Binding of a diverse set of ligands to avidin and streptavidin: an accurate quantitative prediction of their relative affinities by a combination of molecular mechanics and continuum solvent models

Targeting the hSSB1-INTS3 Interface: A Computational Screening Driven Approach to Identify Potential Modulators

Human single-stranded DNA binding protein 1 (hSSB1) forms a heterotrimeric complex, known as a sensor of single-stranded DNA binding protein 1 (SOSS1), in conjunction with integrator complex subunit 3 (INTS3) and C9ORF80. This sensory protein plays an important role in homologous recombination repair of double-strand breaks in DNA to efficiently recruit other repair proteins at the damaged sites. Previous studies have identified elevated hSSB1-mediated DNA repair activities in various cancers, highlighting its potential as an anticancer target. While prior efforts have focused on inhibiting hSSB1 by targeting its DNA binding domain, this study seeks to explore the inhibition of the hSSB1 function by disrupting its interaction with the key partner protein INTS3 in the SOSS1 complex. The investigative strategy entails a molecular docking-based screening of a specific compound library against the three-dimensional structure of INTS3 at the hSSB1 binding interface. Subsequent assessments involve in vitro analyses of protein-protein interaction (PPI) disruption and cellular effects through co-immunoprecipitation and immunofluorescence assays, respectively. Moreover, the study includes an evaluation of the structural stability of ligands at the INTS3 hot-spot site using molecular dynamics simulations. The results indicate a potential in vitro disruption of the INTS3-hSSB1 interaction by three of the tested compounds obtained from the virtual screening with one impacting the recruitment of hSSB1 and INTS3 to chromatin following DNA damage. To our knowledge, our results identify the first set of drug-like compounds that functionally target INTS3-hSSB1 interaction, and this provides the basis for further biophysical investigations that should help to speed up PPI inhibitor discovery.

Machine Learning Methods as a Cost-Effective Alternative to Physics-Based Binding Free Energy Calculations

The rank ordering of ligands remains one of the most attractive challenges in drug discovery. While physics-based in silico binding affinity methods dominate the field, they still have problems, which largely revolve around forcefield accuracy and sampling. Recent advances in machine learning have gained traction for protein-ligand binding affinity predictions in early drug discovery programs. In this article, we perform retrospective binding free energy evaluations for 172 compounds from our internal collection spread over four different protein targets and five congeneric ligand series. We compared multiple state-of-the-art free energy methods ranging from physics-based methods with different levels of complexity and conformational sampling to state-of-the-art machine-learning-based methods that were available to us. Overall, we found that physics-based methods behaved particularly well when the ligand perturbations were made in the solvation region, and they did not perform as well when accounting for large conformational changes in protein active sites. On the other end, machine-learning-based methods offer a good cost-effective alternative for binding free energy calculations, but the accuracy of their predictions is highly dependent on the experimental data available for training the model.

Interaction of Asn297-Linked Glycan Ligands with the Fc Fragment of the Immunoglobulin Class G1: A Molecular Dynamics Simulation Study

The allosteric modulation of the homodimeric H10-03-6 protein to glycan ligands L1 and L2, and the STAB19 protein to glycan ligands L3 and L4, respectively, has been studied by molecular dynamics simulations and free energy calculations. The results revealed that the STAB19 protein has a significantly higher affinity for L3 (-11.38 ± 2.32 kcal/mol) than that for L4 (-5.51 ± 1.92 kcal/mol). However, the combination of the H10-03-6 protein with glycan L2 (1.23 ± 6.19 kcal/mol) is energetically unfavorable compared with that of L1 (-13.96 ± 0.35 kcal/mol). Further, the binding of glycan ligands L3 and L4 to STAB19 would result in the significant closure of the two CH2 domains of the STAB19 conformation with the decrease of the centroid distances between the two CH2 domains compared with the H10-03-6/L1/L2 complex. The CH2 domain closure of STAB19 relates directly to the formation of new hydrogen bonds and hydrophobic interactions between the residues Ser239, Val240, Asp265, Glu293, Asn297, Thr299, Ser337, Asp376, Thr393, Pro395, and Pro396 in STAB19 and glycan ligands L3 and L4, which suggests that these key residues would contribute to the specific regulation of STAB19 to L3 and L4. In addition, the distance analysis revealed that the EF loop in the H10-03-6/L1/L2 model presents a high flexibility and partial disorder compared with the stabilized STAB19/L3/L4 complex. These results will be helpful in understanding the specific regulation through the asymmetric structural characteristics in the CH2 and CH3 domains of the H10-03-6 and STAB19 proteins.

Exploring protein-ligand binding affinity prediction with electron density-based geometric deep learning

Rational structure-based drug design relies on accurate predictions of protein-ligand binding affinity from structural molecular information. Although deep learning-based methods for predicting binding affinity have shown promise in computational drug design, certain approaches have faced criticism for their potential to inadequately capture the fundamental physical interactions between ligands and their macromolecular targets or for being susceptible to dataset biases. Herein, we propose to include bond-critical points based on the electron density of a protein-ligand complex as a fundamental physical representation of protein-ligand interactions. Employing a geometric deep learning model, we explore the usefulness of these bond-critical points to predict absolute binding affinities of protein-ligand complexes, benchmark model performance against existing methods, and provide a critical analysis of this new approach. The models achieved root-mean-squared errors of 1.4-1.8 log units on the PDBbind dataset, and 1.0-1.7 log units on the PDE10A dataset, not indicating significant advantages over benchmark methods, and thus rendering the utility of electron density for deep learning models context-dependent. The relationship between intermolecular electron density and corresponding binding affinity was analyzed, and Pearson correlation coefficients r > 0.7 were obtained for several macromolecular targets.

Molecular docking, molecular dynamics simulation, and MM/PBSA analysis of ginger phytocompounds as a potential inhibitor of AcrB for treating multidrug-resistant Klebsiella pneumoniae infections

The emergence of Multidrug resistance (MDR) in human pathogens has defected the existing antibiotics and compelled us to understand more about the basic science behind alternate anti-infective drug discovery. Soon, proteome analysis identified AcrB efflux pump protein as a promising drug target using plant-driven phytocompounds used in traditional medicine systems with lesser side effects. Thus, the present study aims to explore the novel, less toxic, and natural inhibitors of Klebsiella pneumoniae AcrB pump protein from 69 Zingiber officinale phyto-molecules available in the SpiceRx database through computational-biology approaches. AcrB protein's homology-modelling was carried out to get a 3D structure. The multistep-docking (HTVS, SP, and XP) were employed to eliminate less-suitable compounds in each step based on the docking score. The chosen hit-compounds underwent induced-fit docking (IFD). Based on the XP GScore, the top three compounds, epicatechin (-10.78), 6-gingerol (-9.71), and quercetin (-9.09) kcal/mol, were selected for further calculation of binding free energy (MM/GBSA). Furthermore, the short-listed compounds were assessed for their drug-like properties based on in silico ADMET properties and Pa, Pi values. In addition, the molecular dynamics simulation (MDS) studies for 250 ns elucidated the binding mechanism of epicatechin, 6-gingerol, and quercetin to AcrB. From the dynamic binding free energy calculations using MM/PBSA, 6-gingerol exhibited a strong binding affinity towards AcrB. Further, the 6-gingerol complex's energy fluctuation was observed from the free energy landscape. In conclusion, 6-gingerol has a promising inhibiting potential against the AcrB efflux pump and thus necessitates further validation through in vitro and in vivo experiments.Communicated by Ramaswamy H. Sarma.

Ethnopharmacological basis and pharmacodynamics prospectives for folkloric claims of Rosa webbiana wall. Ex. Royle in diarrhea and asthma via In vitro, In vivo and In silico techniques

ETHNOPHARMACOLOGICAL RELEVANCE

Rosa webbiana (Family: Rosaceae) is used by South Asian herbalists to treat gastrointestinal and respiratory disorders.

AIM OF THE STUDY

This research aimed at multiple targets to verify R. webbiana for treating diarrhea and asthma. In vitro, in vivo, and in silico experiments were planned to demonstrate the antispasmodic and bronchodilator potential of R. webbiana.

MATERIALS AND METHODS

The bioactive compounds of R. webbiana were identified and quantified through LC ESI-MS/MS and HPLC. These compounds were predicted for muti-mechanisms of bronchodilator and antispasmodic potential in network pharmacology and molecular docking. In vitro methods (isolated rabbit trachea, bladder, and jejunum tissues) confirmed these multi-mechanisms for antispasmodic and bronchodilator effects. Antiperistalsis, antidiarrheal, and antisecretory experiments were conducted in in-vivo experiments.

RESULTS

The phytochemical analysis indicates the presence of rutin (742.91 μg/g), kaempferol (726.32 μg/g), and quercitrin (688.20 μg/g) in Rw. EtOH. These bioactive compounds in network pharmacology interfere with the pathogenic genes of diarrhea and asthma, which are the members of calcium-mediated signaling pathways and showed the stronger binding affinity towards voltage-gated L-type calcium channels, myosin light chain-kinase, Calcium calmodulin-dependent-kinase, Phosphodiesterase-4, and phosphoinositide phospholipase-C in molecular docking. Rw. EtOH elicited a spasmolytic response in isolated jejunum, trachea, and urine preparations by relaxing K+ (80 mM) and CCh (1 μM) spastic contractions. Additionally, it suppressed calcium concentration-response curves to the right, like verapamil. Like dicyclomine, it caused a rightward parallel shift of the CCh curves, followed by a non-parallel shift at higher concentrations with suppression of the maximal response. Like papaverine, it also caused isoprenaline-induced inhibitory CRCs to shift to the left. Verapamil did not potentiate isoprenaline-induced inhibitory CRCs, although it was more efficacious against K+ (80 mM) than CCh (1 μM)-induced contractions. R. webbiana EtOH extract exhibited complete antiperistalsis (21.55%), antidiarrheal (80.33%), and antisecretory (82.59±0.60) activities in vivo experiments at the dose of 300 mg/kg.

CONCLUSION

Thus, Rw. EtOH modulated multiple pathways, produced calcium antagonistic, anticholinergic, and phosphodiesterase inhibitory actions, and had antidiarrheal and bronchodilator effects.

Calculation of binding affinity of JAK1 inhibitors via accurately computational estimation

Janus kinase 1 (JAK1) is a tyrosine kinase that is involved in the initiation of responses to a number of different cytokine receptor families. The JAK1-dependent pathway is a therapeutic target, and several JAK inhibitors have been developed thanks to intensive research. However, since the ATP binding sites of JAK family members are quite alike, JAK1 inhibitors can thus be less selective, resulting in unanticipated adverse effects. Despite this, minor variations in the ATP-binding site have been extensively used to find a variety of small compounds with different inhibitory properties. Stronger binding affinity of JAK1 inhibitors is believed to be able to reduce the negative effects, leading to better treatment results. Therefore, a thorough computational search that can effectively identify ligands with extremely high binding affinity for JAK1 to serve as promising inhibitors is required. Here, a method combining steered-molecular dynamic (SMD) simulations with a modified linear interaction energy (LIE) model has been developed to evaluate the binding affinities of known JAK1 inhibitors. The correlation coefficient between the estimated and experimental values was 0.72 and a root-mean-square error was 0.97 kcal•mol-1, revealing that the SMD/LIE method can precisely and quickly predict the binding free energies of JAK1 inhibitors. Furthermore, three marine fungus-derived compounds, namely hansforesters E, hansforesters G and tetroazolemycins B, were identified to be particularly promising JAK1 inhibitors, accordingly. These findings show that the SMD/LIE method has a lot of promise for in silico screening of possible JAK1 inhibitors from a vast number of compounds that are now accessible.Communicated by Ramaswamy H. Sarma.

Green synthesis, anti-proliferative evaluation, docking, and MD simulations studies of novel 2-piperazinyl quinoxaline derivatives using hercynite sulfaguanidine-SA as a highly efficient and reusable nanocatalyst

In this study, the immobilization of sulfaguanidine-SA on the surface of FeAl2O4 (hercynite) MNPs (magnetic nanoparticles) as a novel acid nanocatalyst has been successfully reported for the synthesis of 2-(piperazin-1-yl) quinoxaline derivatives via a one-pot multiple-component reaction under green conditions. The products were characterized by SEM, TEM, TGA, EDS, BET technique, VSM, and FTIR. This series of novel 2-piperazinyl quinoxaline derivatives containing isatin-based thio/semicarbazones and/or Schiff bases of Metformin were evaluated for anticancer activity against both human ovarian and colon-derived tumor cell lines by MTT colorimetric assay. Although most of the investigated hybrid compounds exhibited excellent anti-proliferative activities and high selectivity index (SI) values, the promising compounds N'-[4-(quinoxaline-2-yl)-piperazine-1-yl]methyl-5-chloro-1-H-indole,2,3-dion-3-metformin 4c and N'-[4-(quinoxaline-2-yl)-piperazine-1-yl]methyl-5-bromo-1-H-indole,2,3-dion-3-metformin 4b proved to be the most potent anti-proliferative agents (IC50 values < 1 μM). Molecular docking and dynamics simulation suggest that these hybrid compounds can be wrapped in the catalytic cavity of c-Kit tyrosine kinase receptor and the binding pocket of P-glycoprotein with high scores. Thus, 2-piperazinyl quinoxaline linked isatin-based N-Mannich bases of metformin and/or thio/semicarbazones might be served as suitable candidates for further investigations to develop a new generation of multi-target cancer chemotherapy agents.

From Whispering Gallery Mode Resonators to Biochemical Sensors

Optical biosensors are frontrunners for the rapid and real-time detection of analytes, particularly for low concentrations. Among them, whispering gallery mode (WGM) resonators have recently attracted a growing focus due to their robust optomechanical features and high sensitivity, measuring down to single binding events in small volumes. In this review, we provide a broad overview of WGM sensors along with critical advice and additional "tips and tricks" to make them more accessible to both biochemical and optical communities. Their structures, fabrication methods, materials, and surface functionalization chemistries are discussed. We propose this reflection under a pedagogical approach to describe and explain these biochemical sensors with a particular focus on the most recent achievements in the field. In addition to highlighting the advantages of WGM sensors, we also discuss and suggest strategies to overcome their current limitations, leaving room for further development as practical tools in various applications. We aim to provide new insights and combine different knowledge and perspectives to advance the development of the next generation of WGM biosensors. With their unique advantages and compatibility with different sensing modalities, these biosensors have the potential to become major game changers for biomedical and environmental monitoring, among many other relevant target applications.

Discovery of novel direct small-molecule inhibitors targeting HIF-2α using structure-based virtual screening, molecular dynamics simulation, and MM-GBSA calculations

Hypoxia-inducible factors (HIFs) are the main regulatory factors implicated in the adaptation of cancer cells to hypoxic stress, which has provoked much interest as an attractive target for the design of promising chemotherapeutic agents. Since indirect HIF inhibitors (HIFIs) lead to the occurrence of various side effects, the need of the hour is to develop direct HIFIs, physically interacting with important functional domains within the HIF protein structure. Accordingly, in the present study, it was attempted to develop an exhaustive structure-based virtual screening (VS) process coupled with molecular docking, molecular dynamic (MD) simulation, and MM-GBSA calculations for the identification of novel direct inhibitors against the HIF-2α subunit. For this purpose, a focused library of over 200,000 compounds from the NCI database was used for VS against the PAS-B domain of the target protein, HIF-2α. This domain was suggested to be a possible ligand-binding site, which is characterized by a large internal hydrophobic cavity, unique to the HIF-2α subunit. The top-ranked compounds, NSC106416, NSC217021, NSC217026, NSC215639, and NSC277811 with the best docking scores were taken up for the subsequent in silico ADME properties and PAINS filtration. The selected drug-like hits were employed for carrying out MD simulation which was followed by MM-GBSA calculations to retrieve the candidates showing the highest in silico binding affinity towards the PAS-B domain of HIF-2α. The analysis of results indicated that all molecules, except the NSC277811, fulfilled necessary drug-likeness properties. Four selected drug-like candidates, NSC106416, NSC217021, NSC217026, and NSC215639 were found to expose the stability profiles within the cavity located inside the PAS-B domain of HIF-2α over simulation time. Finally, the results of the MM-GBSA rescoring method were indicative of the highest binding affinity of NSC217026 for the binding site of the HIF-2α PAS-B domain among selected final hits. Consequently, the hit NSC217026 could serve as a promising scaffold for further optimization toward the design of direct HIF-2α inhibitors for cancer therapy.

Molecular dynamic simulations identifying the mechanism of holoenzyme formation by O-GlcNAc transferase and active p38α

O-N-Acetylglucosamine transferase (OGT) can catalyze the O-GlcNAc modification of thousands of proteins. The holoenzyme formation of OGT and adaptor protein is the precondition for further recognition and glycosylation of the target protein, while the corresponding mechanism is still open. Here, static and dynamic schemes based on statistics can successfully screen the feasible identifying, approaching, and binding mechanism of OGT and its typical adaptor protein p38α. The most favorable interface, energy contribution of hotspots, and conformational changes of fragments were discovered. The hydrogen bond interactions were verified as the main driving force for the whole process. The distinct characteristic of active and inactive p38α is explored and demonstrates that the phosphorylated tyrosine and threonine will form strong ion-pair interactions with Lys714, playing a key role in the dynamic identification stage. Multiple method combinations from different points of view may be helpful for exploring other systems of the protein-protein interactions.

Mechanistic insights of Cucumis melo L. seeds for gastrointestinal muscle spasms through calcium signaling pathway-related gene regulation networks in WGCNA and in vitro, in vivo studies

BACKGROUND

In addition to the nutritional benefits of Cucumis melo L., herbalists in Pakistan and India employ seeds to treat various ailments. This study aimed to determine the regulatory role of C. melo seeds in calcium-mediated smooth muscle contraction.

METHODS

We identified and quantified the phytochemicals of C. melo with LC ESI-MS/MS and HPLC, then conducted in vitro and in vivo tests to confirm the involvement in smooth muscle relaxation. Then, diarrhea-predominant irritable bowel syndrome gene datasets from NCBI GEO were acquired, DEGs and WGCNA followed by functional enrichment analysis. Next, molecular docking of key genes was performed.

RESULTS

The quantification of C. melo seeds revealed concentrations of rutin, kaempferol, and quercetin were 702.38 μg/g, 686.29 μg/g, and 658.41 μg/g, respectively. In vitro experiments revealed that C. melo seeds had a dose-dependent relaxant effect for potassium chloride (80 mM)-induced spastic contraction and exhibited calcium antagonistic response in calcium dose-response curves. In in vivo studies, Cm.EtOH exhibited antidiarrheal, antiperistaltic, and antisecretory effects. The functional enrichment of WGCNA and DEGs IBS-associated pathogenic genes, including those involved in calcium-mediated signaling, MAPK cascade, and inflammatory responses. MAPK1 and PIK3CG were identified as key genes with greater binding affinity with rutin, quercitrin, and kaempferol in molecular docking.

CONCLUSIONS

The bronchodilator and antidiarrheal effects of C. melo were produced by altering the regulatory genes of calcium-mediated smooth contraction.

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations

Inhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R=0.748±0.044. Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine compounds from the top 100 ML inhibitors were suggested to bind well to the protease with the domination of van der Waals interactions. Furthermore, the binding affinity of these compounds is also higher than that of nirmatrelvir, which was recently approved by the US FDA to treat COVID-19. In addition, the ligands altered the catalytic triad Cys145 - His41 - Asp187, possibly disturbing the biological activity of SARS-CoV-2.

Suramin, penciclovir, and anidulafungin exhibit potential in the treatment of COVID-19 via binding to nsp12 of SARS-CoV-2

COVID-19, for which no confirmed therapeutic agents are available, has claimed over 48,14,000 lives globally. A feasible and quicker method to resolve this problem may be 'drug repositioning'. We investigated selected FDA and WHO-EML approved drugs based on their previously promising potential as antivirals, antibacterials or antifungals. These drugs were docked onto the nsp12 protein, which reigns the RNA-dependent RNA polymerase activity of SARS-CoV-2, a key therapeutic target for coronaviruses. Docked complexes were reevaluated using MM-GBSA analysis and the top three inhibitor-protein complexes were subjected to 100 ns long molecular dynamics simulation followed by another round of MM-GBSA analysis. The RMSF plots, binding energies and the mode of physicochemical interaction of the active site of the protein with the drugs were evaluated. Suramin, Penciclovir, and Anidulafungin were found to bind to nsp12 with similar binding energies as that of Remdesivir, which has been used as a therapy for COVID-19. In addition, recent experimental evidences indicate that these drugs exhibit antiviral efficacy against SARS-CoV-2. Such evidence, along with the significant and varied physical interactions of these drugs with the key viral enzyme outlined in this investigation, indicates that they might have a prospective therapeutic potential in the treatment of COVID-19 as monotherapy or combination therapy with Remdesivir.

Integrated Mechanisms of Polarity-Based Extracts of Cucumis melo L. Seed Kernels for Airway Smooth Muscle Relaxation via Key Signaling Pathways Based on WGCNA, In Vivo, and In Vitro Analyses

The present study aimed to determine the mechanisms responsible for calcium-mediated smooth muscle contractions in C. melo seeds. The phytochemicals of C. melo were identified and quantified with the aid of Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric (LC/ESI-MS/MS) and high-performance liquid chromatography (HPLC), and then tested in-vitro and in vivo to confirm involvement in smooth muscle relaxation. Allergic asthma gene datasets were acquired from the NCBI gene expression omnibus (GEO) and differentially expressed gene (DEG) analysis, weighted gene co-expression network analysis (WGCNA), and functional enrichment analysis were conducted. Additionally, molecular docking of key genes was carried out. Kaempferol, rutin, and quercetin are identified as phytochemical constituents of C. melo seeds. Results indicated that C. melo seeds exhibit a dose-dependent relaxant effect for potassium chloride (80 mM)- induced spastic contraction and calcium antagonistic response in calcium dose-response curves. The functional enrichment of WGCNA and DEG asthma-associated pathogenic genes showed cytokine-mediated pathways and inflammatory responses. Furthermore, CACNA1A, IL2RB, and NOS2 were identified as key genes with greater binding affinity with rutin, quercitrin, and kaempferol in molecular docking. These results show that the bronchodilator and antidiarrheal effects of C. melo were produced by altering the regulatory genes of calcium-mediated smooth muscle contraction.

MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins

Predicting protein-ligand binding free energy rapidly and accurately remains a challenging question in modern drug discovery. Molecular mechanics/Poisson-Boltzmann (Generalized Born) surface area (MM/PB(GB)SA) has emerged as an essential tool for accelerating cost-efficient binding free energy calculation. This study presents benchmarks with three membrane-bound protein systems and six soluble protein systems. Different parameters were sampled for different benchmarks to explore the highest accuracy. These include ligand charges, protein force fields, extra points, GB models, nonpolar optimization methods, internal dielectric constants and membrane dielectric constants. Comparisons of accuracy were made between MM/PB(GB)SA, docking and free energy perturbation (FEP). The results reveal a competitive performance between MM/PB(GB)SA and FEP. In summary, MM/PB(GB)SA is a powerful approach to predict ligand binding free energy rapidly and accurately. Parameters of MM/PB(GB)SA calculations, such as the GB models and membrane dielectric constants, need to be optimized for different systems. This method can be served as a powerful tool for drug design.

Membrane Lipids Are an Integral Part of Transmembrane Allosteric Sites in GPCRs: A Case Study of Cannabinoid CB1 Receptor Bound to a Negative Allosteric Modulator, ORG27569, and Analogs

A growing number of G-protein-coupled receptor (GPCR) structures reveal novel transmembrane lipid-exposed allosteric sites. Ligands must first partition into the surrounding membrane and take lipid paths to these sites. Remarkably, a significant part of the bound ligands appears exposed to the membrane lipids. The experimental structures do not usually account for the surrounding lipids, and their apparent contribution to ligand access and binding is often overlooked and poorly understood. Using classical and enhanced molecular dynamics simulations, we show that membrane lipids are critical in the access and binding of ORG27569 and its analogs at the transmembrane site of cannabinoid CB1 receptor. The observed differences in the binding affinity and cooperativity arise from the functional groups that interact primarily with lipids. Our results demonstrate the significance of incorporating membrane lipids as an integral component of transmembrane sites for accurate characterization, binding-affinity calculations, and lead optimization in drug discovery.

Computational methods for calculation of protein-ligand binding affinities in structure-based drug design

Drug design is an expensive and time-consuming process. Any method that allows reducing the time the costs of the drug development project can have great practical value for the pharmaceutical industry. In structure-based drug design, affinity prediction methods are of great importance. The majority of methods used to predict binding free energy in protein-ligand complexes use molecular mechanics methods. However, many limitations of these methods in describing interactions exist. An attempt to go beyond these limits is the application of quantum-mechanical description for all or only part of the analyzed system. However, the extensive use of quantum mechanical (QM) approaches in drug discovery is still a demanding challenge. This chapter briefly reviews selected methods used to calculate protein-ligand binding affinity applied in virtual screening (VS), rescoring of docked poses, and lead optimization stage, including QM methods based on molecular simulations.

Antispasmodic activity of the ethanol extract of Citrullus lanatus seeds: Justifying ethnomedicinal use in Pakistan to treat asthma and diarrhea

ETHNOPHARMACOLOGICAL RELEVANCE

Citrullus lanatus (Thunb.) belongs to the ground family, Cucurbitaceae, known for edible fruit. Besides nutritional benefits, the traditional herbal practitioners in Pakistan and India used their seeds to treat gastrointestinal, respiratory, and urinary disorders. In Northern Sudan, its seeds are often used as a laxative. Its root is laxative and emetic at a high dose. Its seeds are also used to treat bedwetting and urinary tract obstruction.

AIM OF THE STUDY

This study aimed to elucidate the multi-target mechanisms of Citrullus lanatus seeds to treat asthma and diarrhea. The pharmacological experiments were designed and conducted, along with the pharmacology network and molecular docking predictions, to verify the seeds biopotency for antispasmodic and bronchodilator properties.

METHODS

LC ESI-MS/MS were performed to identify the potentially active compounds in hydroethanolic extract of Citrullus lanatus seeds, then to quantify them by HPLC. The quantified bioactive compounds of Citrullus lanatus, i.e., stigmasterol, quinic acid, malic acid, epicatechin, caffeic acid, rutin, p-coumaric acid, quercetin, ferulic acid, scopoletin, apigenin, and kaempferol were subjected to in silico studies for molecular docking. The hydroethanolic extract of Citrullus lanatus seeds was examined on isolated rabbit tissue, i.e., jejunum, trachea, and urinary bladder. The antiperistalsis, antidiarrheal and antisecretory studies were also performed in animal models.

RESULTS

In silico studies revealed that bioactive compounds of C. lanatus seeds interfere with asthma and diarrhea-associated target genes, which are a member of calcium mediate signaling, regulation of cytosolic calcium concentration, smooth muscle contraction, and inflammatory responses. It was also found that rutin, quercetin, kaempferol, and scopoletin were stronger binding to voltage-gated calcium channels, calcium/calmodulin-dependent protein kinase, myosin light chain kinase, and phosphoinositide phospholipase C, thus, exerting calcium channel blocker activity. The hydroethanolic extract of C. lanatus seeds exerted a concentration-dependent relaxant response for the spasmolytic response on isolated jejunum and trachea preparations and caused relaxation of spastic contraction of K⁺ (80 mM). Furthermore, it caused a non-parallel rightward shift with suppression of calcium concentration-response curves. In animal models, the Cl.EtOH showed antiperistalsis, antidiarrheal and antisecretory response.

CONCLUSION

Thus, we confirm Citrullus lanatus seeds have some medicinal effects by regulating the contractile response through target proteins of calcium mediates signaling and can be a promising component in the medical treatment for asthma and diarrhea.

Interdisciplinary in silico studies to understand in-depth molecular level mechanism of drug resistance involving NS3-4A protease of HCV

Hepatitis C virus (HCV) causes hepatitis, a life-threatening disease responsible for liver cirrhosis. Urgent measures have been taken to develop therapeutics against this deadly pathogen. NS3/4A protease is an extremely important target. A series of inhibitors have been developed against this viral protease including Faldaprevir. Unfortunately, the error-prone viral RNA polymerase causes the emergence of resistance, thereby causing reduced effectiveness of those peptidomimetic inhibitors. Among the drug resistant variants, three single amino acid residues (R155, A156 and D168) are notable for their presence in clinical isolates and also their effectivity against most of the known inhibitors in clinical development. Therefore, it is crucial to understand the mechanistic role of those drug resistant variants while designing potent novel inhibitors. In this communication, we have deeply analyzed through using in silico studies to understand the molecular mechanism of alteration of inhibitor binding between wild type and its R155K, A156V and D168V variants. Principal component analysis was carried to identify the backbone fluctuations of important residues in HCV NS3/4A responsible for the inhibitor binding and maintaining drug resistance. Free energy landscape as a function of the principal components has been used to identify the stability and conformation of the key residues that regulate inhibitor binding and their impact in developing drug resistance. Our findings are consistent with the trend of experimental results. The observations are also true in case of other Faldaprevir-like peptidomimetic inhibitors. Understanding this binding mechanism would be significant for the development of novel inhibitors with less susceptibility towards drug resistance.

Identifying Possible AChE Inhibitors from Drug-like Molecules via Machine Learning and Experimental Studies

Acetylcholinesterase (AChE) is one of the most important drug targets for Alzheimer's disease (AD) treatment. In this work, a machine learning model was trained to rapidly and accurately screen large chemical databases for the potential inhibitors of AChE. The obtained results were then validated via in vitro enzyme assay. Moreover, atomistic simulations including molecular docking and molecular dynamics simulations were then used to understand molecular insights into the binding process of ligands to AChE. In particular, two compounds including benzyl trifluoromethyl ketone and trifluoromethylstyryl ketone were indicated as highly potent inhibitors of AChE because they established IC₅₀ values of 0.51 and 0.33 μM, respectively. The obtained IC₅₀ of two compounds is significantly lower than that of galantamine (2.10 μM). The predicted log(BB) suggests that the compounds may be able to traverse the blood-brain barrier. A good agreement between computational and experimental studies was observed, indicating that the hybrid approach can enhance AD therapy.

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.

Metabolomics based mechanistic insights to vasorelaxant and cardioprotective effect of ethanolic extract of Citrullus lanatus (Thunb.) Matsum. & Nakai. seeds in isoproterenol induced myocardial infraction

BACKGROUND

Cardiovascular diseases (CVDs) are a significant cause of morbidity and death in the current world, posing a challenge to both developing and industrialized nation's health systems. Citrullus lanatus (Thunb.) Matsum. & Nakai. seeds have long been utilized to supplement and enhance health and treat cardiovascular illnesses. However, its treatments for CVDs are still unknown. More research is required to fully comprehend the impact of C. lanatus seeds on vasorelaxation and myocardial infractions.

PURPOSE

Therefore, an integrated metabolomics profiling technique was used to investigate possible pathways of C. lanatus in isoproterenol (ISO)-induced myocardial infarction (MI). Isoproterenol causes long-term cardiac hypertrophy by causing cardiomyocyte compensatory loss, eventually leading to heart failure.

METHODS

In vitro models of vasoconstriction, atrium, and in vivo models of invasive blood pressure measurement and isoproterenol (ISO) induced cardiac hypertrophy in rats were used to understand underlying mechanistic by LC-MS/MS based dynamic metabolomics analysis of the serum and heart samples to be investigated the effect of ethanolic extract of C. lanatus (Cl.EtOH).

RESULTS

Cl.EtOH exhibited vasorelaxant, negative chronotropic, and inotropic effects in in-vitro models whereas, a potent hypotensive effect was observed in normotensive rats. The Cl.EtOH protected the animals from ISO-induced myocardial infarction (MI) with therapeutic interventions in left ventricular thickness, cardiomyocyte hypertrophy, mRNA gene expression, biochemical assays, and metabolomic profiling of serum and heart tissues.

CONCLUSIONS

For the first time, our study confirmed that C. lanatus seeds (Cl.EtOH) possess significant antihypertensive and prevent ISO-induced myocardial infarction. These findings comprehensively demonstrated mechanistic insights of Cl.EtOH in vasorelaxation and myocardial infarction. The current study provides evidence for further mechanistic studies and the development of C. lanatus seeds as a potential therapeutic intervention for patients with cardiovascular disorders.

Possible Mechanisms Underlying the Antispasmodic, Bronchodilator, and Antidiarrheal Activities of Polarity-Based Extracts of Cucumis sativus L. Seeds in In Silico, In Vitro, and In Vivo Studies

Apart from the nutritional value, Cucumis sativus L. has also been used in the traditional medicine of Iran, Pakistan, and India. Its seeds are used by herbalists to treat gastrointestinal, respiratory, and urinary problems. However, more investigations are required to explain its mechanisms for treating GI, respiratory, and urinary diseases. Accordingly, the aim of the present work was to investigate the antispasmodic, bronchodilator, and antidiarrheal activities of C. sativus seeds extracts and the underlying mechanisms of action. For this purpose, sequential extracts of C. sativus seeds were prepared in n-hexane, dichloromethane, ethanol, and water. Bioactive compounds in C. sativus seed extracts were identified and quantified by utilizing LC ESI–MS/MS and HPLC. Moreover, network pharmacology and molecular docking were employed to examine the antispasmodic and bronchodilator effects of the bioactive substances in the extracts. In vitro and in vivo experiments were also conducted to validate the mechanistic insights gained from the in silico analysis. Results indicated the presence of kaempferol with a concentration of 813.74 µg/g (highest concentration) in the seed extract of C. sativus, followed by quercetin (713.83 µg/g), narcissin (681.87 µg/g), and orientin (676.19 µg/g). In silico investigations demonstrated that the bioactive chemicals in C. sativus seeds inhibited the expression of the target genes involved in smooth muscle contraction and calcium-mediated signaling. Sequential seed extracts of C. sativus caused a dose-dependent relaxant response for spasmolytic reaction and resulted in a relaxation of K⁺ (80 mM) spastic contraction. In animal models, C. sativus seed extracts exhibited partial or complete antiperistalsis, antidiarrheal, and antisecretory actions. By modulating the contractile response through calcium-mediated signaling target proteins, C. sativus seeds generated bronchodilator, antispasmodic, and antidiarrheal therapeutic effects.

RNA-ligand molecular docking: advances and challenges

With rapid advances in computer algorithms and hardware, fast and accurate virtual screening has led to a drastic acceleration in selecting potent small molecules as drug candidates. Computational modeling of RNA-small molecule interactions has become an indispensable tool for RNA-targeted drug discovery. The current models for RNA-ligand binding have mainly focused on the docking-and-scoring method. Accurate docking and scoring should tackle four crucial problems: (1) conformational flexibility of ligand, (2) conformational flexibility of RNA, (3) efficient sampling of binding sites and binding poses, and (4) accurate scoring of different binding modes. Moreover, compared with the problem of protein-ligand docking, predicting ligand binding to RNA, a negatively charged polymer, is further complicated by additional effects such as metal ion effects. Thermodynamic models based on physics-based and knowledge-based scoring functions have shown highly encouraging success in predicting ligand binding poses and binding affinities. Recently, kinetic models for ligand binding have further suggested that including dissociation kinetics (residence time) in ligand docking would result in improved performance in estimating in vivo drug efficacy. More recently, the rise of deep-learning approaches has led to new tools for predicting RNA-small molecule binding. In this review, we present an overview of the recently developed computational methods for RNA-ligand docking and their advantages and disadvantages.

Metronidazole, acyclovir and tetrahydrobiopterin may be promising to treat COVID-19 patients, through interaction with interleukin-12

COVID-19 patients have shown overexpressed serum levels of several pro-inflammatory cytokines, leading to a high mortality rate due to numerous complications. Also, previous studies demonstrated that the metronidazole (MTZ) administration reduced pro-inflammatory cytokines and improved the treatment outcomes for inflammatory disorders. However, the effect and mechanism of action of MTZ on cytokines have not been studied yet. Thus, the current study aimed to identify anti-cytokine therapeutics for the treatment of COVID-19 patients with cytokine storm. The interaction of MTZ with key cytokines was investigated using molecular docking studies. MTZ-analogues, and its structurally similar FDA-approved drugs were also virtually screened against interleukin-12 (IL-12). Moreover, their mechanism of inhibition regarding IL-12 binding to IL-12 receptor was investigated by measuring the change in volume and area. IL-12-metronidazole complex is found to be more stable than all other cytokines under study. Our study also revealed that the active sites of IL-12 are inhibited from binding to its target, IL-12 receptor, by modifying the position of the methyl and hydroxyl functional groups in MTZ. Three MTZ analogues, metronidazole phosphate, metronidazole benzoate, 1-[1-(2-Hydroxyethyl)-5-nitroimidazol-2-yl]-N-methylmethanimine-oxide, and two FDA-approved drugs acyclovir (ACV), and tetrahydrobiopterin (THB) were also found to prevent binding of IL-12 to IL-12 receptor similar to MTZ by changing the surface and volume of IL-12 upon IL-12-drug/ligand complex formation. According to the RMSD results, after 100 ns MD simulations of human IL-12-MTZ/ACV/THB drug complexes, it was also observed that each complex was swinging within a few Å compared to their corresponding docking poses, indicating that the docking poses were reliable. The current study demonstrates that three FDA-approved drugs, namely, metronidazole, acyclovir and tetrahydrobiopterin, are potential repurposable treatment options for overexpressed serum cytokines found in COVID-19 patients. Similar approach is also useful to develop therapeutics against other human disorders.

Mechanistic Origin of Different Binding Affinities of SARS-CoV and SARS-CoV-2 Spike RBDs to Human ACE2

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (RBD_CoV2) has a higher binding affinity to the human receptor angiotensin-converting enzyme 2 (ACE2) than the SARS-CoV RBD (RBD_CoV). Here, we performed molecular dynamics (MD) simulations, binding free energy (BFE) calculations, and interface residue contact network (IRCN) analysis to explore the mechanistic origin of different ACE2-binding affinities of the two RBDs. The results demonstrate that, when compared to the RBD_CoV2-ACE2 complex, RBD_CoV-ACE2 features enhanced dynamicsand inter-protein positional movements and increased conformational entropy and conformational diversity. Although the inter-protein electrostatic attractive interactions are the primary determinant for the high ACE2-binding affinities of both RBDs, the significantly enhanced electrostatic attractive interactions between ACE2 and RBD_CoV2 determine the higher ACE2-binding affinity of RBD_CoV2 than of RBD_CoV. Comprehensive comparative analyses of the residue BFE components and IRCNs between the two complexes reveal that it is the residue changes at the RBD interface that lead to the overall stronger inter-protein electrostatic attractive force in RBD_CoV2-ACE2, which not only tightens the interface packing and suppresses the dynamics of RBD_CoV2-ACE2, but also enhances the ACE2-binding affinity of RBD_CoV2. Since the RBD residue changes involving gain/loss of the positively/negatively charged residues can greatly enhance the binding affinity, special attention should be paid to the SARS-CoV-2 variants carrying such mutations, particularly those near or at the binding interfaces with the potential to form hydrogen bonds and/or salt bridges with ACE2.

Syzygium cumini (L.) Skeels extracts; in vivo anti-nociceptive, anti-inflammatory, acute and subacute toxicity assessment

ETHNOPHARMACOLOGICAL RELEVANCE

Syzygium cumini (L.) Skeels has been extensively used in the ancient medical system of Pakistan, India, Bangladesh, and Sri Lanka to combat diabetes, inflammation, and renal disorders. These health-promoting aspects of S. cumini are related to bioactive metabolites such as phenolic acids, anthocyanins, tannins, and flavonoids.

AIM OF THE STUDY

Earlier to this study, we have reported S. cumini extracts as potential sources of bioactive compounds bearing antioxidant and anti-inflammatory properties. However, prior further suggesting S. cumini fruit extracts for consumption against inflammatory disorders, it was mandatory to validate the claim and explore toxicity of the extracts. This study aims to determine the in vivo anti-nociceptive, anti-inflammatory, acute, and subacute toxicity properties of S. cumini crude extracts, followed by identifying and quantifying bioactive metabolites.

MATERIAL AND METHODS

In the present study, the anti-nociceptive and anti-inflammatory potential of S. cumini sequential crude extracts were evaluated using formalin and glutamate-induced paw licking method in mice. The acute and sub-acute toxicity assessment of active extract was performed by oral administration in rats. An acute toxicity trial was performed with two different doses, i.e., 2000 mg/kg and 3000 mg/kg for consecutive 14 days, whereas a sub-acute toxicity study was conducted at doses of 750 mg/kg and 1500 mg/kg for the next 28 days. Identification of bioactive compounds was performed using HPLC, and at the end, in silico docking calculations of identified compounds were performed.

RESULTS

The 100% methanolic extract (SCME) protected the mice from painful stimulation of formalin and glutamate in a dose-dependent manner with the maximum effect of 49% and 67% at 200 mg/kg, respectively, followed by moderate and non-influential effects of 50% methanolic extract and dichloromethane (DCM) extracts when compared to control, i.e., normal saline. The results of acute toxicity recorded LD₅₀ of SCME over 3000 mg/kg, and no antagonistic effects were recorded during the subacute study when SCME dispensed at the rate of 750 mg/kg and 1500 mg/kg. SCME was found to induce no adverse effects to kidney, heart, liver, spleen, and paired lungs examined by hematological, serum biochemical, histological analysis. HPLC analysis of S. cumini 100% methanolic extracts revealed the presence of delphinidin 3-glucoside, peonidin-3,5-diglucoside, scopoletin, and umbelliferone at the concentration of 127.4, 2104, 31.3, 10.4 μg/g whereas in 50% methanolic extract, the quinic acid, catechin, and myricetin were present at the concentration of 54.9, 63.7, 12.3 μg/g, respectively. Umbelliferone and scopoletin are newly reported compounds in the present study. In silico docking calculations of these compounds indicated the potential of anti-nociceptive and anti-inflammatory activities.

CONCLUSIONS

These findings validate that S. cumini fruit extracts are a rich source of bioactive compounds that needs to be considered to enhance biological activities with lesser side effects.

Scientific basis for medicinal use of Citrullus lanatus (Thunb.) in diarrhea and asthma: In vitro, in vivo and in silico studies

BACKGROUND

Citrullus lanatus (Thunb.) is a member of the Cucurbitaceae family, commonly farmed as an edible vegetable around the globe. It has been used in traditional therapies in addition to nutritional advantages. Traditional herbal practitioners employ C. lanatus seeds to treat gastrointestinal, respiratory, and urinary diseases in Pakistan and India. However, more investigation is needed to understand the effect of C. lanatus seeds on treating gastrointestinal, respiratory, and urinary disorders.

PURPOSE

This research aimed to use network pharmacology and molecular docking to understand multi-target mechanisms of C. lanatus seeds against asthma and diarrhea and to validate its effects using biological tests to investigate antispasmodic and bronchodilator capabilities.

METHODS

The ground seeds of C. lanatus were extracted in hexane, dichloromethane, ethanol, and aqueous for sequential extracts. The bioactive components in sequential extracts of C. lanatus seeds were identified using LC ESI-MS/MS, and specific compounds were quantified using HPLC. The quantified bioactive compounds of C. lanatus were subjected to in silico studies for network pharmacology and molecular docking to elucidate their role in antispasmodic and bronchodilator properties. The sequential extracts were tested on isolated rabbit tissue, i.e., jejunum, trachea, and urinary bladder. The antiperistalsis, antidiarrheal and antisecretory studies were also performed in animal models.

RESULTS

In silico studies indicate that bioactive chemicals from sequential extracts of C. lanatus seeds interfere with asthma and diarrhea-associated pathogenic genes. Those are members of calcium mediate signaling, cholinergic synapse, regulation of cytosolic calcium concentration, smooth muscle contraction, and inflammatory responses. It was also found that rutin, quercitrin, stearic acid, umbelliferone, and kaempferol were stronger binding to voltage-gated calcium channels and muscarinic M3 receptor, thus exerting calcium channel blocker activity and cholinergic receptor stimulant response. On isolated jejunum, trachea, and urinary preparations, sequential extracts of C. lanatus seeds elicited the spasmolytic response and showed the relaxation of spastic contractions of K+ (80 mM) and carbachol (1 µM). Furthermore, it induced a non-parallel rightward shift in calcium concentration-response curves with suppression. In animal models, C. lanatus seed extracts exhibited partially or completely antiperistalsis, antidiarrheal, and antisecretory effects.

CONCLUSION

Thus, Citrullus lanatus had therapeutic benefits by modulating the contractile response through calcium-mediated signaling target proteins, hence exerting bronchodilator and antidiarrheal properties. The current study provides evidence for further mechanistic studies and the development of C. lanatus seeds as a potential therapeutic intervention for patients with gastrointestinal, respiratory, and urinary disorders.

Metabolomics analysis delineates the therapeutic effects of hydroethanolic extract of Cucumis sativus L. seeds on hypertension and isoproterenol-induced myocardial infarction

Cucumis sativus L., widely cultivated as an edible vegetable. Its seeds are well reputed for cardiovascular preventive properties. However, the mechanisms underlying for cardiovascular protection of C. sativus are still unidentified. Therefore, this study utilized a metabolomics approach to investigate putative mechanisms of C. sativus seeds in myocardial infarction (MI) and in vitro models of vasoconstriction, atrium, and invasive blood pressure measurement. Results showed that Cu.EtOH extract showed a vasorelaxant response with potent hypotensive effect in normotensive rats and L-NAME induced hypertension. Cu.EtOH caused a negative inotropic and positive chronotropic effect on the atrium. Cu.EtOH protected the animals from ISO-induced myocardial infarction (MI) interventions in left ventricular thickness, cardiomyocyte hypertrophy, mRNA gene expression, and biochemical assays. The metabolomics data suggested that Cu.EtOH mainly affected amino acid metabolism, BCAA degradation, ketone bodies degradation, and oxidative stress. Our study showed that Cu.EtOH suppressed inflammation with a strong anti-myocardial infarction impact. Additionally, our findings indicated Cu.EtOH reverted the amino acid metabolism, BCAA, and ketone bodies degradation. The findings show the antihypertensive mechanism of Cu.EtOH may include the modulation of endothelium-derived relaxing factor (EDRF) produced from nitric oxide (NO) and is connected with vascular endothelial function. C. sativus seeds, in particular, played a pivotal role in the treatment of myocardial and vascular disorders by enhancing the EDRF mechanism, energy generation, and antioxidant capacity. In summary, our findings showed the mechanistic insights on the therapeutic potential of C. sativus seeds for cardiovascular disorders.

Unveiling of Pyrimidindinones as Potential Anti-Norovirus Agents-A Pharmacoinformatic-Based Approach

The RNA-dependent RNA polymerase (RdRp) receptor is an attractive target for treating human norovirus (HNV). A computer-aided approach like e-pharmacophore, molecular docking, and single point energy calculations were performed on the compounds retrieved from the Development Therapeutics Program (DTP) AIDS Antiviral Screen Database to identify the antiviral agent that could target the HNV RdRp receptor. Induced-fit docking (IFD) results showed that compounds ZINC1617939, ZINC1642549, ZINC6425208, ZINC5887658 and ZINC32068149 bind with the residues in the active site-B of HNV RdRp receptor via hydrogen bonds, salt bridge, and electrostatic interactions. During the molecular dynamic simulations, compounds ZINC6425208, ZINC5887658 and ZINC32068149 displayed an unbalanced backbone conformation with HNV RdRp protein, while ZINC1617939 and ZINC1642549 maintained stability with the protein backbone when interacting with the residues. Hence, the two new concluding compounds discovered by the computational approach can be used as a chemotype to design promising antiviral agents aimed at HNV RdRp.

Identifying the Hot Spot Residues of the SARS-CoV-2 Main Protease Using MM-PBSA and Multiple Force Fields

In this study, we investigated the binding affinities between the main protease of SARS-CoV-2 virus (Mpro) and its various ligands to identify the hot spot residues of the protease. To benchmark the influence of various force fields on hot spot residue identification and binding free energy calculation, we performed MD simulations followed by MM-PBSA analysis with three different force fields: CHARMM36, AMBER99SB, and GROMOS54a7. We performed MD simulations with 100 ns for 11 protein-ligand complexes. From the series of MD simulations and MM-PBSA calculations, it is identified that the MM-PBSA estimations using different force fields are weakly correlated to each other. From a comparison between the force fields, AMBER99SB and GROMOS54a7 results are fairly correlated while CHARMM36 results show weak or almost no correlations with the others. Our results suggest that MM-PBSA analysis results strongly depend on force fields and should be interpreted carefully. Additionally, we identified the hot spot residues of Mpro, which play critical roles in ligand binding through energy decomposition analysis. It is identified that the residues of the S4 subsite of the binding site, N142, M165, and R188, contribute strongly to ligand binding. In addition, the terminal residues, D295, R298, and Q299 are identified to have attractive interactions with ligands via electrostatic and solvation energy. We believe that our findings will help facilitate developing the novel inhibitors of SARS-CoV-2.

Antidiarrheal and Cardio-Depressant Effects of Himalaiella heteromalla (D.Don) Raab-Straube: In Vitro, In Vivo, and In Silico Studies

Himalaiella heteromalla (D.Don) Raab-Straube is a commonly used remedy against various diseases. Crude extract and fractions of H. heteromalla were investigated for a gastrointestinal, bronchodilator, cardiovascular, and anti-inflammatory activities. H. heteromalla crude extract (Hh.Cr) relaxed spontaneous contractions and K+ (80 mM)-induced contraction in jejunum tissue dose-dependently. The relaxation of K+ (80 mM) indicates the presence of Ca++ channel blocking (CCB) effect, which was further confirmed by constructing calcium response curves (CRCs) as they caused rightward parallel shift of CRCs in a manner comparable to verapamil, so the spasmolytic effect of Hh.Cr was due to its CCB activity. Application of Hh.Cr on CCh (1 µM) and K+ (80 mM)-induced contraction in tracheal preparation resulted in complete relaxation, showing its bronchodilator effect mediated through Ca++ channels and cholinergic antagonist activity. Application of Hh.Cr on aortic preparations exhibited vasorelaxant activity through angiotensin and α-adrenergic receptors blockage. It also showed the cardio suppressant effect with negative chronotropic and inotropic response in paired atrium preparation. Similar effects were observed in in vivo models, i.e., decreased propulsive movement, wet feces, and inhibition of edema formation.

Integration of System Biology Tools to Investigate Huperzine A as an Anti-Alzheimer Agent

Aim: The present study aimed to investigate huperzine A as an anti-Alzheimer agent based on the principle that a single compound can regulate multiple proteins and associated pathways, using system biology tools. Methodology: The simplified molecular-input line-entry system of huperzine A was retrieved from the PubChem database, and its targets were predicted using SwissTargetPrediction. These targets were matched with the proteins deposited in DisGeNET for Alzheimer disease and enriched in STRING to identify the probably regulated pathways, cellular components, biological processes, and molecular function. Furthermore, huperzine A was docked against acetylcholinesterase using AutoDock Vina, and simulations were performed with the Gromacs package to take into account the dynamics of the system and its effect on the stability and function of the ligands. Results: A total of 100 targets were predicted to be targeted by huperzine A, of which 42 were regulated at a minimum probability of 0.05. Similarly, 101 Kyoto Encyclopedia of Genes and Genomes pathways were triggered, in which neuroactive ligand-receptor interactions scored the least false discovery rate. Also, huperzine A was predicted to modulate 54 cellular components, 120 molecular functions, and 873 biological processes. Furthermore, huperzine A possessed a binding affinity of -8.7 kcal/mol with AChE and interacted within the active site of AChE via H-bonds and hydrophobic interactions.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Cucumis sativus L. Seeds Ameliorate Muscular Spasm-Induced Gastrointestinal and Respiratory Disorders by Simultaneously Inhibiting Calcium Mediated Signaling Pathway

Cucumis sativus L. is globally cultivated as an edible vegetable. Besides its nutritional benefits, it is used in traditional medicines against various ailments. The current study was designed to elucidate the multi-target mechanisms of a C. sativus seeds extract against asthma and diarrhea using network pharmacology along with a molecular docking approach. Furthermore, in-vitro and in-vivo experiments were conducted to verify the mechanistic insight of in silico studies. LC-ESI-MS/MS was performed to identify the bioactive compounds in the extract; later, some compounds were quantified by HPLC. C. sativus seed. EtOH has kaempferol in higher concentration 783.02 µg/g, followed by quercetin (693.83 µg/g) and luteolin (617.17 µg/g). In silico studies showed that bioactive compounds interfered with asthma and diarrhea-associated target genes, which are members of calcium-mediated signaling to exert a calcium channel blocker activity. The seeds extract exerted a concentration-dependent spasmolytic response on isolated jejunum, trachea, and urinary bladder preparations and caused relaxation of spastic contraction of K+ (80 mM) with suppressed calcium concentration-response curves at dose 0.3 and 1 mg/mL. It also showed antiperistalsis, antidiarrheal and antisecretory activity in animal models. Thus, C. sativus seeds have therapeutic effects by regulating the contractile response through a calcium-mediated signaling pathway.

Improving ligand-ranking of AutoDock Vina by changing the empirical parameters

AutoDock Vina (Vina) achieved a very high docking-success rate, p ^ , but give a rather low correlation coefficient, R , for binding affinity with respect to experiments. This low correlation can be an obstacle for ranking of ligand-binding affinity, which is the main objective of docking simulations. In this context, we evaluated the dependence of Vina R coefficient upon its empirical parameters. R is affected more by changing the gauss2 and rotation than other terms. The docking-success rate p ^ is sensitive to the alterations of the gauss1, gauss2, repulsion, and hydrogen bond parameters. Based on our benchmarks, the parameter set1 has been suggested to be the most optimal. The testing study over 800 complexes indicated that the modified Vina provided higher correlation with experiment R set 1 = 0.556 ± 0.025 compared with R Default = 0.493 ± 0.028 obtained by the original Vina and R Vina 1.2 = 0.503 ± 0.029 by Vina version 1.2. Besides, the modified Vina can be also applied more widely, giving R ≥ 0.500 for 32/48 targets, compared with the default package, giving R ≥ 0.500 for 31/48 targets. In addition, validation calculations for 1036 complexes obtained from version 2019 of PDBbind refined structures showed that the set1 of parameters gave higher correlation coefficient ( R set 1 = 0.617 ± 0.017 ) than the default package ( R Default = 0.543 ± 0.020 ) and Vina version 1.2 ( R Vina 1.2 = 0.540 ± 0.020 ). The version of Vina with set1 of parameters can be downloaded at https://github.com/sontungngo/mvina. The outcomes would enhance the ranking of ligand-binding affinity using Autodock Vina.

Understanding the avidin-biotin binding based on polarized protein-specific charge

In this study, charge updating schemes based on the local polarized protein-specific charge (LPPC) were introduced to vary the atomic charges of the biotin molecule and the residues in close contact during the simulation of the avidin-biotin complexes. The need of the charge variation of the ligand in response to changes in its surroundings was thoroughly studied. The results show that the calculated binding energy difference between biotin (BTN1) and 2'-iminobiotin (BTN2) and avidin is in excellent agreement with the experimental value, thus verifying the feasibility of updating the atomic charges of ligands during the simulation.

Discovery of novel hit compounds as potential HDAC1 inhibitors: The case of ligand- and structure-based virtual screening

Histone deacetylases (HDACs) as an important family of epigenetic regulatory enzymes are implicated in the onset and progression of carcinomas. As a result, HDAC inhibition has been proven as a compelling strategy for reversing the aberrant epigenetic changes associated with cancer. However, non-selective profile of most developed HDAC inhibitors (HDACIs) leads to the occurrence of various side effects, limiting their clinical utility. This evidence provides a solid ground for ongoing research aimed at identifying isoform-selective inhibitors. Among the isoforms, HDAC1 have particularly gained increased attention as a preferred target for the design of selective HDACIs. Accordingly, in this paper, we have developed a reliable virtual screening process, combining different ligand- and structure-based methods, to identify novel benzamide-based analogs with potential HDAC1 inhibitory activity. For this purpose, a focused library of 736,160 compounds from PubChem database was first compiled based on 80% structural similarity with four known benzamide-based HDAC1 inhibitors, Mocetinostat, Entinostat, Tacedinaline, and Chidamide. Our inclusive in-house 3D-QSAR model, derived from pharmacophore-based alignment, was then employed as a 3D-query to discriminate hits with the highest predicted HDAC1 inhibitory activity. The selected hits were subjected to subsequent structure-based approaches (induced-fit docking (IFD), MM-GBSA calculations and molecular dynamics (MD) simulation) to retrieve potential compounds with the highest binding affinity for HDAC1 active site. Additionally, in silico ADMET properties and PAINS filtration were also considered for selecting an enriched set of the best drug-like molecules. Finally, six top-ranked hit molecules, CID_38265326, CID_56064109, CID_8136932, CID_55802151, CID_133901641 and CID_18150975 were identified to expose the best stability profiles and binding mode in the HDAC1 active site. The IFD and MD results cooperatively confirmed the interactions of the promising selected hits with critical residues within HDAC1 active site. In summary, the presented computational approach can provide a set of guidelines for the further development of improved benzamide-based derivatives targeting HDAC1 isoform.

On the Use of Interaction Entropy and Related Methods to Estimate Binding Entropies

Molecular mechanics combined with Poisson-Boltzmann or generalized Born and solvent-accessible area solvation energies (MM/PBSA and MM/GBSA) are popular methods to estimate the free energy for the binding of small molecules to biomacromolecules. However, the estimation of the entropy has been problematic and time-consuming. Traditionally, normal-mode analysis has been used to estimate the entropy, but more recently, alternative approaches have been suggested. In particular, it has been suggested that exponential averaging of the electrostatic and Lennard-Jones interaction energies may provide much faster and more accurate entropies, the interaction entropy (IE) approach. In this study, we show that this exponential averaging is extremely poorly conditioned. Using stochastic simulations, assuming that the interaction energies follow a Gaussian distribution, we show that if the standard deviation of the interaction energies (σIE) is larger than 15 kJ/mol, it becomes practically impossible to converge the interaction entropies (more than 10 million energies are needed, and the number increases exponentially). A cumulant approximation to the second order of the exponential average shows a better convergence, but for σIE > 25 kJ/mol, it gives entropies that are unrealistically large. Moreover, in practical applications, both methods show a steady increase in the entropy with the number of energies considered.

Molecular Dynamics Simulations in Designing DARPins as Phosphorylation-Specific Protein Binders of ERK2

Extracellular signal-regulated kinases 1 and 2 (ERK1/2) play key roles in promoting cell survival and proliferation through the phosphorylation of various substrates. Remarkable antitumour activity is found in many inhibitors that act upstream of the ERK pathway. However, drug-resistant tumour cells invariably emerge after their use due to the reactivation of ERK1/2 signalling. ERK1/2 inhibitors have shown clinical efficacy as a therapeutic strategy for the treatment of tumours with mitogen-activated protein kinase (MAPK) upstream target mutations. These inhibitors may be used as a possible strategy to overcome acquired resistance to MAPK inhibitors. Here, we report a class of repeat proteins-designed ankyrin repeat protein (DARPin) macromolecules targeting ERK2 as inhibitors. The structural basis of ERK2-DARPin interactions based on molecular dynamics (MD) simulations was studied. The information was then used to predict stabilizing mutations employing a web-based algorithm, MAESTRO. To evaluate whether these design strategies were successfully deployed, we performed all-atom, explicit-solvent molecular dynamics (MD) simulations. Two mutations, Ala → Asp and Ser → Leu, were found to perform better than the original sequence (DARPin E40) based on the associated energy and key residues involved in protein-protein interaction. MD simulations and analysis of the data obtained on these mutations supported our predictions.

In Silico Characterization of the Interaction between the PBP2a "Decoy" Protein of Resistant Staphylococcus aureus and the Monomeric Units of Eudragit E-100 and Poly(Maleic Acid-alt-Octadecene) Polymers

Antimicrobial treatment alternatives for methicillin-resistant Staphylococcus aureus (MRSA) are increasingly limited. MRSA strains are resistant to methicillin due to the formation of β-lactamase enzymes, as well as the acquisition of the mecA gene, which encodes the penicillin-binding protein (PBP2a) that reduces the affinity for β-lactam drugs. Previous studies have shown that the use of ampicillin-loaded nanoparticles can improve antimicrobial activity on resistant S. aureus strains. However, the biological mechanism of this effect has not yet been properly elucidated. Therefore, this short communication focused on characterizing the in silico interactions of the PBP2a membrane receptor protein from S. aureus against the monomeric units of two polymeric materials previously used in the development of different nanoparticles loaded with ampicillin. Such polymers correspond to Eudragit E-100 chloride (EuCl) and the sodium salt of poly(maleic acid-alt-octadecene) (PAM-18Na). For this, molecular coupling studies were carried out in the active site of the PBP2a protein with the monomeric units of both polymers in neutral and ionized form, as well as with ampicillin antibiotic (model β-lactam drug). The results showed that ampicillin, as well as the monomeric units of EuCl and PAM18Na, described a slight binding free energy to the PBPa2 protein. In addition, it was found that the amino acids of the active site of the PBPa2 protein have interactions of different types and intensities, suggesting, in turn, different forms of protein–substrate coupling.

Insights into the molecular mechanism of positive cooperativity between partial agonist MK-8666 and full allosteric agonist AP8 of hGPR40 by Gaussian accelerated molecular dynamics (GaMD) simulations

Activation of human free fatty acid receptor 1 (FFAR1, also called hGPR40) enhances insulin secretion in a glucose-dependent manner. Hence, the development of selective agonist targeting hGPR40 has been proposed as a therapeutic strategy of type 2 diabetes mellitus. Some agonists targeting hGPR40 were reported. The radioligand-binding studies and the crystal structures reveal that there are multiple sites on GPR40, and there exists positive binding cooperativity between the partial agonist MK-8666 and full allosteric agonist (AgoPAM) AP8. In this work, we carried out long-time Gaussian accelerated molecular dynamics (GaMD) simulations on hGPR40 to shed light on the mechanism of the cooperativity between the two agonists at different sites. Our results reveal that the induced-fit conformational coupling is bidirectional between the two sites. The movements and rotations of TM3, TM4, TM5 and TM6 due to their inherent flexibility are crucial in coupling the conformational changes of the two agonists binding sites. These helices adopt similar conformational states upon alternative ligand or both ligands binding. The Leu138^4.57, Leu186^5.42 and Leu190^5.46 play roles in coordinating the rearrangements of residues in the two pockets, which makes the movements of residues in the two sites like gear movements. These results provide detailed information at the atomic level about the conformational coupling between different sites of GPR40, and also provide the structural information for further design of new agonists of GPR40. In addition, these results suggest that it is necessary by considering the effect of other site bound in structure-based ligands discovery.

Computational design of ultrashort peptide inhibitors of the receptor-binding domain of the SARS-CoV-2 S protein

Targeting the interaction between severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2)-receptor-binding domain (RBD) and angiotensin-converting enzyme 2 (ACE2) is believed to be an effective strategy for drug design to inhibit the infection of SARS-CoV-2. Herein, several ultrashort peptidase inhibitors against the RBD-ACE2 interaction were obtained by a computer-aided approach based on the RBD-binding residues on the protease domain (PD) of ACE2. The designed peptides were tested on a model coronavirus GX_P2V, which has 92.2 and 86% amino acid identity to the SARS-CoV-2 spike protein and RBD, respectively. Molecular dynamics simulations and binding free energy analysis predicted a potential binding pocket on the RBD of the spike protein, and this was confirmed by the specifically designed peptides SI5α and SI5α-b. They have only seven residues, showing potent antiviral activity and low cytotoxicity. Enzyme-linked immunosorbent assay result also confirmed their inhibitory ability against the RBD-ACE2 interaction. The ultrashort peptides are promising precursor molecules for the drug development of Corona Virus Disease 2019, and the novel binding pocket on the RBD may be helpful for the design of RBD inhibitors or antibodies against SARS-CoV-2.

Structurally disordered C-terminal residues of GTP cyclohydrolase II are essential for its enzymatic activity

GTP cyclohydrolase II (GCHII) is one of the rate limiting enzymes in riboflavin biosynthesis pathway and is shown to be a potential drug target for most of the pathogens. Previous biochemical and structural studies have identified the active site residues and elucidated the steps involved in the catalytic mechanism of GCHII. However, the last ∼20-25 C-terminal residues of GCHII remains unstructured in all the crystal structures determined to date and their role in the catalytic activity, if any, remains elusive. Therefore, to understand the role of these unstructured C-terminal residues, a series of C-terminal deletion mutants of GCHII from Helicobacter pylori (hGCHII) were generated and their catalytic activity was compared with its wild-type. Surprisingly, none of the C-terminal deletion mutants shows any enzymatic activity indicating that these are essential for GCHII function. To get additional insights for such loss of activity, homology models of full-length and deletion mutants of hGCHII in complex with GTP, Mg²⁺, and Zn²⁺ were generated and subjected to molecular dynamics simulation studies. The simulation studies show that a conserved histidine at 190^th position from the unstructured C-terminal region of hGCHII interacts with α-phosphate of GTP. We propose that His-190 may play a role in the hydrolysis of pyrophosphate from GTP and in releasing the product, DARP. In summary, we demonstrate that the unstructured C-terminal residues of GCHII are important for its enzymatic activity and must be considered during rational drug designing. Communicated by Ramaswamy H. Sarma.

Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro

The COVID-19 pandemic has killed millions of people worldwide since its outbreak in December 2019. The pandemic is caused by the SARS-CoV-2 virus whose main protease (Mpro) is a promising drug target since it plays a key role in viral proliferation and replication. Currently, developing an effective therapy is an urgent task, which requires accurately estimating the ligand-binding free energy to SARS-CoV-2 Mpro. However, it should be noted that the accuracy of a free energy method probably depends on the protein target. A highly accurate approach for some targets may fail to produce a reasonable correlation with the experiment when a novel enzyme is considered as a drug target. Therefore, in this context, the ligand-binding affinity to SARS-CoV-2 Mpro was calculated via various approaches. The molecular docking approach was manipulated using Autodock Vina (Vina) and Autodock4 (AD4) protocols to preliminarily investigate the ligand-binding affinity and pose to SARS-CoV-2 Mpro. The binding free energy was then refined using the fast pulling of ligand (FPL), linear interaction energy (LIE), molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA), and free energy perturbation (FEP) methods. The benchmark results indicated that for docking calculations, Vina is more accurate than AD4, and for free energy methods, FEP is the most accurate method, followed by LIE, FPL, and MM-PBSA (FEP > LIE ≈ FPL > MM-PBSA). Moreover, atomistic simulations revealed that the van der Waals interaction is the dominant factor. The residues Thr26, His41, Ser46, Asn142, Gly143, Cys145, His164, Glu166, and Gln189 are essential elements affecting the binding process. Our benchmark provides guidelines for further investigations using computational approaches.

Molecular Dynamics Simulation Study on Allosteric Regulation of CD44-Hyaluronan Binding as a Force Sensing Mechanism

CD44 protein exists on surfaces of a variety of human cells, acts as a receptor for the hyaluronan (HA) molecule, and mediates cell adhesion via the HA binding in leukocyte trafficking, cell rolling, and so on. The molecular structures of both CD44 and HA are well known, and the previous work shows that the external-mechanical force induces the partially disordered (PD) conformation from the ordered (O) conformation of CD44. The PD conformation has the higher HA affinity compared to the O conformation. However, the details of force-sensing mechanics have remained unclear. This study provides new insights into allosteric regulation of HA binding by conformational shift from the O to the PD conformation of the CD44 HA binding domain by using the classical molecular dynamics simulations. The O conformation was more favorable than the PD conformation under the equilibrium state, and the O conformation showed weak HA-binding affinity. Our simulation suggests that the PD conformation induced by the external force can refold to a compact structure similar to the O conformation keeping the bound HA. This new conformation showed a higher affinity than the O and PD conformations. Our results show that the unfolding of a remote disordered region from the ligand binding site by the external force allosterically regulates the HA affinity. This study promotes understanding not only the mechanism of CD44-mediated cell rolling but also the allosteric regulation induced by the external mechanical force.