Classification of VUS and unclassified variants in BRCA1 BRCT repeats by molecular dynamics simulation

A novel small molecule ZYZ384 targeting SMYD3 for hepatocellular carcinoma via reducing H3K4 trimethylation of the Rac1 promoter

SMYD3 (SET and MYND domain-containing 3) is a histone lysine methyltransferase highly expressed in different types of cancer(s) and is a promising epigenetic target for developing novel antitumor therapeutics. No selective inhibitors for this protein have been developed for cancer treatment. Therefore, the current study describes developing and characterizing a novel small molecule ZYZ384 screened and synthesized based on SMYD3 structure. Virtual screening was initially used to identify a lead compound and followed up by modification to get the novel molecules. Several technologies were used to facilitate compound screening about these novel molecules' binding affinities and inhibition activities with SMYD3 protein; the antitumor activity has been assessed in vitro using various cancer cell lines. In addition, a tumor-bearing nude mice model was established, and the activity of the selected molecule was determined in vivo. Both RNA-seq and chip-seq were performed to explore the antitumor mechanism. This work identified a novel small molecule ZYZ384 targeting SMYD3 with antitumor activity and impaired hepatocellular carcinoma tumor growth by reducing H3K4 trimethylation of the Rac1 promoter triggering the tumor cell cycle arrest through the AKT pathway.

Cholinergic Inhibition and Antioxidant Potential of Gongronema latifolium Benth Leaf in Neurodegeneration: Experimental and In Silico Study

The use of Gongronema latifolium for the management of various forms of neurological disorders has generated a lot of interest in the need to further investigate its neurotherapeutic constituents. This work, therefore, focused on assessing the inhibitory potential of selected bioactive components derived from G. latifolium against key neurotherapeutic targets and oxidant species associated with neurodegeneration using in vitro analysis and biomolecular modelling. G. latifolium methanol extract (GLME), solvent partition, chromatographic fractions (A-F) of GLME and pregnane compounds (Iloneoside and marsectohexol) derived from fraction-B with the highest activity were investigated for in vitro acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and monoamine oxidase (MAO) inhibition in addition to their in vitro antioxidant activities. The interactions of iloneoside, marsectohexol, and reference drugs with human acetylcholinesterase, butyrylcholinesterase, and β-secretase (BACE-1) were further assessed using molecular docking, binding free energy calculations, cluster analysis, and molecular dynamics simulations. The GLME and fractions inhibited the activities of both acetylcholinesterase and butyrylcholinesterase in a dose-dependent manner. Iloneoside and marsectohexol exhibited in vitro concentration-dependent inhibitory activities against acetylcholinesterase (IC50 = 19.28, 184.9 µM, respectively) and butyrylcholinesterase (IC50 = 30.75, 43.4 µM, respectively). These compounds also possess ferric ion-reducing, hydroxyl, and superoxide radical-scavenging activities. Iloneoside had the highest docking scores of -9.8, -9.9 -9.4 Kcal for AChE, BChE, and BACE1, respectively. The stability of the interaction of the bioactive compounds with the catalytic residues of the protein targets was preserved in a 100 ns molecular dynamics simulation. Iloneoside, a rare pregnane glycoside, was identified as a neurotherapeutic constituent of G. latifolium leaf. Further studies are suggested to investigate the neurotherapeutic potential in animal models.

Comprehensive classification of TP53 somatic missense variants based on their impact on p53 structural stability

Somatic variation is a major type of genetic variation contributing to human diseases including cancer. Of the vast quantities of somatic variants identified, the functional impact of many somatic variants, in particular the missense variants, remains unclear. Lack of the functional information prevents the translation of rich variation data into clinical applications. We previously developed a method named Ramachandran Plot-Molecular Dynamics Simulations (RP-MDS), aiming to predict the function of germline missense variants based on their effects on protein structure stability, and successfully applied to predict the deleteriousness of unclassified germline missense variants in multiple cancer genes. We hypothesized that regardless of their different genetic origins, somatic missense variants and germline missense variants could have similar effects on the stability of their affected protein structure. As such, the RP-MDS method designed for germline missense variants should also be applicable to predict the function of somatic missense variants. In the current study, we tested our hypothesis by using the somatic missense variants in TP53 as a model. Of the 397 somatic missense variants analyzed, RP-MDS predicted that 195 (49.1%) variants were deleterious as they significantly disturbed p53 structure. The results were largely validated by using a p53-p21 promoter-green fluorescent protein (GFP) reporter gene assay. Our study demonstrated that deleterious somatic missense variants can be identified by referring to their effects on protein structural stability.

Machine Learning of Three-Dimensional Protein Structures to Predict the Functional Impacts of Genome Variation

Research in the human genome sciences generates a substantial amount of genetic data for hundreds of thousands of individuals, which concomitantly increases the number of variants of unknown significance (VUS). Bioinformatic analyses can successfully reveal rare variants and variants with clear associations with disease-related phenotypes. These studies have had a significant impact on how clinical genetic screens are interpreted and how patients are stratified for treatment. There are few, if any, computational methods for variants comparable to biological activity predictions. To address this gap, we developed a machine learning method that uses protein three-dimensional structures from AlphaFold to predict how a variant will influence changes to a gene's downstream biological pathways. We trained state-of-the-art machine learning classifiers to predict which protein regions will most likely impact transcriptional activities of two proto-oncogenes, nuclear factor erythroid 2 (NFE2L2)-related factor 2 (NRF2) and c-Myc. We have identified classifiers that attain accuracies higher than 80%, which have allowed us to identify a set of key protein regions that lead to significant perturbations in c-Myc or NRF2 transcriptional pathway activities.

Identification of potential inhibitors of cholinergic and β-secretase enzymes from phytochemicals derived from Gongronema latifolium Benth leaf: an integrated computational analysis

Neurodegenerative disorders (NDDs) are associated with increased activities of the brain acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and β-secretase enzyme (BACE1). Inhibition of these enzymes affords therapeutic option for managing NDDs such as Alzheimer's disease (AD) and Parkinson's disease (PD). Although, Gongronema latifolium Benth (GL) has been widely documented in ethnopharmacological and scientific reports for the management of NDDs, there is paucity of information on its underlying mechanism and neurotherapeutic constituents. Herein, 152 previously reported Gongronema latifolium derived-phytochemicals (GLDP) were screened against hAChE, hBChE and hBACE-1 using molecular docking, molecular dynamics (MD) simulations, free energy of binding calculations and cluster analysis. The result of the computational analysis identified silymarin, alpha-amyrin and teraxeron with the highest binding energies (-12.3, -11.2, -10.5 Kcal/mol) for hAChE, hBChE and hBACE-1 respectively as compared with those of the reference inhibitors (-12.3, -9.8 and - 9.4 for donepezil, propidium and aminoquinoline compound respectively). These best docked phytochemicals were found to be orientated in the hydrophobic gorge where they interacted with the choline-binding pocket in the A-site and P-site of the cholinesterase and subsites S1, S3, S3' and flip (67-75) residues of the pocket of the BACE-1. The best docked phytochemicals complexed with the target proteins were stable in a 100 ns molecular dynamic simulation. The interactions with the catalytic residues were preserved during the simulation as observed from the MMGBSA decomposition and cluster analyses. The presence of these phytocompounds most notably silymarin, which demonstrated dual high binding tendencies to both cholinesterases, were identified as potential neurotherapeutics subject to further investigation.

Elemental evaluation, nutritional analysis, GC-MS analysis and ameliorative effects of Artocarpus communis J.R.Forst. & G.Forst. seeds' phytoconstituents on metabolic syndrome via in silico approach

The nutritional as well as beneficial effects of the Artocarpus communis seed on metabolic syndrome complications have not been studied. In this research, the aim was to investigate the nutritional composition and beneficial effects of Artocarpus communis seeds' phytoconstituents on the p53 core, fat mass and obesity-associated (FTO) protein and cytochrome P450 CYP11A1 domains. The elements and phytochemicals in the seed were determined through atomic absorption spectroscopy assay and gas chromatography-mass spectrometry (GC-MS) analysis, respectively. Also, the compounds detected were docked to the p53 core, FTO protein and cytochrome P450 CYP11A1 domains protein. Artocarpus communis seed contains sodium (7.824 ± 0.0134 ppm), magnesium (10.187 ± 0.0239 ppm) and iron (1.924 ± 0.0017), while zinc and cadmium were undetected. Phenolics and flavonoids were the most abundant phytochemicals in the seed. Phytoconstituents, such as pentadecanoic acid, hexadecanoic acid and methyl ester, possessing different therapeutic effects were identified via GC-MS analysis. In A. communis seed, 3-methyl-4-nitro-5-(1-pyrazolyl) pyrazole and phenanthrene were able to bind more peculiarly and specifically to the p53 core, FTO protein and cytochrome P450 CYP11A1 domains. One of the important processes that were hypothesized for the recovery of metabolic syndrome in affected victims is shown by the molecular dynamics analysis, which shows that the binding of these chemicals to the targeted structure stabilized the proteins. Therefore, Artocarpus communis seeds could be a new strategy for the management of metabolic syndrome.Communicated by Ramaswamy H. Sarma.

Computational Screening of Neuropilin-1 Unveils Novel Potential Anti-SARS-CoV-2 Therapeutics

Neuropilin 1 (NRP-1) inhibition has shown promise in reducing the infectivity of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and preventing the virus entry into nerve tissues, thereby mitigating neurological symptoms in COVID-19 patients. In this study, we employed virtual screening, including molecular docking, Molecular Dynamics (MD) simulation, and Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculations, to identify potential NRP-1 inhibitors. From a compendium of 1930 drug-like natural compounds, we identified five potential leads: CNP0435132, CNP0435311, CNP0424372, CNP0429647, and CNP0427474, displaying robust binding energies of -8.2, -8.1, -10.7, -8.2, and -8.2 kcal/mol, respectively. These compounds demonstrated interactions with critical residues Tyr297, Trp301, Thr316, Asp320, Ser346, Thr349, and Tyr353 located within the b1 subdomain of NRP-1. Furthermore, MD simulations and MM-PBSA calculations affirmed the stability of the complexes formed, with average root mean square deviation, radius of gyration, and solvent accessible surface area values of 0.118 nm, 1.516 nm, and 88.667 nm2 , respectively. Notably, these lead compounds were estimated to penetrate the blood-brain barrier and displayed antiviral properties, with Pa values ranging from 0.414 to 0.779. The antagonistic effects of these lead compounds merit further investigation, as they hold the potential to serve as foundational scaffolds for the development of innovative therapeutics aimed at reducing the neuroinfectivity of SARS-CoV-2.

Therapeutic Study of Cinnamic Acid Derivative for Oxidative Stress Ablation: The Computational and Experimental Answers

This study aimed to examine the therapeutic activity of the cinnamic acid derivative KAD-7 (N'-(2,4-dichlorobenzylidene)-3-(4-methoxyphenyl) acrylohydrazide) on Fe2+-induced oxidative hepatic injury via experimental and computational models. In addition, the role of ATPase and ectonucleoside triphosphate diphosphohydrolase (ENTPDase) in the coordination of cellular signals is speculated upon to proffer suitable therapeutics for metabolic stress disorder upon their inhibition. While we know little about therapeutics with flexible dual inhibitors for these protein targets, this study was designed to screen KAD-7's (N'-(2,4-dichlorobenzylidene)-3-(4-methoxyphenyl) acrylohydrazide) inhibitory potential for both protein targets. We induced oxidative hepatic damage via the incubation of hepatic tissue supernatant with 0.1 mM FeSO4 for 30 min at 37 °C. We achieved the treatment by incubating the hepatic tissues with KAD-7 under the same conditions. The catalase (CAT), glutathione (GSH), malondialdehyde (MDA), ATPase, and ENTPDase activity were all measured in the tissues. We predicted how the drug candidate would work against ATPase and ENTPDase targets using molecular methods. When hepatic injury was induced, there was a significant decrease in the levels of the GSH, CAT, and ENTPDase (p < 0.05) activities. In contrast, we found a noticeable rise in the MDA levels and ATPase activity. KAD-7 therapy resulted in lower levels of these activities overall (p < 0.05), as compared to the control levels. We found the compound to have a strong affinity for ATPase (-7.1 kcal/mol) and ENTPDase (-7.4 kcal/mol), and a better chemical reactivity than quercetin. It also met all drug-likeness parameters. Our study shows that KAD-7 can protect the liver from damage caused by FeSO4 by reducing oxidative stress and purinergic actions. Our studies indicate that KAD-7 could be developed as a therapeutic option since it can flexibly inhibit both ATPase and ENTPDase.

Screening of potential inhibitors of Leishmania major N-myristoyltransferase from Azadirachta indica phytochemicals for leishmaniasis drug discovery by molecular docking, molecular dynamics simulation and density functional theory methods

Leishmaniasis is one of the most neglected parasitic diseases worldwide. The toxicity of current drugs used for its treatment is a major obstacle to their effectiveness, necessitating the discovery and development of new therapeutic agents for better disease control. In Leishmania parasites, N-Myristoyltransferase (NMT) has been identified as a promising target for drug development. Thus, exploring well-known medicinal plants such as Azadirachta indica and their phytochemicals can offer a diverse range of treatment options, potentially leading to disease prevention and control. To assess the therapeutic potential of these compounds, their ADMET prediction and drug-likeness properties were analyzed. The top 4 compounds were selected which had better and significantly low binding energy than the reference molecule QMI. Based on the binding energy score of the top compounds, the results show that Isonimocinolide has the highest binding affinity (-9.8 kcal/mol). In addition, a 100 ns MD simulation of the four best compounds showed that Isonimocinolide and Nimbolide have good stability with LmNMT. These compounds were then subjected to MMPBSA (last 30 ns) calculation to analyze protein-ligand stability and dynamic behavior. Nimbolide and Meldenin showed lowest binding free energy i.e. -84.301 kJ/mol and -91.937 kJ/mol respectively. DFT was employed to calculate the HOMO-LUMO energy gap, global reactivity parameters, and molecular electrostatic potential of all hit molecules. The promising results obtained from MD simulations and MMPBSA analyses provide compelling evidence for the potential use of these compounds in future drug development efforts for the treatment of leishmaniasis.Communicated by Ramaswamy H. Sarma.

In silico and structure-based assessment to classify VUS identified in the α-helical domain of BRCA2

Breast cancer type 2 susceptibility (BRCA2) protein plays a crucial role in DNA double-strand breaks repair mechanism by homologous recombination. Pathogenic mutations in the BRCA2 gene confer an increased risk of hereditary breast and ovarian cancer (HBOC). Different missense mutations are identified from a larger cohort of patient populations in the BRCA2. However, most missense mutations are classified as 'Variants of Uncertain Significance' (VUS) due to a lack of data from structural, functional, and clinical assessments. Therefore, this study focused on assessing VUS identified in the α-helical domain of h-BRCA2 using different in silico tools and structure-based molecular dynamics simulation. A total of 286 identified VUS were evaluated using Align-GVGD, PROVEAN and PANTHER servers and 18 variants were predicted to be pathogenic. Further, out of 18 variants analyzed using the ConSurf server, 16 variants were found to be evolutionary conserved. These 16 conserved variants were submitted to PremPS and Dynamut server to assess the effect of the mutation at the protein structure level; 12 mutations were predicted to have a destabilizing effect on the native protein structure. Finally, molecular dynamics simulations revealed 5 variants BRCA2 Cys2646Tyr, Asp2665Val, Trp2619Arg, Trp2619Ser and Tyr2660Cys can alter the folding pattern and need further validation using in vitro, structural and in vivo studies to classify as pathogenic.Communicated by Ramaswamy H. Sarma.

Antispasmodic Effect of Alstonia boonei De Wild. and Its Constituents: Ex Vivo and In Silico Approaches

BACKGROUND

Alstonia boonei, belonging to the family Apocynaceae, is one of the best-known medicinal plants in Africa and Asia. Stem back preparations are traditionally used as muscle relaxants. This study investigated the antispasmodic properties of Alstonia boonei Stem back and its constituents.

METHOD

The freeze-dried aqueous Stem back extract of A. boonei, as well as dichloromethane (DCM), ethyl acetate, and aqueous fractions, were evaluated for their antispasmodic effect via the ex vivo method. Two compounds were isolated from the DCM fraction using chromatographic techniques, and their antispasmodic activity was evaluated. An in silico study was conducted by evaluating the interaction of isolated compounds with human PPARgamma-LBD and human carbonic anhydrase isozyme.

RESULTS

The Stem back crude extract, DCM, ethyl acetate, and aqueous fractions showed antispasmodic activity on high-potassium-induced (K+ 80 mM) contractions on isolated rat ileum with IC50 values of 0.03 ± 0.20, 0.02 ± 0.05, 0.03 ± 0.14, and 0.90 ± 0.06 mg/mL, respectively. The isolated compounds from the DCM fraction were β-amyrin and boonein, with only boonein exhibiting antispasmodic activity on both high-potassium-induced (IC50 = 0.09 ± 0.01 µg/mL) and spontaneous (0.29 ± 0.05 µg/mL) contractions. However, β-amyrin had a stronger interaction with the two proteins during the simulation.

CONCLUSION

The isolated compounds boonein and β-amyrin could serve as starting materials for the development of antispasmodic drugs.

Statistical Mechanics Metrics in Pairing and Parsing In Silico and Phenotypic Data of a Novel Genetic NFκB1 (c.T638A) Variant

(1) Background: Mutations in NFκB1, a transcriptional regulator of immunomodulating proteins, are a known cause of inborn errors of immunity. Our proband is a 22-year-old male with a diagnosis of common variable immunodeficiency (CVID), cytopenias with massive splenomegaly, and nodular regenerative hyperplasia of the liver. Genetic studies identified a novel, single-point mutation variant in NFκB1, c. T638A p. V213E. (2) Methods: Next-generation panel sequencing of the patient uncovered a novel single-point mutation in the NFκB1 gene that was modeled using the I-TASSER homology-modeling software, and molecular dynamics were assessed using the YASARA2 software (version 20.14.24). (3) Results: This variant replaces valine with glutamic acid at position 213 in the NFκB1 sequence. Molecular modeling and molecular dynamic studies showed altered dynamics in and around the rel homology domain, ankyrin regions, and death domain of the protein. We postulate that these changes alter overall protein function. (4) Conclusions: This case suggests the pathogenicity of a novel variant using protein-modeling techniques and molecular dynamic simulations.

Classification of PTEN missense VUS through exascale simulations

Phosphatase and tensin homolog (PTEN), a tumor suppressor with dual phosphatase properties, is a key factor in PI3K/AKT signaling pathway. Pathogenic germline variation in PTEN can abrogate its ability to dephosphorylate, causing high cancer risk. Lack of functional evidence lets numerous PTEN variants be classified as variants of uncertain significance (VUS). Utilizing Molecular Dynamics (MD) simulations, we performed a thorough evaluation for 147 PTEN missense VUS, sorting them into 66 deleterious and 81 tolerated variants. Utilizing replica exchange molecular dynamic (REMD) simulations, we further assessed the variants situated in the catalytic core of PTEN's phosphatase domain and uncovered conformational alterations influencing the structural stability of the phosphatase domain. There was a high degree of agreement between our results and the variants classified by Variant Abundance by Massively Parallel Sequencing, saturation mutagenesis, multiplexed functional data and experimental assays. Our extensive analysis of PTEN missense VUS should benefit their clinical applications in PTEN-related cancer.

SIGNIFICANCE STATEMENT

Classification of PTEN variants affecting its lipid phosphatase activity is important for understanding the roles of PTEN variation in the pathogenesis of hereditary and sporadic malignancies. Of the 3000 variants identified in PTEN, 1296 (43%) were assigned as VUS. Here, we applied MD and REMD simulations to investigate the effects of PTEN missense VUS on the structural integrity of the PTEN phosphatase domain consisting the WPD, P and TI active sites. We classified a total of 147 missense VUS into 66 deleterious and 81 tolerated variants by referring to the control group comprising 54 pathogenic and 12 benign variants. The classification was largely in concordance with these classified by experimental approaches.

Phyllanthus emblica (Amla) methanolic extract regulates multiple checkpoints in 15-lipoxygenase mediated inflammopathies: Computational simulation and in vitro evidence

Amla (Phyllanthus emblica) has long been used in traditional folk medicine to prevent and cure a variety of inflammatory diseases. In this study, the antioxidant activity (DPPH scavenging and reducing power), anti-inflammatory activity (RBC Membrane Stabilization and 15-LOX inhibition), and anticoagulation activity (Serin protease inhibition and Prothrombin Time assays) of the methanolic extract of amla were conducted. Amla exhibited a substantial amount of phenolic content (TPC: 663.53 mg GAE/g) and flavonoid content (TFC: 418.89 mg GAE/g). A strong DPPH scavenging effect was observed with an IC50 of 311.31 µg/ml as compared to standard ascorbic acid with an IC50 of 130.53 µg/ml. In reducing power assay, the EC50 value of the extract was found to be 196.20 µg/ml compared to standard ascorbic acid (EC50 = 33.83 µg/ml). The IC50 value of the RBC membrane stabilization and 15-LOX assays was observed as 101.08 µg/ml (IC50 of 58.62 µg/ml for standard aspirin) and 195.98 µg/ml (IC50 of 19.62 µg/ml for standard quercetin), respectively. The extract also strongly inhibited serine protease (trypsin) activity with an IC50 of 505.81 µg/ml (IC50 of 295.44 µg/ml for standard quercetin). The blood coagulation time (PTT) was found to be 11.91 min for amla extract and 24.11 min for standard Warfarin. Thus, the findings of an in vitro study revealed that the methanolic extract of amla contains significant antioxidant, anti-inflammatory, and anticoagulation activity. Furthermore, in silico docking and simulation of reported phytochemicals of amla with human 15-LOXA and 15-LOXB were carried out to validate the anti-inflammatory activity of amla. In this analysis, epicatechin and catechin showed greater molecular interaction and were considerably stable throughout the 100 ns simulation with 15-lipoxygenase A (15-LOXA) and 15-lipoxygenase B (15-LOXB) respectively.

DARVIC: Dihedral angle-reliant variant impact classifier for functional prediction of missense VUS

BACKGROUND

Of the large number of genetic variants identified, the functional impact for most of them remains unknown. Mutations in DNA damage repair genes such as MUTYH, which is involved in repairing A:8-oxoG mismatches caused by reactive oxygen species, can cause a higher risk of cancer. Mutations happening in other key genes such as TP53 also pose huge health threats and risk of cancer. The interpretation of genetic variants' functional impact is a forefront issue that needs to be addressed. Many different in silico methods based on different principles have been developed and applied in interpreting genetic variants. However, a current challenge is that many existing methods tend to overpredict the pathogenicity of benign variants. A new approach is needed to tackle this issue to improve genetic variant interpretation through the use of in silico methods.

METHODS

In this study, we developed another protein structural-based approach called Dihedral angle-reliant variant impact classifier (DARVIC) to predict the deleterious impact of the coding-changing missense variants. DARVIC uses Ramachandran's principle of protein stereochemistry as the theoretical foundation and uses molecular dynamics simulations coupled with a supervised machine learning algorithm XGBoost to determine the functional impact of missense variants on protein structural stability.

RESULTS

We characterized the features of dihedral angles in dynamic protein structures. We also tested the performance of DARVIC in MUTYH and TP53 missense variants and achieved satisfactory results in reflecting the functional impacts of the variants on protein structure. The method achieved a balanced accuracy of 84% in a functionally validated MUTYH dataset containing both benign and pathogenic missense variants, higher than other existing in silico methods. Along with that, DARVIC was able to predict 119 (47%) deleterious variants from a dataset of 254 MUTYH VUS. Further application of DARVIC to a functionally validated TP53 dataset had a balanced accuracy of 94%, topping other methods, demonstrating DARVIC's robustness.

CONCLUSION

DARVIC provides a valuable tool to predict the functional impacts of missense variants based on their effects on protein structural stability and motion. At its current state, DARVIC performed well in predicting the functional impact of the missense variants both in MUTYH and TP53. We expect its high potential to predict functional impact for the missense variants in other genes.

A computational study of structural analysis of Class I human glucose-6-phosphate dehydrogenase (G6PD) variants: Elaborating the correlation to chronic non-spherocytic hemolytic anemia (CNSHA)

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the most common human enzyme defect that affects more than 500 million people worldwide. Individuals affected with G6PD deficiency may occasionally suffer mild-to-severe chronic hemolytic anemia. Chronic non-spherocytic hemolytic anemia (CNSHA) is a potential result of the Class I G6PD variants. This comparative computational study attempted to correct the defect in variants structure by docking the AG1 molecule to selected Class I G6PD variants [G6PD^Nashville (Arg393His), G6PD^Alhambra (Val394Leu), and G6PD^Durham (Lys238Arg)] at the dimer interface and structural NADP⁺ binding site. It was followed by an analysis of the enzyme conformations before and after binding to the AG1 molecule using the molecular dynamics simulation (MDS) approach, while the severity of CNSHA was determined via root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), hydrogen bonds, salt bridges, radius of gyration (Rg), solvent accessible surface area analysis (SASA), and principal component analysis (PCA). The results revealed that G6PD^Nashville (Arg393His) and G6PD^Durham (Lys238Arg) had lost the direct contact with structural NADP⁺ and salt bridges at Glu419 - Arg427 and Glu206 - Lys407 were disrupted in all selected variants. Furthermore, the AG1 molecule re-stabilized the enzyme structure by restoring the missing interactions. Bioinformatics approaches were also used to conduct a detailed structural analysis of the G6PD enzyme at a molecular level to understand the implications of these variants toward enzyme function. Our findings suggest that despite the lack of treatment for G6PDD to date, AG1 remains a novel molecule that promotes activation in a variety of G6PD variants.

A global perspective on the ethnic-specific BRCA variation and its implication in clinical application

Pathogenic BRCA1 and BRCA2 (BRCA) variation is the genetic predisposition for high cancer risk affecting mostly breast and ovarian. BRCA variation information is widely used in clinical diagnosis, treatment, and prevention of BRCA-related cancer. The positive selection imposed on human BRCA leads to highly ethnic-specific BRCA variation to adapt different living environment on earth. Most of the human BRCA variants identified so far were from the European descendant populations and used as the standard reference for global human populations, whereas BRCA variation in other ethnic populations remains poorly characterized. This review addresses the origin of ethnic-specific BRCA variation, the importance of ethnic-specific BRCA variation in clinical application, the limitation of current BRCA variation data, and potential solutions to fill the gap.

Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods

Proteins sample an ensemble of conformers under physiological conditions, having access to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the adaptation to various interactions in the cell, and largely assist in, if not determine, viable mechanisms of biological function. In recent years, machine learning frameworks have proven uniquely useful in structural biology, and recent studies further provide evidence to the utility and/or necessity of considering intrinsic dynamics for increasing their predictive ability. Efficient quantification of dynamics-based attributes by recently developed physics-based theories and models such as elastic network models provides a unique opportunity to generate data on dynamics for training ML models towards inferring mechanisms of protein function, assessing pathogenicity, or estimating binding affinities.

In silico prediction of the possible antidiabetic and anti-inflammatory targets of Nymphaea lotus-derived phytochemicals and mechanistic insights by molecular dynamics simulations

Nymphaea lotus is used traditionally for the treatment of diabetes and its complications. However, the mode of action and the likely bioactive phytochemicals involved are not yet fully explored. GC-MS analysis was employed to identify the inherent compounds in N. lotus leaves. To gain an insight into the antidiabetic mode of action of this plant, the identified phytochemicals were subjected to computational studies against four molecular targets of diabetes, dipeptidyl peptidase-4, glycogen synthase kinase 3, NADPH oxidase (NOX), sodium-glucose co-transporter-2, and one target of inflammation, cyclooxygenase-2. Compounds with notable binding affinity were subjected to druggability test. Results from molecular docking showed that seven of the compounds investigated exhibited druggability properties and had outstanding binding affinity values for these targets relative to values obtained for the respective standards of each of the targets. Analysis of the MD trajectories from a 100 ns atomistic run shows that the integrities of the complex systems were more stable and preserved throughout the simulation than the unbound protein. These results indicated that the antidiabetic and anti-inflammatory effects of these compounds might be via the inhibition of these targets, laying the foundation for further studies, such as in vitro and in vivo studies to fully validate the anti-diabetic agents from this plant.Communicated by Ramaswamy H. Sarma.

Evaluation of Antimalarial Activity of Ethanolic Extract of Annona muricata L.: An in vivo and an in silico Approach

In Nigeria, Annona muricata L. has been used to treat a variety of ailments. The mechanism of the antimalarial activity of ethanolic leaf extract of Annona muricata (EEAML) was investigated using both an in vivo and an in silico approach. The experimental mice were divided into five groups: A-F. The mice in groups B-F were inoculated with Plasmodium berghei NK-65 and treated accordingly. Groups A and B are the negative and positive controls (infected and untreated), respectively. Group C received 10 mg/kg chloroquine (standard drug), whereas groups D-F received 100, 200, and 300 mg/kg body weight of the extract orally respectively. The mice were euthanized eight days after infection, and their liver and blood were collected and used in biochemical tests. Molecular docking was performed using the extract's HPLC compounds and Plasmodium falciparum proteins. In the suppressive, prophylactic, and curative tests, there was a significant decrease (p < 0.05) in parasitemia levels in groups treated with the extract compared to the positive control and standard drug. When compared to the positive control, there was a significant (p < 0.05) reduction in liver MDA, total cholesterol, and total triglyceride levels. The binding energies of luteolin and apigenin-pfprotein complexes were significantly (p < 0.05) higher compared to their respective references. The anti-plasmodial activity of the extract may result from its hypolipidemic effect, which deprives the parasite of essential lipid molecules needed for parasite growth, as well as from the inhibitory effects of apigenin and luteolin on specific proteins required for the Plasmodium metabolic pathway.

In Silico and Structure-Based Assessment of Similar Variants Discovered in Tandem Repeats of BRCT Domains of BRCA1 and BARD1 To Characterize the Folding Pattern

BRCA1 and BARD1 are important proteins in the homologous DNA damage repair pathways. Different genetic variants identified in these proteins have been clinically correlated with the occurrence of hereditary breast and ovarian cancer (HBOC). Variants of unknown significance (VUS) reported in the BRCT domains of BRCA1 and BARD1 substantiate the importance of BRCT domain-containing proteins for genomic integrity. To classify the pathogenicity of variants, in silico, structural and molecular dynamics (MD)-based approaches were explored. Different variants reported in the BRCT region were retrieved from cBioPortal, LOVD3, BRCA Exchange, and COSMIC databases to evaluate the pathogenicity. Multiple sequence alignment and superimposition of the structures of BRCA1 BRCT and BARD1 BRCT domains were performed to compare alterations in folding patterns. From 11 in silico predictions servers, variants reported to be pathogenic by 70% of the servers were considered for structural analysis. To our observations, four residue pairs of both the proteins were reported, harboring 11 variants, H1686Y, W1718L, P1749L, P1749S, and W1837L variants for BRCA1 BRCT and H606D, H606N, W635L, P657L, P657S, and W762F for BARD1 BRCT. MD simulations of the BRCT repeat regions of these variants and wild-type proteins were performed to evaluate the differences of folding patterns. Root mean square deviation (RMSD), R _g, solvent-accessible surface area (SASA), and root mean square fluctuation (RMSF) of variants showed slight differences in the folding patterns from the wild-type proteins. Furthermore, principal components analysis of H1686Y, P1749S, and W1718L variants of BRCA1 showed less flexibility than the wild type, whereas that of H606D, W635L, and W762F of BARD1 showed more flexibility than the wild type. Normal mode analysis of the energy minima from the simulation trajectories revealed that most of the variants do not show much differences in the flexibility compared to the wild-type proteins, except for the discrete regions in the BRCT repeats, most prominently in the 1798-1801 amino acid region of BRCA1 and at the residue 744 in BARD1.

A bioinformatics approach to the identification of novel deleterious mutations of human TPMT through validated screening and molecular dynamics

Polymorphisms of Thiopurine S-methyltransferase (TPMT) are known to be associated with leukemia, inflammatory bowel diseases, and more. The objective of the present study was to identify novel deleterious missense SNPs of TPMT through a comprehensive in silico protocol. The initial SNP screening protocol used to identify deleterious SNPs from the pool of all TPMT SNPs in the dbSNP database yielded an accuracy of 83.33% in identifying extremely dangerous variants. Five novel deleterious missense SNPs (W33G, W78R, V89E, W150G, and L182P) of TPMT were identified through the aforementioned screening protocol. These 5 SNPs were then subjected to conservation analysis, interaction analysis, oncogenic and phenotypic analysis, structural analysis, PTM analysis, and molecular dynamics simulations (MDS) analysis to further assess and analyze their deleterious nature. Oncogenic analysis revealed that all five SNPs are oncogenic. MDS analysis revealed that all SNPs are deleterious due to the alterations they cause in the binding energy of the wild-type protein. Plasticity-induced instability caused by most of the mutations as indicated by the MDS results has been hypothesized to be the reason for this alteration. While in vivo or in vitro protocols are more conclusive, they are often more challenging and expensive. Hence, future research endeavors targeted at TPMT polymorphisms and/or their consequences in relevant disease progressions or treatments, through in vitro or in vivo means can give a higher priority to these SNPs rather than considering the massive pool of all SNPs of TPMT.

African derived phytocompounds may interfere with SARS-CoV-2 RNA capping machinery via inhibition of 2'-O-ribose methyltransferase: An in silico perspective

Despite the ongoing vaccination against the life-threatening COVID-19, there is need for viable therapeutic interventions. The S-adenosyl-l-Methionine (SAM) dependent 2-O'-ribose methyltransferase (2'-O-MTase) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a therapeutic target against COVID-19 infection. In a bid to profile bioactive principles from natural sources, a custom-made library of 226 phytochemicals from African medicinal plants with especially anti-malarial activity was screened for direct interactions with SARS-CoV-2 2'-O-MTase (S2RMT) using molecular docking and molecular dynamics (MD) simulations as well as binding free energies methods. Based on minimal binding energy lower than sinefungin (a reference methyl-transferase inhibitor) and binding mode analysis at the catalytic site of S2RMT, a list of 26 hit phytocompounds was defined. The interaction of these phytocompounds was compared with the 2'-O-MTase of SARS-CoV and MERS-CoV. Among these compounds, the lead phytocompounds (LPs) viz: mulberrofuran F, 24-methylene cycloartenol, ferulate, 3-benzoylhosloppone and 10-hydroxyusambarensine interacted strongly with the conserved KDKE tetrad within the substrate binding pocket of the 2'-O-MTase of the coronavirus strains which is critical for substrate binding. The thermodynamic parameters analyzed from the MD simulation trajectories of the LPs-S2RMT complexes presented an eminent structural stability and compactness. These LPs demonstrated favorable druggability and in silico ADMET properties over a diverse array of molecular computing descriptors. The LPs show promising prospects in the disruption of S2RMT capping machinery in silico. However, these LPs should be validated via in vitro and in vivo experimental models.

Inhibition mechanism of alpha-amylase, a diabetes target, by a steroidal pregnane and pregnane glycosides derived from Gongronema latifolium Benth

Alpha-amylase is widely exploited as a drug target for preventing postprandial hyperglycemia in diabetes and other metabolic diseases. Inhibition of this enzyme by plant-derived pregnanes is not fully understood. Herein, we used in vitro, in silico, and in vivo studies to provide further insights into the alpha-amylase inhibitory potential of selected pregnane-rich chromatographic fractions and four steroidal pregnane phytochemicals (SPPs), viz: marsectohexol (P1), 3-O-[6-deoxy-3-O-methyl-β-D-allopyranosyl-(1→14)-β-D-oleandropyranosyl]-11,12-di-O-tigloyl-17β-marsdenin (P2), 3-O-[6-deoxy-3-O-methyl-β-D-allopyranosyl-(1→4)-β-D-oleandropyranosyl]-17β-marsdenin (P3), and 3-O-[6-deoxy-3-O-methyl-β-D-allopyranosyl-(1→4)-β-D-canaropyranosyl]-17β-marsdenin (P4) derived from Gongronema latifolium Benth. The results revealed that the SPPs source pregnane-rich chromatographic fractions and the SPPs (P1–P4) exhibited inhibitory potential against porcine pancreatic alpha-amylase in vitro. Compounds P1 and P2 with IC50 values 10.01 and 12.10 µM, respectively, showed greater inhibitory potential than the reference acarbose (IC50 = 13.47 µM). Molecular docking analysis suggests that the SPPs had a strong binding affinity to porcine pancreatic alpha-amylase (PPA), human pancreatic alpha-amylase (HPA), and human salivary alpha-amylase (HSA), interacting with the key active site residues through an array of hydrophobic interactions and hydrogen bonds. The strong interactions of the SPPs with Glu233 and Asp300 residues may disrupt their roles in the acid-base catalytic mechanism and proper orientation of the polymeric substrates, respectively. The interactions with human pancreatic amylase were maintained in a dynamic environment as indicated by the root mean square deviation, radius of gyration, surface accessible surface area, and number of hydrogen bonds computed from the trajectories obtained from a 100-ns molecular dynamics simulation. Key loop regions of HPA that contribute to substrate binding exhibited flexibility and interaction potential toward the compounds as indicated by the root mean square fluctuation. Furthermore, P1 significantly reduced blood glucose levels and area under the curve in albino rats which were orally challenged with starch. Therefore, Gongronema latifolium and its constituent SPPs may be exploited as inhibitors of pancreatic alpha-amylase as an oral policy for impeding postprandial blood glucose rise.

In Silico Study and Excito-Repellent Activity of Vitex negundo L. Essential Oil against Anopheles gambiae

(1) Background: Essential oil from Vitex negundo is known to have repellent and insecticidal properties toward the Anopheles gambiae and this is linked to its monoterpene and sesquiterpene content. In this work, an effort is made to delineate the constitution of V. negundo essential oil (VNEO) and their interaction with odorant-binding proteins (OBPs) of A. gambiae and hence access its repellent efficiency as cost-effective and safer malaria vector control alternatives. (2) Methods: Anopheles species authentication was performed by genomic DNA analysis and was subjected to behavioral analysis. GC-MS profiling was used to identify individual components of VNEO. Anopheles OBPs were obtained from the RCSB protein data bank and used for docking studies. Determination of ligand efficiency metrics and QSAR studies were performed using Hyper Chem Professional 8.0.3, and molecular dynamics simulations were performed using the Desmond module. (3) Results: GC-MS analysis of VNEO showed 28 compounds (monoterpenes, 80.16%; sesquiterpenes, 7.63%; and unknown constituents, 10.88%). The ligand efficiency metrics of all four ligands against the OBP 7 were within acceptable ranges. β-selinene (−12.2 kcal/mol), β-caryophellene (−9.5 kcal/mol), sulcatone (−10.9 kcal/mol), and α-ylangene (−9.3 kcal/mol) showed the strongest binding affinities for the target proteins. The most stable hydrophobic interactions were observed between β-selinene (Phe111 and Phe120), Sulcatone (Phe54 and Phe120), and α-ylangene (Phe111), while only sulcatone (Tyr49) presented H-bond interactions in the simulated environment. (4) Conclusions: Sulcatone and β-caryophyllene presented the best log p values, 6.45 and 5.20, respectively. These lead phytocompounds can be used in their purest as repellent supplement or as a natural anti-mosquito agent in product formulations.

Insighting isatin derivatives as potential antiviral agents against NSP3 of COVID-19

The world is now facing intolerable damage in all sectors of life because of the deadly COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2. The discovery and development of anti-SARS-CoV-2 drugs have become pragmatic in the time needed to fight against this pandemic. The non-structural protein 3 is essential for the replication of transcriptase complex (RTC) and may be regarded as a possible target against SARS-CoV-2. Here, we have used a comprehensive in silico technique to find potent drug molecules against the NSP3 receptor of SARS-CoV-2. Virtual screening of 150 Isatin derivatives taken from PubChem was performed based on their binding affinity estimated by docking simulations, resulting in the selection of 46 ligands having binding energy greater than -7.1 kcal/mol. Moreover, the molecular interactions of the nine best-docked ligands having a binding energy of ≥ -8.5 kcal/mol were analyzed. The molecular interactions showed that the three ligands (S5, S16, and S42) were stabilized by forming hydrogen bonds and other significant interactions. Molecular dynamic simulations were performed to mimic an in vitro protein-like aqueous environment and to check the stability of the best three ligands and NSP3 complexes in an aqueous environment. The binding energy of the S5, S16, and S42 systems obtained from the molecular mechanics Poisson-Boltzmann surface area also favor the system's stability. The MD and MM/PBSA results explore that S5, S16, and S42 are more stable and can be considered more potent drug candidates against COVID-19 disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11696-022-02298-7.

Homology Modeling, de Novo Design of Ligands, and Molecular Docking Identify Potential Inhibitors of Leishmania donovani 24-Sterol Methyltransferase

The therapeutic challenges pertaining to leishmaniasis due to reported chemoresistance and toxicity necessitate the need to explore novel pathways to identify plausible inhibitory molecules. Leishmania donovani 24-sterol methyltransferase (LdSMT) is vital for the synthesis of ergosterols, the main constituents of Leishmania cellular membranes. So far, mammals have not been shown to possess SMT or ergosterols, making the pathway a prime candidate for drug discovery. The structural model of LdSMT was elucidated using homology modeling to identify potential novel 24-SMT inhibitors via virtual screening, scaffold hopping, and de-novo fragment-based design. Altogether, six potential novel inhibitors were identified with binding energies ranging from −7.0 to −8.4 kcal/mol with e-LEA3D using 22,26-azasterol and S1–S4 obtained from scaffold hopping via the ChEMBL, DrugBank, PubChem, ChemSpider, and ZINC15 databases. These ligands showed comparable binding energy to 22,26-azasterol (−7.6 kcal/mol), the main inhibitor of LdSMT. Moreover, all the compounds had plausible ligand efficiency-dependent lipophilicity (LELP) scores above 3. The binding mechanism identified Tyr92 to be critical for binding, and this was corroborated via molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) calculations. The ligand A1 was predicted to possess antileishmanial properties with a probability of activity (Pa) of 0.362 and a probability of inactivity (Pi) of 0.066, while A5 and A6 possessed dermatological properties with Pa values of 0.205 and 0.249 and Pi values of 0.162 and 0.120, respectively. Structural similarity search via DrugBank identified vabicaserin, daledalin, zanapezil, imipramine, and cefradine with antileishmanial properties suggesting that the de-novo compounds could be explored as potential antileishmanial agents.

Pathogenicity Reclassification of Genetic Variants Related to Early-Onset Breast Cancer among Women of Mongoloid Origin

BACKGROUND

Germline alterations in BRCA1, BRCA2, and other genes are responsible for early-onset breast cancer. However, up to 20% of molecular tests report genetic variant of unknown significance (VUS) or novel variants that have never been previously described and their clinical significance are unknown. This study aimed to reclassify variant of unknown significance (VUS) or novel variants by using the ActiveDriveDB database that annotates variants through the lens of sites of post-translational modifications (PTM).

METHODS

Our study included thirty-eighth young Buryat BC patients, belonging to the Mongoloid race and anthropologically to the Central Asia. Genomic DNA was extracted from the peripheral blood lymphocytes using the phenol/chloroform method. DNA library were prepared using the Hereditary Cancer SolutionTM kit (Sophia GENETICS, Switzerland) to cover 27 genes, such as ATM, APC, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, FAM175A, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PALB2, PIK3CA, PMS2, PMS2CL, PTEN, RAD50, RAD51C, RAD51D, STK11, TP53, and XRCC2. Paired-end sequencing (2 x 150 bp) was conducted using NextSeq 500 system (Illumina, USA).

RESULTS

We re-examined 135 rare variants (41 VUS, 25 conflicting, 64 benign and 5 new variants). We identified 10 out of 135 (7.4%) mutations that affected the sites of post-translational modification in proteins. Of 135 rare mutations, 1 benign variant was reclassified as network-rewiring - motif loss mutation, 3 VUS and 1 new variant were reclassified as distal PTM- mutations, 2 new and 1 benign variant were classified as proximal PTM- mutations and 1 benign and 1 conflicting variant were classified as direct PTM- mutations.

CONCLUSIONS

For the first time, 7.4% (10 out of 135) of mutations that affected the sites of post-translational modification in proteins were identified among early-onset breast cancer women of Mongoloid origin.

Computer-aided identification of cholinergic and monoaminergic inhibitory flavonoids from Hibiscus sabdariffa L

BACKGROUND

The reduced levels of acetylcholine and dopamine lead to Alzheimer's disease AD and Parkinson disease PD, respectively, due to the action of cholinesterase and monoamine oxidase B.

METHODS

Therapeutic options for AD and PD involve respective cholinergic and monoaminergic inhibitors, and considering the adverse outcomes of cholinergic- and monoaminergic- inhibitory therapeutics, phytoconstituents may be promising alternatives. Reports have shown that different extracts of the calyx of Hibiscus sabdariffa exhibit anticholinesterase and monoamine oxidase B inhibitory properties with potential to delay and prevent the development of AD and PD. However, there is limited knowledge on the multitarget cholinergic and monoaminergic inhibitory activities of individual compounds in this plant. Computational methods were used to identify the specific compounds responsible for the observed cholinergic and monoaminergic inhibitory activities of the H. sabdariffa calyx extracts.

RESULTS

Results confirm that three flavonoids: delphinidin-3-sambubioside, kaempferol-3-O-rutinoside and quercetin-3-rutinoside showed strong binding affinity with acetylcholinesterase, butyrylcholinesterase and monoamine oxidase B while the observed stability of the ligands-enzymes complexes over the MD simulation time suggests their cholinergic and monoaminergic inhibitory properties.

CONCLUSION

The three flavonoids may be responsible for the reported anticholinergic and monoaminergic inhibitory potentials of H. sabdariffa extracts and could be enlisted as multi-target inhibitory agents for cholinesterases and monoamine oxidase B.

Understanding the Driving Forces That Trigger Mutations in SARS-CoV-2: Mutational Energetics and the Role of Arginine Blockers in COVID-19 Therapy

SARS-CoV-2 is a global challenge due to its ability to mutate into variants that spread more rapidly than the wild-type virus. Because the molecular biology of this virus has been studied in such great detail, it represents an archetypal paradigm for research into new antiviral drug therapies. The rapid evolution of SARS-CoV-2 in the human population is driven, in part, by mutations in the receptor-binding domain (RBD) of the spike (S-) protein, some of which enable tighter binding to angiotensin-converting enzyme (ACE2). More stable RBD-ACE2 association is coupled with accelerated hydrolysis of furin and 3CLpro cleavage sites that augment infection. Non-RBD and non-interfacial mutations assist the S-protein in adopting thermodynamically favorable conformations for stronger binding. The driving forces of key mutations for Alpha, Beta, Gamma, Delta, Kappa, Lambda and Omicron variants, which stabilize the RBD-ACE2 complex, are investigated by free-energy computational approaches, as well as equilibrium and steered molecular dynamic simulations. Considered also are the structural hydropathy traits of the residues in the interface between SARS-CoV-2 RBD and ACE2 protein. Salt bridges and π-π interactions are critical forces that create stronger complexes between the RBD and ACE2. The trend of mutations is the replacement of non-polar hydrophobic interactions with polar hydrophilic interactions, which enhance binding of RBD with ACE2. However, this is not always the case, as conformational landscapes also contribute to a stronger binding. Arginine, the most polar and hydrophilic among the natural amino acids, is the most aggressive mutant amino acid for stronger binding. Arginine blockers, such as traditional sartans that bear anionic tetrazoles and carboxylates, may be ideal candidate drugs for retarding viral infection by weakening S-protein RBD binding to ACE2 and discouraging hydrolysis of cleavage sites. Based on our computational results it is suggested that a new generation of “supersartans”, called “bisartans”, bearing two anionic biphenyl-tetrazole pharmacophores, are superior to carboxylates in terms of their interactions with viral targets, suggesting their potential as drugs in the treatment of COVID-19. In Brief: This in silico study reviews our understanding of molecular driving forces that trigger mutations in the SARS-CoV-2 virus. It also reports further studies on a new class of “supersartans” referred to herein as “bisartans”, bearing two anionic biphenyltetrazole moieties that show potential in models for blocking critical amino acids of mutants, such as arginine, in the Delta variant. Bisartans may also act at other targets essential for viral infection and replication (i.e., ACE2, furin cleavage site and 3CLpro), rendering them potential new drugs for additional experimentation and translation to human clinical trials.

Impact of the R292K Mutation on Influenza A (H7N9) Virus Resistance towards Peramivir: A Molecular Dynamics Perspective

In March 2013, a novel avian influenza A (H7N9) virus emerged in China. By March 2021, it had infected more than 1500 people, raising concerns regarding its epidemic potential. Similar to the highly pathogenic H5N1 virus, the H7N9 virus causes severe pneumonia and acute respiratory distress syndrome in most patients. Moreover, genetic analysis showed that this avian H7N9 virus carries human adaptation markers in the hemagglutinin and polymerase basic 2 (PB2) genes associated with cross-species transmissibility. Clinical studies showed that a single mutation, neuraminidase (NA) R292K (N2 numbering), induces resistance to peramivir in the highly pathogenic H7N9 influenza A viruses. Therefore, to evaluate the risk for human public health and understand the possible source of drug resistance, we assessed the impact of the NA-R292K mutation on avian H7N9 virus resistance towards peramivir using various molecular dynamics approaches. We observed that the single point mutation led to a distorted peramivir orientation in the enzyme active site which, in turn, perturbed the inhibitor's binding. The R292K mutation induced a decrease in the interaction among neighboring amino acid residues when compared to its wild-type counterpart, as shown by the high degree of fluctuations in the radius of gyration. MM/GBSA calculations revealed that the mutation caused a decrease in the drug binding affinity by 17.28 kcal/mol when compared to the that for the wild-type enzyme. The mutation caused a distortion of hydrogen bond-mediated interactions with peramivir and increased the accessibility of water molecules around the K292 mutated residue.

Optimizing peptide inhibitors of SARS-Cov-2 nsp10/nsp16 methyltransferase predicted through molecular simulation and machine learning

Coronaviruses, including the recent pandemic strain SARS-Cov-2, use a multifunctional 2'-O-methyltransferase (2'-O-MTase) to restrict the host defense mechanism and to methylate RNA. The nonstructural protein 16 2'-O-MTase (nsp16) becomes active when nonstructural protein 10 (nsp10) and nsp16 interact. Novel peptide drugs have shown promise in the treatment of numerous diseases and new research has established that nsp10 derived peptides can disrupt viral methyltransferase activity via interaction of nsp16. This study had the goal of optimizing new analogous nsp10 peptides that have the ability to bind nsp16 with equal to or higher affinity than those naturally occurring. The following research demonstrates that in silico molecular simulations can shed light on peptide structures and predict the potential of new peptides to interrupt methyltransferase activity via the nsp10/nsp16 interface. The simulations suggest that misalignments at residues F68, H80, I81, D94, and Y96 or rotation at H80 abrogate MTase function. We develop a new set of peptides based on conserved regions of the nsp10 protein in the Coronaviridae species and test these to known MTase variant values. This results in the prediction that the H80R variant is a solid new candidate for potential new testing. We envision that this new lead is the beginning of a reputable foundation of a new computational method that combats coronaviruses and that is beneficial for new peptide drug development.

Computational studies on the cholinesterase, beta-secretase 1 (BACE1) and monoamine oxidase (MAO) inhibitory activities of endophytes-derived compounds: towards discovery of novel neurotherapeutics

Cholinesterases, beta-secretase 1 (BACE1) and monoamine oxidase (MAO) are significant in the etiology of neurodegenerative diseases. Inhibition of these enzymes is therefore a major strategy for the development of neurotherapeutics. Even though, this strategy has birthed some approved synthetic drugs, they are characterized by adverse effects. It is therefore, imperative to explore promising alternatives. Consequently, we assessed the inhibitory activities of some endophytes-derived compounds against selected targets towards discovery of novel neurotherapeutics. Standard inhibitors and 83 endophytes-derived compounds were docked against acetylcholinesterase (AChE), butyrylcholinesterase (BChE), BACE 1 and MAO using AutodockVina while the molecular interactions between the selected targets and the compounds with notable binding affinity were viewed through Discovery Studio Visualizer. Druglikeness and Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) and blood brain barrier (BBB) properties of the top 4 compounds were evaluated using the Swiss online ADME web tool and OSIRIS server; ligands-enzymes complex stability was assessed through molecular dynamics (MD) simulation. From the 83 compounds, asperflavin, ascomfurans C, camptothecine and corynesidone A exhibited remarkable inhibitory activity against all the four target enzymes compared to the respective standard inhibitors. However, only corynesidone A could transverse the BBB and predicted to be safe. MD simulation of the unbound and complexed enzymes with corynesidone A showed that the complexes were stable throughout the simulation time. Given the exceptional inhibitory activity of endophytes-derived corynesidone A against the four selected targets, its ability to permeate the BBB, excellent drugability properties as well as its stability when complexed with the enzymes, it is a good candidate for further studies towards development of new neurotherapeutics.Communicated by Ramaswamy H. Sarma.

Machine learning-based prediction of drug and ligand binding in BCL-2 variants through molecular dynamics

Venetoclax is a BH3 (BCL-2 Homology 3) mimetic used to treat leukemia and lymphoma by inhibiting the anti-apoptotic BCL-2 protein thereby promoting apoptosis of cancerous cells. Acquired resistance to Venetoclax via specific variants in BCL-2 is a major problem for the successful treatment of cancer patients. Replica exchange molecular dynamics (REMD) simulations combined with machine learning were used to define the average structure of variants in aqueous solution to predict changes in drug and ligand binding in BCL-2 variants. The variant structures all show shifts in residue positions that occlude the binding groove, and these are the primary contributors to drug resistance. Correspondingly, we established a method that can predict the severity of a variant as measured by the inhibitory constant (Ki) of Venetoclax by measuring the structure deviations to the binding cleft. In addition, we also applied machine learning to the phi and psi angles of the amino acid backbone to the ensemble of conformations that demonstrated a generalizable method for drug resistant predictions of BCL-2 proteins that elucidates changes where detailed understanding of the structure-function relationship is less clear.

RBD Double Mutations of SARS-CoV-2 Strains Increase Transmissibility through Enhanced Interaction between RBD and ACE2 Receptor

The COVID-19 pandemic, caused by SARS-CoV-2, has led to catastrophic damage for global human health. The initial step of SARS-CoV-2 infection is the binding of the receptor-binding domain (RBD) in its spike protein to the ACE2 receptor in the host cell membrane. Constant evolution of SARS-CoV-2 generates new mutations across its genome including the coding region for the RBD in the spike protein. In addition to the well-known single mutation in the RBD, the recent new mutation strains with an RBD "double mutation" are causing new outbreaks globally, as represented by the delta strain containing RBD L452R/T478K. Although it is considered that the increased transmissibility of double-mutated strains could be attributed to the altered interaction between the RBD and ACE2 receptor, the molecular details remain to be elucidated. Using the methods of molecular dynamics simulation, superimposed structural comparison, free binding energy estimation, and antibody escaping, we investigated the relationship between the ACE2 receptor and the RBD double mutants of L452R/T478K (delta), L452R/E484Q (kappa), and E484K/N501Y (beta, gamma). The results demonstrated that each of the three RBD double mutants altered the RBD structure and enhanced the binding of the mutated RBD to ACE2 receptor. Together with the mutations in other parts of the virus genome, the double mutations increase the transmissibility of SARS-CoV-2 to host cells.

Dietary stigmastane-type saponins as promising dual-target directed inhibitors of SARS-CoV-2 proteases: a structure-based screening

Despite the development of COVID-19 vaccines, at present, there is still no approved antiviral drug against the pandemic. The SARS-CoV-2 3-chymotrypsin-like proteases (S-3CLpro) and papain-like protease (S-PLpro) are essential for the viral proliferation cycle, hence attractive drug targets. Plant-based dietary components that have been extensively reported for antiviral activities may serve as cheap sources of preventive nutraceuticals and/or antiviral drugs. A custom-made library of 176 phytochemicals from five West African antiviral culinary herbs was screened for potential dual-target-directed inhibitors of S-3CLpro and S-PLpro in silico. The docking analysis revealed fifteen steroidal saponins (FSS) from Vernonia amygdalina with the highest binding tendency for the active sites of S-3CLpro and S-PLpro. In an optimized docking analysis, the FSS were further docked against four equilibrated conformers of the S-3CLpro and S-PLpro. Three stigmastane-type steroidal saponins (vernonioside A2, vernonioside A4 and vernonioside D2) were revealed as the lead compounds. These compounds interacted with the catalytic residues of both S-3CLpro and S-PLpro, thereby exhibiting dual inhibitory potential against these SARS-CoV-2 cysteine proteases. The binding free energy calculations further corroborated the static and optimized docking analysis. The complexed proteases with these promising phytochemicals were stable during a full atomistic MD simulation while the phytochemicals exhibited favourable physicochemical and ADMET properties, hence, recommended as promising inhibitors of SARS-CoV-2 cysteine proteases.

Interactive Mechanism of Potential Inhibitors with Glycosyl for SARS-CoV-2 by Molecular Dynamics Simulation

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a type of Ribonucleic Acid (RNA) coronavirus and it has infected and killed many people around the world. It is reported that the receptor binding domain of the spike protein (S_RBD) of the SARS-CoV-2 virus is responsible for attachment to human angiotensin converting enzyme II (ACE2). Many researchers are attempting to search potential inhibitors for fighting SARS-CoV-2 infection using theoretical or experimental methods. In terms of experimental and theoretical research, Cefuroxime, Erythromycin, Lincomycin and Ofloxacin are the potential inhibitors of SARS-CoV-2. However, the interactive mechanism of the protein SARS-CoV-2 and the inhibitors are still elusive. Here, we investigated the interactions between S_RBD and the inhibitors using molecular dynamics (MD) simulations. Interestingly, we found that there are two binding sites of S_RBD for the four small molecules. In addition, our analysis also illustrated that hydrophobic and π-π stacking interactions play crucial roles in the interactions between S_RBD and the small molecules. In our work, we also found that small molecules with glycosyl group have more effect on the conformation of S_RBD than other inhibitors, and they are also potential inhibitors for the genetic variants of SARS-CoV-2. This study provides in silico-derived mechanistic insights into the interactions of S_RBD and inhibitors, which may provide new clues for fighting SARS-CoV-2 infection.

Discovery and Validation of Lmj_04_BRCT Domain, a Novel Therapeutic Target: Identification of Candidate Drugs for Leishmaniasis

Since many of the currently available antileishmanial treatments exhibit toxicity, low effectiveness, and resistance, search and validation of new therapeutic targets allowing the development of innovative drugs have become a worldwide priority. This work presents a structure-based drug discovery strategy to validate the Lmj_04_BRCT domain as a novel therapeutic target in Leishmania spp. The structure of this domain was explored using homology modeling, virtual screening, and molecular dynamics studies. Candidate compounds were validated in vitro using promastigotes of Leishmania major, L. amazonensis, and L. infantum, as well as primary mouse macrophages infected with L. major. The novel inhibitor CPE2 emerged as the most active of a group of compounds against Leishmania, being able to significantly reduce the viability of promastigotes. CPE2 was also active against the intracellular forms of the parasites and significantly reduced parasite burden in murine macrophages without exhibiting toxicity in host cells. Furthermore, L. major promastigotes treated with CPE2 showed significant lower expression levels of several genes (α-tubulin, Cyclin CYCA, and Yip1) related to proliferation and treatment resistance. Our in silico and in vitro studies suggest that the Lmj_04_BRCT domain and its here disclosed inhibitors are new potential therapeutic options against leishmaniasis.

Amyloid β fibrils disruption by kolaviron: Molecular docking and extended molecular dynamics simulation studies

Garcinia kola (GK) produces notable effects against neurodegenerative conditions, including experimentally-induced Alzheimer's disease (AD). These remarkable effects are basically attributable to kolaviron (KV), a bioflavonoid constituent of this seed. Specifically, it has been reported that in AD models, KV produces interesting neuroprotective effects, being able to diminish associated neurotoxicity, via modulation of antioxidative, inflammatory and other disease modifying processes. Intriguingly, the effect of KV on amyloid-beta (Aβ) aggregation and disruption of preformed Aβ fibrils have not been studied. In this study, we have described a thorough computational study on the mechanism of action of KV as an Aβ fibrils disruptor at molecular level. We used comprehensive in silico docking evaluations and extended molecular dynamics simulation to mimic KV/Aβ fibrils system. Results indicate that KV was able to move within the Aβ fibrils, binding with important residues and components in the Aβ peptide identified to be vital for stabilizing preformed fibrils. KV destabilized the assembled Aβ fibrils, indicating the ability KV as a potential anti-amyloidogenic agent. Furthermore, this work highlighted the possibility of identifying new multifunctional phytocompounds as potent AD drugs.

SARS-CoV-2 host cell entry: an in silico investigation of potential inhibitory roles of terpenoids

BACKGROUND

Targeting viral cell entry proteins is an emerging therapeutic strategy for inhibiting the first stage of SARS-CoV-2 infection. In this study, 106 bioactive terpenoids from African medicinal plants were screened through molecular docking analysis against human angiotensin-converting enzyme 2 (hACE2), human transmembrane protease serine 2 (TMPRSS2), and the spike (S) proteins of SARS-CoV-2, SARS-CoV, and MERS-CoV. In silico absorption-distribution-metabolism-excretion-toxicity (ADMET) and drug-likeness prediction, molecular dynamics (MD) simulation, binding free energy calculations, and clustering analysis of MD simulation trajectories were performed on the top docked terpenoids to respective protein targets.

RESULTS

The results revealed eight terpenoids with high binding tendencies to the catalytic residues of different targets. Two pentacyclic terpenoids (24-methylene cycloartenol and isoiguesteri) interacted with the hACE2 binding hotspots for the SARS-CoV-2 spike protein, while the abietane diterpenes were found accommodated within the S1-specificity pocket, interacting strongly with the active site residues TMPRSS2. 3-benzoylhosloppone and cucurbitacin interacted with the RBD and S2 subunit of SARS-CoV-2 spike protein respectively. These interactions were preserved in a simulated dynamic environment, thereby, demonstrating high structural stability. The MM-GBSA binding free energy calculations corroborated the docking interactions. The top docked terpenoids showed favorable drug-likeness and ADMET properties over a wide range of molecular descriptors.

CONCLUSION

The identified terpenoids from this study provides core structure that can be exploited for further lead optimization to design drugs against SARS-CoV-2 cell-mediated entry proteins. They are therefore recommended for further in vitro and in vivo studies towards developing entry inhibitors against the ongoing COVID-19 pandemic.

Dual targeting of cytokine storm and viral replication in COVID-19 by plant-derived steroidal pregnanes: An in silico perspective

The high morbidity and mortality rate of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection arises majorly from the Acute Respiratory Distress Syndrome and "cytokine storm" syndrome, which is sustained by an aberrant systemic inflammatory response and elevated pro-inflammatory cytokines. Thus, phytocompounds with broad-spectrum anti-inflammatory activity that target multiple SARS-CoV-2 proteins will enhance the development of effective drugs against the disease. In this study, an in-house library of 117 steroidal plant-derived pregnanes (PDPs) was docked in the active regions of human glucocorticoid receptors (hGRs) in a comparative molecular docking analysis. Based on the minimal binding energy and a comparative dexamethasone binding mode analysis, a list of top twenty ranked PDPs docked in the agonist conformation of hGR, with binding energies ranging between -9.8 and -11.2 kcal/mol, was obtained and analyzed for possible interactions with the human Janus kinases 1 and Interleukins-6 and SARS-CoV-2 3-chymotrypsin-like protease, Papain-like protease and RNA-dependent RNA polymerase. For each target protein, the top three ranked PDPs were selected. Eight PDPs (bregenin, hirundigenin, anhydroholantogenin, atratogenin A, atratogenin B, glaucogenin A, glaucogenin C and glaucogenin D) with high binding tendencies to the catalytic residues of multiple targets were identified. A high degree of structural stability was observed from the 100 ns molecular dynamics simulation analyses of glaucogenin C and hirundigenin complexes of hGR. The selected top-eight ranked PDPs demonstrated high druggable potentials and favourable in silico ADMET properties. Thus, the therapeutic potentials of glaucogenin C and hirundigenin can be explored for further in vitro and in vivo studies.

The Antiviral and Virucidal Activities of Voacangine and Structural Analogs Extracted from Tabernaemontana cymosa Depend on the Dengue Virus Strain

Currently, no specific licensed antiviral exists for treating the illness caused by dengue virus (DENV). Therefore, the search for compounds of natural origin with antiviral activity is an important area of research. In the present study, three compounds were isolated and identified from seeds of Tabernaemontana cymosa plants. The in vitro antiviral effect of those compounds and voacangine against different DENV strains was assessed using different experimental approaches: compounds added before the infection (Pre), at the same time with the virus (Trans), after the infection (Post) or compounds present in all moments of the experiment (Pre-Trans-Post, Combined treatment). In silico studies (docking and molecular dynamics) were also performed to explain the possible antiviral mechanisms. The identified compounds were three structural analogs of voacangine (voacangine-7-hydroxyindolenine, rupicoline and 3-oxo-voacangine). In the Pre-treatment, only voacangine-7-hydroxyindolenine and rupicoline inhibited the infection caused by the DENV-2/NG strain (16.4% and 29.6% infection, respectively). In the Trans-treatment approach, voacangine, voacangine-7-hydroxyindolenine and rupicoline inhibited the infection in both DENV-2/NG (11.2%, 80.4% and 75.7% infection, respectively) and DENV-2/16681 infection models (73.7%, 74.0% and 75.3% infection, respectively). The latter strain was also inhibited by 3-oxo-voacangine (82.8% infection). Moreover, voacangine (most effective virucidal agent) was also effective against one strain of DENV-1 (DENV-1/WestPac/74) and against the third strain of DENV-2 (DENV-2/S16803) (48.5% and 32.4% infection, respectively). Conversely, no inhibition was observed in the post-treatment approach. The last approach (combined) showed that voacangine, voacangine-7-hydroxyindolenine and rupicoline inhibited over 90% of infections (3.5%, 6.9% and 3.5% infection, respectively) of both strains (DENV-2/NG and DENV-2/16681). The free energy of binding obtained with an in silico approach was favorable for the E protein and compounds, which ranged between −5.1 and −6.3 kcal/mol. Finally, the complex formed between DENV-2 E protein and the best virucidal compound was stable for 50 ns. Our results show that the antiviral effect of indole alkaloids derived from T. cymose depends on the serotype and the virus strain.

BRCA1 and BRCA2 Variation in Taiwanese General Population and the Cancer Cohort

BRCA1 and BRCA2 (BRCA) play essential roles in maintaining genome stability. Rapidly evolving human BRCA generates oncogenic variants causing high cancer risk. BRCA variation is ethnic-specific in reflecting adaptation and/or effects of genetic drift. Taiwanese population of 23.8 million is an admixture of multiple ethnic origins; Taiwan's subtropical and tropical climate and geographically islandic location provide a unique natural environment. Therefore, Taiwanese population provides a unique model to study human BRCA variation. Through collecting, standardizing, annotating, and classifying publicly available BRCA variants derived from Taiwanese general population and the cancer cohort, we identified 335 BRCA variants, of which 164 were from 1,517 non-cancer individuals, 126 from 2,665 cancer individuals, and 45 from both types of individuals. We compared the variant data with those from other ethnic populations such as mainland Chinese, Macau Chinese, Japanese, Korean, Indian, and non-Asians. We observed that the sharing rates with other Asian ethnic populations were correlated with its genetic relationship. Over 60% of the 335 Taiwanese BRCA variants were VUS, unclassified variants, or novel variants, reflecting the ethnic-specific features of Taiwanese BRCA variation. While it remains challenging to classify these variants, our structural and in silico analyses predicted their enrichment of BRCA deleterious variants. We further determined the 3.8% prevalence of BRCA pathogenic variants in the Taiwanese breast cancer cohort, and determined 0.53% prevalence of the BRCA pathogenic variants in Taiwanese general population, with the estimated 126,140 BRCA pathogenic variant carriers. We identified BRCA2 c.5164_5165delAG at BRCA2 BRC6 motif as a potential founder mutation in Taiwanese population. Our study on BRCA variation in Taiwanese and other East Asian populations demonstrates that ethnic specificity is a common phenomenon for BRCA variation in East Asian population; the data generated from the study provide a reference for clinical applications in BRCA-related cancer in Taiwanese population.