Biomolecular simulations: recent developments in force fields, simulations of enzyme catalysis, protein-ligand, protein-protein, and protein-nucleic acid noncovalent interactions

Olanzapine manipulates neuroactive signals and may onset metabolic disturbances

Olanzapine is one of the most prescribed atypical antipsychotics to treat psychiatric illness and is associated with weight gain and metabolic disturbance. The present study investigated the olanzapine-regulated metabolic pathways using functional enrichent analysis including binding affinity with G-protein-coupled receptors (GPCRs). Proteins modulated by olanzapine were retrieved from SwissTargetPrediction, DIGEP-Pred, and BindingDB and then enriched in Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) to assess molecular function, biological process, and cellular components including Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We used homology modeling to improve the 3D structure for GPCR synapse proteins including dopamine, serotonin, muscarinic, and histamine receptors which were then optimized using molecular dynamics (MD) simulations. The protein-olanzapine binding mechanisms for different GPCR binders were evaluated using molecular docking; later refined by MD simulations. Binding mechanism of olanzapine with D2, 5HT1A, 5HT2A, 5HT2B, 5HT2C, M1, and M2 receptors were created using homology modeling and optimized using MD simulations. In target identification, it was observed that olanzapine majority targeted G-protein coupled receptors. Further, enrichment analysis identified around 76% of the total genes regulated in molecular function, biological process, and cellular components were common including KEGG pathways. Moreover, it was observed that olanzapine had a major potency over the neurotransmitter synapse including neuroactive signals . Olanzapine-induced weight gain and metabolic alterations could be due to the deregulation of multiple synapses like dopamine, serotonin, muscarinic, and histamine at the feeding center followed by cGMP-PKG, cAMP, and PI3K-Akt signaling pathways. HIGHLIGHTSOlanzapine is used in the management of psychiatric illnesses.Olanzapine causes disturbance in lipids and glucosehomeostasis and manipulates energy expenditure.Olanzapine-induced weight gain may occur due to the deregulation of the multiple synapse and cGMP-PKG, cAMP, and PI3K-Akt signaling pathwayCommunicated by Ramaswamy H. Sarma.

Curcumin interferes with chitin synthesis in Aedes aegypti: a computational and experimental investigation

Throughout history, vector-borne diseases have consistently posed significant challenges to human health. Among the strategies for vector control, chemical insecticides have seen widespread use since their inception. Nevertheless, their effectiveness is continually undermined by the steady growth of insecticide resistance within these vector populations. As such, the demand for more robust, efficient, and cost-effective natural insecticides has become increasingly pressing. One promising avenue of research focuses on chitin, a crucial structural component of mosquitoes' exoskeletons and other insects. Chitin not only provides protection and rigidity but also lends flexibility to the insect body. It undergoes substantial transformations during insect molting, a process known as ecdysis. Crucially, the production of chitin is facilitated by an enzyme known as chitin synthase, making it an attractive target for potential novel insecticides. Our recent study delved into the impacts of curcumin, a natural derivative of turmeric, on chitin synthesis and larval development in Aedes aegypti, a mosquito species known to transmit dengue and yellow fever. Our findings demonstrate that even sub-lethal amounts of curcumin can significantly reduce overall chitin content and disrupt the cuticle development in the 4th instar larvae of Aedes aegypti. Further to this, we utilized computational analyses to investigate how curcumin interacts with chitin synthase. Techniques such as molecular docking, pharmacophore feature mapping, and molecular dynamics (MD) simulations helped to illustrate that curcumin binds to the same site as polyoxin D, a recognized inhibitor of chitin synthase. These findings point to curcumin's potential as a natural, bioactive larvicide that targets chitin synthase in mosquitoes and potentially other insects.

Identification of inhibitors for neurodegenerative diseases targeting dual leucine zipper kinase through virtual screening and molecular dynamics simulations

Neurodegenerative diseases lead to a gradual decline in cognitive and motor functions due to the progressive loss of neurons in the central nervous system. The role of dual leucine zipper kinase (DLK) in regulating stress responses and neuronal death pathways highlights its significance as a target against neurodegenerative diseases. The non-availability of FDA-approved drugs emphasizes a need to identify novel DLK-inhibitors. We screened NPAtlas (Natural products) and MedChemExpress (FDA-approved) libraries to identify potent ATP-competitive DLK inhibitors. ADMET analyses identified four compounds (two natural products and two FDA-approved) with favourable features. Subsequently, we performed molecular dynamics simulations to examine the binding-stability and ligand-induced conformational dynamics. Molecular mechanics Poisson Boltzmann surface area (MM-PBSA) calculations demonstrated CID139591660, dithranol, and danthron having greater affinity, while CID156581477 showed lower affinity than control sunitinib. PCA and network analysis results indicated structural and network alteration post-ligand binding. Furthermore, we identified an analogue of CID156581477 using the deep learning-based web server DeLA Drug which demonstrated a higher affinity than its parent compound and the control and identified several crucial interacting residues. Overall, our study provides significant theoretical guidance for designing potent novel DLK inhibitors and compounds that could emerge as promising drug candidates against DLK following laboratory validation.

Atomic Insight into the Enzymatic Selectivity of Acetyltransferase for Endogenous Polyamines

The N1-Spermidine/spermine acetyltransferase (SSAT) serves as the rate-limiting enzyme in the polyamine metabolism pathway, specifically catalyzing the acetylation of spermidine, spermine, and other specific polyamines. The source of its enzymatic selectivity remains elusive. Here, we used quantum mechanics and molecular mechanics simulations combined with various technologies to explore the enzymatic mechanism of SSAT for endogenous polyamines from an atomic perspective. The static binding and chemical transformation were considered. The binding affinity was identified to be dependent on protonated state of polyamine. The order of the binding affinity for Spm, Spd, and Put is consistent with the experimental results, which is also verified by the dynamic separation of polyamine and SSAT. Hydrogen bond interactions and salt bridges contribute most, and the common hot residues were identified. In addition, the transfer of acetyl and proton between polyamine and AcCoA was discovered to follow a concert mechanism, and thermodynamic properties are responsible for the catalytic efficiency of SSAT. This work may be helpful for development of polyamine derivatives based on catalysis to regulate polyamine metabolism.

Anticancer potential of novel symmetrical and asymmetrical dihydropyridines against breast cancer via EGFR inhibition: molecular design, synthesis, analysis and screening

A series of novel symmetrical and asymmetrical dihydropyridines (HD 1-15) were designed, subjected to in silico ADMET prediction, synthesized, analyzed by IR, NMR, Mass analytical techniques and evaluated against epidermal growth factor receptor (EGFR) as inhibitors against Breast cancer. The results of predicted ADMET studies demonstrated the drug-likeness properties of the reported compounds. The in vitro cytotoxicity assessment of the synthesized compounds revealed that all of them showed good activity (IC50 ranging from 16.75 to 66.54 μM) towards MCF-7 breast cancer cells compared to the standard drug, Lapatinib (IC50 = 2.02 μM). Among these, compounds HD-6, HD-7, and HD-8 displayed the most potent activity with IC50 value of 21.26, 16.75, and 18.33 μM, respectively. Cytotoxicity of all compounds was tested on normal vero cells for comparison at different concentrations using the MTT assay. In addition to the MTT assay, the potent dihydropyridines derivatives were screened for EGFRwt kinase inhibition assay at concentrations ranging from 1 nM to 360 nM. Among the three compounds tested, HD-8 showed reasonably good inhibition with an IC50 value of 15.90 ± 1.20 nM compared to a standard Lapatinib IC50 value of 10.28 ± 1.01 nM. Based on the molecular docking study against EGFR, the most active derivatives HD-7 and HD-8 were docked against the active site of the protein and showed better binding affinity than the standard lapatinib. Additionally, molecular dynamics (MD) simulations were performed to explore the stability of the protein-ligand complex, its dynamic behavior, and the binding affinity.

Biochemical and computational inhibition of α-glucosidase by novel metronidazole-linked 1H-1,2,3-triazole and carboxylate moieties: kinetics and dynamic investigations

In the current study, metronidazole derivatives containing 1H-1,2,3-triazole and carboxylate moieties were evaluated in vitro and by computational methods for their anti-diabetic potential to insight into their medicinal use for the management of type II diabetes mellitus. Interestingly all 14 compounds displayed high to significant inhibitory capability against the key carbohydrate's digestive enzyme α-glucosidase with IC50 values in range of 9.73-56.39 μM, as compared to marketed drug acarbose (IC50 = 873.34 ± 1.67 μM). Compounds 5i and 7c exhibited the highest inhibition, therefore, these two compounds were further evaluated for their mechanistic studies to explore its type of inhibition. Compounds 5i and 7c both displayed a concentration-dependent (competitive type of inhibition) with Ki values 7.14 ± 0.01, 6.15 ± 0.02 μM, respectively, which conclude their favourable interactions with the active site residues of the α-glucosidase. Interestingly all compounds are non-cytotoxic against BJ cell line. To further validate our findings, in-silico approaches like molecular docking, and molecular dynamic simulations were applied to investigate the mode of bindings of compounds with the enzyme and identifies their inhibition mechanism, which strongly complements our experimental findings.Communicated by Ramaswamy H. Sarma.

Identification of novel compounds and repurposing of FDA drugs for 1-deoxy-D-xylulose 5-phosphate reductoisomerase enzyme of Plasmodium falciparum to combat malaria resistance

The rise of Plasmodium falciparum resistance to Artemisinin-based combination therapies (ACTs) is a significant concern in the fight against malaria. This situation calls for the search for novel anti-malarial candidates. 1-deoxy-D-xylulose 5-phosphate reductoisomerase (IspC) is a potential target involved in various cellular processes in P. falciparum (Pf). We screened ∼0.69 billion novel compounds from the ZINC20 library and repurposed ∼1400 FDA drugs using computational drug discovery methods against PfIspC. Following our computational pipeline, we found five novel ZINC20 compounds (Z-2, Z-3, Z-10, Z-13, and Z-14) and three FDA drugs (Aliskiren, Ceftolozane, and Ombitasvir) that showed striking docking energy (ranging from -8.405 to -10.834 kcal/mol), and strong interactions with key binding site residues (Ser269, Ser270, Ser306, Asn311, Lys312, and Met360) of PfIspC. The novel anti-malarial compounds also exhibited favorable pharmacokinetics and physicochemical properties. Furthermore, through molecular dynamics simulation, we observed the stable dynamics of PfIspC-inhibitor complexes and the influence of inhibitor binding on the protein's conformational arrangements. Notably, the binding free energy estimation confirmed high binding affinity (varied from -11.68 to -33.16 kcal/mol) of these compounds for PfIspC. Our findings could contribute to the ongoing efforts in combating malaria and invite experimental-lab researchers for validation.

Prediction of interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins from dihedral angles

Intrinsically disordered proteins (IDPs) are proteins that do not form uniquely defined three-dimensional (3-D) structures. Experimental research on IDPs is difficult since they go against the traditional protein structure-function paradigm. Although there are several predictors of disorder based on amino acid sequences, but very limited based on the 3-D structures of proteins. Dihedral angles have a significant role in predicting protein structure because they establish a protein's backbone, which, coupled with its side chain, establishes its overall shape. Here, we have carried out atomistic Molecular Dynamics (MD) simulations on four different proteins: one ordered protein (Monellin), two partially disordered proteins (p53-TAD and Amyloid beta (Aβ1-42) peptide), and one completely disordered protein (Histatin 5). The MD simulation trajectories for the corresponding four proteins were used to conduct dihedral angle (ϕ and ѱ) analysis. Then, the average dihedral angles for each of the residues were calculated and plotted against the residue index. We noticed steep rises or falls in the average ϕ value at certain locations in the plot. These sudden shifts in the average ϕ value reflect the interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins. Using this method, the probable conformer of a protein with a higher degree of disorder can be found among the ensembles of structures sampled during the MD simulations. The results of our study offer new understandings on precisely identifying regions of various degrees of disorder in intrinsically disordered proteins.Communicated by Ramaswamy H. Sarma.

Leveraging QM/MM and Molecular Dynamics Simulations to Decipher the Reaction Mechanism of the Cas9 HNH Domain to Investigate Off-Target Effects

The clustered regularly interspaced short palindromic repeats (CRISPR) technology is an RNA-guided targeted genome-editing tool using Cas family proteins. Two magnesium-dependent nuclease domains of the Cas9 enzyme, termed HNH and RuvC, are responsible for cleaving the target DNA (t-DNA) and nontarget DNA strands, respectively. The HNH domain is believed to determine the DNA cleavage activity of both endonuclease domains and is sensitive to complementary RNA-DNA base pairing. However, the underlying molecular mechanisms of CRISPR-Cas9, by which it rebukes or accepts mismatches, are poorly understood. Thus, investigation of the structure and dynamics of the catalytic state of Cas9 with either matched or mismatched t-DNA can provide insights into improving its specificity by reducing off-target cleavages. Here, we focus on a recently discovered catalytic-active form of the Streptococcus pyogenes Cas9 (SpCas9) and employ classical molecular dynamics and coupled quantum mechanics/molecular mechanics simulations to study two possible mechanisms of t-DNA cleavage reaction catalyzed by the HNH domain. Moreover, by designing a mismatched t-DNA structure called MM5 (C to G at the fifth position from the protospacer adjacent motif region), the impact of single-guide RNA (sgRNA) and t-DNA complementarity on the catalysis process was investigated. Based on these simulations, our calculated binding affinities, minimum energy paths, and analysis of catalytically important residues provide atomic-level details of the differences between matched and mismatched cleavage reactions. In addition, several residues exhibit significant differences in their catalytic roles for the two studied systems, including K253, K263, R820, K896, and K913.

Epitopes mapping for identification of potential cross-reactive peptide against leptospirosis

Leptospira, the pathogenic helical spirochetes that cause leptospirosis, is an emerging zoonotic disease with effective dissemination tactics in the host and can infect humans and animals with moderate or severe illnesses. Thus, peptide-based vaccines may be the most effective strategy to manage the immune response against Leptospira to close these gaps. In the current investigation, highly immunogenic proteins from the proteome of Leptospira interorgan serogroup Icterohaemorrhagie serovar Lai strain 56601 were identified using immunoinformatic methods. It was discovered that the conserved and most immunogenic outer membrane Lepin protein was both antigenic and non-allergenic by testing 15 linear B-cells and the ten best T-cell (Helper-lymphocyte (HTL) with the most significant number of HLA-DR binding alleles and the eight cytotoxic T lymphocyte (CTL)) epitopes. Furthermore, a 3D structural model of CTL epitopes was created using the Pep-Fold3 platform. Using the Autodock 4.2 docking server, research was conducted to determine how well the top-ranked CTL peptide models attach to HLA-A*0201 (PDB ID: 4U6Y). With HLA-A*0201, the epitope SSGTGNLHV binds with a binding energy of -1.29 kcal/mol. Utilizing molecular dynamics modeling, the projected epitope-allele docked complex structure was optimized, and the stability of the complex system was assessed. Therefore, this epitope can trigger an immunological response and produce effective Leptospira vaccine candidates. Overall, this study offers a unique vaccination candidate and may encourage additional research into leptospirosis vaccines.Communicated by Ramaswamy H. Sarma.

Synthesis of novel coumarin-based thiosemicarbazones and their implications in diabetic management via in-vitro and in-silico approaches

Diabetes mellitus has a high prevalence rate and it has been deemed a severe chronic metabolic disorder with long-term complications. This research aimed to identify compounds that could potentially inhibit the vital metabolic enzyme α-glucosidase and thereby exert an anti-hyperglycemic effect. The main goal was to establish an effective approach to control diabetes. To proceed with this study, a series of novel coumarin-derived thiosemicarbazones 3a-3m was synthesized and examined using a variety of spectroscopic methods. Moreover, all the compounds were subjected to α-glucosidase inhibition bioassay to evaluate their antidiabetic potential. Fortunately, all the compounds exhibited several folds potent α-glucosidase inhibitory activities with IC50 values ranging from 2.33 to 22.11 µM, in comparison to the standard drug acarbose (IC50 = 873.34 ± 1.67 µM). The kinetic studies of compound 3c displayed concentration-dependent inhibition. Furthermore, the binding modes of these molecules were elucidated through a molecular docking strategy which depicted that the thiosemicarbazide moiety of these molecules plays a significant role in the interaction with different residues of the α-glucosidase enzyme. However, their conformational difference is responsible for their varied inhibitory potential. The molecular dynamics simulations suggested that the top-ranked compounds (3c, 3g and 3i) have a substantial effect on the protein dynamics which alter the protein function and have stable attachment in the protein active pocket. The findings suggest that these molecules have the potential to be investigated further as novel antidiabetic medications.

Amplification of oxidative stress by lipid surface-coated single-atom Au nanozymes for oral cancer photodynamic therapy

Single-atom nanozymes (SANs) are the latest trend in biomaterials research and promote the application of single atoms in biological fields and the realization of protein catalysis in vivo with inorganic nanoparticles. Carbon quantum dots (CDs) have excellent biocompatibility and fluorescence properties as a substrate carrying a single atom. It is difficult to break through pure-phase single-atom materials with quantum dots as carriers. In addition, there is currently no related research in the single-atom field in the context of oral cancer, especially head and neck squamous cell carcinoma. This research developed a lipid surface-coated nanozyme combined with CDs, single-atomic gold, and modified lipid ligands (DSPE-PEG) with transferrin (Tf) to treat oral squamous cell carcinoma. The study results have demonstrated that surface-modified single-atom carbon quantum dots (m-SACDs) exhibit excellent therapeutic effects and enable in situ image tracking for diagnosing and treating head and neck squamous carcinoma (HNSCC).

Uncovering the interactions between PME and PMEI at the gene and protein levels: Implications for the design of specific PMEI

CONTEXT

Pectin methylesterase inhibitor (PMEI) can specifically bind and inhibit the activity of pectin methylesterase (PME), which has been widely used in fruit and vegetable juice processing. However, the limited three-dimensional structure, unclear action mechanism, low thermal stability and biological activity of PMEI severely limited its application. In this work, molecular recognition and conformational changes of PME and PMEI were analyzed by various molecular simulation methods. Then suggestions were proposed for improving thermal stability and affinity maturation of PMEI through semi-rational design.

METHODS

Phylogenetic trees of PME and PMEI were established using the Maximum likelihood (ML) method. The results show that PME and PMEI have good sequence and structure conservation in various plants, and the simulated data can be widely adopted. In this work, MD simulations were performed using AMBER20 package and ff14SB force field. Protein interaction analysis indicates that H-bonds, van der Waals forces, and the salt bridge formed of K224 with ID116 are the main driving forces for mutual molecular recognition of PME and PMEI. According to the analyses of free energy landscape (FEL), conformational cluster, and motion, the association with PMEI greatly disrupts PME's dispersed functional motion mode and biological function. By monitoring the changes of residue contact number and binding free energy, IG35M/ IG35R: IT93F and IT113W/ IT113W: ID116W mutations contribute to thermal stability and affinity maturation of the PME-PMEI complex system, respectively. This work reveals the interaction between PME and PMEI at the gene and protein levels and provides options for modifying specific PMEI.

Investigation of the Inhibition Mechanism of Xanthine Oxidoreductase by Oxipurinol: A Computational Study

Xanthine oxidoreductase (XOR) is an enzyme found in various organisms. It converts hypoxanthine to xanthine and urate, which are crucial steps in purine elimination in humans. Elevated uric acid levels can lead to conditions like gout and hyperuricemia. Therefore, there is significant interest in developing drugs that target XOR for treating these conditions and other diseases. Oxipurinol, an analogue of xanthine, is a well-known inhibitor of XOR. Crystallographic studies have revealed that oxipurinol directly binds to the molybdenum cofactor (MoCo) in XOR. However, the precise details of the inhibition mechanism are still unclear, which would be valuable for designing more effective drugs with similar inhibitory functions. In this study, molecular dynamics and quantum mechanics/molecular mechanics calculations are employed to investigate the inhibition mechanism of XOR by oxipurinol. The study examines the structural and dynamic effects of oxipurinol on the pre-catalytic structure of the metabolite-bound system. Our results provide insights on the reaction mechanism catalyzed by the MoCo center in the active site, which aligns well with experimental findings. Furthermore, the results provide insights into the residues surrounding the active site and propose an alternative mechanism for developing alternative covalent inhibitors.

Computational Characterization of the Inhibition Mechanism of Xanthine Oxidoreductase by Topiroxostat

Xanthine oxidase (XO) is a member of the molybdopterin-containing enzyme family. It interconverts xanthine to uric acid as the last step of purine catabolism in the human body. The high uric acid concentration in the blood directly leads to human diseases like gout and hyperuricemia. Therefore, drugs that inhibit the biosynthesis of uric acid by human XO have been clinically used for many years to decrease the concentration of uric acid in the blood. In this study, the inhibition mechanism of XO and a new promising drug, topiroxostat (code: FYX-051), is investigated by employing molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) calculations. This drug has been reported to act as both a noncovalent and covalent inhibitor and undergoes a stepwise inhibition by all its hydroxylated metabolites, which include 2-hydroxy-FYX-051, dihydroxy-FYX-051, and trihydroxy-FYX-051. However, the detailed mechanism of inhibition of each metabolite remains elusive and can be useful for designing more effective drugs with similar inhibition functions. Hence, herein we present the computational investigation of the structural and dynamical effects of FYX-051 and the calculated reaction mechanism for all of the oxidation steps catalyzed by the molybdopterin center in the active site. Calculated results for the proposed reaction mechanisms for each metabolite's inhibition reaction in the enzyme's active site, binding affinities, and the noncovalent interactions with the surrounding amino acid residues are consistent with previously reported experimental findings. Analysis of the noncovalent interactions via energy decomposition analysis (EDA) and noncovalent interaction (NCI) techniques suggests that residues L648, K771, E802, R839, L873, R880, R912, F914, F1009, L1014, and A1079 can be used as key interacting residues for further hybrid-type inhibitor development.

Mechanism exploration and prognosis study of Astragali Radix-Spreading hedyotis herb for the treatment of lung adenocarcinoma based on bioinformatics approaches and molecular dynamics simulation

Background: Herb pair of Astragali Radix (AR) and Spreading Hedyotis Herb (SH) has been frequently prescribed in clinical for the treatment of lung cancer owing to its favorable efficacy. Yet, the mechanism under the therapeutic effects remained unveiled, which has limited its clinical applications, and new drug development for lung cancer.

Methods: The bioactive ingredients of AR and SH were retrieved from the Traditional Chinese Medicine System Pharmacology Database, with the targets of obtained components predicted by Swiss Target Prediction. Genes related to lung adenocarcinoma (LUAD) were acquired from GeneCards, OMIM and CTD databases, with the hub genes of LUAD screened by CTD database. The intersected targets of LUAD and AR-SH were obtained by Venn, with David Database employed to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Survival analysis of the hub genes of LUAD was carried out using TCGA-LUAD dataset. Molecular docking of core proteins and active ingredients was performed by Auto-Dock Vina software, followed by molecular dynamics simulations of protein-ligand complexes with well-docked conformations.

Results: 29 active ingredients were screened out with 422 corresponding targets predicted. It is revealed that AR-SH can act on various targets such as EGFR, MAPK1, and KARS by ursolic acid (UA), Astragaloside IV(ASIV), and Isomucronulatol 7,2′-di-O-glucoside (IDOG) to alleviate the symptoms of LUAD. Biological processes involved are protein phosphorylation, negative regulation of apoptotic process, and pathways involved are endocrine resistance, EGFR tyrosine kinase inhibitor resistance, PI3K-Akt, and HIF-1 pathway. Molecular docking analysis indicated that the binding energy of most of the screened active ingredients to proteins encoded by core genes was less than −5.6 kcal/mol, with some active ingredients showing even lower binding energy to EGFR than Gefitinib. Three ligand-receptor complexes including EGFR-UA, MAPK1-ASIV, and KRAS-IDOG were found to bind relatively stable by molecular dynamics simulation, which was consistent with the results of molecule docking.

Conclusion: We suggested that the herb pair of AR-SH can act on targets like EGFR, MAPK1 and KRAS by UA, ASIV and IDOG, to play a vital role in the treatment and the enhancement of prognosis of LUAD.

AI-driven drug repurposing and binding pose meta dynamics identifies novel targets for Monkeypox virus

Monkeypox virus (MPXV) was confirmed in May 2022 and designated a global health emergency by WHO in July 2022. MPX virions are big, enclosed, brick-shaped, and contain a linear, double-stranded DNA genome as well as enzymes. MPXV particles bind to the host cell membrane via a variety of viral-host protein interactions. As a result, the wrapped structure is a potential therapeutic target. DeepRepurpose, an artificial intelligence-based compound-viral proteins interaction framework, was used via a transfer learning setting to prioritize a set of FDA approved and investigational drugs which can potentially inhibit MPXV viral proteins. To filter and narrow down the lead compounds from curated collections of pharmaceutical compounds, we used a rigorous computational framework that included homology modeling, molecular docking, dynamic simulations, binding free energy calculations, and binding pose metadynamics. We identified Elvitegravir as a potential inhibitor of MPXV virus using our comprehensive pipeline.

The activity and mechanism of vidofludimus as a potent enzyme inhibitor against NDM-1-positive E. coli

New Delhi metallo-β-lactamase-1 (NDM-1) is the most important and prevalent enzyme among all metallo-β-lactamases. NDM-1 can hydrolyze almost all-available β-lactam antibiotics including carbapenems, resulting in multidrug resistance, which poses an increasing clinical threat. However, there is no NDM-1 inhibitor approved for clinical treatment. Therefore, identifying a novel and potential enzyme inhibitor against NDM-1-mediated infections is an urgent need. In this study, vidofludimus was identified as a potential NDM-1 inhibitor by structure-based virtual screening and an enzyme activity inhibition assay. Vidofludimus significantly inhibited NDM-1 hydrolysis activity with a significant dose-dependent effect. When the vidofludimus concentration was 10 μg/ml, the inhibition rate and 50% inhibitory concentration were 93.3% and 13.8 ± 0.5 μM, respectively. In vitro, vidofludimus effectively restored the antibacterial activity of meropenem against NDM-1-positive Escherichia coli (E. coli), and the minimum inhibitory concentration of meropenem was decreased from 64 μg/ml to 4 μg/ml, a 16-fold reduction. The combination of vidofludimus and meropenem showed a significant synergistic effect with a fractional inhibitory concentration index of 0.125 and almost all the NDM-1-positive E. coli were killed within 12 h. Furthermore, the synergistic therapeutic effect of vidofludimus and meropenem in vivo was evaluated in mice infected with NDM-1 positive E. coli. Compared with the control treatment, vidofludimus combined with meropenem significantly improved the survival rate of mice infected with NDM-1-positive E. coli (P < 0.05), decreased the white blood cell count, the bacterial burden and inflammatory response induced by NDM-1-positive E. coli (P < 0.05), and alleviated histopathological damage in infected mice. It was demonstrated by molecular dynamic simulation, site-directed mutagenesis and biomolecular interaction that vidofludimus could interact directly with the key amino acids (Met67, His120, His122 and His250) and Zn²⁺ in the active site of NDM-1, thereby competitively inhibiting the hydrolysis activity of NDM-1 on meropenem. In summary, vidofludimus holds promise as anNDM-1 inhibitor, and the combination of vidofludimus and meropenem has potential as a therapeutic strategy for NDM-1-mediated infections.

Molecular Dynamics Simulation for Investigating Antigen-Antibody Interaction

Molecular dynamics (MD) simulation is a computational method which elucidates the protein dynamics. Following analyses characterize the dynamics and structural change as well as interaction energy. To characterize the protein structure effectively, the internal angular coordinates are often useful. Directional analysis provides the averages and variances of those coordinates in a mathematically rigorous way. Here, we describe not only a standard MD simulation procedure for the antigen-antibody system but also an umbrella sampling method following a multistep targeted MD simulation (US/mTMD), which is useful for evaluating the free energy profile along the antigen-antibody dissociation coordinate.

A Comprehensive in vitro and in silico Assessment on Inhibition of CYP51B and Ergosterol Biosynthesis by Eugenol in Rhizopus oryzae

Mucormycosis, also known as Zygomycosis, is a disease caused by invasive fungi, predominantly Rhizopus species belonging to the Order of Mucorales. Seeing from the chemistry perspective, heterocyclic compounds with an "azole" moiety are widely employed as antifungal agent for minimising the effect of mucormycosis as a prescribed treatment. These azoles serve as non-competitive inhibitors of fungal CYP51B by predominantly binding to its heme moiety, rendering its inhibition. However, long-term usage and abuse of azoles as antifungal medicines has resulted in drug resistance among certain fungal pathogens. Hence, there is an unmet need to find alternative therapeutic compounds. In present study, we used various in vitro tests to investigate the antifungal activity of eugenol against R. oryzae/R. arrhizus, including ergosterol quantification to test inhibition of ergosterol production mediated antifungal action. The minimum inhibitory concentration (MIC) value obtained for eugenol was 512 μg/ml with reduced ergosterol concentration of 77.11 ± 3.25% at MIC/2 concentration. Further, the molecular interactions of eugenol with fungal CYP51B were meticulously studied making use of proteomics in silico study including molecular docking and molecular dynamics simulations that showed eugenol to be strongly interacting with heme in an identical fashion to that shown by azole drugs (in this case, clotrimazole was evaluated). This is the first of a kind study showing the simulation study of eugenol with CYP51B of fungi. This inhibition results in ergosterol synthesis and is also studied and compared with keeping clotrimazole as a reference.

Finding potential inhibitors against RNA-dependent RNA polymerase (RdRp) of bovine ephemeral fever virus (BEFV): an in-silico study

The bovine ephemeral fever virus (BEFV) is an enzootic agent that affects millions of bovines and causes major economic losses. Though the virus is seasonally reported with a very high morbidity rate (80-100%) from African, Australian, and Asiatic continents, it remains a neglected pathogen in many of its endemic areas, with no proper therapeutic drugs or vaccines presently available for treatment. The RNA-dependent RNA polymerase (RdRp) catalyzes the viral RNA synthesis and is an appropriate candidate for antiviral drug developments. We utilized integrated computational tools to build the 3D model of BEFV-RdRp and then predicted its probable active binding sites. The virtual screening and optimization against these active sites, using several small-molecule inhibitors from a different category of Life Chemical database and FDA-approved drugs from the ZINC database, was performed. We found nine molecules that have docking scores varying between -6.84 to -10.43 kcal/mol. Furthermore, these complexes were analyzed for their conformational dynamics and thermodynamic stability using molecular dynamics simulations in conjunction with the molecular mechanics generalized Born surface area (MM-GBSA) scheme. The binding free energy calculations depict that the electrostatic interactions play a dominant role in the RdRp-inhibitor binding. The hot spot residues, such as Arg565, Asp631, Glu633, Asp740, and Glu707, were found to control the RdRp-inhibitor interaction. The ADMET analysis strongly suggests favorable pharmacokinetics of these compounds that may prove useful for treating the BEFV ailment. Overall, we anticipate that these findings would help explore and develop a wide range of anti-BEFV therapy.Communicated by Ramaswamy H. Sarma.

Potential dual inhibition of SE and CYP51 by eugenol conferring inhibition of Candida albicans: Computationally curated study with experimental validation

Ergosterol is the key sterol component in the cell membrane of fungi including moulds and yeasts. Any decrease in the levels of ergosterol in the cell membrane of fungi render them venerable to cell membrane damage and even its death. Majority of antifungal drug targets the key enzymes involved in ergosterol biosynthesis pathway. The biochemical pathway for the synthesis of Ergosterol is a complex one, though the reactions carried by Squalene Epoxidase (SE) and 14α-demethylase (CYP51- a member of Cytochrome P450 family) serves to the key rate limiting reactions that can impact the overall production of Ergosterol. Allylamines class of antifungal drug target SE while Azoles target the CYP51. Currently advancement in the drug development is focused to introduce newer drugs that can simultaneously inhibit both this rate limiting enzymes. However, natural compounds established to possess antifungal activity but the major loophole about their understanding lies in the fact that their mode of action are severely unstudied. One such well-established antifungal natural phytochemical is Eugenol, and in current manuscript we investigated its efficacy to interact with both, SE and CYP51 of Candida albicans using molecular Docking, Free energy change calculations and Molecular Dynamics (MD) simulation, showing promising outcomes. For experimental studies, terbinafine, clotrimazole and eugenol showed 4 μg/ml, 2 μg/ml, and 512 μg/ml MIC₉₀ values, respectively against C. albicans and also showed reduction in Ergosterol production at sub-MIC levels. The obtained result indicates the involvement of eugenol in the inhibition of enzymes require in the ergosterol biosynthesis pathway.

Predicting Conserved Water Molecules in Binding Sites of Proteins Using Machine Learning Methods and Combining Features

Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it is difficult to identify the conserved water molecules (CWMs) from free water molecules (FWMs) directly as CWMs are normally deeply embedded in proteins and form strong hydrogen bonds with surrounding polar groups. To circumvent this difficulty, in this work, the abundance of spatial structure information and physicochemical properties of water molecules in proteins inspires us to adopt machine learning methods for identifying the CWMs. Therefore, in this study, a machine learning framework to identify the CWMs in the binding sites of the proteins was presented. First, by analyzing water molecules' physicochemical properties and spatial structure information, six features (i.e., atom density, hydrophilicity, hydrophobicity, solvent-accessible surface area, temperature B-factors, and mobility) were extracted. Those features were further analyzed and combined to reach a higher CWM identification rate. As a result, an optimal feature combination was determined. Based on this optimal combination, seven different machine learning models (including support vector machine (SVM), K-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), discriminant analysis (DA), naïve Bayes (NB), and ensemble learning (EL)) were evaluated for their abilities in identifying two categories of water molecules, i.e., CWMs and FWMs. It showed that the EL model was the desired prediction model due to its comprehensive advantages. Furthermore, the presented methodology was validated through a case study of crystal 3skh and extensively compared with Dowser++. The prediction performance showed that the optimal feature combination and the desired EL model in our method could achieve satisfactory prediction accuracy in identifying CWMs from FWMs in the proteins' binding sites.

Molecular insights on ar-turmerone as a structural, functional and pharmacophoric analogue of synthetic mosquito repellent DEET by comprehensive computational assessment

Mosquitoes are vectors for a variety of infectious illnesses, and chemical synthetic insecticides have made it possible to control them effectively. Mosquito repellents are a typical means of keeping mosquitos at bay. Because of its main effectiveness of skin permeability, N,N-Diethyl-meta-toluamide (DEET) is one of the most extensively used mosquito repellents but a dangerous synthetic chemical. DEET was identified about a decade ago to inhibit mosquito's Odorant Binding Protein 1 (OBP1), impairing the mosquito's ability to recognise the host body odour. OBP1 has been identified as a possible target for the development of new mosquito repellents since its discovery. Essential oils from different plants, on the other hand, have been used to repel mosquitos since antiquity. One essential oil from the Curcuma longa (Zingiberales: Zingiberaceae) rhizome display mosquito repellent properties, according to the literature. Furthermore, one of the phytochemicals found in abundance in C. longa essential oil, ar-turmerone, exhibits mosquito repellency as comparable to synthetic DEET. Till date studies on in-silico interaction of natural ar-turmerone with OBP1, which we depict in our current work are scarce. Further, there exist no published reports demonstrating the literary evidence on detailed insights of interaction of DEET with OBP1 along with Molecular Dynamics (MD) simulation studies. We further performed detailed molecular investigations using pharmacophore analysis of ar-turmerone and compared it with DEET, where our findings in the current manuscript unveils for the first time that ar-turmerone is a functional, structural and pharmacophoric analogue of DEET.

Molecular modelling study to discover novel JAK2 signaling pathway inhibitor

The JAK2/STAT signaling cascades facilitates receptor signals which is responsible for cell growth, survival and homeostasis. Ligand binding to JAKs causes phosphorylation other proteins known as STATs, which translocate to the nucleus and regulate transcription of several important proteins. Growth hormone, prolactin and γ-interferon known agonists of JAK STAT receptors, signal to the nucleus by a more direct manner than the receptor tyrosine kinases. Mutations in JAKs may be responsible for immunodeficiency and myeloproliferative disorders because of its important role in cytokine signaling and making the pathway a therapeutic target for various disease. The present study screened Zinc database to find novel JAK2 inhibitors using virtual high throughput screening techniques. Selection of compound for further study was on the basis of docking score, free energy and binding pattern of the compound. Molecular simulation and MM/GBSA free energy was evaluated for the binding interactions and the stability of docked conformations. Several parameters which determine protein ligand interaction like RMSD, RMSF, Rg and binding pattern were observed. Hydrogen bonds (Glu 930, 932 and Asp 994) after 150 ns simulation were observed between identified compound INC000096136346 and it was similar to known inhibitor ruxolitinib. MM/GBSA free energy was comparable to known inhibitor ruxolitinib. ZINC000096136346 qualify Lipinski's rule of five, rule of three, WDI like rule and there is one violation in lead like rule.Communicated by Ramaswamy H. Sarma.

Fisetin 8-C-glucoside as entry inhibitor in SARS CoV-2 infection: molecular modelling study

Coronaviruses are RNA viruses that infect varied species including humans. TMPRSS2 is gateway for SARS CoV-2 entry into the host cell. It causes proteolytic activation of spike protein and discharge of the peptide into host cell. The TMPRSS2 inhibition could be one of the approaches to stop the viral entry, therefore, interaction pattern and binding energies for Fisetin and TMPRSS2 have been explored in the present study. TMPRSS2 peptide was used for homology modelling and then for further study. Molecular docking score and MMGBSA Binding energy of Fisetin was better than Nafamostat, a known inhibitor of TMPRSS2. Post docking MM-GBSA free energy for Fisetin and Nafamostat was -42.78 and -21.11 kcal/mol, respectively. Fisetin forms H bond with Val 25, His 41, Lys 42, Lys 45, Glu 44, Ser186. Nafamostat formed H bonds with Lys 85, Asp 90, Asp 203. RMSD plots of TMPRSS2, TMPRSS2-Fisetin and TMPRSS2-Nafamostat complex showed stable profile with very small fluctuation during entire simulation of 150 ns. Significant decrease in TMPRSS2-Fisetin and TMPRSS2-Nafamostat complex fluctuation occurred around His 41, Glu 44, Gly 136, Ser 186 in RMSF study. During simulation Fisetin interaction was observed with residues Val 25, His 41, Glu 44, Lys 45, Lys 87, Gly 136, Gln 183, Ser 186 likewise interaction of Nafamostat with Lys 85, Asp 90, Asn 163, Asp 203 and Ser 205. Post simulation MM-GBSA free energy was found to be -51.87 ± 4.3 and -48.23 ± 4.39 kcal/mol for TMPRSS2 with Fisetin and Nafamostat, respectively.Communicated by Ramaswamy H. Sarma.

Combination of multiple methods and views for recognition, transportation, and structure-guided modification of lysine-specific demethylase phenylcyclopropylamine inhibitor

Lysine-Specific Demethylase 1 (LSD1) is a typical histone-specific demethylase, which plays an important role in protein methylation modification. It is a member of the amine oxidase family (MAO) that specifically removes methyl groups from monomethylated H3K4, dimethylated H3K4 and H3K9 sites associated with tumorigenesis. Phenylcyclopropylamine derivatives are a class of specific LSD1 inhibitors, drawing attention due to their high efficiency. Here, extensive molecular dynamics (MD) simulations are combined with a three-dimensional quantitative structure-activity relationship (3D-QSAR) in order to design a new phenylcyclopropylamine inhibitor from multiple perspectives. In a ligand-oriented point of view, a 3D-QSAR model with comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) can be built based on the 55 phenylcyclopropylamine compounds targeting LSD1 obtained experimentally. The aromatic and piperazine rings are identified as the potential key groups regulating the activity of the compounds. In an interaction-oriented view, the representative compound is defined with the highest inhibitory efficiency. The binding and delivery mechanism and conformational dependence of activity, including channel and dynamic properties, are studied using RAMD and umbrella sampling technologies. The direct hydrogen bond and conjugated interactions are identified as a major driving force in this procedure. The dominant region of the phenylcyclopropylamine influences the free energy and detects the key residues in recognition and delivery. On the basis of both the ligand and interaction, a series of new inhibitor structures were designed, and two of them showed better efficiency. In order to select the inhibitor with a longer residence time, a comparison is conducted between the designed inhibitors and the experimentally obtained inhibitor from the perspective of static binding and dynamic delivery properties. This work creates new guidance for the phenylcyclopropylamine inhibitor design of LDS1 by combining the ligand and receptor, considering both static and dynamic properties. This scheme could be applied in other inhibitor design systems.

Discovery of Histone Deacetylase Inhibitor Using Molecular Modeling and Free Energy Calculations

The histone acetylation-deacetylation at lysine regulates the functions of many cellular proteins. An increased expression of HDAC6 can cause an increased amount of deacetylated histones, which leads to an inhibition of gene expression and has been associated with cancer cell proliferation. The present study screened the ZINC database to find novel HDAC6 inhibitors using virtual high-throughput screening techniques. The docking score, free energy, and binding pattern of the complexes were used to select a best ligand for further study. Molecular dynamic simulations, binding interactions, and the stability of docked conformations were investigated. Several parameters that determine protein-ligand interactions, such as root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and binding pattern, were observed. Hydrogen bonds were observed at His 573 and Gly 582 after a 150 ns simulation with identified compound ZINC000002845205, and they were similar to known inhibitor Panobinostat. The molecular mechanics with generalised Born and surface area solvation (MM/GBSA) free energy was comparable to known inhibitor Panobinostat. ZINC000002845205 qualifies drug-likeness according to Lipinski's rule-of-five, rule-of-three, and the World Drug Index (WDI)-like rule, but there is one violation in the lead-like rule.

Investigation of molecular mechanism leading to gefitinib and osimertinib resistance against EGFR tyrosine kinase: molecular dynamics and binding free energy calculation

Tyrosine kinase (TK) is an important protein responsible for phosphorylation of variety of proteins that helps in signal transduction process in transferring signal to regulate various physiological and biochemical processes. Drugs inhibiting signal transduction pathways can be a very rational approach to inhibit cellular physiological and biochemical process. Tyrosine kinase inhibitors are a wide family of drugs that have been used successfully in cancer chemotherapy. Certain mutations around the catalytic cleft may cause conformational changes at binding site and leads to decrease in inhibitor sensitivity to TK mutants. EGFR^T790M mutation is the first recognized acquired resistance after tyrosine kinase inhibitor therapy that leads to resistant to first generation TKI in about 50% of non-small cell lung carcinoma patients. Third generation EGFR-TKIs bind irreversibly to the C797, which is present in the ATP-binding pocket. The present work provides a molecular mechanism for understanding the Gefitinib and Osimertinib sensitivities with the EGFR^WILD, EGFR^L858R, EGFR^T790M, EGFR^T790M+C797S mutants using molecular modelling techniques. Changes in response against Gefitinib and Osimertinib were observed with the change of amino acids at the tyrosine kinase domain of EGFR^WILD and its mutants (EGFR^L858R, EGFR^T790M, EGFR^T790M+C797S). RMSD, RMSF and binding energies calculation well correlates with the change in clinical observation.Communicated by Ramaswamy H. Sarma.

Impact of Remdesivir Incorporation along the Primer Strand on SARS-CoV-2 RNA-Dependent RNA Polymerase

Remdesivir was the first antiviral drug that received emergency use authorization from the United States Food and Drug Administration and is now formally approved to treat COVID-19. Remdesivir is a nucleotide analogue that targets the RNA-dependent RNA polymerase (RdRp) of coronaviruses, including SARS-CoV-2. The solution of multiple RdRp structures has been one of the main axes of research in the race against the SARS-CoV-2 virus. Several hypotheses of the mechanism of inhibition of RdRp by remdesivir have been proposed, although open questions remain. This work uses molecular dynamics simulations to explore the impact of remdesivir and two analogues as incoming nucleotides and of up to four incorporations of remdesivir along the primer strand on RdRp. The simulation results suggest that the overall structure and the dynamical behavior of RdRp are destabilized by remdesivir and the two analogues in the incoming position. The incorporation of remdesivir along the primer strand impacts specific non-bonded interactions between the nascent RNA and the polymerase subunit, as well as the overall dynamical networks on RdRp. The strongest impact on the structure and dynamics are observed after three incorporations, when remdesivir is located at position -A3, in agreement with previously reported experimental and computational results. Our results provide atomic-level details of the role played by remdesivir on the disruption of RNA synthesis by RdRp and the main drivers of these disruptions.

Perceiving SARS-CoV-2 Mpro and PLpro dual inhibitors from pool of recognized antiviral compounds of endophytic microbes: an in silico simulation study

Coronavirus disease 2019 (COVID-19) persists and shook the global population where the endgame to this pandemic is brought on by developing vaccines in record-breaking time. Nevertheless, these vaccines are far from perfect where their efficiency ranges from 65 to 90%; therefore, vaccines are not the one only solution to overcome this situation, and apart from administration of vaccines, the scientific community is at quest for finding alternative solutions to incumber SARS-CoV-2 infection. In this study, our research group is keen on identifying a bioactive molecule that is independent in its mode of action from existing vaccines which can potentially target the SARS-CoV-2 virus replicative efficacy. Papain-like protease (PLpro) and main protease (Mpro) are the most lucrative targets of COVIDs against which the drugs can be developed, as these proteases play a vital role in the replication and development of viral particles. Researchers have modelled a compound such as GRL0617 and X77 as an inhibitor of Mpro and PLpro, respectively, but use of these compounds has several limitations on hosts like toxicity and solubility. Under the current study by deploying rigorous computational assessments, pool of microbial secondary metabolites was screened and handpicked to search a structural or functional analogue of GRL0617 and X77, with an idea to identify a compound that can serve as dual inhibitor for both PLpro and Mpro. From the manually curated database of known antiviral compounds from fungal origin, we found cytonic acids A and B to potentially serve as dual inhibitor of PLpro and Mpro.

Computational studies suggest compounds restoring function of p53 cancer mutants can bind SARS-CoV-2 spike protein

It is reasonable to think that cancer patients undergoing chemotherapy or immunotherapy may have a more aggressive course if they are positive for the novel coronavirus disease. Their compulsive condition requires investigation into effective drugs. We applied computational techniques to a series of compounds known for restoring the function of p53 cancer mutant p53^R175H and p53^G245S. Two potent inhibitors, 1-(3-chlorophenyl)-3-(1, 3 -thiazol-2-yl) urea (CTU, PubChem NSC321792) with the highest binding affinity -6.92 kcal/mol followed by a thiosemicarbazone compound N'-(1-(Pyridin-2-yl)ethylidene) azetidine - 1 -carbothiohydrazide (NPC, PubChem NSC319726) with -6.75 kcal/mol were subjected to Molecular Dynamics simulation with receptor binding domain (RBD) and compared with control ligand dexamethasone. In particular, CTU adheres to pocket 1 with an average free energy of binding -21.65 ± 2.89 kcal/mol at the RBD - angiotensin-converting enzyme 2 binding region with the highest frequency of amino acid residues after reaching a local equilibrium in 100 ns MD simulation trajectory. A significant enthalpy contribution from the independent simulations unfolds the possibility of dual binding sites for NPC as shifted pocket 1 (-15.59 ± 5.98 kcal/mol) and pocket 2 (-18.90 ± 5.02 kcal/mol). The obtained results for these two compounds are in good agreement with dexamethasone (-18.45 ± 2.42 kcal/mol). Taken together our findings could facilitate the discovery of small molecules that restore the function of p53 cancer mutants newly against COVID-19 in cancer patients.

Binding free energy of protein/ligand complexes calculated using dissociation Parallel Cascade Selection Molecular Dynamics and Markov state model

We recently proposed a computational procedure to simulate the dissociation of protein/ligand complexes using the dissociation Parallel Cascade Selection Molecular Dynamics simulation (dPaCS-MD) method and to analyze the generated trajectories using the Markov state model (MSM). This procedure, called dPaCS-MD/MSM, enables calculation of the dissociation free energy profile and the standard binding free energy. To examine whether this method can reproduce experimentally determined binding free energies for a variety of systems, we used it to investigate the dissociation of three protein/ligand complexes: trypsin/benzamine, FKBP/FK506, and adenosine A_2A receptor/T4E. First, dPaCS-MD generated multiple dissociation pathways within a reasonable computational time for all the complexes, although the complexes differed significantly in the size of the molecules and in intermolecular interactions. Subsequent MSM analyses produced free energy profiles for the dissociations, which provided insights into how each ligand dissociates from the protein. The standard binding free energies obtained by dPaCS-MD/MSM are in good agreement with experimental values for all the complexes. We conclude that dPaCS-MD/MSM can accurately calculate the binding free energies of these complexes.

Effect of Ions and Sequence Variants on the Antagonist Binding Properties of the Histamine H1 Receptor

The histamine H₁ receptor (H₁R) is a G protein-coupled receptor (GPCR) and represents a main target in the treatment of allergic reactions as well as inflammatory reactions and depressions. Although the overall effect of antagonists on H₁ function has been extensively investigated, rather little is known about the potential modulatory effect of ions or sequence variants on antagonist binding. We investigated the dynamics of a phosphate ion present in the crystal structure and of a sodium ion, for which we determined the position in the allosteric pocket by metadynamics simulations. Both types of ions exhibit significant dynamics within their binding site; however, some key contacts remain stable over the simulation time, which might be exploited to develop more potent drugs targeting these sites. The dynamics of the ions is almost unaffected by the presence or absence of doxepin, as also reflected in their small effect (less than 1 kcal·mol^-1) on doxepin binding affinity. We also examined the effect of four H₁R sequence variants observed in the human population on doxepin binding. These variants cause a reduction in doxepin affinity of up to 2.5 kcal·mol^-1, indicating that personalized medical treatments that take into account individual mutation patterns could increase precision in the dosage of GPCR-targeting drugs.

Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

G protein-coupled receptors (GPCRs) make up the largest superfamily of integral membrane proteins and play critical signal transduction roles in many physiological processes. Developments in molecular biology, biophysical, biochemical, pharmacological, and computational techniques aimed at these important therapeutic targets are beginning to provide unprecedented details on the structural as well as functional basis of their pleiotropic signaling mediated by G proteins, β arrestins, and other transducers. This pleiotropy presents a pharmacological challenge as the same ligand-receptor interaction can cause a therapeutic effect as well as an undesirable on-target side-effect through different downstream pathways. GPCRs don't function as simple binary on-off switches but as finely tuned shape-shifting machines described by conformational ensembles, where unique subsets of conformations may be responsible for specific signaling cascades. X-ray crystallography and more recently cryo-electron microscopy are providing snapshots of some of these functionally-important receptor conformations bound to ligands and/or transducers, which are being utilized by computational methods to describe the dynamic conformational energy landscape of GPCRs. In this chapter, we review the progress in computational conformational sampling methods based on molecular dynamics and discrete sampling approaches that have been successful in complementing biophysical and biochemical studies on these receptors in terms of their activation mechanisms, allosteric effects, actions of biased ligands, and effects of pathological mutations. Some of the sampled simulation time scales are beginning to approach receptor activation time scales. The list of conformational sampling methods and example uses discussed is not exhaustive but includes representative examples that have pushed the limits of classical molecular dynamics and discrete sampling methods to describe the activation energy landscape of GPCRs.

Unravelling the antifungal mode of action of curcumin by potential inhibition of CYP51B: A computational study validated in vitro on mucormycosis agent, Rhizopus oryzae

Like human, fungi too are known to share lot of structural similarities amongst their CYPs (Cytochrome P450 super family of enzymes) which allows antifungal 'azole' compounds to interact with CYPs of human. Clotrimazole, an 'azole' antifungal drug, is a known inhibitor of fungal CYP named CYP51B. Curcumin, a phytochemical obtained from Curcuma longa has the ability to interact with several different human CYPs to induce inhibition. The sequence and the structural similarities amongst both human and fungal CYPs suggest a strong possibility for curcumin to interact with fungal CYP51B to behave like an antifungal agent. To test this hypothesis a study was designed involving mucormycosis agent, Rhizopus oryzae. The ability of curcumin to interact with fungal CYP51B was analysed computationally through molecular docking, MM-GBSA and Molecular Dynamics (MD) simulation assessment. Further, interaction profile for fungal CYP51B-curcumin was compared with human CYP3A4-curcumin, as there are published evidence describing curcumin as an inhibitor of human CYPs. Additionally, to validate in silico findings, an in vitro assay was performed to examine the antifungal potentials of curcumin on the R. oryzae. Conclusive results allow us to determine a plausible mode of action of curcumin to act as an antifungal against a mucormycosis agent.

Docking and scoring for nucleic acid-ligand interactions: Principles and current status

Nucleic acid (NA)-ligand interactions have crucial roles in many cellular processes and, thus, are increasingly attracting therapeutic interest in drug discovery. Molecular docking is a valuable tool for studying molecular interactions. However, because NAs differ significantly from proteins in both their physical and chemical properties, traditional docking algorithms and scoring functions for protein-ligand interactions might not be applicable to NA-ligand docking. Therefore, various sampling strategies and scoring functions for NA-ligand interactions have been developed. Here, we review the basic principles and current status of docking algorithms and scoring functions for DNA/RNA-ligand interactions. We also discuss challenges and limitations of current docking and scoring approaches.

Molecular modelling of the FOXO4-TP53 interaction to design senolytic peptides for the elimination of senescent cancer cells

BACKGROUND

Senescent cells accumulate in tissues over time as part of the natural ageing process and the removal of senescent cells has shown promise for alleviating many different age-related diseases in mice. Cancer is an age-associated disease and there are numerous mechanisms driving cellular senescence in cancer that can be detrimental to recovery. Thus, it would be beneficial to develop a senolytic that acts not only on ageing cells but also senescent cancer cells to prevent cancer recurrence or progression.

METHODS

We used molecular modelling to develop a series of rationally designed peptides to mimic and target FOXO4 disrupting the FOXO4-TP53 interaction and releasing TP53 to induce apoptosis. We then tested these peptides as senolytic agents for the elimination of senescent cells both in cell culture and in vivo.

FINDINGS

Here we show that these peptides can act as senolytics for eliminating senescent human cancer cells both in cell culture and in orthotopic mouse models. We then further characterized one peptide, ES2, showing that it disrupts FOXO4-TP53 foci, activates TP53 mediated apoptosis and preferentially binds FOXO4 compared to TP53. Next, we show that intratumoural delivery of ES2 plus a BRAF inhibitor results in a significant increase in apoptosis and a survival advantage in mouse models of melanoma. Finally, we show that repeated systemic delivery of ES2 to older mice results in reduced senescent cell numbers in the liver with minimal toxicity.

INTERPRETATION

Taken together, our results reveal that peptides can be generated to specifically target and eliminate FOXO4+ senescent cancer cells, which has implications for eradicating residual disease and as a combination therapy for frontline treatment of cancer.

FUNDING

This work was supported by the Cancer Early Detection Advanced Research Center at Oregon Health & Science University.

Protein-Ligand Binding Molecular Details Revealed by Terahertz Optical Kerr Spectroscopy: A Simulation Study

Picosecond fast motions and their involvement in the biochemical processes such as protein-ligand binding has engaged significant attention. Terahertz optical Kerr spectroscopy (OKE) has the superior potential to probe these fast motions directly. Application of OKE in protein-ligand binding study is, however, limited by the difficulty of quantitative atomistic interpretation, and the calculation of Kerr spectrum for entire solvated protein complex was considered not yet feasible, due to the lack of one consistent polarizable model for both configuration sampling and polarizability calculation. Here, we analyzed the biochemical relevance of OKE to the lysozyme-triacetylchitotriose binding based on the first OKE simulation using one consistent Drude polarizable model. An analytical multipole and induced dipole scheme was employed to calculate the off-diagonal Drude polarizability more efficiently and accurately. Further theoretical analysis revealed how the subtle twisting and stiffening of aromatic protein residues' spatial arrangement as well as the confinement of small water clusters between ligand and protein cavity due to the ligand binding can be examined using Kerr spectroscopy. Comparison between the signals of bound complex and that of uncorrelated protein/ligand demonstrated that binding action alone has reflection in the OKE spectrum. Our study indicated OKE as a powerful terahertz probe for protein-ligand binding chemistry and dynamics.

A Possible Mechanism of Graphene Oxide to Enhance Thermostability of D-Psicose 3-Epimerase Revealed by Molecular Dynamics Simulations

Thermal stability is a limiting factor for effective application of D-psicose 3-epimerase (DPEase) enzyme. Recently, it was reported that the thermal stability of DPEase was improved by immobilizing enzymes on graphene oxide (GO) nanoparticles. However, the detailed mechanism is not known. In this study, we investigated interaction details between GO and DPEase by performing molecular dynamics (MD) simulations. The results indicated that the domain (K248 to D268) of DPEase was an important anchor for immobilizing DPEase on GO surface. Moreover, the strong interactions between DPEase and GO can prevent loop α1′-α1 and β4-α4 of DPEase from the drastic fluctuation. Since these two loops contained active site residues, the geometry of the active pocket of the enzyme remained stable at high temperature after the DPEase was immobilized by GO, which facilitated efficient catalytic activity of the enzyme. Our research provided a detailed mechanism for the interaction between GO and DPEase at the nano–biology interface.

Repurposing the antibacterial drugs for inhibition of SARS-CoV2-PLpro using molecular docking, MD simulation and binding energy calculation

Papain-like protease (nsp-3; non-structural protein) of novel corona virus is an ideal target for developing drugs as it plays multiple important functions for viral growth and replication. For instance, role of nsp-3 has been recognized in cleavage of viral polyprotein; furthermore, in infected host it weakens the immune system via downregulating the production of type I interferon. This downregulation is promoted by removal of ubiquitin-like interferon-stimulated gene 15 protein (ISG15) from interferon-responsive factor 3 (IRF3) protein. Among known inhibitors of SARS-CoV-PLpro GRL0617 is by far the most effective inhibitor. As PLpro of SARS-CoV2 is having more than 80% similarity with SARS-CoV-PLpro, GRL0617 is reported to be effective even against SARS-CoV2. Owing to this similarity, certain key amino acids remain the same/conserved in both proteins. Among conserved amino acids Tyr268 for SARS-CoV2 and Tyr269 for SARS-CoV produce important hydrophobic interactions with aromatic rings of GRL0617. Here, in this study antibacterial compounds were collected from ZINC database, and they were filtered to select compounds that are having similar structural features as GRL0617. This filtered library of compound was then docked with SARS-CoV and CoV2-PLpro. Five hits were noted that were able to interact with Tyr268 (SARS-CoV2) and Tyr269 (SARS-CoV). Further, best hit 2-(2-((benzofuran-2-carboxamido)methyl)-5-methoxy-1H-indol-1-yl)acetic acid (ZINC44459905) was studied using molecular dynamic simulation where stability of protein–ligand complex as well as stability of produced interactions was noted.

Revealing the molecular interplay of curcumin as Culex pipiens Acetylcholine esterase 1 (AChE1) inhibitor

Emergence of vector borne diseases has continued to take toll on millions of lives since its inception. The use of insecticides began as vector control strategy in the early 1900's but the menace of insects is still prevalent. Additionally, the inadequate use of organophosphates and carbamates which target acetylcholine esterase (AChE), are known to develop resistance amongst vectors of transmission and are toxic to humans. In this study, extensive computational screening was performed using homology modelling, molecular docking, molecular dynamics (MD) simulation and free energy change calculation, which highlighted curcumin as a lead molecule out of ~ 1700 phytochemicals against Culex pipiens AChE. In vivo larvicidal activity was carried out along with in vivo and in vitro AChE inhibition assay to determine the biochemical efficacy of curcumin. Our study reveals that curcumin induces mortality in Cx. pipiens at an early stage of its life cycle by AChE inhibition. This also underlines the use of curcumin as a coming-age natural product insecticide.

Comparative assessment of RNA-dependent RNA polymerase (RdRp) inhibitors under clinical trials to control SARS-CoV2 using rigorous computational workflow

The devastating effect of SARS-CoV2 continues and the scientific community is pursuing to find the strategy to combat the spread of the virus. The approach is adapted to target this virus with medicine in combination with existing vaccines. For this, the medications that can specifically inhibit an enzyme essential for viral replication 'RNA-dependant-RNA polymerase (RdRp)' of SARS-CoV2 are being developed. RdRp is the enzyme commonly found in all RNA viruses but is absent in humans. There are in total 60 different RdRp inhibitors already under clinical trials for combating other RNA viruses, which are sought to even work for SARS-CoV2. These inhibitors are classified as nucleoside/nucleotide analogues and nonnucleoside/nonnucleotide analogues. In this study, all the known RdRp inhibitors were computationally targeted in the native form and their active form making the use of molecular docking, MM-GBSA and molecular dynamics (MD) simulations to find the top two of each nucleoside/nucleotide analogues and nonnucleoside/nonnucleotide analogues. The results showed ribavirin 5'-triphosphate and favipiravir ribonucleoside triphosphate (favipiravir-RTP) to be the top two nucleotide analogues while pimodivir and dihydropyrazolopyridinone analogue 8d were the top two nonnucleosides/non-nucleotide analogues.

Meticulous assessment of natural compounds from NPASS database for identifying analogue of GRL0617, the only known inhibitor for SARS-CoV2 papain-like protease (PLpro) using rigorous computational workflow

The latest global outbreak of 2019 respiratory coronavirus disease (COVID-19) is triggered by the inception of novel coronavirus SARS-CoV2. If recent events are of any indicators of the epidemics of past, it is undeniable to state a fact that the SARS-CoV2 viral infection is highly transmissible with respect to its previously related SARS-CoV’s. Papain-like protease (PLpro) is an enzyme that is required by the virus itself for replicating into the host system; and it does so by processing its polyproteins into a functional replicase complex. PLpro is also known for downregulating the genes responsible for producing interferons, an essential family of molecules produced in response to viral infection, thus making this protein an indispensable drug target. In this study, PLpro inhibitors were identified through high throughput structure-based virtual screening approach from NPASS natural product library possessing ~ 35,000 compounds. Top five hits were scrutinised based on structural aromaticity and ability to interact with a key active site residue of PLpro, Tyr268. For second level of screening, the MM-GBSA End-Point Binding Free Energy Calculation of the docked complexes was performed, which identified Caesalpiniaphenol A as the best hit. Caesalpiniaphenol A not only possess a double ring aromatic moiety but also has lowest minimum binding energy, which is at par with the control GRL0617, the only known inhibitor of SARS-CoV2 PLpro. Details of the Molecular Dynamics (MD) simulation and ADMET analysis helped to conclusively determine Caesalpiniaphenol A as potentially an inhibitor of SARS-CoV2 PLpro.

Discovery of anti-MERS-CoV small covalent inhibitors through pharmacophore modeling, covalent docking and molecular dynamics simulation

Middle east respiratory syndrome coronavirus (MERS-CoV) is a fatal pathogen that poses a serious health risk worldwide and especially in the middle east countries. Targeting the MERS-CoV 3-chymotrypsin-like cysteine protease (3CLpro) with small covalent inhibitors is a significant approach to inhibit replication of the virus. The present work includes generating a pharmacophore model based on the X-ray crystal structures of MERS-CoV 3CLpro in complex with two covalently bound inhibitors. In silico screening of covalent chemical database having 31,642 compounds led to the identification of 378 compounds that fulfils the pharmacophore queries. Lipinski rules of five were then applied to select only compounds with the best physiochemical properties for orally bioavailable drugs. 260 compounds were obtained and subjected to covalent docking-based virtual screening to determine their binding energy scores. The top three candidate compounds, which were shown to adapt similar binding modes as the reported covalent ligands were selected. The mechanism and stability of binding of these compounds were confirmed by 100 ns molecular dynamic simulation followed by MM/PBSA binding free energy calculation. The identified compounds can facilitate the rational design of novel covalent inhibitors of MERS-CoV 3CLpro enzyme as anti-MERS CoV drugs.

Reckoning γ-Glutamyl-S-allylcysteine as a potential main protease (mpro) inhibitor of novel SARS-CoV-2 virus identified using docking and molecular dynamics simulation

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2 or COVID-19), outbreak was first reported in December 2019 in the Wuhan, China. COVID-19 managed to spread worldwide and so far more than 9.1 million cases and more than 4.7 lakh death has been reported globally. Children, pregnant women, elderly population, immunocompromised patients, and patients with conditions like asthma, diabetes, etc. are highly vulnerable to COVID infection. Currently, there is no treatment available for COVID-19 infection. Traditional medicinal plants have provided bioactive molecules in the past that are efficiently used during conditions like cancer, malaria, microbial infections, immune-compromised states, etc. AYUSH India has recommended the use of Curcuma longa, Allium sativum, Ocimum tenuiflorum, and Withania somnifera for immune-boosting during SARS-CoV-2 infection. In the present study, we investigated the potential of 63-major bioactive molecules of these plants against SARS-CoV-2 main protease (Mpro) through docking studies and compared the results with known inhibitor 11a. Our results proposed cuscohygrine, γ-Glutamyl-S-allylcysteine, anahygrine, and S-allylcystein as the potent inhibitors against Mpro identified using molecular docking and molecular simulation dynamics. Interestingly, these molecules are from A. sativum, and W. somnifera, which are known for their antimicrobial and immunomodulatory potential. None of the proposed molecules have earlier been reported as antiviral molecules. Our results predict very strong potential of these four-molecules against SARS-CoV-2 Mpro, especially γ-glutamyl-S-allylcysteine, as all four form hydrogen bonding with Glu166 that is a crucial residue for the formation of the biologically active dimeric form of Mpro. Therefore, we strongly recommend further research on these biomolecules against SARS-CoV-2.