The potential role of in silico approaches to identify novel bioactive molecules from natural resources

In silico assessment of biocompatibility and toxicity: molecular docking and dynamics simulation of PMMA-based dental materials for interim prosthetic restorations

AIM

This study aimed to comprehensively assess the biocompatibility and toxicity profiles of poly(methyl methacrylate) (PMMA) and its monomeric unit, methyl methacrylate (MMA), crucial components in dental materials for interim prosthetic restorations.

METHODOLOGY

Molecular docking was employed to predict the binding affinities, energetics, and steric features of MMA and PMMA with selected receptors involved in bone metabolism and tissue development, including RANKL, Fibronectin, BMP9, NOTCH2, and other related receptors. The HADDOCK standalone version was utilized for docking calculations, employing a Lamarckian genetic algorithm to explore the conformational space of ligand-receptor interactions. Furthermore, molecular dynamics (MD) simulations over 100 nanoseconds were conducted using the GROMACS package to evaluate dynamic actions and structural stability. The LigandScout was utilized for pharmacophore modeling, which employs a shape-based screening approach to identify potential ligand binding sites on protein targets.

RESULTS

The molecular docking studies elucidated promising interactions between PMMA and MMA with key biomolecular targets relevant to dental applications. MD simulation results provided strong evidence supporting the structural stability of PMMA complexes over time. Pharmacophore modeling highlighted the significance of carbonyl and hydroxyl groups as pharmacophoric features, indicating compounds with favorable biocompatibility profiles.

CONCLUSION

This study underscores the potential of PMMA in dental applications, emphasizing its structural stability, molecular interactions, and safety considerations. These findings lay a foundation for future advancements in dental biomaterials, guiding the design and optimization of materials for enhanced biocompatibility. Future directions include experimental validation of computational findings and the development of PMMA-based dental materials with improved biocompatibility and clinical performance.

Detection of natural compounds by virtual screening, molecular docking and dynamics studies and evaluation of their effects on tau level in vitro Alzheimer's model

In Alzheimer's disease (AD), neurofibrillary tangles are composed of hyperphosphorylated tau protein, and tau hyperphosphorylation reduces microtubule binding. Many protein kinases are thought to be involved in tau hyperphosphorylation. Based on the fact that tau hyperphosphorylation can be prevented by inhibition of glycogen synthase kinase-3β (GSK-3β), which is one of the tau kinases, the effectiveness of potential GSK-3β inhibitors determined by virtual screening, molecular docking, and dynamics simulations studies on Alzheimer's pathology has been examined and its role in neurodegeneration has been investigated by studies. Neomangiferin was determined as the most effective molecule according to the results of studies with potential compounds determined by virtual screening and molecular docking to be GSK-3β inhibitors in the in vitro Alzheimer's model created by neuronal differentiation studies. Neomangiferin has been shown to have a protective role in induced neurodegeneration by the MTT method and Real Time Cell Analysis. It has been determined that Neomangiferin inhibits GSK-3β and reduces the level of phosphorylated tau. In summary, our findings suggested Neomangiferin can be a therapeutic candidate for AD treatment.Communicated by Ramaswamy H. Sarma.

In Silico and In Vitro Approach for Evaluation of the Anti-Inflammatory and Antioxidant Potential of Mygalin

There is a great interest in describing new molecules to be used as therapeutic targets in various diseases, particularly those that play a role in inflammatory responses and infection control. Mygalin is a synthetic analogue of spermidine, and previous studies have demonstrated its bactericidal effect against Escherichia coli, as well as its ability to modulate the inflammatory response of macrophages against lipopolysaccharide (LPS). However, the mechanisms through which mygalin regulates this inflammatory response remain poorly characterized. A set of platforms using molecular docking analysis was employed to analyze various properties of mygalin, including toxicity, biodistribution, absorption, and the prediction of its anti-inflammatory properties. In in vitro assays, we evaluated the potential of mygalin to interact with products of the inflammatory response, such as reactive oxygen species (ROS) and antioxidant activity, using the BMDM cell. The in silico analyses indicated that mygalin is not toxic, and can interact with proteins from the kinase group, and enzymes and receptors in eukaryotic cells. Molecular docking analysis showed interactions with key amino acid residues of COX-2, iNOS and 5-LOX enzymes. In vitro, assays demonstrated a significant reduction in the expression of iNOS and COX-2 induced by LPS, along with a decrease in the oxidative stress caused by the treatment with PMA, all without altering cell viability. Mygalin exhibited robust antioxidant activity in DPPH assays, regardless of the dose used, and inhibited heat-induced hemolysis. These studies suggest that mygalin holds promise for further investigation as a new molecule with anti-inflammatory and antioxidant properties.

Molecular docking and molecular dynamics simulation analysis of bioactive compounds of Cichorium intybus L. seed against hepatocellular carcinoma

In this article, bioactive compounds present in Cichorium intybus L. seeds were collected from literature review and analyzed for probable remedy for hepatocellular carcinoma. Cichorium intybus L. is a traditional plant used all over the world mainly in hepatic disorders and renal diseases. This therapeutic plant has many bioactive compounds like chicoric acid, chlorogenic acid, sesquiterpne lactones, stigmasterols etc are found in seeds. Here, the target protein p53 (PDB ID: 2OCJ) which is involved in many cancerous pathways, is chosen. The preADMET study filtered out some compounds which were then subjected to molecular docking studies by Autodock tool 4.2. Afterwards, two best compounds (Esculetin and Isochlorogenic acid) were screened out on the basis of binding energy as compared to the standard compound (Doxorubicin). All these complexes were then analyzed for stability by molecular dynamics using online GROMACS tool. In the comparative simulation study, the compound Esculetin shows a stable interaction with the p53 over the 100 ns trajectory. Hepatocellular carcinoma accounts for high mortality of cancer related death worldwide. These findings suggest that these compound can be used to treat the hepatocellular carcinoma.Communicated by Ramaswamy H. Sarma.

Synthesis and Anti-Inflammatory Activity of 1-Methylhydantoin Cinnamoyl Imides

In this study, 1-methylhydantoin cinnamic imides were synthesized from 1-methylhydantoin and trans-cinnamic acid, and their anti-inflammatory activity was investigated. The anti-inflammatory activity in vitro was evaluated by measuring the contents of NO, TNF-α and IL-1β in the supernatant of RAW264.7 cells stimulated by LPS. The cytotoxicity of 1-methylhydantoin cinnamoyl imides on RAW264.7 cells was detected using the CCK-8 method. The results showed that compounds 2 and 4 can significantly inhibit the release of NO and reduce the secretion of TNF-α and IL-1β. Compound 3 inhibited the production of TNF-α. The inhibition rate of COX was evaluated in vitro. The in vivo anti-inflammatory activities of the five compounds were evaluated by establishing an animal model of xylene ear swelling. The results showed that 1-methylhydantoin cinnamic imides could alleviate xylene-induced ear edema in mice in a dose-dependent manner. Among them, the effect of compound 5 was the most significant. Under the action of high dosage, its ear swelling inhibition rate was as high as 52.08%.

Insights into antiradical mechanism and pro-oxidant enzyme inhibitor activity of walterolactone A/B 6-O-gallate-β-d-pyranoglucoside originating from Euonymus laxiflorus Champ. using in silico study

The ability of a new compound, Wal, (walterolactone A/B 6-O-gallate-β-d-pyranoglucoside) originating from Euonymus laxiflorus Champ. as a hydroperoxyl radical scavenger and pro-oxidant enzyme inhibitor was studied in silico. Different mechanisms, reaction locations, and chemical species of Wal in aqueous solution were taken into consideration. Formal hydrogen transfer from the OH group has been discovered as the chemical process that contributes most to the antioxidant properties of Wal in nonpolar and aqueous solutions. The overall rate coefficients for polar and non-polar environments are expected to have values of 7.85 × 106 M-1 s-1 and 4.84 × 105 M-1 s-1, respectively. According to the results of the investigation, Wal has greater scavenging activity against the HOO˙ radical than the reference antioxidant Trolox at physiological pH (7.4). In addition, docking results indicate that Wal's antioxidant properties involve the inhibition of the activity of enzyme families (CP450, MP, NO, and XO) that are responsible for ROS production.

In-silico and in-vitro hybrid approach to identify glucagon-like peptide-1 receptor agonists from anti-diabetic natural products

Natural products have contributed immensely towards the treatment of various diseases including diabetes. Here, a database of small molecules from nature possessing antidiabetic properties was analysed and shortlisted according to their structural diversity. Later, those structures were screened by in-silico docking studies to understand their affinity towards glucagon-like peptide-1 (GLP-1) receptor. The selected molecules were isolated and investigated further by integrated in-vitro and in-silico approaches. Alpha-mangostin was found to be suitable due to its excellent docking score and isolation yield. A pancreatic beta cell line was used to test the activity of alpha-mangostin and observed a 3-fold increase in insulin secretion compared to 15 mM glucose control. Further, in-silico molecular dynamics simulations studies have validated its target by showing conformational changes at the functionally active part of the GLP-1 receptor. This screening strategy can be applied to identify pertinent natural products rapidly for various therapeutic targets.

A Recent Look into Natural Products that have Potential to Inhibit Cholinesterases and Monoamine Oxidase B: Update for 2010-2019

With respect to the unknowns of pathophysiology of Alzheimer's Disease (AD)-, and Parkinson's Disease (PD)-like neurodegenerative disorders, natural product research is still one of the valid tools in order to provide alternative and/or better treatment options. At one hand, various extracts of herbals provide a combination of actions targeting multiple receptors, on the other hand, the discovery of active natural products (i.e., secondary metabolites) generally offers alternative chemical structures either ready to be employed in clinical studies or available to be utilized as important scaffolds for the design of novel agents. Regarding the importance of certain enzymes (e.g. cholinesterase and monoamine oxidase B), for the treatment of AD and PD, we have surveyed the natural product research within this area in the last decade. Particularly novel natural agents discovered within this period, concomitant to novel biological activities displayed for known natural products, are harmonized within the present study.

A chemoinformatic analysis of atoms, scaffolds and functional groups in natural products

In the quest to know why natural products (NPs) have often been considered as privileged scaffolds for drug discovery purposes, many investigations into the differences between NPs and synthetic compounds have been carried out. Several attempts to answer this question have led to the investigation of the atomic composition, scaffolds and functional groups (FGs) of NPs, in comparison with synthetic drugs analysis. This chapter briefly describes an atomic enumeration method for chemical libraries that has been applied for the analysis of NP libraries, followed by a description of the main differences between NPs of marine and terrestrial origin in terms of their general physicochemical properties, most common scaffolds and “drug-likeness” properties. The last parts of the work describe an analysis of scaffolds and FGs common in NP libraries, focusing on huge NP databases, e.g. those in the Dictionary of Natural Products (DNP), NPs from cyanobacteria and the largest chemical class of NP – terpenoids.

Alkaloids in Contemporary Drug Discovery to Meet Global Disease Needs

An overview is presented of the well-established role of alkaloids in drug discovery, the application of more sustainable chemicals, and biological approaches, and the implementation of information systems to address the current challenges faced in meeting global disease needs. The necessity for a new international paradigm for natural product discovery and development for the treatment of multidrug resistant organisms, and rare and neglected tropical diseases in the era of the Fourth Industrial Revolution and the Quintuple Helix is discussed.

A Multifunctional Peptide From Bacillus Fermented Soybean for Effective Inhibition of SARS-CoV-2 S1 Receptor Binding Domain and Modulation of Toll Like Receptor 4: A Molecular Docking Study

Fermented soybean products are traditionally consumed and popular in many Asian countries and the northeastern part of India. To search for potential agents for the interruption of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Spike glycoprotein 1 (S1) and human angiotensin-converting enzyme 2 (ACE2) receptor interactions, the in silico antiviral prospective of peptides identified from the proteome of kinema was investigated. Soybean was fermented using Bacillus licheniformis KN1G, Bacillus amyloliquefaciens KN2G and two different strains of Bacillus subtilis (KN2B and KN2M). The peptides were screened in silico for possible antiviral activity using two different web servers (AVPpred and meta-iAVP), and binding interactions of selected 44 peptides were further explored against the receptor-binding domain (RBD) of the S1 protein (PDB ID: 6M0J) by molecular docking using ZDOCK. The results showed that a peptide ALPEEVIQHTFNLKSQ (P13) belonging to B. licheniformis KN1G fermented kinema was able to make contacts with the binding motif of RBD by blocking specific residues designated as critical (GLN493, ASN501) in the binding of human angiotensin-converting enzyme 2 (ACE2) cell receptor. The selected peptide was also observed to have a significant affinity towards human toll like receptor 4 (TLR4)/Myeloid Differentiation factor 2 (MD2) (PDB ID: 3FXI) complex known for its essential role in cytokine storm. The energy properties of the docked complexes were analyzed through the Generalized Born model and Solvent Accessibility method (MM/GBSA) using HawkDock server. The results showed peptidyl amino acids GLU5, GLN8, PHE11, and LEU13 contributed most to P13-RBD binding. Similarly, ARG90, PHE121, LEU61, PHE126, and ILE94 were appeared to be significant in P13-TLR4/MD2 complex. The findings of the study suggest that the peptides from fermented soy prepared using B. licheniformis KN1G have better potential to be used as antiviral agents. The specific peptide ALPEEVIQHTFNLKSQ could be synthesized and used in combination with experimental studies to validate its effect on SARS-CoV-2-hACE2 interaction and modulation of TLR4 activity. Subsequently, the protein hydrolysate comprising these peptides could be used as prophylaxis against viral diseases, including COVID-19.

Machine learning approaches for elucidating the biological effects of natural products

Covering: 2000 to 2020 Machine learning (ML) is an efficient tool for the prediction of bioactivity and the study of structure-activity relationships. Over the past decade, an emerging trend for combining these approaches with the study of natural products (NPs) has developed in order to manage the challenge of the discovery of bioactive NPs. In the present review, we will introduce the basic principles and protocols for using the ML approach to investigate the bioactivity of NPs, citing a series of practical examples regarding the study of anti-microbial, anti-cancer, and anti-inflammatory NPs, etc. ML algorithms manage a variety of classification and regression problems associated with bioactive NPs, from those that are linear to non-linear and from pure compounds to plant extracts. Inspired by cases reported in the literature and our own experience, a number of key points have been emphasized for reducing modeling errors, including dataset preparation and applicability domain analysis.

Colombian Contributions Fighting Leishmaniasis: A Systematic Review on Antileishmanials Combined with Chemoinformatics Analysis

Leishmaniasis is a parasitic morbid/fatal disease caused by Leishmania protozoa. Twelve million people worldwide are appraised to be currently infected, including ca. two million infections each year, and 350 million people in 88 countries are at risk of becoming infected. In Colombia, cutaneous leishmaniasis (CL) is a public health problem in some tropical areas. Therapeutics is based on traditional antileishmanial drugs, but this practice has several drawbacks for patients. Thus, the search for new antileishmanial agents is a serious need, but the lack of adequately funded research programs on drug discovery has hampered its progress. Some Colombian researchers have conducted different research projects focused on the assessment of the antileishmanial activity of naturally occurring and synthetic compounds against promastigotes and/or amastigotes. Results of such studies have separately demonstrated important hits and reasonable potential, but a holistic view of them is lacking. Hence, we present the outcome from a systematic review of the literature (under PRISMA guidelines) on those Colombian studies investigating antileishmanials during the last thirty-two years. In order to combine the general efforts aiming at finding a lead against Leishmania panamensis (one of the most studied and incident parasites in Colombia causing CL) and to recognize structural features of representative compounds, fingerprint-based analyses using conventional machine learning algorithms and clustering methods are shown. Abstraction from such a meta-description led to describe some function-determining molecular features and simplify the clustering of plausible isofunctional hits. This systematic review indicated that the Colombian efforts for the antileishmanials discovery are increasingly intensified, though improvements in the followed pathways must be definitively pursued. In this context, a brief discussion about scope, strengths and limitations of such advances and relationships is addressed.

Cheminformatics in Natural Product-based Drug Discovery

This review seeks to provide a timely survey of the scope and limitations of cheminformatics methods in natural product-based drug discovery. Following an overview of data resources of chemical, biological and structural information on natural products, we discuss, among other aspects, in silico methods for (i) data curation and natural products dereplication, (ii) analysis, visualization, navigation and comparison of the chemical space, (iii) quantification of natural product-likeness, (iv) prediction of the bioactivities (virtual screening, target prediction), ADME and safety profiles (toxicity) of natural products, (v) natural products-inspired de novo design and (vi) prediction of natural products prone to cause interference with biological assays. Among the many methods discussed are rule-based, similarity-based, shape-based, pharmacophore-based and network-based approaches, docking and machine learning methods.

Zoopharmacology: A Way to Discover New Cancer Treatments

Zoopharmacognosy is the multidisciplinary approach of the self-medication behavior of many kinds of animals. Recent studies showed the presence of antitumoral secondary metabolites in some of the plants employed by animals and their use for the same therapeutic purposes in humans. Other related and sometimes confused term is Zootherapy, which consists on the employment of animal parts and/or their by-products such as toxins, venoms, etc., to treat different human ailments. Therefore, the aim of this work is to provide a brief insight for the use of Zoopharmacology (comprising Zoopharmacognosy and Zootherapy) as new paths to discover drugs studying animal behavior and/or using compounds derived from animals. This work is focused on the approaches related to cancer, in order to propose a new promising line of research to overcome multidrug resistance (MDR). This novel subject will encourage the use of new alternative prospective ways to find new medicines.

Fragment-based drug design of nature-inspired compounds

Natural product (NP)-derived drugs can be extracts, biological macromolecules, or purified small molecule substances. Small molecule drugs can be originally purified from NPs, can represent semisynthetic molecules, natural fragments containing small molecules, or are fully synthetic molecules that mimic natural compounds. New semisynthetic NP-like drugs are entering the pharmaceutical market almost every year and reveal growing interests in the application of fragment-based approaches for NPs. Thus, several NP databases were constructed to be implemented in the fragment-based drug design (FBDD) workflows. FBDD has been established previously as an approach for hit identification and lead generation. Several biophysical and computational methods are used for fragment screening to identify potential hits. Once the fragments within the binding pocket of the protein are identified, they can be grown, linked, or merged to design more active compounds. This work discusses applications of NPs and NP scaffolds to FBDD. Moreover, it briefly reviews NP databases containing fragments and reports on case studies where the approach has been successfully applied for the design of antimalarial and anticancer drug candidates.

Antitussive and Anti-inflammatory Dual-active Agents Developed from Natural Product Lead Compound 1-Methylhydantoin

Natural products play an important role in drug discovery. This work employed a natural product 1-methylhydantoin as the lead compound to develop novel dual-active drugs. 1-Methylhydantoin was isolated from Oviductus Ranae, which is a traditional Chinese medicine that has been used for tussive and inflammation treatment for a long time. An in silico study screened the more active 1-methylhydantoin derivatives. Antitussive assessment indicated that the newly synthesized agent had similar bioactivity with the natural product. An anti-inflammatory model used xylene induced ear edema model. At the same dosage (100 mg/Kg), the newly prepared agent had an inhibition rate 53.18% which was much higher than that of the lead compound (22.69%). The results might be ascribed to the cyclooxygenases-1 (COX-1) and cyclooxygenases-2 (COX-2) selectivity, and the fitness of the compound, and the binding pocket. The anti-particulate matter (PM 2.5) acute pneumonia was evaluated through an in vivo model constructed by nasal instillation with PM 2.5 suspension. The results of the above models suggested that this novel agent had remarkable antitussive, anti-inflammatory, and anti-PM 2.5 acute pneumonia activities.

Review on chemogenomic approaches towards hepatitis C viral targets

Hepatitis C virus (HCV) is the most prevalent viral pathogen that infects more than 185 million people worldwide. HCV infection leads to chronic liver diseases such as liver cirrhosis and hepatocellular carcinoma. Direct-acting antivirals (DAAs) are the recent combination therapy for HCV infection with reduced side effects than prior therapies. Sustained virological response (SVR) acts as a gold standard marker to monitor the success of antiviral treatment. Older treatment therapies attain 50-55% of SVR compared with DAAs which attain around 90-95%. The current review emphasizes the recent chemogenomic updates that have been unfolded through structure-based drug design of HCV drug target proteins (NS3/4A, NS5A, and NS5B) and ligand-based drug design of DAAs in achieving a stable HCV viral treatment strategies.

Online structure-based screening of purchasable approved drugs and natural compounds: retrospective examples of drug repositioning on cancer targets

Drug discovery is a long and difficult process that benefits from the integration of virtual screening methods in experimental screening campaigns such as to generate testable hypotheses, accelerate and/or reduce the cost of drug development. Current drug attrition rate is still a major issue in all therapeutic areas and especially in the field of cancer. Drug repositioning as well as the screening of natural compounds constitute promising approaches to accelerate and improve the success rate of drug discovery. We developed three compounds libraries of purchasable compounds: Drugs-lib, FOOD-lib and NP-lib that contain approved drugs, food constituents and natural products, respectively, that are optimized for structure-based virtual screening studies. The three compounds libraries are implemented in the MTiOpenScreen web server that allows users to perform structure-based virtual screening computations on their selected protein targets. The server outputs a list of 1,500 molecules with predicted binding scores that can then be processed further by the users and purchased for experimental validation. To illustrate the potential of our service for drug repositioning endeavours, we selected five recently published drugs that have been repositioned in vitro and/or in vivo on cancer targets. For each drug, we used the MTiOpenScreen service to screen the Drugs-lib collection against the corresponding anti-cancer target and we show that our protocol is able to rank these drugs within the top ranked compounds. This web server should assist the discovery of promising molecules that could benefit patients, with faster development times, and reduced costs and risk.