Improving the binding affinity and interaction of 5-Pentyl-2-Phenoxyphenol against Mycobacterium Enoyl ACP reductase by computational approach

Computable properties of selected monomeric acylphloroglucinols with anticancer and/or antimalarial activities and first-approximation docking study

CONTEXT

Malaria and cancer tend to become drug-resistant a few years after a drug is introduced into clinical use. This prompts the search for new molecular structures that are sufficiently different from the drugs for which resistance has developed. The present work considers eight selected acylphloroglucinols (ACPLs) with proven antimalarial and/or anticancer activities. ACPLs are compounds of natural origin structurally derivative from 1,3,5-trihydroxybenzene and characterized by the presence of an acyl group R-C = O. The selected ACPLs contain only one acylphloroglucinol moiety and are, therefore, monomeric ACPLs (also occasionally called "simple" ACPLs). They were studied computationally in vacuo and in-three-solvents with different polarities, using different levels of theory. The findings on molecular properties relevant to the understanding of biological activities align with previous studies, enhancing the reliability of predictions for molecules of the same class and providing insights into their behaviour in different environments. Structure-based virtual screening was used to study the interactions between these molecules and selected proteins known as relevant drug targets for antimalarial and anticancer activities; the screening showed that most of these ACPLs bind well with the selected proteins, thus being interesting for further studies. The results also suggest that most of these ACPLs have the potential for dual therapeutic applications (antimalarial and anticancer), offering a cost-effective drug development option. Furthermore, the ADME-T predictions indicated favourable pharmacokinetic properties for these ACPLs.

METHODS

Computational studies of the selected ACPLs were performed using Gaussian-09, in vacuo and in-three-solvents with different polarities. Three different levels of theory were used - Hartree Fock (HF), Density Functional Theory (DFT) with the B3LYP functional, and second order Møller-Plesset Perturbation Theory (MP2). HF and MP2 used a 6-31G(d,p) basis set, while DFT used a 6-31G + (d,p), for consistency with previous studies on ACPLs. The investigated molecular properties include conformational preferences, intramolecular hydrogen bonding patterns, HOMO-LUMO energy gap, dipole moments, as well as the solvent effect for the three considered solvents. Virtual screening was conducted using the Schrödinger suite, including Maestro 9.3 with GLIDE for docking and GlideScore for evaluating binding affinities. In addition, the QikProp tool provided ADME-T predictions for pharmacokinetic properties.

Investigation and drug design for novel molecules from natural products as inhibitors for controlling multiple myeloma disease using in-silico tools

Multiple myeloma (MM) is a disease that causes plasma cell growth in the bone marrow and immune globulin buildup in blood and urine. Despite recent advances in MM therapy, many still die due to its high mortality rate. A study using computational simulations analyzed 100 natural ingredients from the SANC database to determine if they inhibited the IgH domain, a known cause of multiple myeloma. Natural component Diospyrin inhibited the IgH enzyme with the best binding energy of -10.3 kcal/mol and three carbon-hydrogen bonds, followed by Parviflorone F complex with a binding energy of -10.1 kcal/mol and two conventional-hydrogen bonds. As a result, the Molecular Dynamic simulation was used to test the stability of the two complexes. During the simulation, the Diospyrin molecule dissociated from the protein at roughly 67.5 ns, whereas the Parviflorone F molecule stayed attached to the protein throughout. The latter was the subject of the investigation. The analysis of the production run data revealed that the Parviflorone F molecule exhibits a variety of conformations within the binding pocket while keeping a relatively constant distance from the protein's center of mass. The analysis of the production run data revealed that the Parviflorone F molecule exhibited a variety of conformations within the binding pocket while keeping a relatively constant distance from the protein's center of mass. The root mean square deviation (RMSD) plots for both the protein and complex showed a stable and steady average value of 4.4 Å for the first 82 nanoseconds of manufacture. As a result, the average value increased to 8.3 Å. Furthermore, the components of the binding free energy, as computed by MM-GBSA, revealed that the mean binding energy of the Parviflorone F molecule was -23.88 kcal/mol. Finally, after analyzing all of the examination data, Parviflorone F was identified as a powerful inhibitor of the IgH domain and hence of the MM disease, which requires further in-vivo conformation.

Exploring natural products library to identify potential inhibitors targeting isoniazid-resistant tuberculosis

Mycobacterium tuberculosis (MTB) causing tuberculosis (TB) infection is a leading source of illness and death in developing nations, and the emergence of drug-resistant TB remains a significant global threat and a challenge in treating the disease. Mutations in the inhA and katG genes are connected to the principal molecular mechanism of isoniazid (INH) resistance, and continuous treatment of INH for more than a decade led to the evolution of INH resistant-TB (inhR-TB). Structure-based drug discovery approaches on traditional natural compounds are the contemporary source to identify significant lead molecules. This work focuses on discovering effective small compounds from natural compound libraries and applying pharmacophore-based virtual screening to filter out the molecules. The best-identified hit complexes were used for molecular dynamics simulations (MDS) to observe their stability and compactness. A three-dimensional e-pharmacophore hypothesis and screening generated 62 hits based on phase fitness scores from the pharmacophore-based virtual screening. Molecular docking experiments in Maestro's GLIDE module indicated that ZINC000002383126 and ASN22022 may be potential inhibitors of inhA and katG (native, inhA mutants S94A, Y158A, Y158F and Y158S and D137S, Y229F, S315T, W321F, and R418L mutants of katG). In addition, MDS analysis indicated that the native and mutant docked complexes of inhA and katG had good stability and remained compact in the binding pocket of the targets. In vitro studies can further validate the compounds that can act as INH competitive inhibitors.Communicated by Ramaswamy H. Sarma.

The potential of Sonneratia caseolaris mangrove leaves extract as a bioactive food ingredient using various water extract

Background

Sonneratia caseolaris, has been widely utilized by the Indonesian. S. caseolaris leaves contain various active compounds, contributing to their popularity in the treatment of various diseases. Mangrove leaves are also known to exhibit very high antioxidant activity. This study aims to assess the antioxidant activity of S . caseolaris leaves extracted using different solvents. The resulting extract was evaluated for antioxidant activity by the 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity (DPPH) techniques.

Methods

Analysis of total flavonoids, total phenols, identification of active compounds with Liquid Chromatography High Resolution Mass Spectrometry (LC-HRMS), and bioinformatics were also carried out to obtain temporary conclusions about the antioxidant activity of S. caseolaris leaf extract.

Results

The results indicated that S. caseolaris leaves extracted with methanol and distilled water exhibited the highest antioxidant activity compared to other extracts. The analysis of total flavonoids and total phenols yielded results consistent with the antioxidant activity tests. LC-HRMS results identified three compounds in all S. caseolaris leaf extracts with antioxidant activity, namely TEMPO, Choline, and Betaine. TEMPO demonstrated a higher antioxidant activity than Choline and Betaine, as indicated by the binding affinity values in the bioinformatics analysis.

Conclusions

It is evident that S. caseolaris leaf extracts has the potential to serve as an effective antioxidant agent. Further research is needed to confirm how the potential compounds in S. caseolaris leaf water extracts interact with the target protein Keap1. This research aims to utilize S. caseolaris as active components in food products, thereby enhancing antioxidant consumption among consumers.

Structure based interaction and molecular dynamics studies of cysteine protease Cathepsin B against curcumin and resveratrol

The lysosomal cysteine peptidase Cathepsin B is identified as a pivotal contributor to cancer development. In the pursuit of discovering less toxic inhibitors for Cathepsin B, various organic compounds have undergone thorough investigation and are being studied at the moment in clinical studies for cancer treatment. Notably, curcumin and resveratrol emerge as prominent candidates. However, the precise molecular mechanism underlying the inhibition of Cathepsin B by these compounds remains elusive. To address this gap, we conducted molecular docking and dynamics studies to unravel the interaction dynamics between Cathepsin B and phytochemicals such as curcumin and resveratrol. Remarkably, Molecular docking studies revealed that curcumin and resveratrol exhibit high binding affinities 7.599 and 6.103 kcal/mol, respectively, positioning them as promising inhibitors for Cathepsin B. Further insights from 150 ns of molecular dynamics simulations, incorporating structural analyses encompassing RMSF, RMSD, Rg, SASA, and H-bond analysis, indicate the superior stability of curcumin compared to resveratrol. Additionally, we assessed their drug-likeness properties using the PreADMET web server, and the MM/BPSA method facilitated the calculation of binding energies for the complexes. On targeting Cathepsin B, this research promises to contribute to the development of drugs that inhibit the progression of cancer.

Computational Exploration of Potential Pharmacological Inhibitors Targeting the Envelope Protein of the Kyasanur Forest Disease Virus

The limitations of the current vaccination strategy for the Kyasanur Forest Disease virus (KFDV) underscore the critical need for effective antiviral treatments, highlighting the crucial importance of exploring novel therapeutic approaches through in silico drug design. Kyasanur Forest Disease, caused by KFDV, is a tick-borne disease with a mortality of 3-5% and an annual incidence of 400 to 500 cases. In the early stage of infection, the envelope protein plays a crucial role by facilitating host-virus interactions. The objective of this research is to develop effective antivirals targeting the envelope protein to disrupt the virus-host interaction. In line with this, the 3D structure of the envelope protein was modeled and refined through molecular modeling techniques, and subsequently, ligands were designed via de novo design and pharmacophore screening, yielding 12 potential hits followed by ADMET analysis. The top five candidates underwent geometry optimization and molecular docking. Notably, compounds L4 (SA28) and L3 (CNP0247967) are predicted to have significant binding affinities of -8.91 and -7.58 kcal/mol, respectively, toward the envelope protein, based on computational models. Both compounds demonstrated stability during 200 ns molecular dynamics simulations, and the MM-GBSA binding free-energy values were -85.26 ± 4.63 kcal/mol and -66.60 ± 2.92 kcal/mol for the envelope protein L3 and L4 complexes, respectively. Based on the computational prediction, it is suggested that both compounds have potential as drug candidates for controlling host-virus interactions by targeting the envelope protein. Further validation through in-vitro assays would complement the findings of the present in silico investigations.

Identifying potential monkeypox virus inhibitors: an in silico study targeting the A42R protein

Monkeypox (now Mpox), a zoonotic disease caused by the monkeypox virus (MPXV) is an emerging threat to global health. In the time span of only six months, from May to October 2022, the number of MPXV cases breached 80,000 and many of the outbreaks occurred in locations that had never previously reported MPXV. Currently there are no FDA-approved MPXV-specific vaccines or treatments, therefore, finding drugs to combat MPXV is of utmost importance. The A42R profilin-like protein of the MPXV is involved in cell development and motility making it a critical drug target. A42R protein is highly conserved across orthopoxviruses, thus A42R inhibitors may work for other family members. This study sought to identify potential A42R inhibitors for MPXV treatment using computational approaches. The energy minimized 3D structure of the A42R profilin-like protein (PDB ID: 4QWO) underwent virtual screening using a library of 36,366 compounds from Traditional Chinese Medicine (TCM), AfroDb, and PubChem databases as well as known inhibitor tecovirimat via AutoDock Vina. A total of seven compounds comprising PubChem CID: 11371962, ZINC000000899909, ZINC000001632866, ZINC000015151344, ZINC000013378519, ZINC000000086470, and ZINC000095486204, predicted to have favorable binding were shortlisted. Molecular docking suggested that all seven proposed compounds have higher binding affinities to A42R (-7.2 to -8.3 kcal/mol) than tecovirimat (-6.7 kcal/mol). This was corroborated by MM/PBSA calculations, with tecovirimat demonstrating the highest binding free energy of -68.694 kJ/mol (lowest binding affinity) compared to the seven shortlisted compounds that ranged from -73.252 to -97.140 kJ/mol. Furthermore, the 7 compounds in complex with A42R demonstrated higher stability than the A42R-tecovirimat complex when subjected to 100 ns molecular dynamics simulations. The protein-ligand interaction maps generated using LigPlot+ suggested that residues Met1, Glu3, Trp4, Ile7, Arg127, Val128, Thr131, and Asn133 are important for binding. These seven compounds were adequately profiled to be potential antivirals via PASS predictions and structural similarity searches. All seven potential lead compounds were scored Pa > Pi for antiviral activity while ZINC000001632866 and ZINC000015151344 were predicted as poxvirus inhibitors with Pa values of 0.315 and 0.215, and Pi values of 0.052 and 0.136, respectively. Further experimental validations of the identified lead compounds are required to corroborate their predicted activity. These seven identified compounds represent solid footing for development of antivirals against MPXV and other orthopoxviruses.

Antifungal Constituents of Piper crocatum and Their Activities as Ergosterol Biosynthesis Inhibitors Discovered via In Silico Study Using ADMET and Drug-Likeness Analysis

Along with the increasing resistance of Candida spp. to some antibiotics, it is necessary to find new antifungal drugs, one of which is from the medicinal plant Red Betel (Piper crocatum). The purpose of this research is to isolate antifungal constituents from P. crocatum and evaluate their activities as ergosterol biosynthesis inhibitors via an in silico study of ADMET and drug-likeness analysis. Two new active compounds 1 and 2 and a known compound 3 were isolated, and their structures were determined using spectroscopic methods, while their bioactivities were evaluated via in vitro and in silico studies, respectively. Antifungal compound 3 was the most active compared to 1 and 2 with zone inhibition values of 14.5, 11.9, and 13.0 mm, respectively, at a concentration of 10% w/v, together with MIC/MFC at 0.31/1.2% w/v. Further in silico study demonstrated that compound 3 had a stronger ΔG than the positive control and compounds 1 and 2 with -11.14, -12.78, -12.00, and -6.89 Kcal/mol against ERG1, ERG2, ERG11, and ERG24, respectively, and also that 3 had the best Ki with 6.8 × 10-3, 4 × 10-4, 1.6 × 10-3, and 8.88 μM. On the other hand, an ADMET analysis of 1-3 met five parameters, while 1 had one violation of Ro5. Based on the research data, the promising antifungal constituents of P. crocatum allow P. crocatum to be proposed as a new antifungal candidate to treat and cure infections due to C. albicans.

In Silico Study of Thiourea Derivatives as Potential Epidermal Growth Factor Receptor Inhibitors

Over the years, the escalation of cancer cases has been linked to the resistance, less selectivity, and toxicity of available anticancer drugs to normal cells. Therefore, continuous efforts are necessary to find new anticancer drugs with high selectivity of epidermal growth factor receptor tyrosine kinase (EGFR-TK) as a therapeutic target. The EGFR-TK protein has a crucial role in cell proliferation and cancer progression. With about 30% of cancer cases involved with the protein, it has piqued the interest as a therapeutic target. The potential of theoretically designed thiourea derivatives as anticancer agents in this report was evaluated against EGFR-TK via in silico techniques, including molecular docking (AutoDock Vina), molecular dynamics simulations (GROMACS), pharmacokinetics, and drug-likeness properties (SwissADME and Molinspiration). New hybrid molecules of the thiourea derivative moiety were designed in this study based on the fragment-based drug discovery and linked with diverse pharmacophoric fragments with reported anticancer potential ([Formula: see text]) and the modification of the methyl position on phenyl ring ([Formula: see text]). These fragments include pyridine, thiophene, furan, pyrrole and styrene groups. Out of 15 compounds, compound 13 displayed the most potent inhibitory activity, with the lowest binding affinity in docking of [Formula: see text]8.7 kcal/mol compared to the positive control erlotinib of [Formula: see text]6.7 kcal/mol. Our molecular dynamics (MD) simulations revealed that molecule 13, comprising styrene and 2-methylphenyl substituents on [Formula: see text] and [Formula: see text], respectively, showed adequate compactness, uniqueness and satisfactory stability. Subsequently, the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties and drug-likeness properties also indicate that this theoretically designed inhibitor ( 13) is less toxic and contains high druggable properties. Thus, compound 13 could be promising against EGFR-TK.

Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review

Computer-aided drug design (CADD) is one of the pivotal approaches to contemporary pre-clinical drug discovery, and various computational techniques and software programs are typically used in combination, in a bid to achieve the desired outcome. Several approved drugs have been developed with the aid of CADD. On SciFinder®, we evaluated more than 600 publications through systematic searching and refining, using the terms, virtual screening; software methods; computational studies and publication year, in order to obtain data concerning particular aspects of CADD. The primary focus of this review was on the databases screened, virtual screening and/or molecular docking software program used. Furthermore, we evaluated the studies that subsequently performed molecular dynamics (MD) simulations and we reviewed the software programs applied, the application of density functional theory (DFT) calculations and experimental assays. To represent the latest trends, the most recent data obtained was between 2015 and 2020, consequently the most frequently employed techniques and software programs were recorded. Among these, the ZINC database was the most widely preferred with an average use of 31.2%. Structure-based virtual screening (SBVS) was the most prominently used type of virtual screening and it accounted for an average of 57.6%, with AutoDock being the preferred virtual screening/molecular docking program with 41.8% usage. Following the screening process, 38.5% of the studies performed MD simulations to complement the virtual screening and GROMACS with 39.3% usage, was the popular MD software program. Among the computational techniques, DFT was the least applied whereby it only accounts for 0.02% average use. An average of 36.5% of the studies included reports on experimental evaluations following virtual screening. Ultimately, since the inception and application of CADD in pre-clinical drug discovery, more than 70 approved drugs have been discovered, and this number is steadily increasing over time.