS-CoV-2 antigens. Enrichment analyses indicated that eugenol exerted extensive biological effects such as regulating immune infiltration of macrophage, lipid localization, monooxyenase activity, iron ion binding and PPAR signaling. The results of the integrated analysis of eugenol targets and immunotranscription profile of COVID-19 cases shows that eugenol also plays an important role in strengthen of immunologic functions and regulating cytokine signaling. As a complement to the integrated analysis, the results of molecular docking indicated the potential binding interactions between eugenol and four proteins relating to cytokine production/release and the function of T type lymphocytes, including human TLR-4, TCR, NF-κB, JNK and AP-1. Furthermore, results of molecular docking and molecular dynamics (100ns) simulations implicated that stimulated modification of eugenol to the SARS-CoV-2 Omicron Spike-ACE2 complex, especially for human ACE2, and the molecular interaction of eugenol to SARS-CoV-2 RdRp, were no less favorable than two positive controls, molnupiravir and nilotinib. Dynamics (200ns) simulations indicated that the binding capacities and stabilities of eugenol to finger subdomain of RdRp is no less than molnupiravir. However, the simulated binding capacity of eugenol to SARS-CoV-2 wild type RBD and Omicron mutant RBD were less than nilotinib. Eugenol was predicted to have more favor LD50 value and lower cytotoxicity than two positive controls, and eugenol can pass through the blood-brain barrier (BBB). In a brief, eugenol is helpful for attenuating systemic inflammation induced by SARS-CoV-2 infection, due to the direct interaction of eugenol to SARS-CoV-2 proteins and extensive bio-manipulation of pro-inflammatory factors. This study carefully suggests eugenol is a candidate compound of developing drugs and supplement agents against SARS-CoV-2 and its Omicron variants.

Prediction of dual NF-κB/IκB inhibitors using an integrative in-silico approaches

Multiple lines of evidence indicate that the NF-κB signaling pathway plays a pivotal role in carcinogenesis; activation of NF-κB in cancer increases cell proliferation and suppresses apoptosis, both of which define tumor mass development. Inhibiting NF-κB leads to tumor suppression by blocking the IKK-α/β enzymes, thus inhibiting its translocation. Furthermore, protecting p65 from acetylation and phosphorylation inhibits NF-κB through its active site. Some small molecules are assumed to inhibit NF-κB and IκB function separately. This study took one of the previously reported NF-κB inhibitors (compound D4) as a promising lead and predicted some dual NF-κB and IκB inhibitors. We performed a virtual screening (VS) workflow on a library with 186,146 compounds with 75% similarity to compound D4 on both NF-κB and IκB proteins. A total of 186 compounds were extracted from three steps of VS 36 were common in both proteins. These compounds were subjected to the quantum polarized ligand docking to elect potent compounds with the highest binding affinity for NF-κB and IκB proteins. The MM-GBSA method calculates the lowest binding free energy for eight selected compounds. These analyses found three top-ranked compounds for each protein with suitable pharmacokinetics properties and higher in-silico inhibitory ability. In the last screening, compound CID_4969 was introduced to a molecular dynamics (MDs) simulation study as a common inhibitor for both proteins. The MDs confirmed the main interactions between the final elected compound and NF-κB/IκB proteins. Consequently, the presented computational approaches could be used for designing promising anti-cancer agents.Communicated by Ramaswamy H. Sarma

Structure-based virtual screening of novel natural products as chalcone derivatives against SARS-CoV-2 Mpro

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, has spread quickly around the world, causing a global pandemic. It has infected more than 500 million people as of April 28, 2022. Much research has been reported to stop the virus from spreading, but there are currently no approved medicines to treat COVID-19. In this work, a dataset of 142 natural products collected from various medicinal plants was used to perform structure-based virtual screening (SBVS) through the combined application of molecular docking and molecular dynamics (MD) simulation methods. First, the dataset of compounds was optimized using the density functional theory (DFT) approach. The optimized compounds were then submitted to the first screening, which was done by the pKCM web server to look for drug-likeness and the PyRx to look for binding affinity. Among the 142 natural substances, 10 compounds were selected for docking validation. Compounds that interact with CYS145 and LEU141, the essential catalytic residues, as well as compounds with binding affinities less than −8.0 kcal/mol, are considered promising anti-SARS-CoV-2 drug candidates. The top-ranked compounds were then evaluated by MD simulations and MM-GBSA method. These results could help researchers come up with new natural compounds that could be used to treat SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Evaluating the ability of end-point methods to predict the binding affinity tendency of protein kinase inhibitors.

Because of the high economic cost of exploring the experimental impact of mutations occurring in kinase proteins, computational approaches have been employed as alternative methods for evaluating the structural and energetic aspects of kinase mutations. Among the main computational methods used to explore the affinity linked to kinase mutations are docking procedures and molecular dynamics (MD) simulations combined with end-point methods or alchemical methods. Although it is known that end-point methods are not able to reproduce experimental binding free energy (ΔG) values, it is also true that they are able to discriminate between a better or a worse ligand through the estimation of ΔG. In this contribution, we selected ten wild-type and mutant cocrystallized EGFR-inhibitor complexes containing experimental binding affinities to evaluate whether MMGBSA or MMPBSA approaches can predict the differences in affinity between the wild type and mutants forming a complex with a similar inhibitor. Our results show that a long MD simulation (the last 50 ns of a 100 ns-long MD simulation) using the MMGBSA method without considering the entropic components reproduced the experimental affinity tendency with a Pearson correlation coefficient of 0.779 and an R2 value of 0.606. On the other hand, the correlation between theoretical and experimental ΔΔG values indicates that the MMGBSA and MMPBSA methods are helpful for obtaining a good correlation using a short rather than a long simulation period.

Molecular docking and dynamics simulation study of medicinal fungi derived secondary metabolites as potential inhibitor for COVID-19 treatment

The severity of COVID-19, lack of specific treatment, and controversies on the vaccine's efficacy demand the development of new drugs against SARS-CoV-2. Fungi produce various metabolites with diverse molecular structures that have emerged as promising antiviral drug candidates. Therefore, the present study aimed to investigate medicinal fungi derived secondary metabolites as potential inhibitors of 3 different targets associated with viral entry (human TMPRSS2) and replication (main and papain-like protease) through molecular docking and dynamic simulation studies. Based on our findings, we identified Phelligridin E, Lepiotaprocerine G, and Inoscavin A as the potential blockers of SARS-CoV-2 main protease, papain-like protease, and human TMPRSS2, respectively. These compounds strongly interacted with their corresponding target, passed Lipinski Rule's and had acceptable ADMET properties. Drug-protein complexes showed good stability during MD simulation. Estimation of binding free energy using the MM-GBSA method validated the inhibitor potential of identified compounds. Taken together, we believe that further in vitro and in vivo investigations on our proposed molecules may contribute to expanding the therapeutic arsenal in our fight against COVID-19.

Comparative Analysis of the Interfaces between Monomers in the Dimers of Bacterial Histone-Like HU Proteins by the MM-GBSA Method

Comparative Analysis of the Interfaces between Monomers in the Dimers of Bacterial Histone-Like HU Proteins by the MM-GBSA Method

Identification of new potent agonists for toll-like receptor 8 by virtual screening methods, molecular dynamics simulation, and MM-GBSA

Toll-like receptor 8 (TLR8), as an endosomal transmembrane receptor, plays a crucial role in the innate immune response to neoplasia and viruses. Previous studies have shown that TLR8 agonists e.g. Motolimod can be used to treat patients with last-stage cancer. In this study, in order to find new suitable ligands for TLR8, 16 PBD codes related to TLR8 complexes were collected to design the pharmacophore models using the Pharmit server. Then the PubChem, and ZINC databases were screened by them. Subsequently, the ADME-Tox features of the compounds were detected using FAF-Drugs4 and the selected compounds were docked to TLR8 (PDB: 3w3j). Molecular dynamics simulation was used to compare compounds with the best docking scores, with Motolimod in complex with TLR8. Finally, two compounds were identified, PubChem: 124126919 (A) and PubChem: 18559540 (B), each with advantages over Motolimod. As the RMSD results showed that compound A has very good flexibility, in terms of energy calculated using the MM-GBSA method, complex B and TLR8 showed the lowest energy level compared to the rest of the complexes. These observations suggest that these two compounds could be used as TLR8 agonists with the desired pharmacological features in future experimental studies. Communicated by Ramaswamy H. Sarma

Can de-phosphorylation of serine-5 in the C-terminal domain of human polymerase II affect its interaction with the PA C-terminal domain of bat Flu A polymerase?

Influenza viruses depend on the host transcription machinery to create their new progeny viral mRNA. They need the host transcription machinery to hijack the 5’-capped RNA from the host RNAs in order to utilize them to activate their viral transcription. In this study, we computationally regenerated the interaction between 3 heptad repeats, phosphorylated at the fifth serine residue in each repeat, from human polymerase and the CT D of the PA subunit of viral RNA polymerase (Holo 3SEP). We also studied the effect of the de-phosphorylation of the Serine-5 in the middle heptad repeat on the stability of the interaction (Holo 2SEP). The dynamics of the protein association and the heptad repeat in both cases are studied using appropriate in silico tools. This is followed by applying the MM-GBSA method based on relative binding estimation to show the effect of the de-phosphorylation of the middle Serine-5. Results indicate a clear change in total relative binding energy in Holo 2SEP, compared to Holo 3SEP, with no shift in occupied amino acids involved in the interaction in both cases. Knowing that de-phosphorylation of one serine-5 has no significant contribution to the investigated interactions opens the door for further studies to understand the role of the middle heptad serine-5 in these interactions, as its dephosphorylation caused a decrease by ≈13% in the binding affinity values obtained using MM-GBSA. The current in silico study represents a one-step-ahead insight into the RNA-dependent RNA polymerase (RdRP) mechanism that is yet to be verified in the lab. Communicated by Ramaswamy H. Sarma

Deciphering the active constituents of Dabushen decoction of ameliorating osteoarthritis via PPARγ preservation by targeting DNMT1.

Osteoarthritis (OA) is a multifactorial and chronic degenerative joint disease. Due to the adverse effects of currently used drugs, a safer and more effective therapy for treating OA is needed. Peroxisome proliferator-activated receptor-γ (PPARγ) is a key protein protecting cartilage. DNMT1-mediated hypermethylation of PPARγ promoter leads to its suppression. Therefore, DNMT1 might be an effective target for exerting cartilage protective effects by regulating the epigenetic expression of PPARγ. Dabushen decoction (DD) is a representative prescription of Dunhuang ancient medical prescription, which has a potential therapeutic effect on OA. So far, the research of the efficacy and material basis of DD in the treatment of OA remains unclear. In this study, Micro-CT, HE staining, S-O staining, and immunohistochemistry analysis were used to demonstrate that DD increased the expression of PPARγ and collagen synthesis in an OA rat model. Next, the structure of DNMT1 was used to screen the active constituents of DD by molecular docking method for treatment OA. Seven potential active constituents, including isoliquiritigenin, emodin, taxifolin, catalpol, alisol A, zingerone, and schisandrin C were hited. The protective effect of the potential active constituents to chondrocytes were evaluated by protein capillary electrophoresis, immunofluorescence assays, and ex vivo culture of rat knee cartilage. The five constituents, such as alisol A, emodin, taxifolin, isoliquiritigenin, and schisandrin C could promote the expression of PPARγ and ameliorate IL-1β-induced downregulation of collagen II and the production of MMP-13. Alisol A and Emodin could effectively mitigate cartilage damage. At last, molecular dynamics simulations with MM-GBSA method was applied to investigate the interaction pattern of the active constituents and DNMT1 complexes. The five constituents, such as alisol A, emodin, taxifolin, isoliquiritigenin, and schisandrin C achieved a stable binding pattern with DNMT1, in which alisol A has a relatively high binding free energy. In conclusion, this study elucidates that the active constituents of DD (alisol A, emodin, taxifolin, isoliquiritigenin, and schisandrin C) could ameliorate osteoarthritis via PPARγ preservation by targeting DNMT1.These findings facilitated clinical use of DD and provided a valuable strategy for developing natural epigenetic modulators from Chinese herbal formula.

In silico approaches and in vitro assays identify a coumarin derivative as antiviral potential against SARS-CoV-2

COVID-19, a disease caused by SARS-CoV-2, was declared a pandemic in 2020 and created a global crisis in health systems, with more than 545 million confirmed cases and 6.33 million deaths. In this sense, this work aims to identify possible inhibitors of the SARS-CoV-2 RdRp enzyme using in silico approaches. RdRp is a crucial enzyme in the replication and assembly cycle of new viral particles and a critical pharmacological target in the treatment of COVID-19. We performed a virtual screening based on molecular docking from our in-house chemical library, which contains a diversity of 313 structures from different chemical classes. Nine compounds were selected since they showed important interactions with the active site from RdRp. Next, the ADME-Tox in silico predictions served as a filter and selected the three most promising compounds: a coumarin LMed-052, a hydantoin LMed-087, and a guanidine LMed-250. Molecular dynamics simulations revealed details such as changes in the positions of ligands and catalytic residues during the simulations compared to the complex from molecular docking studies. Binding free energy analysis was performed using the MMGBSA method, demonstrating that LMed-052 and LMed-087 have better affinities for the RdRp by energetic contributions to the stability of the complexes when compared to LMed-250. Furthermore, LMed-052 showed significant in vitro inhibition against MHV-3, decreasing 99% of viral titers. Finally, these findings are useful to guide structural modifications aiming to improve the potential of these compounds to act as inhibitors of SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Atomistic insights into the binding of SARS-CoV-2 spike receptor binding domain with the human ACE2 receptor: The importance of residue 493

SARS-CoV-2 is a coronavirus that has created a global pandemic. The virus contains a spike protein which has been shown to bind to the ACE2 receptor on the surface of human cells. Vaccines have been developed that recognize elements of the SARS-CoV-2 spike protein and they have been successful in preventing infection. Recently, the Omicron variant of the SARS-CoV-2 virus was reported and quickly became a variant of concern due to its transmissibility. This variant contained an unusually large number (32) of point mutations, of which 15 of those mutations are in the receptor binding domain of the spike protein. While several computational and experimental investigations comparing the binding of the Omicron and wild type RBD to the human ACE2 receptor have been conducted, many of these report contradictory findings. In order to assess the differential binding ability, we conducted 2 μs of classical molecular dynamics (cMD) simulation to estimate the binding affinities and behaviors. Based upon MM-GBSA binding affinity, per-residue energy decomposition analysis, center of mass distance measurements, ensemble clustering, pairwise residue decomposition and hydrogen bonding analysis, our results suggest that a single point mutation is responsible for the enhanced binding of the Omicron mutant relative to the WT. While the 15-point mutations in the receptor binding domain contribute positively and negatively to the affinity of the spike protein for the human ACE2 receptor, it is the point mutation Q493R that confers enhanced binding while the Q493K mutation results in similar binding. The MM-GBSA binding estimations over a 2 μs trajectory, suggest that the wild type binds to ACE2 with a value of −29.69 kcal/mol while the Q493K and Q493R Omicron mutants bind with energy values of −26.67 and −34.56 kcal/mol, respectively. These values are significantly different, given the error estimates associated with the MM-GBSA method. In general, while some mutations increase binding, more mutations diminish binding, leading to an overall similar picture of binding for Q493K and enhanced binding for Q493R.

Glycosylated Flavonoid Compounds as Potent CYP121 Inhibitors of Mycobacterium tuberculosis.

Due to the concerning rise in the number of multiple- and prolonged-drug-resistant (MDR and XDR) Mycobacterium tuberculosis (Mtb) strains, unprecedented demand has been created to design and develop novel therapeutic drugs with higher efficacy and safety. In this study, with a focused view on implementing an in silico drug design pipeline, a diverse set of glycosylated flavonoids were screened against the Mtb cytochrome-P450 enzyme 121 (CYP121), which is established as an approved drug target for the treatment of Mtb infection. A total of 148 glycosylated flavonoids were screened using structure-based virtual screening against the crystallized ligand, i.e., the L44 inhibitor, binding pocket in the Mtb CYP121 protein. Following this, only the top six compounds with the highest binding scores (kcal/mol) were considered for further intermolecular interaction and dynamic stability using 100 ns classical molecular dynamics simulation. These results suggested a considerable number of hydrogen and hydrophobic interactions and thermodynamic stability in comparison to the reference complex, i.e., the CYP121-L44 inhibitor. Furthermore, binding free energy via the MMGBSA method conducted on the last 10 ns interval of MD simulation trajectories revealed the substantial affinity of glycosylated compounds with Mtb CYP121 protein against reference complex. Notably, both the docked poses and residual energy decomposition via the MMGBSA method demonstrated the essential role of active residues in the interactions with glycosylated compounds by comparison with the reference complex. Collectively, this study demonstrates the viability of these screened glycosylated flavonoids as potential inhibitors of Mtb CYP121 for further experimental validation to develop a therapy for the treatment of drug-resistant Mtb strains.

Identification of Potential Cytochrome P450 3A5 Inhibitors: An Extensive Virtual Screening through Molecular Docking, Negative Image-Based Screening, Machine Learning and Molecular Dynamics Simulation Studies.

Cytochrome P450 3A5 (CYP3A5) is one of the crucial CYP family members and has already proven to be an important drug target for cardiovascular diseases. In the current study, the PubChem database was screened through molecular docking and high-affinity molecules were adopted for further assessment. A negative image-based (NIB) model was used for a similarity search by considering the complementary shape and electrostatics of the target and small molecules. Further, the molecules were segregated into active and inactive groups through six machine learning (ML) matrices. The active molecules found in each ML model were used for in silico pharmacokinetics and toxicity assessments. A total of five molecules followed the acceptable pharmacokinetics and toxicity profiles. Several potential binding interactions between the proposed molecules and CYP3A5 were observed. The dynamic behavior of the selected molecules in the CYP3A5 was explored through a molecular dynamics (MD) simulation study. Several parameters obtained from the MD simulation trajectory explained the stability of the protein–ligand complexes in dynamic states. The high binding affinity of each molecule was revealed by the binding free energy calculation through the MM-GBSA methods. Therefore, it can be concluded that the proposed molecules might be potential CYP3A5 molecules for therapeutic application in cardiovascular diseases subjected to in vitro/in vivo validations.