More than a contaminant: How zinc promotes carbonate-mineralizing bacteria metabolism and adaptation by reshaping precipitation conditions

Although microbial-induced carbonate precipitation (MICP) technology is both environmentally friendly and cost-effective, its efficiency is constrained by challenges such as low bacterial activity and heavy metal stress. This study explored the enhancement of mineralization efficiency by incorporating zinc (Zn) into the cultivation system of carbonate-mineralized bacteria. All Zn salts at a concentration of 30 μmol/L significantly enhanced the density and heavy metal resistance of bacterial cells, while also promoting CO2 hydration efficiency. The activities of urease and carbonic anhydrase (CA) were significantly elevated after treatment with 30 μmol/L ZnCl2 and Zn(C3H5O3)2 (ZnL) compared to the control. The results from qRT-PCR and ELISA confirmed that ZnL exhibited a stable biological effect on CA gene expression. Through the analysis of surface chemistry of cells and the subcellular distribution pattern of cadmium (Cd), it was observed that Zn supplementation maintained the cell surface stability and strengthened the cellular barrier against Cd uptake. SEM, FTIR and XRD results further confirmed that Zn supplementation significantly increased the complexity of the mineral morphology, resulting in a more stable crystal structure of CdCO3. This study offers additional theoretical and technical backing, opening a new avenue for the practical application of MICP technology in heavy metal remediation.

Stabilization of dimeric PYR/PYL/RCAR family members relieves abscisic acid-induced inhibition of seed germination

Abscisic acid (ABA) is the primary preventing factor of seed germination, which is crucial to plant survival and propagation. ABA-induced seed germination inhibition is mainly mediated by the dimeric PYR/PYL/RCAR (PYLs) family members. However, little is known about the relevance between dimeric stability of PYLs and seed germination. Here, we reveal that stabilization of PYL dimer can relieve ABA-induced inhibition of seed germination using chemical genetic approaches. Di-nitrobensulfamide (DBSA), a computationally designed chemical probe, yields around ten-fold improvement in receptor affinity relative to ABA. DBSA reverses ABA-induced inhibition of seed germination mainly through dimeric receptors and recovers the expression of ABA-responsive genes. DBSA maintains PYR1 in dimeric state during protein oligomeric state experiment. X-ray crystallography shows that DBSA targets a pocket in PYL dimer interface and may stabilize PYL dimer by forming hydrogen networks. Our results illustrate the potential of PYL dimer stabilization in preventing ABA-induced seed germination inhibition.

Design, Synthesis, and Herbicidal Activity of Natural Naphthoquinone Derivatives Containing Diaryl Ether Structures

Photosynthesis system II (PS II) is an important target for the development of bioherbicides. In this study, a series of natural naphthoquinone derivatives containing diaryl ether were designed and synthesized based on the binding model of lawsone and PS II D1. Bioassays exhibited that most compounds had more than 80% inhibition of Portulaca oleracea and Echinochloa crusgalli roots at a dose of 100 μg/mL and compounds B4, B5, and C3 exhibited superior herbicidal activities against dicotyledonous and monocotyledon weeds to commercial atrazine. In particular, compound B5 exhibited excellent herbicidal activity at a dosage of 150 g a.i./ha. In addition, compared with atrazine, compound B5 causes less damage to crops. Molecular docking studies revealed that compound B5 effectively interacted with Pisum sativum PS II D1 via diverse interaction models, such as π-π stacking and hydrogen bonds. Molecular dynamics simulation studies and chlorophyll fluorescence measurements revealed that compound B5 acted on PS II. This is the first report of natural naphthoquinone derivatives targeting PS II and compound B5 may be a candidate molecule for the development of new herbicides targeting PS II.

Discovery of Novel N-Phenyltriazinone Derivatives Containing Oxime Ether or Oxime Ester Moieties as Promising Protoporphyrinogen IX Oxidase Inhibitors

Protoporphyrinogen IX oxidase (PPO, EC 1.3.3.4) is one of the most important targets for the discovery of green herbicides. In order to find novel PPO inhibitors with a higher herbicidal activity, a series of novel N-phenyltriazinone derivatives containing oxime ether and oxime ester groups were designed and synthesized based on the strategy of pharmacophore and scaffold hopping. Bioassay results revealed that some compounds showed herbicidal activities; especially, compound B16 exhibited broad-spectrum and excellent 100% herbicidal effects to Echinochloa crusgalli, Digitaria sanguinalis, Setaria faberii, Abutilon juncea, Amaranthus retroflexus, and Portulaca oleracea at a concentration of 37.5 g a.i./ha, which were comparable to trifludimoxazin. Nicotiana tabacum PPO (NtPPO) enzyme inhibitory assay indicated that B16 showed an excellent enzyme inhibitory activity with a value of 32.14 nM, which was similar to that of trifludimoxazin (31.33 nM). Meanwhile, compound B16 revealed more safety for crops (rice, maize, wheat, peanut, soybean, and cotton) than trifludimoxazin at a dose of 150 g a.i./ha. Moreover, molecular docking and molecular dynamics simulation further showed that B16 has a very strong and stable binding to NtPPO. It indicated that B16 can be used as a potential PPO inhibitor and herbicide candidate for application in the field.

Recent advances in the area of plant-based anti-cancer drug discovery using computational approaches

Phytocompounds are a well-established source of drug discovery due to their unique chemical and functional diversities. In the area of cancer therapeutics, several phytocompounds have been used till date to design and develop new drugs. One of the desired interests of pharmaceutical companies and researchers globally is that new anti-cancer leads are discovered, for which phytocompounds can be considered a valuable source. Simultaneously, in recent years, the growth of computational approaches like virtual screening (VS), molecular dynamics (MD), pharmacophore modelling, Quantitative structure-activity relationship (QSAR), Absorption Distribution Metabolism Excretion and Toxicity (ADMET), network biology, and machine learning (ML) has gained importance due to their efficiency, reduced time-consuming nature, and cost-effectiveness. Therefore, the present review amalgamates the information on plant-based molecules identified for cancer lead discovery from in silico approaches. The mandate of this review is to discuss studies published in the last 5-6 years that aim to identify the phytomolecules as leads against cancer with the help of traditional computational approaches as well as newer techniques like network pharmacology and ML. This review also lists the databases and webservers available in the public domain for phytocompounds related information that can be harnessed for drug discovery. It is expected that the present review would be useful to pharmacologists, medicinal chemists, molecular biologists, and other researchers involved in the development of natural products (NPs) into clinically effective lead molecules.

Mutation V65I in the β1 Subunit of the Nicotinic Acetylcholine Receptor Confers Neonicotinoid and Sulfoxaflor Resistance in Insects

Neonicotinoids have been widely used to control pests with remarkable effectiveness. Excessive insecticides have led to serious insect resistance. Mutations of the nicotinic acetylcholine receptor (nAChR) are one of the reasons for neonicotinoid resistance conferred in various agricultural pests. Two mutations, V65I and V104I, were found in the nAChR β1 subunit of two neonicotinoid-resistant aphid populations. However, the specific functions of the two mutations remain unclear. In this study, we cloned and identified four nAChR subunits (α1, α2, α8, and β1) of thrips and found them to be highly homologous to the nAChR subunits of other insects. Subsequently, we successfully expressed two subtypes nAChR (α1/α2/α8/β1 and α1/α8/β1) by coinjecting three cofactors for the first time in thrips, and α1/α8/β1 showed abundant current rapidly. Acetylcholine, neonicotinoids, and sulfoxaflor exhibited different activation capacities for the two subtypes of nAChRs. Finally, V65I was found to significantly reduce the binding ability of nAChR to neonicotinoids and sulfoxaflor through electrophysiology and computer simulations. V104I caused a decrease in agonist affinity (pEC50) but an increase in the efficacy (Imax) of nAChR against neonicotinoids and reduced the binding ability of nAChR to sulfoxaflor. This study provides theoretical and technical support for studying the molecular mechanisms of neonicotinoid resistance in pests.

Decoding the structural integrity and multifunctional role of Era protein in the survival of Mycobacterium tuberculosis H37Rv

Era, a widely known GTP binding protein found in many organisms including prokaryotes and eukaryotes and plays a significant role in many fundamental cellular processes like cell growth, differentiation and signaling. In Mycobacterium tuberculosis (Mtb) H37Rv, Era protein had been proved as a GTPase protein but its structural and functional insights are still lacking. Through comparative analysis, structural modeling, docking and using various bioinformatic tools, a detailed investigation of Era was carried out to deduce the structure, function and residues involved in the activity of the protein. Intriguingly, docking results revealed high binding affinity of Era not only with GTP but also with ATP. Myristoylation modifications and phosphorylations on Era were predicted to possibly aid in regulating Era activity and localization; and also the role of Era in translation regulation was foreseen by showing its association with 16s rRNA. Moreover, point mutation of Era residues revealed the effect of W288G and K19G in highly destabilizing the protein structure and activity. Additionally, Era protein was docked with 25 GTPase/ATPase inhibitors, where, Dynasore inhibitor showed the highest affinity for the protein's GTP binding sites and can be used for further drug trials to inhibit growth of mycobacteria.Communicated by Ramaswamy H. Sarma.

Potential Antidiabetic Activity of β-sitosterol from Zingiber roseum Rosc. via Modulation of Peroxisome Proliferator-activated Receptor Gamma (PPARγ)

AIM

To evaluate the antidiabetic potential of β-sitosterol from Zingiber roseum.

BACKGROUND

Diabetes mellitus is a cluster of metabolic disorders, and 90% of diabetic patients are affected with Type II diabetes (DM2). For the treatment of DM2, thiazolidinedione drugs (TZDs) were proposed, but recent studies have shown that TZDs have several detrimental effects, such as weight gain, kidney enlargement (hypertrophy), fluid retention, increased risk of bone fractures, and potential harm to the liver (hepatotoxicity). That is why a new molecule is needed to treat DM2.

OBJECTIVE

The current research aimed to assess the efficacy of β-Sitosterol from methanolic extract of Zingiber roseum in managing diabetes via PPARγ modulation.

METHODS

Zingiber roseum was extracted using methanol, and GC-MS was employed to analyze the extract. Through homology modeling, PPARγ structure was predicted. Molecular docking, MD simulation, free binding energies, QSAR, ADMET, and bioactivity and toxicity scores were all used during the in-depth computer-based research.

RESULTS

Clinically, agonists of synthetic thiazolidinedione (TZDs) have been used therapeutically to treat DM2, but these TZDs are associated with significant risks. Hence, GC-MS identified phytochemicals to search for a new PPAR-γ agonist. Based on the in-silico investigation, β-sitosterol was found to have a higher binding affinity (-8.9 kcal/mol) than standard drugs. MD simulations and MMGBSA analysis also demonstrated that β-sitosterol bound to the PPAR-γ active site stably.

CONCLUSION

It can be concluded that β-sitosterol from Z. roseum attenuates Type-II diabetes by modulating PPARγ activity.

The Power of Molecular Dynamics Simulations and Their Applications to Discover Cysteine Protease Inhibitors

A large family of enzymes with the function of hydrolyzing peptide bonds, called peptidases or cysteine proteases (CPs), are divided into three categories according to the peptide chain involved. CPs catalyze the hydrolysis of amide, ester, thiol ester, and thioester peptide bonds. They can be divided into several groups, such as papain-like (CA), viral chymotrypsin-like CPs (CB), papainlike endopeptidases of RNA viruses (CC), legumain-type caspases (CD), and showing active residues of His, Glu/Asp, Gln, Cys (CE). The catalytic mechanism of CPs is the essential cysteine residue present in the active site. These mechanisms are often studied through computational methods that provide new information about the catalytic mechanism and identify inhibitors. The role of computational methods during drug design and development stages is increasing. Methods in Computer-Aided Drug Design (CADD) accelerate the discovery process, increase the chances of selecting more promising molecules for experimental studies, and can identify critical mechanisms involved in the pathophysiology and molecular pathways of action. Molecular dynamics (MD) simulations are essential in any drug discovery program due to their high capacity for simulating a physiological environment capable of unveiling significant inhibition mechanisms of new compounds against target proteins, especially CPs. Here, a brief approach will be shown on MD simulations and how the studies were applied to identify inhibitors or critical information against cysteine protease from several microorganisms, such as Trypanosoma cruzi (cruzain), Trypanosoma brucei (rhodesain), Plasmodium spp. (falcipain), and SARS-CoV-2 (Mpro). We hope the readers will gain new insights and use our study as a guide for potential compound identifications using MD simulations.

Oncoinformatic screening of the gene clusters involved in the HER2-positive breast cancer formation along with the in silico pharmacodynamic profiling of selective long-chain omega-3 fatty acids as the metastatic antagonists

The HER2-positive patients occupy ~ 30% of the total breast cancer patients globally where no prevalent drugs are available to mitigate the frequent metastasis clinically except lapatinib and neratinib. This scarcity reinforced researchers' quest for new medications where natural substances are significantly considered. Valuing the aforementioned issues, this research aimed to study the ERBB2-mediated string networks that work behind the HER2-positive breast cancer formation regarding co-expression, gene regulation, GAMA-receptor-signaling pathway, cellular polarization, and signal inhibition. Following the overexpression, promotor methylation, and survivability profiles of ERBB2, the super docking position of HER2 was identified using the quantum tunneling algorithm. Supramolecular docking was conducted to study the target specificity of EPA and DHA fatty acids followed by a comprehensive molecular dynamic simulation (100 ns) to reveal the RMSD, RMSF, Rg, SASA, H-bonds, and MM/GBSA values. Finally, potential drug targets for EPA and DHA in breast cancer were constructed to determine the drug-protein interactions (DPI) at metabolic stages. Considering the values resulting from the combinational models of the oncoinformatic, pharmacodynamic, and metabolic parameters, long-chain omega-3 fatty acids like EPA and DHA can be considered as potential-targeted therapeutics for HER2-positive breast cancer treatment.

Unveiling the Anthelminthic Potential of Merremia vitifolia Stem through in Vitro and in Silico Approach

This study aimed to assess the anthelmintic activity of methanol extracts from Merremia vitifolia stems using a combination approach encompassing experimental, in vitro, and in silico evaluations. Despite the well-recognized pharmacological properties of M. vitifolia, its potential as an anthelmintic agent remained unexplored. This plant's anthelmintic potential was assessed on adult earthworms (Pheretima posthuma), revealing a dose-dependent reduction in spontaneous motility leading to paralysis and eventual mortality. The most effective dose of M. vitifolia (200 mg/ml) for anthelmintic effects on Pheretima posthuma was identified. Complementary in silico investigations were also conducted, employing Autodock PyRx 0.8 for docking studies of reported M. vitifolia compounds. Notably, quercetin emerged as a promising candidate with superior binding energies against β-tubulin (-8.3 Kcal/mol). Moreover, this comprehensive research underlines the anthelmintic potential of Merremia vitifolia stem extract and highlights quercetin as a noteworthy compound for further investigation in the quest for novel anthelmintic agents.

Design and Synthesis of Novel Oxathiapiprolin Derivatives as Oxysterol Binding Protein Inhibitors and Their Application in Phytopathogenic Oomycetes

Oomycetes, particularly those from the genus Phytophthora, are significant threats to global food security and natural ecosystems. Oxathiapiprolin (OXA) is an effective oomycete fungicide that targets an oxysterol binding protein (OSBP), while the binding mechanism of OXA is still unclear, which limits the pesticide design, induced by the low sequence identity of Phytophthora and template models. Herein, we generated the OSBP model of the well-reported Phytophthora capsici using AlphaFold 2 and studied the binding mechanism of OXA. Based on it, a series of OXA analogues were designed. Then, compound 2l, the most potent candidate, was successfully designed and synthesized, showing a control efficiency comparable to that of OXA. Moreover, field trial experiments showed that 2l exhibited nearly the same activity (72.4%) as OXA against cucumber downy mildew at 25 g/ha. The present work indicated that 2l could be used as a leading compound for the discovery of new OSBP fungicides.

Target-specificity of different amyrin subunits in impeding HCV influx mechanism inside the human cells considering the quantum tunnel profiles and molecular strings of the CD81 receptor: a combined in silico and in vivo study

HCV is a hepatotropic RNA virus recognized for its frequent virulence and fatality worldwide. Despite many vaccine development programs underway, researchers are on a quest for natural bioactive compounds due to their multivalent efficiencies against viral infections, considering which the current research aimed to figure out the target-specificity and therapeutic potentiality of α, β, and δ subunits of amyrin, as novel bioactive components against the HCV influx mechanism. Initially, the novelty of amyrin subunits was conducted from 203 pharmacophores, comparing their in-silico pharmacokinetic and pharmacodynamic profiles. Besides, the best active site of CD81 was determined following the quantum tunneling algorithm. The molecular dynamic simulation was conducted (100 ns) following the molecular docking steps to reveal the parameters- RMSD (Å); Cα; RMSF (Å); MolSA (Ų); Rg (nm); PSA (Å); SASA (Ų), and the MM-GBSA dG binding scores. Besides, molecular strings of CD81, along with the co-expressed genes, were classified, as responsible for encoding CD81-mediated protein clusters during HCV infection, resulting in the potentiality of amyrins as targeted prophylactics in HCV infection. Finally, in vivo profiling of the oxidative stress marker, liver-specific enzymes, and antioxidant markers was conducted in the DMN-induced mice model, where β-amyrin scored the most significant values in all aspects.

CIPDB: A biological structure databank for studying cation and π interactions

As major forces for modulating protein folding and molecular recognition, cation and π interactions are extensively identified in protein structures. They are even more competitive than hydrogen bonds in molecular recognition, thus, are vital in numerous biological processes. In this review, we introduce the methods for the identification and quantification of cation and π interactions, provide insights into the characteristics of cation and π interactions in the natural state, and reveal their biological function together with our developed database (Cation and π Interaction in Protein Data Bank; CIPDB; http://chemyang.ccnu.edu.cn/ccb/database/CIPDB). This review lays the foundation for the in-depth study of cation and π interactions and will guide the use of molecular design for drug discovery.

In silico screening and covalent binding of phytochemicals of Ocimum sanctum against SARS-CoV-2 (COVID 19) main protease

Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has compelled the scientific community to search for an effective drug that can cure or a vaccine that can prevent the disease. Alternatively, symptomatic treatment and traditional immunity boosters are prescribed. Holy Tulsi (Ocimum sanctum) has been known as an ancient remedy for cure of common cold and respiratory ailment. Several reports have come on virtual screening of phytochemicals including those of Tulsi against various enzymes of the virus. We undertook in silico analysis of the ethanol extracted phytochemicals of Tulsi as inhibitors of SARS-CoV-2 (2019-nCoV) main protease with an approach to look into the possibility of covalent ligand binding with the catalytic residue Cys145, which makes the report unique. The results suggest that the flavonoids and polyphenolic compounds of Tulsi, have potential to covalently bind to the catalytic residue Cys145 of main protease and irreversibly inhibit the viral enzyme. Luteolin-7-O-glucuronide is specially considered for its optimum properties, namely, low toxicity (LD₅₀ 5000 mg/kg body weight), high drug-likeness score (0.71), the active site binding free energy (ΔG_bind) -19.19 kcal/mol by GBSA method and covalent binding energy -24.23 kcal/mol. Further experimental validations are required to establish the theoretical findings.Communicated by Ramaswamy H. Sarma.

A new serotonin 2A receptor antagonist with potential benefits in Non-Alcoholic Fatty Liver Disease

Peripheral 5-hydroxytryptamine 2A receptor (5-HT2AR) could be a new pharmacological target for NASH, an evolution of NAFLD characterized by hepatic steatosis, cytoskeletal alterations, and hepatic inflammation that can arise with or without fibrosis. SJT4a is a synthetic β-carboline antagonist for 5-HT2AR developed by SJT molecular research to treat NASH. We performed a combined in silico/in vivo study on this potential drug to elucidate its activity and possible mechanism of action. The in silico protocol compares SJT4a with four known 5-HT2AR ligands with different activities (LSD, methiothepin, zotepine, risperidone). We performed molecular docking calculations, evaluation of binding energy by AI-based methods and Molecular Dynamics simulations of the five ligand-target complexes. Moreover, we used a pseudo-semantic analysis to evaluate the potential mechanism of action of SJT4a. In silico predictions and pseudo-semantic analysis suggested antagonistic activity for SJT4a. The in silico prediction was confirmed by [³H]-5HT radioligand binding together with SJT4a competition analysis in CHO-K1 cell cultures expressing 5-HT2AR. SJT4a was then tested in vivo. We investigated the effect of 8 weeks of treatment with SJT4A on metabolic parameters, liver pathology, NAFLD activity score, and fibrosis stage in male DIO-NASH C57BL/6 J mice diet-induced obesity fed with an obesogenic diet compared with DIO-NASH and LEAN-CHOW vehicles. In our tests, SJT4a showed intense activity in diminishing the most relevant hallmarks of NASH in the DIO-NASH mice model. We proposed a possible mode of action for SJT4a based on its 5-HT2AR antagonist activity.

Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter

Inadequate bioavailability is one of the most critical reasons for the failure of oral drug development. However, the way that substructures affect bioavailability remains largely unknown. Serotonin transporter (SERT) inhibitors are first-line drugs for major depression disorder, and improving their bioavailability may be able to decrease side-effects by reducing daily dose. Thus, it is an excellent model to probe the relationship between substructures and bioavailability. Here, we proposed the concept of "nonbioavailable substructures", referring to substructures that are unfavorable to bioavailability. A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. A more potent SERT inhibitor DH4 was discovered with a bioavailability of 83.28% in rats by replacing the nonbioavailable substructure of approved drug vilazodone. DH4 exhibits promising anti-depression efficacy in animal experiments. The concept of nonbioavailable substructures may open up a new venue for the improvement of drug bioavailability.

Mechanisms Contributing to Acquired Activated Protein C Resistance in Patients Treated with Thalidomide: A Molecular Dynamics Study

INTRODUCTION

There is a high incidence of venous thromboembolism (VTE) in patients with Multiple Myeloma (MM), however; until now, the exact mechanisms behind VTE in MM are unknown, and some of the elements that may play a significant role are the treatment with an immunomodulator (IMiD) and acquired resistance to activated protein C (APC).

OBJECTIVE

The study aims to reveal the possible mechanisms linked to the reduced antithrombotic activity of APC associated with thalidomide.

METHODS

The molecular docking approach was used to ascertain the in silico inhibitory potential of thalidomide on the APC protease domain in the architecture of the catalytic triad and its interaction with major substrate binding sites.

RESULTS

The coupling showed that the inhibitory activity of thalidomide depends on the induction of structural changes in the protease domain of APC, at the level of the Ser/His/Asp catalytic triad, as a result of a significant increase between the distances of CαAsp102 and Cα Ser195 (11.175 angstroms, increase 14.83%) and between CαSer195 and CαHis57 (9.478 angstroms, increase 13.78 %). This can result in an inefficient transfer of the proton between these residues, the other possible mechanism of inhibition, is a potential reduced binding of the substrate as a result of a direct interaction through a carbon-hydrogen bond on His57, an H-bond on Arg306, and a carbon hydrogen bond on Arg506.

CONCLUSION

We demonstrate the in silico inhibitory potential of thalidomide on APC, through two possible inhibition mechanisms, a pathophysiologically relevant finding to understand the factors that can affect the stability and functions of APC in vivo.

Prophylactic and therapeutic potential of selected immunomodulatory agents from Ayurveda against coronaviruses amidst the current formidable scenario: an in silico analysis

There is currently a dearth of specific therapies to treat respiratory infections caused by the three related species of coronaviruses viz. SARS-CoV-2, SARS-CoV and MERS-CoV. Prevention from disease is currently the safest and most convenient alternative available. The present study aimed to evaluate the preventive and therapeutic effect of fifteen phytoconstituents from medicinal plants of Ayurveda against coronaviruses by in silico screening. All the phytoconstituents exhibited rapid GI absorption and bioavailability and most of them had no toxicity versus reference drug chloroquine. BAS analyses revealed that most of the phytocomponents had favorable bioactivity scores towards biological target proteins. Principal component analysis revealed that most of the phytoconstituents fell close to chloroquine in 3D projection of chemical space. Affinity of phytoconstituents towards SARS-CoV-2 spike protein-human ACE2 complex decreased as isomeldenin > tinosporaside > EGCG whereas in case of unbound ACE2, the strength of binding followed the order isomeldenin > tinosporaside > ellagic acid. Towards SARS-CoV-2 main and papain-like proteases, the affinity decreased as isomeldenin > EGCG > tinosporaside and EGCG > tinosporaside > isomeldenin, respectively. Most phytoconstituents displayed significant binding kinetics to the selected protein targets than chloroquine. SAR analysis revealed that isomeldenin, tinosporaside, EGCG and ellagic acid bind to viral spike glycoproteins via H-bond, Pi-Pi, Pi-sigma and Pi-alkyl type interactions. Molecular dynamics simulation of isomeldenin and EGCG with SARS-CoV and SARS-CoV-2 spike glycoproteins exhibited low deviations throughout the 100 ns simulation indicating good stability and compactness of the protein-ligand complexes. Thus, the above four phytoconstituents have the potential to emerge as prophylactic and therapeutic agents against coronaviruses if investigated further in vitro and in vivo.

High throughput virtual screening strategy to develop a potential treatment for bronchial asthma by targeting interleukin 13 cytokine signaling

Chronic inflammation in the airway passage leads to the clinical syndrome of pediatric asthma. Allergic reactions caused by bacterial, viral, and fungal infection lead to the immune dis-balance which primes T helper cells (Th2), a specific cluster of differentiation 4 (CD4) T cell differentiation. This favors the Th2-specific response by activating the inter-leukin 4/interleukin 13 (IL-4/IL-13) cytokine signaling and further activates the secretion of immunoglobulin E (IgE). IL-13 develops bronchial asthma by elevating bronchial hyperresponsiveness and enables production of immunoglobulin M (IgM) and IgE. The present study aims to target IL-13 signaling using molecular docking and understanding molecular dynamic simulation (MDS) to propose a compelling candidate to treat asthma. We developed a library of available allergic drugs (n=20) and checked the binding affinity against IL-13 protein (3BPN.pdb) through molecular docking and confirmed the best pose binding energy of -3.84 and -3.71 for epinephrine and guaifenesin, respectively. Studying the interaction of hydrogen bonds and Van der Walls, it is estimated that electrostatic energy is sufficient to interact with the active site of the IL-13 and has shown to inhibit inflammatory signaling. These computational results confirm epinephrine and guaifenesin as potential ligands showing potential inhibitory activity for IL-13 signaling. This study also suggests the designing of a new ligand and screening of a large cohort of drugs, in the future, to predict the exact mechanism to control the critical feature of asthma.

Virtual Screening for SARS-CoV-2 Main Protease Inhibitory Peptides from the Putative Hydrolyzed Peptidome of Rice Bran

The Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the loss of life and has affected the life quality, economy, and lifestyle. The SARS-CoV-2 main protease (Mpro), which hydrolyzes the polyprotein, is an interesting antiviral target to inhibit the spreading mechanism of COVID-19. Through predictive digestion, the peptidomes of the four major proteins in rice bran, albumin, glutelin, globulin, and prolamin, with three protease enzymes (pepsin, trypsin, and chymotrypsin), the putative hydrolyzed peptidome was established and used as the input dataset. Then, the prediction of the antiviral peptides (AVPs) was performed by online bioinformatics tools, i.e., AVPpred, Meta-iAVP, AMPfun, and ENNAVIA programs. The amino acid composition and cytotoxicity of candidate AVPs were analyzed by COPid and ToxinPred, respectively. The ten top-ranked antiviral peptides were selected and docked to the SARS-CoV-2 main protease using GalaxyPepDock. Only the top docking scored candidate (AVP4) was further analyzed by molecular dynamics simulation for one nanosecond. According to the bioinformatic analysis results, the candidate SARS-CoV-2 main protease inhibitory peptides were 7–33 amino acid residues and formed hydrogen bonds at Thr22–24, Glu154, and Thr178 in domain 2 with short bonding distances. In addition, these top-ten candidate bioactive peptides contain hydrophilic amino acid residues and have a positive net charge. We hope that this study will provide a potential starting point for peptide-based therapeutic agents against COVID-19.

Computational discovery of novel inhibitory candidates targeting versatile transcriptional repressor MBD2

Genome methylation is a key epigenetic mechanism in various biological events such as development, cellular differentiation, cancer progression, aging, and iPSC reprogramming. Crosstalk between DNA methylation and gene expression is mediated by MBD2, known as the reader of DNA methylation and suggested as a drug target. Despite its magnitude of significance, a scarcely limited number of small molecules to be used as inhibitors have been detected so far. Therefore, we screened a comprehensive compound library to elicit MBD2 inhibitor candidates. Promising molecules were subjected to computational docking analysis by targeting the methylated DNA-binding domain of human MBD2. We could detect reasonable binding energies and docking residues, presumably located in druggable pockets. Docking results were also validated via MD simulation and per-residue energy decomposition calculation. Drug-likeness of these small molecules was assessed through ADMET prediction to foresee off-target side effects for future studies. All computational approaches notably highlighted two compounds named CID3100583 and 8,8-ethylenebistheophylline. These compounds have become prominent as novel candidates, possibly disrupting MBD2_MBD-DNA interaction. Consequently, these compounds have been considered prospective inhibitors with the usage potential in a wide range of applications from cancer treatment to somatic cell reprogramming protocols.

Exploring the phytochemicals of Platycodon grandiflorus for TMPRSS2 inhibition in the search for SARS-CoV-2 entry inhibitors

Platycodon grandiflorus (Jacq.) A. DC. (Campanulaceae) is commonly known as a balloon flower whose rhizomes have been widely utilized in traditional Chinese medicine (TCM) and in various Japanese prescriptions for the treatment of respiratory diseases, diabetes, and inflammatory disorders. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) global pandemic requires priming of the virus's spike (S) protein by cleavage of the S proteins by a multi-domain type II transmembrane serine protease, transmembrane protease serine 2 (TMPRSS2) to gain entry into the host cell. The current research aims at the screening of active phytocompounds of P. grandiflorus as potential inhibitors of cellular TMPRSS2 using molecular docking and molecular dynamics simulations approach. In silico toxicity analyses show that out of a total of 34 phytocompounds selected for the study, 12 compounds obey Lipinski’s rule of five and have favourable pharmacokinetic properties. The top three lead molecules identified here were Apigenin, Luteolin and Ferulic acid which exhibited binding energies of −7.47 kcal/mol, −6.8 kcal/mol and −6.62 kcal/mol respectively with corresponding inhibition constants of 3.33 µM, 10.39 µM and 13.95 µM. The complexes between the lead molecules and the receptor were held by hydrogen bond interactions with key residues such as Gly383, Gly385, Glu389, Lys390, Asp435, Ser436, Ser441, Cys465 and Lys467, and hydrophobic interactions with surrounding residues. The stability of the protein–ligand complexes was evaluated during 100 ns molecular dynamics (MD) simulation by analysing key geometric properties such as RMSD, RMSF, radius of gyration, total solvent accessible surface area and the number of hydrogen bonds. The binding free energies analysis using MD simulations revealed that the compounds and TMPRSS2 have favourable thermodynamic interactions, which are primarily driven by van der Waals forces. As a result, the selected bioactive phytochemicals from P. grandiflorus that target the cellular TMPRSS2 could offer an alternative treatment option against SARS-CoV-2 infections.

Key Residues Affecting Binding Affinity of Sirex noctilio Fabricius Odorant-Binding Protein (SnocOBP9) to Aggregation Pheromone

Sirex noctilio Fabricius (Hymenoptera Siricidae) is a major quarantine pest responsible for substantial economic losses in the pine industry. To achieve better pest control, (Z)-3-decen-ol was identified as the male pheromone and used as a field chemical trapping agent. However, the interactions between odorant-binding proteins (OBPs) and pheromones are poorly described. In this study, SnocOBP9 had a higher binding affinity with Z3D (Ki = 1.53 ± 0.09 μM) than other chemical ligands. Molecular dynamics simulation and binding mode analysis revealed that several nonpolar residues were the main drivers for hydrophobic interactions between SnocOBP9 and Z3D. Additionally, computational alanine scanning results indicated that five amino acids (MET54, PHE57, PHE71, PHE74, LEU116) in SnocOBP9 could potentially alter the binding affinity to Z3D. Finally, we used single-site-directed mutagenesis to substitute these five residues with alanine. These results imply that the five residues play crucial roles in the SnocOBP9-Z3D complex. Our research confirmed the function of SnocOBP9, uncovered the key residues involved in SnocOBP9-Z3D interactions, and provides an inspiration to improve the effects of pheromone agent traps.

Real-Time Fluorescence Imaging of the Abscisic Acid Receptor Allows Nondestructive Visualization of Plant Stress

Environmental stress greatly decreases crop yield. The application of noninvasive techniques is one of the most practical and feasible ways of monitoring the health condition of plants under stress. However, it remains largely unsolved. A chemical fluorescent probe can be applied as a typical nondestructive method, but it has not been applied in living plants for stress detection to date. The abscisic acid (ABA) receptor plays a central role in conferring tolerance to environmental stresses and is an excellent target for developing fluorescent probes. Herein, we developed a fluorescence molecular imaging technology to monitor live plant stress by visualizing the protein expression level of the ABA receptor PYR1. A computer-aided designed indicator dye, flubactin, exhibited an 8-fold enhancement in fluorescence intensity upon interaction with PYR1. In vitro and in vivo experiments showed that flubactin is suitable to be used to detect salt stress in plants in real time. Moreover, the low toxicity of flubactin promotes its application in the future. Our work opens a new era for the nondestructive visualization of plant stress in vivo.

Novel Pyrazole Amides as Potential 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors

4-Hydroxyphenylpyruvate dioxygenase (HPPD) is an important target for the development of new herbicides. HPPD inhibitors can hinder photosynthesis and induce weed death with bleaching symptoms. To explore the novel skeleton of HPPD inhibitors, a series of novel pyrazole amide derivatives were synthesized and evaluated for their inhibitory effects on Arabidopsis thaliana HPPD (AtHPPD) and herbicidal activities. Some compounds had excellent inhibitory activities against AtHPPD. Among them, compound B5 displayed top-rank inhibitory activity against AtHPPD with an IC₅₀ value of 0.04 μM, which was obviously superior to that of topramezone (IC₅₀ value of 0.11 μM). Furthermore, compounds B2 and B7 had 100% herbicidal activities in Petri dish assays against Portulaca oleracea and Amaranthus tricolor at 100 μg/mL. In particular, compound B7 not only possessed strong AtHPPD inhibitory activity but also exhibited significant preemergence herbicidal activity. However, compound B7 was completely harmless to soybean, cotton, and wheat. In addition, the molecular docking and microscale thermophoresis measurement experiment verified that compounds can bind well with AtHPPD via π-π interactions. The present work provides a new approach for the rational design of more effective HPPD inhibitors, and pyrazole amides could be used as useful substructures for the development of new HPPD inhibitors and preemergence herbicidal agents.

Fast approximative methods for study of ligand transport and rational design of improved enzymes for biotechnologies

Acceleration of chemical reactions by the enzymes optimized using protein engineering represents one of the key pillars of the contribution of biotechnology towards sustainability. Tunnels and channels of enzymes with buried active sites enable the exchange of ligands, ions, and water molecules between the outer environment and active site pockets. The efficient exchange of ligands is a fundamental process of biocatalysis. Therefore, enzymes have evolved a wide range of mechanisms for repetitive conformational changes that enable periodic opening and closing. Protein-ligand interactions are traditionally studied by molecular docking, whereas molecular dynamics is the method of choice for studying conformational changes and ligand transport. However, computational demands make molecular dynamics impractical for screening purposes. Thus, several approximative methods have been recently developed to study interactions between a protein and ligand during the ligand transport process. Apart from identifying the best binding modes, these methods also provide information on the energetics of the transport and identify problematic regions limiting the ligand passage. These methods use approximations to simulate binding or unbinding events rapidly (calculation times from minutes to hours) and provide energy profiles that can be used to rank ligands or pathways. Here we provide a critical comparison of available methods, showcase their results on sample systems, discuss their practical applications in molecular biotechnologies and outline possible future developments.

Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations

Protein kinases play crucial roles in many cellular signaling processes, making them become important targets for drug discovery. But drug resistance mediated by mutation puts a barrier to the therapeutic effect of kinase inhibitors. Fragment-based drug discovery has been successfully applied to overcome such resistance. However, the complicate kinase-inhibitor fragment interaction and fragment-to-lead process seriously limit the efficiency of kinase inhibitor discovery against resistance caused by mutation. Here, we constructed a comprehensive web platform KinaFrag for the fragment-based kinase inhibitor discovery to overcome resistance. The kinase-inhibitor fragment space was investigated from 7783 crystal kinase-inhibitor fragment complexes, and the structural requirements of kinase subpockets were analyzed. The core fragment-based virtual screening workflow towards specific subpockets was developed to generate new kinase inhibitors. A series of tropomyosin receptor kinase (TRK) inhibitors were designed, and the most potent compound YT9 exhibits up to 70-fold activity improvement than marketed drugs larotrectinib and selitrectinib against G595R, G667C and F589L mutations of TRKA. YT9 shows promising antiproliferative against tumor cells in vitro and effectively inhibits tumor growth in vivo for wild type TRK and TRK mutants. Our results illustrate the great potential of KinaFrag in the kinase inhibitor discovery to combat resistance mediated by mutation. KinaFrag is freely available at http://chemyang.ccnu.edu.cn/ccb/database/KinaFrag/.

Point-specific interactions of isovitexin with the neighboring amino acid residues of the hACE2 receptor as a targeted therapeutic agent in suppressing the SARS-CoV-2 influx mechanism

Objective:

Despite the development of several vaccines against severe acute respiratory syndrome coronavirus-2, the need for an additional prophylactic agent is evident. In recent in silico studies, isovitexin exhibited a higher binding affinity against the human angiotensin converting-enzyme 2 (hACE2) receptor than existing antiviral drugs. The research aimed to find out the point specificity of isovitexin for the hACE2 receptor and to assess its therapeutic potential, depending on the stability of the isovitexin–hACE2 complex.

Materials and Methods:

The pharmacokinetic profile of isovitexin was analyzed. The crystal structure of the hACE2 receptor and the ligand isovitexin were docked to form a ligand–protein complex following molecular optimization. To determine the isovitexin–hACE2 complex stability, their binding affinity, hydrogen bonding, and hydrophobic interactions were studied. Lastly, the root mean square deviation (RMSD), root mean square fluctuation, solvent accessible surface area, molecular surface area, radius of gyration (Rg), polar surface area, and principal component analysis values were found by simulating the complex with molecular dynamic (MD).

Results:

The predicted Lethal dose₅₀ for isovitexin was 2.56 mol/kg, with an acceptable maximum tolerated dose and no hepatotoxicity or AMES toxicity. Interactions with the amino acid residues Thr371, Asp367, Glu406, Pro346, His345, Phe274, Tyr515, Glu375, Thr347, Glu402, and His374 of the hACE2 protein were required for the high binding affinity and specificity of isovitexin. Based on what was learned from the MD simulation, the hACE2 receptor-blocking properties of isovitexin were looked at.

Conclusions:

Isovitexin is a phytochemical with a reasonable bioactivity and safety profile for use in humans, and it can potentially be used as a hACE2-specific therapeutic to inhibit COVID-19 infection.

Differences in ligand-induced protein dynamics extracted from an unsupervised deep learning approach correlate with protein-ligand binding affinities

Prediction of protein–ligand binding affinity is a major goal in drug discovery. Generally, free energy gap is calculated between two states (e.g., ligand binding and unbinding). The energy gap implicitly includes the effects of changes in protein dynamics induced by ligand binding. However, the relationship between protein dynamics and binding affinity remains unclear. Here, we propose a method that represents ligand-binding-induced protein behavioral change with a simple feature that can be used to predict protein–ligand affinity. From unbiased molecular simulation data, an unsupervised deep learning method measures the differences in protein dynamics at a ligand-binding site depending on the bound ligands. A dimension reduction method extracts a dynamic feature that strongly correlates to the binding affinities. Moreover, the residues that play important roles in protein–ligand interactions are specified based on their contribution to the differences. These results indicate the potential for binding dynamics-based drug discovery.

Differences in ligand-induced protein dynamics extracted as a single feature from a deep learning-based analysis of MD simulations correlate with ligand binding affinity.

In Silico and In Vitro Evaluations of Fluorophoric Thiazolo-[2,3-b]quinazolinones as Anti-cancer Agents Targeting EGFR-TKD

Epidermal growth factor receptor tyrosine kinase domain (EGFR-TKD) plays a pivotal role in cellular signaling, growth, and metabolism. The EGFR-TKD is highly expressed in cancer cells and was endorsed as a therapeutic target for cancer management to overcome metastasis, cell proliferation, and angiogenesis. The novel thiazolo-[2,3-b]quinazolinones series were strategically developed by microwave-assisted organic synthesis and multi dominos reactions aimed to identify the potent thiazolo-[2,3-b]quinazolinone inhibitor against EGFR-TKD. This study explores the binding stability and binding strength of newly developed series via molecular docking, molecular dynamics simulation, and MM/PBSA and MM/GBSA calculations. The binding interaction was observed to be through the functional groups on aryl substituents at positions 3 and 5 of the thiazolo-[2, 3-b]quinazolinone scaffold. The methyl substituents at position 8 of the ligands had prominent hydrophobic interactions corroborating their bindings similar to the reference FDA-approved drug erlotinib in the active site. ADMET predictions reveal that derivatives 5ab, 5aq, and 5bq are drug-like and may be effective in in vitro study. Molecular dynamics simulation for 100 ns of docked complexes revealed their stability at the atomistic level. The ΔGbinding of thiazolo-[2,3-b]quinazolinone was found to be 5ab - 22.45, 5aq - 22.23, and 5bq - 20.76 similar to standard drug, and erlotinib - 24.11 kcal/mol was determined by MM/GBSA method. Furthermore, the anti-proliferative activity of leads of thiazolo-[2,3-b]quinazolinones (n = 3) was studied against breast cancer cell line (MCF-7) and non-small lung carcinoma cell line (H-1299). The highest inhibitions in cell proliferation were shown by 5bq derivatives, and the IC₅₀ was found to be 6.5 ± 0.67 µM against MCF-7 and 14.8 µM against H-1299. The noscapine was also taken as a positive control and showed IC₅₀ at higher concentrations 37 ± 1 against MCF-7 and 46.5 ± 1.2 against H-1299.

Exploring nature's bounty: identification of Withania somnifera as a promising source of therapeutic agents against COVID-19 by virtual screening and in silico evaluation

Coronaviruses are etiological agents of extreme human and animal infection resulting in abnormalities primarily in the respiratory tract. Presently, there is no defined COVID-19 intervention and clinical trials of prospective therapeutic agents are still in the nascent stage. Withania somnifera (L.) Dunal (WS), is an important medicinal plant in Ayurveda. The present study aimed to evaluate the antiviral potential of selected WS phytoconstituents against the novel SARS-CoV-2 target proteins and human ACE2 receptor using in silico methods. Most of the phytoconstituents displayed good absorption and transport kinetics and were also found to display no associated mutagenic or adverse effect(s). Molecular docking analyses revealed that most of the WS phytoconstituents exhibited potent binding to human ACE2 receptor, SAR-CoV and SARS-CoV-2 spike glycoproteins as well as the two main SARS-CoV-2 proteases. Most of the phytoconstituents were predicted to undergo Phase-I metabolism prior to excretion. All phytoconstituents had favorable bioactivity scores with respect to various receptor proteins and target enzymes. SAR analysis revealed that the number of oxygen atoms in the withanolide backbone and structural rearrangements were crucial for effective binding. Molecular simulation analyses of SARS-CoV-2 spike protein and papain-like protease with Withanolides A and B, respectively, displayed a stability profile at 300 K and constant RMSDs of protein side chains and Cα atoms throughout the simulation run time. In a nutshell, WS phytoconstituents warrant further investigations in vitro and in vivo to unravel their molecular mechanism(s) and modes of action for their future development as novel antiviral agents against COVID-19.

Active site-specific quantum tunneling of hACE2 receptor to assess its complexing poses with selective bioactive compounds in co-suppressing SARS-CoV-2 influx and subsequent cardiac injury

Objective:

This research aims to study the target specificity of selective bioactive compounds in complexing with the human angiotensin-converting enzyme (hACE2) receptor to impede the severe acute respiratory syndrome coronavirus 2 influx mechanism resulting in cardiac injury and depending on the receptor’s active site properties and quantum tunneling.

Materials and Methods:

A library of 120 phytochemical ligands was prepared, from which 5 were selected considering their absorption, distribution, metabolism, and excretion (ADMET) and quantitative structure–activity relationship (QSAR) profiles. The protein active sites and belonging quantum tunnels were defined to conduct supramolecular docking of the aforementioned ligands. The hydrogen bond formation and hydrophobic interactions between the ligand–receptor complexes were studied following the molecular docking steps. A comprehensive molecular dynamic simulation (MDS) was conducted for each of the ligand–receptor complexes to figure out the values – root mean square deviation (RMSD) (Å), root mean square fluctuation (RMSF) (Å), H-bonds, Cα, solvent accessible surface area (SASA) (Ų), molecular surface area (MolSA) (Ų), Rg (nm), and polar surface area (PSA) (Å). Finally, computational programming and algorithms were used to interpret the dynamic simulation outputs into their graphical quantitative forms.

Results:

ADMET and QSAR profiles revealed that the most active candidates from the library to be used were apigenin, isovitexin, piperolactam A, and quercetin as test ligands, whereas serpentine as the control. Based on the binding affinities of supramolecular docking and the parameters of molecular dynamic simulation, the strength of the test ligands can be classified as isovitexin > quercetin > piperolactam A > apigenin when complexed with the hACE2 receptor. Surprisingly, serpentine showed lower affinity (−8.6 kcal/mol) than that of isovitexin (−9.9 kcal/mol) and quercetin (−8.9 kcal/mol). The MDS analysis revealed all ligands except isovitexin having a value lower than 2.5 Ǻ. All the test ligands exhibited acceptable fluctuation ranges of RMSD (Å), RMSF (Å), H-bonds, Cα, SASA (Ų), MolSA (Ų), Rg (nm), and PSA (Å) values.

Conclusion:

Considering each of the parameters of molecular optimization, docking, and dynamic simulation interventions, all of the test ligands can be suggested as potential targeted drugs in blocking the hACE2 receptor.

Antitussive noscapine and antiviral drug conjugates as arsenal against COVID-19: a comprehensive chemoinformatics analysis

Coronavirus pandemic has caused a vast number of deaths worldwide. Thus creating an urgent need to develop effective counteragents against novel coronavirus disease (COVID-19). Many antiviral drugs have been repurposed for treatment but implicated minimal recovery, which further advanced the need for clearer insights and innovation to derive effective therapeutics. Strategically, Noscapine, an approved antitussive drug with positive effects on lung linings may show favorable outcomes synergistically with antiviral drugs in trials. Hence, we have theoretically examined the combinatorial drug therapy by culminating the existing experimental results with in silico analyses. We employed the antitussive noscapine in conjugation with antiviral drugs (Chloroquine, Umifenovir, Hydroxychloroquine, Favlplravir and Galidesivir). We found that Noscapine-Hydroxychloroquine (Nos-Hcq) conjugate has strong binding affinity for the main protease (Mpro) of SARS-CoV-2, which performs key biological function in virus infection and progression. Nos-Hcq was analyzed through molecular dynamics simulation. The MD simulation for 100 ns affirmed the stable binding of conjugation unprecedentedly through RMSD and radius of gyration plots along with critical reaction coordinate binding free energy profile. Also, dynamical residue cross-correlation map with principal component analysis depicted the stable binding of Nos-Hcq conjugate to Mpro domains with optimal secondary structure statistics of complex dynamics. Also, we reveal the drugs with stable binding to major domains of Mpro can significantly improve the work profile of reaction coordinates, drug accession and inhibitory regulation of Mpro. The designed combinatorial therapy paves way for further prioritized in vitro and in vivo investigations for drug with robust binding against Mpro of SARS-CoV-2.

Identification of SARS-CoV-2 inhibitors from extracts of Houttuynia cordata Thunb

Houttuynia cordata Thunb., a perennial herb belonging to the Saururaceae family is a well-known ingredient of Traditional Chinese medicine (TCM) with several therapeutic properties. During the severe acute respiratory syndrome (SARS) outbreak in China, it was one of the approved ingredients in SARS preventative formulations and therefore, the plant may contain novel bioactive chemicals that can be used to suppress the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a virus for which there are currently no effective drugs available. Like all RNA viruses, SARS-CoV-2 encode RNA-dependent RNA polymerase (RdRp) enzyme which aids viral gene transcription and replication. The present study is aimed at understanding the potential of bioactive compounds from H. cordata as inhibitors of the SARS-CoV-2 RdRp enzyme. We investigated the drug-likeness of the plant's active constituents, such as alkaloids, polyphenols, and flavonoids, as well as their binding affinity for the RdRp enzyme. Molecular docking experiments show that compounds 3 (1,2,3,4,5-pentamethoxy-dibenzo-quinolin-7-one), 14 (7-oxodehydroasimilobine), and 21 (1,2-dimethoxy-3-hydroxy-5-oxonoraporphine) have a high affinity for the drug target and that the complexes are maintained by hydrogen bonds with residues like Arg553, Cys622 and Asp623, as well as hydrophobic interactions with other residues. The lead compounds' complexes with the target enzyme remained stable throughout the molecular dynamics simulation. Analysis of molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and molecular mechanics generalized Born surface area (MM-GBSA) revealed the key residues contributing considerably to binding free energy. Thus, the findings reveal the potential of H. cordata bioactive compounds as anti-SARS-CoV-2 drug candidate molecules against the target enzyme.

Discovery of TGFBR1 (ALK5) as a potential drug target of quercetin glycoside derivatives (QGDs) by reverse molecular docking and molecular dynamics simulation

Quercetin glycoside derivatives (QGDs) are a class of common compounds with a wide range of biological activities, such as antitumor activities. However, their molecular targets associated with biological activities have not been investigated. In this study, four common QGDs with mutual bioconversion were selected, and studied in the large-scale reverse docking experiments. Network pharmacology analysis showed that most of the four QGDs can bind several potential protein targets that were closely related to breast cancer disease. Among them, a druggable protein, transforming growth factor beta receptor I (TGFBR1/ALK5) was screened via high docking scores for the four QGDs. This protein has been proven to be an important target for the treatment of breast cancer by regulating the proliferation and migration of cancer cells in the past. Subsequently, the molecular dynamics (MD) simulation and MM/GBSA calculation demonstrated that all QGDs could thermodynamically bind with TGFBR1, indicating that TGFBR1 might be one of the potential protein targets of QGDs. Finally, the cytotoxicity test and wound-healing migration assay displayed that isoquercetin, which can perform best in MD experiment, might be a promising agent in the treatment of breast cancer metastasis.

Semi-automated workflow for molecular pair analysis and QSAR-assisted transformation space expansion

In the process of drug discovery, the optimization of lead compounds has always been a challenge faced by pharmaceutical chemists. Matched molecular pair analysis (MMPA), a promising tool to efficiently extract and summarize the relationship between structural transformation and property change, is suitable for local structural optimization tasks. Especially, the integration of MMPA with QSAR modeling can further strengthen the utility of MMPA in molecular optimization navigation. In this study, a new semi-automated procedure based on KNIME was developed to support MMPA on both large- and small-scale datasets, including molecular preparation, QSAR model construction, applicability domain evaluation, and MMP calculation and application. Two examples covering regression and classification tasks were provided to gain a better understanding of the importance of MMPA, which has also shown the reliability and utility of this MMPA-by-QSAR pipeline.

Target specificity of selective bioactive compounds in blocking α-dystroglycan receptor to suppress Lassa virus infection: an in silico approach

Lassa hemorrhagic fever, caused by Lassa mammarenavirus (LASV) infection, accumulates up to 5000 deaths every year. Currently, there is no vaccine available to combat this disease. In this study, a library of 200 bioactive compounds was virtually screened to study their drug-likeness with the capacity to block the α-dystroglycan (α-DG) receptor and prevent LASV influx. Following rigorous absorption, distribution, metabolism, and excretion (ADME) and quantitative structure-activity relationship (QSAR) profiling, molecular docking was conducted with the top ligands against the α-DG receptor. The compounds chrysin, reticuline, and 3-caffeoylshikimic acid emerged as the top three ligands in terms of binding affinity. Post-docking analysis revealed that interactions with Arg76, Asn224, Ser259, and Lys302 amino acid residues of the receptor protein were important for the optimum binding affinity of ligands. Molecular dynamics simulation was performed comprehensively to study the stability of the protein-ligand complexes. In-depth assessment of root-mean-square deviation (RMSD), root mean square fluctuation (RMSF), polar surface area (PSA), B-Factor, radius of gyration (Rg), solvent accessible surface area (SASA), and molecular surface area (MolSA) values of the protein-ligand complexes affirmed that the candidates with the best binding affinity formed the most stable protein-ligand complexes. To authenticate the potentialities of the ligands as target-specific drugs, an in vivo study is underway in real time as the continuation of the research.

Type 2 Diabetes Mellitus Mediation by the Disruptive Activity of Environmental Toxicants on Sex Hormone Receptors: In Silico Evaluation

This study investigates the disruptive activity of environmental toxicants on sex hormone receptors mediating type 2 diabetes mellitus (T2DM). Toxicokinetics, gene target prediction, molecular docking, molecular dynamics, and gene network analysis were applied in silico techniques. From the results, permethrin, perfluorooctanoic acid, dichlorodiphenyltrichloroethane, O-phenylphenol, bisphenol A, and diethylstilbestrol were the active toxic compounds that could modulate androgen (AR) and estrogen-α and -β receptors (ER) to induce T2DM. Early growth response 1 (EGR1), estrogen receptor 1 (ESR1), and tumour protein 63 (TP63) were the major transcription factors, while mitogen-activated protein kinases (MAPK) and cyclin-dependent kinases (CDK) were the major kinases upregulated by these toxicants via interactions with intermediary proteins such as PTEN, AKT1, NfKβ1, SMAD3 and others in the gene network analysis to mediate T2DM. These toxicants pose a major challenge to public health; hence, monitoring their manufacture, use, and disposal should be enforced. This would ensure reduced interaction between people and these toxic chemicals, thereby reducing the incidence and prevalence of T2DM.

Molecular classification of hepatocellular carcinoma: prognostic importance and clinical applications

Hepatocellular carcinoma (HCC) is a lethal human malignancy with a very low overall and long-term survival rate. Poor prognostic outcomes are predominantly associated with HCC due to a huge landscape of heterogeneity found in the deadliest disease. However, molecular subtyping of HCC has significantly improved the knowledge of the underlying mechanisms that contribute towards the heterogeneity and progression of the disease. In this review, we have extensively summarized the current information available about molecular classification of HCC. This review can be of great significance for providing the insight information needed for development of novel, efficient and personalized therapeutic options for the treatment of HCC patients globally.

Web resources facilitate drug discovery in treatment of COVID-19

The infectious disease Coronavirus 2019 (COVID-19) continues to cause a global pandemic and, thus, the need for effective therapeutics remains urgent. Global research targeting COVID-19 treatments has produced numerous therapy-related data and established data repositories. However, these data are disseminated throughout the literature and web resources, which could lead to a reduction in the levels of their use. In this review, we introduce resource repositories for the development of COVID-19 therapeutics, from the genome and proteome to antiviral drugs, vaccines, and monoclonal antibodies. We briefly describe the data and usage, and how they advance research for therapies. Finally, we discuss the opportunities and challenges to preventing the pandemic from developing further.

Rational Redesign of Enzyme via the Combination of Quantum Mechanics/Molecular Mechanics, Molecular Dynamics, and Structural Biology Study

Increasing demands for efficient and versatile chemical reactions have prompted innovations in enzyme engineering. A major challenge in engineering α-ketoglutarate-dependent oxygenases is to develop a rational strategy which can be widely used for directly evolving the desired mutant to generate new products. Herein, we report a strategy for rational redesign of a model enzyme, 4-hydroxyphenylpyruvate dioxygenase (HPPD), based on quantum mechanics/molecular mechanics (QM/MM) calculation and molecular dynamic simulations. This strategy enriched our understanding of the HPPD catalytic reaction pathway and led to the discovery of a series of HPPD mutants producing hydroxyphenylacetate (HPA) as the alternative product other than the native product homogentisate. The predicted HPPD-Fe(IV)═O-HPA intermediate was further confirmed by the crystal structure of Arabidopsis thaliana HPPD/S267W complexed with HPA. These findings not only provide a good understanding of the structure-function relationship of HPPD but also demonstrate a generally applicable platform for the development of biocatalysts.

Molecular modelling studies unveil potential binding sites on human serum albumin for selected experimental and in silico COVID-19 drug candidate molecules

Human serum albumin (HSA) is the most prevalent protein in the blood plasma which binds an array of exogenous compounds. Drug binding to HSA is an important consideration when developing new therapeutic molecules, and it also aids in understanding the underlying mechanisms that govern their pharmacological effects. This study aims to investigate the molecular binding of coronavirus disease 2019 (COVID-19) therapeutic candidate molecules to HSA and to identify their putative binding sites. Binding energies and interacting residues were used to evaluate the molecular interaction. Four drug candidate molecules (β-D-N4-hydroxycytidine, Chloroquine, Disulfiram, and Carmofur) demonstrate weak binding to HSA, with binding energies ranging from −5 to −6.7 kcal/mol. Ivermectin, Hydroxychloroquine, Remdesivir, Arbidol, and other twenty drug molecules with binding energies ranging from −6.9 to −9.5 kcal/mol demonstrated moderate binding to HSA. The strong HSA binding drug candidates consist of fourteen molecules (Saquinavir, Ritonavir, Dihydroergotamine, Daclatasvir, Paritaprevir etc.) with binding energies ranging from −9.7 to −12.1 kcal/mol. All these molecules bind to different HSA subdomains (IA, IB, IIA, IIB, IIIA, and IIIB) through molecular forces such as hydrogen bonds and hydrophobic interactions. Various pharmacokinetic properties (gastrointestinal absorption, blood-brain barrier permeation, P-glycoprotein substrate, and cytochrome P450 inhibitor) of each molecule were determined using SwissADME program. Further, the stability of the HSA-ligand complexes was analyzed through 100 ns molecular dynamics simulations considering various geometric properties. The binding free energy between free HSA and compounds were calculated using Molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) approach. The findings of this study might be useful in understanding the mechanism of COVID-19 drug candidates binding to serum albumin protein, as well as their pharmacodynamics and pharmacokinetics.

An in silico drug repositioning workflow for host-based antivirals

Drug repositioning represents a cost- and time-efficient strategy for drug development. Artificial intelligence-based algorithms have been applied in drug repositioning by predicting drug-target interactions in an efficient and high throughput manner. Here, we present a workflow of in silico drug repositioning for host-based antivirals using specially defined targets, a refined list of drug candidates, and an easily implemented computational framework. The workflow described here can also apply to more general purposes, especially when given a user-defined druggable target gene set. For complete details on the use and execution of this protocol, please refer to Li et al. (2021).

HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study

Protein-nucleic acid interactions play essential roles in many biological processes, such as transcription, replication and translation. In protein-nucleic acid interfaces, hotspot residues contribute the majority of binding affinity toward molecular recognition. Hotspot residues are commonly regarded as potential binding sites for compound molecules in drug design projects. The dynamic property is a considerable factor that affects the binding of ligands. Computational approaches have been developed to expedite the prediction of hotspot residues on protein-nucleic acid interfaces. However, existing approaches overlook hotspot dynamics, despite their essential role in protein function. Here, we report a web server named Hotspots In silico Scanning on Nucleic Acid and Protein Interface (HISNAPI) to analyze hotspot residue dynamics by integrating molecular dynamics simulation and one-step free energy perturbation. HISNAPI is capable of not only predicting the hotspot residues in protein-nucleic acid interfaces but also providing insights into their intensity and correlation of dynamic motion. Protein dynamics have been recognized as a vital factor that has an effect on the interaction specificity and affinity of the binding partners. We applied HISNAPI to the case of SARS-CoV-2 RNA-dependent RNA polymerase, a vital target of the antiviral drug for the treatment of coronavirus disease 2019. We identified the hotspot residues and characterized their dynamic behaviors, which might provide insight into the target site for antiviral drug design. The web server is freely available via a user-friendly web interface at http://chemyang.ccnu.edu.cn/ccb/server/HISNAPI/ and http://agroda.gzu.edu.cn:9999/ccb/server/HISNAPI/.

MDM-TASK-web: MD-TASK and MODE-TASK web server for analyzing protein dynamics

The web server, MDM-TASK-web, combines the MD-TASK and MODE-TASK software suites, which are aimed at the coarse-grained analysis of static and all-atom MD-simulated proteins, using a variety of non-conventional approaches, such as dynamic residue network analysis, perturbation-response scanning, dynamic cross-correlation, essential dynamics and normal mode analysis. Altogether, these tools allow for the exploration of protein dynamics at various levels of detail, spanning single residue perturbations and weighted contact network representations, to global residue centrality measurements and the investigation of global protein motion. Typically, following molecular dynamic simulations designed to investigate intrinsic and extrinsic protein perturbations (for instance induced by allosteric and orthosteric ligands, protein binding, temperature, pH and mutations), this selection of tools can be used to further describe protein dynamics. This may lead to the discovery of key residues involved in biological processes, such as drug resistance. The server simplifies the set-up required for running these tools and visualizing their results. Several scripts from the tool suites were updated and new ones were also added and integrated with 2D/3D visualization via the web interface. An embedded work-flow, integrated documentation and visualization tools shorten the number of steps to follow, starting from calculations to result visualization. The Django-powered web server (available at https://mdmtaskweb.rubi.ru.ac.za/) is compatible with all major web browsers. All scripts implemented in the web platform are freely available at https://github.com/RUBi-ZA/MD-TASK/tree/mdm-task-web and https://github.com/RUBi-ZA/MODE-TASK/tree/mdm-task-web.

Pomegranate peel extract polyphenols attenuate the SARS-CoV-2 S-glycoprotein binding ability to ACE2 Receptor: In silico and in vitro studies

The novel coronavirus disease (Covid-19) has become a major health threat globally. The interaction of SARS-CoV-2 spike (S) glycoprotein receptor-binding domain (RBD) with ACE2 receptor on host cells was recognized as the first step of virus infection and therefore as one of the primary targets for novel therapeutics. Pomegranate extracts are rich sources of bioactive polyphenols that were already recognized for their beneficial health effects. In this study, both in silico and in vitro methods were employed for evaluation of pomegranate peel extract (PoPEx), their major polyphenols, as well as their major metabolite urolithin A, to attenuate the contact of S-glycoprotein RBD and ACE2. Our results showed that PoPEx, punicalin, punicalagin and urolithin A exerted significant potential to block the S-glycoprotein-ACE2 contact. These in vitro results strongly confirm the in silico predictions and provide a valuable insight in the potential of pomegranate polyphenols for application in SARS-CoV-2 infection.

β-Carboline alkaloids induce structural plasticity and inhibition of SARS-CoV-2 nsp3 macrodomain more potently than remdesivir metabolite GS-441524: computational approach

The nsp3 macrodomain is implicated in the viral replication, pathogenesis and host immune responses through the removal of ADP-ribosylation sites during infections of coronaviruses including the SARS-CoV-2. It has ever been modulated by macromolecules including the ADP-ribose until Ni and co-workers recently reported its inhibition and plasticity enhancement unprecedentedly by remdesivir metabolite, GS-441524, creating an opportunity for investigating other biodiverse small molecules such as β-Carboline (βC) alkaloids. In this study, 1497 βC analogues from the HiT2LEAD chemical database were screened, using computational approaches of Glide XP docking, molecular dynamics simulation and pk-CSM ADMET predictions. Selectively, βC ligands, 129, 584, 1303 and 1323 demonstrated higher binding affinities to the receptor, indicated by XP docking scores of -10.72, -10.01, -9.63 and -9.48 kcal/mol respectively than remdesivir and GS-441524 with -4.68 and -9.41 kcal/mol respectively. Consistently, their binding free energies were -36.07, -23.77, -24.07 and -17.76 kcal/mol respectively, while remdesivir and GS-441524 showed -21.22 and -24.20 kcal/mol respectively. Interestingly, the selected βC ligands displayed better stability and flexibility for enhancing the plasticity of the receptor than GS-441524, especially 129 and 1303. Their predicted ADMET parameters favour druggability and low expressions for toxicity. Thus, they are recommended as promising adjuvant/standalone anti-SARS-CoV-2 candidates for further study.Key words: SARS-CoV-2, nsp3 macrodomain, ADP-ribose, β-carboline, bioinformatics, drug design.