Improving the Prediction of Absolute Solvation Free Energies Using the Next Generation OPLS Force Field

Experimental and computational study of binary mixture ethanolamine and 2-amino-2-methyl-1-propanol

The present work involves experimental and computational investigations into the density of pure and mixed states of ethanolamine (ET) and 2-amino-2-methyl-1-propanol (AMP) under a pressure of 1 atm and temperatures ranging from 293.15 K to 333.15 K The density data were used to derive the excess molar volume, thermal expansion coefficient, and isothermal coefficient of pressure excess molar enthalpy. The Redlich-Kister equation was employed to calculate the excess molar and its accompanying coefficients. In the gas phase, density functional theory (DFT) was utilized to explore the most stable structures of ET … ET, AMP … AMP, and the ET … AMP mixture. Molecular dynamics simulation (MD) was used to calculate the structural properties of these mixtures in the liquid phase. Radial distribution function (RDFs) combined distribution function (CDF) and spatial distribution function (SDF) in different mole fractions calculated in the liquid phase. The intramolecular and intermolecular interactions of ethanolamine and AMP were obtained using the radial distribution function in different molar fractions. It was found that the ethanolamine molecule has a greater tendency to form intramolecular hydrogen bonds, while the AMP molecule has a greater tendency to form intermolecular hydrogen bonds.

A cell based assay using virus-like particles to screen AM type mimics for SARS-CoV-2 neutralisation

A number of small molecule and protein therapeutic candidates have been developed in the last four years against SARS-CoV-2 spike. However, there are hardly a few molecules that have advanced through the subsequent discovery steps to eventually work as a therapeutic agent. This is majorly because of the hurdles in determining the affinity of potential therapeutics with live SARS-CoV-2 virus. Furthermore, affinity determined for the receptor binding domain (RBD) of the SARS-CoV-2 spike protein, at times, fails to mimic physiological conditions of the host-virus interaction. To bridge this gap between in vitro and in vivo methods of therapeutic agent screening, we report an improved screening protocol for therapeutic candidates using SARS-CoV-2 virus like particles (VLPs). To minimise the interference from the bulkier reporters like GPF in the affinity studies, a smaller hemagglutinin (HA) tag has been fused to one of the proteins of VLP. This HA tag serves as readout, when probed with fluorescent anti-HA antibodies. Outcome of this study sheds light on the lesser known virus neutralisation capabilities of AM type miniprotein mimics. Further, to assess the stability of SARS-CoV-2 spike - miniprotein complex, we have performed molecular dynamic simulations on the membrane embedded protein complex. Simulation results reveal extremely stable intermolecular interactions between RBD and one of the AM type miniproteins, AM1. Furthermore, we discovered a robust network of intramolecular interactions that help stabilise AM1. Findings from our in vitro and in silico experiments concurrently highlight advantages and capabilities of mimic based miniprotein therapeutics.

Identification of imidazole-based small molecules to combat cognitive disability caused by Alzheimer's disease: A molecular docking and MD simulations based approach

Alzheimer's disease (AD) is a chronic neurodegenerative disorder that is the primary cause of dementia. It is characterised by the gradual loss of brain cells, which results in memory loss and cognitive dysfunction. One of the hallmarks of AD is an abnormally upregulated glutaminyl-peptide cyclotransferase (QPCT or QC) enzyme. Not only AD, but QC has also been implicated with pathological conditions like Huntington's disease (HD), melanomas, carcinomas, atherosclerosis, and septic arthritis. Therefore, the inhibition of QC emerged as a potential strategy for preventing multiple pathological conditions. Considering this, we screened a library of 153,536 imidazole-based compounds against a doubly mutant (Y115E-Y117E) QC target. Molecular docking based virtual screening and absorption, distribution, metabolism, excretion/toxicity (ADME/T) predictions identified five compounds, namely 118981836, 136459842, 139388116, 139388226, and 139958725. Furthermore, molecular dynamics (MD) simulations of 500 ns were conducted to investigate the behaviour of the identified compounds with the target receptor. The results were compared to the co-ligand by analysing RMSD, RMSF, and SASA parameters. To our knowledge, this is the first computational study that employed a protein with double mutation to identify new imidazole-based QC-inhibitors.

Design, Synthesis, Nematicidal Evaluation, and Molecular Docking Study of Pyrano[3,2-c]pyridones against Meloidogyne incognita

Root-knot nematodes pose a serious threat to crops by affecting production and quality. Over a period of time, substantial work has been done toward the development of effective and environmentally benign nematicidal compounds. However, due to the inefficiencies of previously reported synthetics in achieving the target of safe, selective, and effective treatment, it is necessary to develop new efficacious and safer nematicidal agents considering human health and environment on top priority. This work aims to highlight the efficient and convenient l-proline catalyzed synthesis of pyrano[3,2-c]pyridone and their use as potential nematicidal agents. In vitro results of larval mortality and egg hatching inhibition revealed maximum nematicidal activity against Meloidogyne incognita from compounds 15b, 15m, and 15w with LC50 values of 28.8, 46.8, and 49.18 μg/mL at 48 h, respectively. Under similar conditions, pyrano[3,2-c]pyridones derivatives 15b (LC50 = 28.8 μg/mL) was found at par with LC50 (26.92 μg/mL) of commercial nematicide carbofuran. The in vitro results were further validated with in silico studies with the most active compound 15b nematicidal within the binding to the pocket of acetylcholine esterase (AChE). In docking, binding free energy values for compound 15b were found to be -6.90 kcal/mol. Results indicated that pyrano[3,2-c]pyridone derivatives have the potential to control M. incognita.

Pharmacophore-based virtual screening of commercial databases against β-secretase 1 for drug development against Alzheimer's disease

β-secretase 1, one of the most important proteins, is an aspartate protease. This membrane-associated protein is used for treating Alzheimer's disease (AD). Several inhibitors have been pursued against β-secretase 1, but they still have not resulted effectively. Virtual screening based on pharmacophores has been shown to be useful for lead optimization and hit identification in the preliminary phase of developing a new drug. Here, we screen the commercially available databases to find the hits against β-secretase 1 for drug discovery against AD. Virtual screening for 200,000 compounds was done using the database from the Vitas-M Laboratory. The phase screen score was utilized to assess the screened hits. Molecular docking was performed on compounds with phase scores >1.9. According to the study, the 66H ligand of the crystal structure has the maximum performance against β-secretase 1. The redocking of the co-crystal ligand showed that the docked ligand was seamlessly united with the crystal structure. The reference complex had three hydrogen bonds with Asp93, Asp289, and Gly291; one van der Waals interaction with Gly74; and three hydrophobic interactions. After equilibration, the RMSD of the reference compound sustained a value of ∼1.5 Å until 30 ns and then boosted to 2.5 Å. On comparison, the RMSD of the S1 complex steadily increased to ∼2.5 Å at 15 ns, displayed slight aberrations at approximately ∼2.5-3 Å until 80 ns, and then achieved steadiness toward the end of the simulation. The arrangements of proteins stayed condensed during the mockup when bonded to these complexes as stable Rg values showed. Furthermore, the MM/GBSA technique was employed to analyze both compounds' total binding free energies (ΔGtotal). Our research study provides a new understanding of using 66H as anti-β-secretase 1 for drug development against AD.

Complexation Mechanisms of Aqueous Amylose: Molecular Dynamics Study Using 3-Pentadecylphenol

Molecular dynamics (MD) simulations of linear amylose fragments containing 10 to 40 glucose units were used to study the complexation of the prototypical compound, 3-pentadecylphenol (PDP)─a natural product with surfactant-like properties─in aqueous solution. The amylose-PDP binding leverages mainly hydrophobic interactions together with excluded volume effects. It was found that while the most stable complexes contained PDP inside the helical structure of the amylose in the expected guest-host (inclusion) complexation manner, at higher temperatures, the commonly observed PDP-amylose complexes often involved more nonspecific interactions than inclusion complexation. In the case where a stoichiometric excess of PDP was added to the simulation box, self-aggregation of the small molecule precluded its ability to enter the internal helical part of the oligosaccharide, and as a result, inclusion complexation became ineffective. MD simulation trajectories were analyzed preliminarily using cluster analysis (CA), followed by more rigorous solvent accessible surface area (SASA) determination over the temperature range spanning from 277 to 433 K. It was found that using the SASA of PDP corrected for its intrinsic conformational changes, together with a generic hidden Markov model (HMM), an adequate quantification of the different types of PDP-amylose aggregates was obtained to allow further analysis. The enthalpy change associated with the guest-host binding equilibrium constant (Kgh) in aqueous solution was estimated to be -75 kJ/mol, which is about twice as high as one might expect based on experimentally measured values of similar complexes in the solid state where the (unsolvated) helical structure of amylose remains rigid. On the other hand, the nonspecific binding (Kns) enthalpy change associated with PDP-amylose interactions in the same solution environment was found to be about half of the inclusion complexation value.

Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus gallolyticus

Streptococcus gallolyticus (Sg) is a non-motile, gram-positive bacterium that causes infective endocarditis (inflammation of the heart lining). Because Sg has gained resistance to existing antibiotics and there is currently no drug available, developing effective anti-Sg drugs is critical. This study combined core proteomics with a subtractive proteomics technique to identify potential therapeutic targets for Sg. Several bioinformatics approaches were used to eliminate non-essential and human-specific homologous sequences from the bacterial proteome. Then, virulence, druggability, subcellular localization, and functional analyses were carried out to specify the participation of significant bacterial proteins in various cellular processes. The pathogen's genome contained three druggable proteins, glucosamine-1phosphate N-acetyltransferase (GlmU), RNA polymerase sigma factor (RpoD), and pantetheine-phosphate adenylyltransferase (PPAT) which could serve as effective targets for developing novel drugs. 3D structures of target protein were modeled through Swiss Model. A natural product library containing 10,000 molecules from the LOTUS database was docked against therapeutic target proteins. Following an evaluation of the docking results using the glide gscore, the top 10 compounds docked against each protein receptor were chosen. LTS001632, LTS0243441, and LTS0236112 were the compounds that exhibited the highest binding affinities against GlmU, PPAT, and RpoD, respectively, among the compounds that were chosen. To augment the docking data, molecular dynamics simulations and MM-GBSA binding free energy were also utilized. More in-vitro research is necessary to transform these possible inhibitors into therapeutic drugs, though computer validations were employed in this study. This combination of computational techniques paves the way for targeted antibiotic development, which addresses the critical need for new therapeutic strategies against S. gallolyticus infections.

Pharmacophore modelling based virtual screening and molecular dynamics identified the novel inhibitors and drug targets against Waddlia chondrophila

Waddlia chondrophila is a possible cause of fetal death in humans. This Chlamydia-related bacterium is an emergent pathogen that causes human miscarriages and ruminant abortions, which results in financial losses. Despite the years of efforts, the underlying mechanism behind the pathogenesis of W. chondrophila is little known which hindered the development of novel treatment options. In the framework of current study, computational approaches were used to identify novel inhibitors (phytocompounds) and drug targets against W. chondrophila. At first, RNA polymerase sigma factor SigA and 3-deoxy-D-manno-octulosonic acid transferase were identified through subtractive proteomics pipeline. Afterwards, extensive docking and simulation analyses were conducted to optimize potentially novel phytocompounds by assessing their binding affinity to target proteins. A 100ns molecular dynamics simulation well complimented the compound's binding affinity and indicated strong stability of predicted compounds at the docked site. The calculation of binding free energies with MMGBSA corroborated the significant binding affinity between phytocompounds and target protein binding sites. The proposed phytocompounds may be a viable treatment option for patients infected with W. chondrophila; however, further research is required to ensure their safety.

Structural, computational and in silico studies of 4-bromo-3-flurobenzonitrile as anti-Alzheimer and anti-Parkinson agents

A novel dimer of the 4-bromo-3-fluorobenzonitrile was crystallized and studied using a spectroscopic method such as the scanning electron microscope method. The computational simulations substantiated the structural analysis findings. The Hirshfeld surface analysis has been performed for visualizing, exploring and quantifying the intra and inter-molecular interactions that stabilize the crystal packing of the compound. The NBO and QTAIM analyses were applied to study the nature and origin of the attractive forces involved in the crystal structure. Further, the pharmacokinetic properties of the compound were evaluated, indicating good brain-blood barrier and central nervous system penetration capability. Hence, in silico studies was carried out to explore the binding pattern of the titled compound against acetylcholinesterase and butyrylcholinesterase, and tumor necrosis factor-alpha converting enzyme proteins using molecular docking and molecular dynamics simulations approach. Further, the titled compound is compared with standard drugs through molecular docking studies. The in silico studies finally predicts that the compound under investigation may act as a good inhibitor for treating Alzheimer's disease and further in vitro and in vivo studies may provide its therapeutic potential.Communicated by Ramaswamy H. Sarma.

Proteomics-based vaccine targets annotation and design of multi-epitope vaccine against antibiotic-resistant Streptococcus gallolyticus

Streptococcus gallolyticus is a non-motile, gram-positive bacterium that causes infective endocarditis. S. gallolyticus has developed resistance to existing antibiotics, and no vaccine is currently available. Therefore, it is essential to develop an effective S. gallolyticus vaccine. Core proteomics was used in this study together with subtractive proteomics and reverse vaccinology approach to find antigenic proteins that could be utilized for the design of the S. gallolyticus multi-epitope vaccine. The pipeline identified two antigenic proteins as potential vaccine targets: penicillin-binding protein and the ATP synthase subunit. T and B cell epitopes from the specific proteins were forecasted employing several immunoinformatics and bioinformatics resources. A vaccine (360 amino acids) was created using a combination of seven cytotoxic T cell lymphocyte (CTL), three helper T cell lymphocyte (HTL), and five linear B cell lymphocyte (LBL) epitopes. To increase immune responses, the vaccine was paired with a cholera enterotoxin subunit B (CTB) adjuvant. The developed vaccine was highly antigenic, non-allergenic, and stable for human use. The vaccine's binding affinity and molecular interactions with the human immunological receptor TLR4 were studied using molecular mechanics/generalized Born surface area (MMGBSA), molecular docking, and molecular dynamic (MD) simulation analyses. Escherichia coli (strain K12) plasmid vector pET-28a ( +) was used to examine the ability of the vaccine to be expressed. According to the outcomes of these computer experiments, the vaccine is quite promising in terms of developing a protective immunity against diseases. However, in vitro and animal research are required to validate our findings.

Revolutionizing and identifying novel drug targets in Citrobacter koseri via subtractive proteomics and development of a multi-epitope vaccine using reverse vaccinology and immuno-informatics

Citrobacter koseri is a gram-negative rod that has been linked to infections in people with significant comorbidities and immunocompromised immune systems. It is most commonly known to cause urinary tract infections. Thus, the development of an efficacious C. koseri vaccine is imperative, as the pathogen has acquired resistance to current antibiotics. Subtractive proteomics was employed during this research to identify potential antigenic proteins to design an effective vaccine against C. koseri. The pipeline identified two antigenic proteins as potential vaccine targets: DP-3-O-acyl-N-acetylglucosamine deacetylase and Arabinose 5-phosphate isomerase. B and T cell epitopes from the specific proteins were forecasted employing several immunoinformatic and bioinformatics resources. A vaccine was created using a combination of seven cytotoxic T cell lymphocytes (CTL), five helper T cell lymphocyte (HTL), and seven linear B cell lymphocyte (LBL) epitopes. An adjuvant (β-defensin) was added to the vaccine to enhance immunological responses. The created vaccine was stable for use in humans, highly antigenic, and non-allergenic. The vaccine's molecular and interactions binding affinity with the human immunological receptor TLR3 were studied using MMGBSA, molecular dynamics (MD) simulations, and molecular docking analyses. E. coli (strain-K12) plasmid vector pET-28a (+) was used to examine the ability of the vaccine to be expressed. The vaccine shows great promise in terms of developing protective immunity against diseases, based on the results of these computer experiments. However, in vitro and animal research are required to validate our findings.Communicated by Ramaswamy H. Sarma.

Selective Bias Virtual Screening for Discovery of Promising Antimalarial Candidates targeting Plasmodium N-Myristoyltransferase

Malaria remains a significant public health challenge, with Plasmodium vivax being the species responsible for the most prevalent form of the disease. Given the limited therapeutic options available, the search for new antimalarials against P. vivax is urgent. This study aims to identify new inhibitors for P. vivax N-myristoyltransferase (PvNMT), an essential drug target against malaria. Through a validated virtual screening campaign, we prioritized 23 candidates for further testing. In the yeast NMT system, seven compounds exhibit a potential inhibitor phenotype. In vitro antimalarial phenotypic assays confirmed the activity of four candidates while demonstrating an absence of cytotoxicity. Enzymatic assays reveal LabMol-394 as the most promising inhibitor, displaying selectivity against the parasite and a strong correlation within the yeast system. Furthermore, molecular dynamics simulations shed some light into its binding mode. This study constitutes a substantial contribution to the exploration of a selective quinoline scaffold and provides valuable insights into the development of new antimalarial candidates.

Unveiling therapeutic efficacy of extract and multi-targeting phytocompounds from Christella dentata (Forssk.) Brownsey & Jermy against multidrug-resistant Pseudomonas aeruginosa

Christella dentata (Forssk.) Brownsey & Jermy has been commonly used in traditional medicinal practices but its effects on multi-drug-resistant (MDR) bacteria have remained unexplored. We aimed to assess the in vitro antibacterial potential of the ethanol extract of Christella dentata (EECD) against MDR Pseudomonas aeruginosa and to identify potential multi-targeting antibacterial phytocompounds through computer-aided drug design focusing on the LasR and LpxC proteins. PPS, FT-IR and GC-MS were used for profiling of the phytocompounds in EECD. The antimicrobial activity of EECD was assessed using in vitro agar well diffusion, disc diffusion, MIC and MBC. Computer-aided drug design was used to identify multi-targeting leads from GC-MS-annotated phytocompounds. EECD exhibited dose-dependent antibacterial activity and revealed the presence of 51 phytocompounds in GC-MS analysis. Among these, three phytocompounds; (2E,4E)-N-isobutylhexadeca-2,4-dienamide (CID 6442402), bicyclo[4.3.0]nonane, 2,2,6,7-tetramethyl-7-hydroxy- (CID 536446) and 1,4-diethylbenzene (CID 7734) were identified as promising antibacterial phytocompounds as they strongly bonded with LasR and LpxC. Of them, CID 536446 and CID 7734 exhibited multiple targeting abilities with LasR and LpxC. On further screening, both CID 536446 and CID 7734 exhibited favorable drug-able, pharmacokinetics and toxicity properties. Finally, molecular dynamics (MD) simulation proved the binding stability of bicyclo[4.3.0]nonane, 2,2,6,7-tetramethyl-7-hydroxy- and 1,4-diethylbenzene to active pockets of LasR and LpxC. The results of this study offer scientific validation for the traditional use of Christella dentata in bacterial infection-related diseases. It also suggests that bicyclo[4.3.0]nonane, 2,2,6,7-tetramethyl-7-hydroxy- and 1,4-diethylbenzene from Christella dentata might be responsible for the antibacterial activity and could act as phytopharmacological leads for the development of LasR and LpxC inhibitors against MDR P. aeruginosa.

Association of epilepsy and neurological impairments with homozygous recessive missense mutations found in the genes responsible for ganglioside biosynthesis (ST3GAL5) and calcium voltage-gated channels (CACNA1H) - insights through molecular dynamic simulations

With over 2.2 million cases, the incidence rate of epilepsy in Pakistan is far higher than the rest of the world due primarily to the frequent, traditionally imposed cousin marriages. In the present study, comprehensive whole exome sequencing (WES) analyses of a three-generation family with four affected members presenting 'unexplained' childhood absence epilepsy (CAE), seizures and dementia, was performed in a quest to identify heritable, epilepsy-causal gene variants to better aid in carrier screening and genetic counselling. The WES data was generated, analyzed, and validated through Sanger's sequencing, molecular dynamic simulation (MDS) analysis, and molecular mechanics with generalized Born and surface area solvation (MM/GBSA) studies. Two homozygous recessive, missense mutations in ST3GAL5 (c.311A > G, p. His104Arg) and CACNA1H (c.6230G > A, p. Arg2077His) genes, earlier regarded as benign or of uncertain significance, have been identified as a potential etiology. Comparative MDS and free binding energy calculations revealed substantial structural perturbations in mutant forms of ST3GAL5 leading to decreased binding and reduced catalytic activity of the p.His104Arg and two other functional variants (p.Val74Glu and p.Arg288Ter) when compared with wild type. Our findings reinforce that WES analyses may uncover 'hidden', heritable variants and together with MDS and MM/GBSA may provide plausible clues to answer the unexplained causes of epilepsy for an effective management and better patient outcome. Further, revisit of epilepsy-associated mutational landscape in population context is imperative as the variants with 'benign' tags may turn out to be 'non-benign', when exist in combination with other benign.Communicated by Ramaswamy H. Sarma.

Computer-aided investigation of Traditional Chinese Medicine mechanisms: A case study of San-Ao decoction in asthma treatment

The San-Ao Decoction (SAD) is a well-known Traditional Chinese Medicine (TCM) formula used to alleviate respiratory symptoms, including asthma. However, its precise mechanisms of action have remained largely unknown. In this study, we utilized computer-aided approaches to explore these mechanisms. Firstly, we conducted a comprehensive analysis of the chemical composition of SAD, which allowed us to identify the 28 main ingredients. Then, we employed computer simulations to investigate the potential active ingredients of SAD and the corresponding binding sites of transient receptor potential vanilloid 1 (TRPV1). The simulations revealed that D509 and D647 were the potential binding sites for TRPV1. Notably, molecular dynamics (MD) studies indicated that site D509 may function as an allosteric site of TRPV1. Furthermore, to validate the computer-aided predictions, we performed experimental studies, including in vitro and in vivo assays. The results of these experiments confirmed the predictions made by our computational models, providing further evidence for the mechanisms of action of San-Ao Decoction in asthma treatment. Our findings demonstrated that: i) D509 and D647 of TRPV1 are the key binding sites for the main ingredients of SAD; ii) SAD or its main ingredients significantly reduce the influx of Ca2+ through TRPV1, following the TCM principle of "Jun, Chen, Zuo, Shi"; iii) SAD shows efficiency in comprehensive in vivo validation. In conclusion, our computer-aided investigation of San-Ao Decoction in asthma treatment has provided valuable insights into the therapeutic mechanisms of this TCM formula. The combination of computational analysis and experimental validation has proven effective in enhancing our understanding of TCM and may pave the way for future discoveries in the field.

In-silico guided design, screening, and molecular dynamic simulation studies for the identification of potential SARS-CoV-2 main protease inhibitors for the targeted treatment of COVID-19

COVID-19, the disease responsible for the recent pandemic, is caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The main protease (Mpro) of SARS-CoV-2 is an essential proteolytic enzyme that plays a number of important roles in the replication of the virus in human host cells. Blocking the function of SARS-CoV-2 Mpro offers a promising and targeted, therapeutic option for the treatment of the COVID-19 infection. Such an inhibitory strategy is currently successful in treating COVID-19 under FDA's emergency use authorization, although with limited benefit to the immunocompromised along with an unfortunate number of side effects and drug-drug interactions. Current COVID vaccines protect against severe disease and death but are mostly ineffective toward long COVID which has been seen in 5-36% of patients. SARS-CoV-2 is a rapidly mutating virus and is here to stay endemically. Hence, alternate therapeutics to treat SARS-CoV-2 infections are still needed. Moreover, because of the high degree of conservation of Mpro among different coronaviruses, any newly developed antiviral agents should better prepare us for potential future epidemics or pandemics. In this paper, we first describe the design and computational docking of a library of novel 188 first-generation peptidomimetic protease inhibitors using various electrophilic warheads with aza-peptide epoxides, α-ketoesters, and β-diketones identified as the most effective. Second-generation designs, 192 compounds in total, focused on aza-peptide epoxides with drug-like properties, incorporating dipeptidyl backbones and heterocyclic ring motifs such as proline, indole, and pyrrole groups, yielding 8 hit candidates. These novel and specific inhibitors for SARS-CoV-2 Mpro can ultimately serve as valuable alternate and broad-spectrum antivirals against COVID-19.Communicated by Ramaswamy H. Sarma.

Determination and mechanism of Xiao-Ai Jie-Du decoction against diffuse large B-cell lymphoma: In silico and In vitro studies

ETHNOPHARMACOLOGICAL RELEVANCE

Xiao-Ai Jie-Du decoction (XAJDD) has been used in clinical practice to treat diffuse large B-cell lymphoma (DLBCL); its prescriptions vary based on the pathogenesis of patients.

AIM OF THE STUDY

We aimed to determine the core formula of XAJDD and investigate its mechanism of action against DLBCL.

MATERIALS AND METHODS

Apriori data mining of 187 clinical cases (including 421 Traditional Chinese Medicines, TCMs) was conducted to retrieve the core formula of XAJDD. Comprehensive in silico modeling was used to identify potential active components and corresponding targets. The potential targets of 16 compounds were identified based on network pharmacology using in silico modeling. Thereafter, experimental determination of the active compounds and their mechanism of action in treating DLBCL was performed using different assays (including CCK-8, Annexin V-FITC/PI double-staining, Western blot, and flow cytometry assays).

RESULTS

The core formula of XAJDD included six herbs: Astragalus mongholicus Bunge (Huangqi, family: Fabaceae), Scutellaria barbata D. Don (Banzhilian, family: Lamiaceae), Prunella vulgaris L. (Xiakucao, family: Lamiaceae), Smilax glabra Roxb. (Tufuling, family Smilacaceae) and Fritillaria thunbergii Miq. (Dabei, family: Liliaceae), and Curcuma zanthorrhiza Roxb. (Ezhu, family: Zingiberaceae); Databases including 62 druggable compounds and 38 DLBCL-related structural targets were constructed; ∼0.3 million data points produced by computational modeling based on potential compounds and targets six components from XAJDD, including astibin, folic acid, baicalin, kaempferol, quercetin, and luteolin, significantly inhibited DLBCL cell proliferation, induced apoptosis, and suppressed the expression of key oncogenes.

CONCLUSION

This study provides an integrated strategy for determining the core formula of XAJDD and reveals the molecular mechanisms underlying the treatment of DLBCL, which were consistent with the principle of "monarch (Jun), minister (Chen), adjunctive (Zuo), and guide (Shi)", confirming that XAJDD may serve as a promising natural therapeutic agent against DLBCL.

Development and Comprehensive Benchmark of a High-Quality AMBER-Consistent Small Molecule Force Field with Broad Chemical Space Coverage for Molecular Modeling and Free Energy Calculation

Biomolecular simulations have become an essential tool in contemporary drug discovery, and molecular mechanics force fields (FFs) constitute its cornerstone. Developing a high quality and broad coverage general FF is a significant undertaking that requires substantial expert knowledge and computing resources, which is beyond the scope of general practitioners. Existing FFs originate from only a limited number of groups and organizations, and they either suffer from limited numbers of training sets, lower than desired quality because of oversimplified representations, or are costly for the molecular modeling community to access. To address these issues, in this work, we developed an AMBER-consistent small molecule FF with extensive chemical space coverage, and we provide Open Access parameters for the entire modeling community. To validate our FF, we carried out benchmarks of quantum mechanics (QM)/molecular mechanics conformer comparison and free energy perturbation calculations on several benchmark data sets. Our FF achieves a higher level of performance at reproducing QM energies and geometries than two popular open-source FFs, OpenFF2 and GAFF2. In relative binding free energy calculations for 31 protein-ligand data sets, comprising 1079 pairs of ligands, the new FF achieves an overall root-mean-square error of 1.19 kcal/mol for ΔΔG and 0.92 kcal/mol for ΔG on a subset of 463 ligands without bespoke fitting to the data sets. The results are on par with those of the leading commercial series of OPLS FFs.

Integrated Network Pharmacology Approach to Evaluate Bioactive Phytochemicals of Acalypha indica and Their Mechanistic Actions to Suppress Target Genes of Tuberculosis

Mycobacterium tuberculosis is responsible for tuberculosis (TB) all over the world. Despite tremendous advancements in biomedical research, new treatment approaches, and preventive measures, TB incidence rates continue to ascend. The herbaceous plant Acalypha indica, also known as Indian Nettle, belongs to the Euphorbiaceae family and is known as one of the most important sources of medicines and pharmaceuticals for the medical therapy for a range of ailments. However, the precise molecular mechanism of its therapeutic action is still unknown. In this study, an integrated network pharmacology approach was employed to explore the potential mechanism of A. indica phytochemicals against TB. The active chemical components of A. indica were collected from two independent databases and published sources, whereas SwissTargetPrediction was used to identify the target genes of these phytochemicals. GeneCards and DisGeNET databases were employed to retrieve tuberculosis-related genes and variants. Following the evaluation of overlapped genes, gene enrichment analysis and PPI network analysis were performed using the DAVID and STRING databases, respectively. Later, to identify the potential target(s) for the disease, molecular docking was performed. A. indica revealed 9 active components with 259 potential therapeutic targets; TB attributed 694 intersecting genes from the two data sets; and both TB and A. indica overlapped 44 potential targets. The in-depth analysis based on the degree revealed that AKT1 and EGFR formed the foundation of the PPI network. Moreover, docking analysis followed by molecular dynamics simulations revealed that phytosterol and stigmasterol have higher binding affinities to AKT1 and EGFR to suppress tuberculosis. This study provides a convincing proof that A. indica can be exploited to target TB after experimental endorsement; further, it lays the framework for more experimental research on A. indica's anti-TB activity.

Alchemical Free Energy Workflows for the Computation of Protein-Ligand Binding Affinities

Alchemical free energy methods can be used for the efficient computation of relative binding free energies during preclinical drug discovery stages. In recent years, this has been facilitated further by the implementation of workflows that enable non-experts to quickly and consistently set up the required simulations. Given the correct input structures, workflows handle the difficult aspects of setting up perturbations, including consistently defining the perturbable molecule, its atom mapping and topology generation, perturbation network generation, running of the simulations via different sampling methods, and analysis of the results. Different academic and commercial workflows are discussed, including FEW, FESetup, FEPrepare, CHARMM-GUI, Transformato, PMX, QLigFEP, TIES, ProFESSA, PyAutoFEP, BioSimSpace, FEP+, Flare, and Orion. These workflows differ in various aspects, such as mapping algorithms or enhanced sampling methods. Some workflows can accommodate more than one molecular dynamics (MD) engine and use external libraries for tasks. Differences between workflows can present advantages for different use cases, however a lack of interoperability of the workflows' components hinders systematic comparisons.

QSAR modelling, molecular docking, molecular dynamic and ADMET prediction of pyrrolopyrimidine derivatives as novel Bruton's tyrosine kinase (BTK) inhibitors

In recent years, there has been a focus on developing and discovering novel Bruton's tyrosine kinase (BTK) inhibitors, as they offer an effective treatment strategy for B-cell malignancies. BTK plays a crucial role in B cell receptor (BCR)-mediated activation and proliferation by regulating downstream factors such as the NF-κB and MAP kinase pathways. To address this challenge and propose potential therapeutic options for B-cell lymphomas, researchers conducted 2D-QSAR and ADMET studies on pyrrolopyrimidine derivatives that act as inhibitors of the BCR site in cytochrome b. These studies aim to improve and identify new compounds that could serve as more potent potential BTK inhibitors, which would lead to the identification of new drug candidates in this field. In our study, we used 2D-QSAR (multiple linear regression, multiple nonlinear regression, and artificial neural networks), molecular docking, molecular dynamics, and ADMET properties to investigate the potential of 35 pyrrolopyrimidine derivatives as BTK inhibitors. A molecular docking study and molecular dynamics simulations of molecule 13 over 10 ns revealed that it establishes multiple hydrogen bonds with several residues and exhibits frequent stability throughout the simulation period. Based on the results obtained by molecular modeling, we proposed six new compounds (Pred1, Pred2, Pred3, Pred4, Pred5, and Pred6) with highly significant predicted activity by MLR models. A study based on the in silico evaluation of the predicted ADMET properties of the new candidate molecules is strongly recommended to classify these molecules as promising candidates for new anticancer agents specifically designed to target Bruton's tyrosine kinase (BTK) inhibition.

Structure-based virtual screening and molecular docking approaches to identify potential inhibitors against KIF2C to combat glioma

Glioma, a kind of malignant brain tumor, is extremely lethal. Kinesin family member 2C (KIF2C) was found to have an aberrant expression in several cancer types, including lung cancer and glioma. KIF2C may therefore be a useful therapeutic target for the treatment of glioma. In the current study, new drug candidates that may function as KIF2C enzyme inhibitors were discovered. MTi OpenScreen was used to carry out the structure-based virtual screening of an inbuilt drug library containing 150,000 compounds. These compounds belong to different classes, such as natural product-based compounds (NP-lib), purchasable approved drugs (Drugs-lib), and food constituents compound collection (FOOD-lib). Based on their binding affinities, a total of 84 compounds were further pushed to calculate ADMET properties. The compounds (16) meeting the ADMET cutoff ranges were then further docked to the receptor to find their plausible binding modes using the Glide tool's standard precision (SP) technique. The docking results were examined using the Glide gscore, and the best binding compounds (Rimacalib and Sarizotan) were chosen to test their stability with KIF2C protein through molecular dynamics (MD) simulation. Similarly, Principal Component Analysis and cross-correlation matrix were also examined. The MM/GBSA binding free energies showed a considerable energy contribution in the binding of hits with the KIF2C. Collectively, these findings strongly suggest the potential of the lead compounds to inhibit the biological function of KIF2C, emphasizing the need for further investigation in this area.Communicated by Ramaswamy H. Sarma.

Identification of novel pyrazole containing ɑ-glucosidase inhibitors: insight into pharmacophore, 3D-QSAR, virtual screening, and molecular dynamics study

Pharmacophore modelling, 3 D QSAR modelling, virtual screening, and molecular dynamics study, all-in-one combination were employed successfully design and develop an alpha-glucosidase inhibitor. To explain the structural prerequisites of biologically active components, 3 D-QSAR models were generated using the selected best hypothesis (AARRR) for compounds 55 included in the model C. The selection of 3 D-QSAR models showed that the Gaussian steric characteristic is crucial to alpha glucosidase's inhibitory potential. The alpha-glucosidase inhibitory potency of the compound is enhanced by other components, including Gaussian hydrophobic groups, Gaussian hydrogen bond acceptor or donor groups, Gaussian electrostatic characteristics, and a Gaussian steric feature. An identification of structure-activity relationships can be obtained from the developed 3 D-QSAR, C model, with R2 = 0.77 and SD = 0.02 for training set, and Q2 = 0.66, RMSE 0.02, and Pearson R = 0.81 for testing set, corresponding to elevated predictive ability. Additionally, docking and MM/GBSA experiments on 1146023 showed that it interacts with critical amino acids in the binding site when coupled with acarbose. Further, five compounds that display a high affinity for alpha-glucosidase were found, and these compounds may serve as potent leads for alpha-glucosidase inhibitor development. Biological activity will be tested for these compounds in the future.Communicated by Ramaswamy H. Sarma.

Drug Aggregation of Sparingly-Soluble Ionizable Drugs: Molecular Dynamics Simulations of Papaverine and Prostaglandin F2α

Aggregation in aqueous solution can have important implications on both the in vivo exposure of a drug and its pharmaceutical manufacturability. However, the drug aggregates formed can be very small and, thus, difficult to interrogate experimentally. On the other hand, at higher supersaturations where larger aggregates are supported, the chemical system is inherently metastable and therefore likewise challenging to study from an experimental standpoint. Understanding aggregation behavior is further complicated in the case of ionizable drugs where, unlike neutral compounds, there can be uncertainty in the kinds of drug molecules (i.e., charged, neutral, or both) that become incorporated into various clusters, particularly at pH values near the pKa. In this paper, we apply physics-based all-atom molecular dynamics (MD) simulations to study aggregation in the weakly basic drug papaverine and in the weakly acidic drug prostaglandin F2α. We employ in silico tools to construct simulation workflows and comprehensive cluster analysis protocols to elucidate the size distributions and dynamics of the drug aggregates formed at both an experimentally relevant concentration and at high supersaturation. We build on a previously published treatment [Solubility of sparingly soluble ionizable drugs. Adv. Drug Deliv. Rev. 2007, 59, 568-590, DOI: 10.1016/j.addr.2007.05.008] to translate the predicted aggregate distributions of each ionized drug into corresponding pH-solubility curves that can be compared directly to experiment. Our findings show that the assumption of a single predominant (charged) aggregate can be misleading in interpreting experimental pH-solubility curves, as it does not adequately reflect the rich diversity revealed in our simulations. Beyond not accounting for the distribution of ionized drug-containing clusters actually observed in solution, for both drugs we find evidence that neutral drug molecules can also participate in the aggregation phenomena. Notably, we observe that many drug molecules remain as free monomers in solution even under simulated conditions designed to mimic those where there is significant deviation of the experimental pH-solubility curve from the Henderson-Hasselbalch (H-H) equation, often taken to be a clear signpost of drug aggregation.

In silico identification of deep-sea fungal alkaloids as potential inhibitors of SARS-CoV-2, Delta and Omicron spikes

Aim: Virtual screening of deep-sea fungal metabolites against SARS-CoV-2 Delta and Omicron spikes as potential antivirals. Materials & methods: Deep-sea fungal alkaloids (n ≥ 150) were evaluated against SARS-CoV-2, Delta and Omicron spikes, using various in silico approaches, including Admet scores, physiochemical properties, molecular docking (MD) and MD simulation (150 ns). Results: The test alkaloids complied with Admet scores and physiochemical properties within acceptable ranges, and followed Lipinski's rule of five. Of these, Cladosporium sphaerospermum-derived cladosin K (tetramate alkaloid) for SARS-CoV-2, Cystobasidium laryngis-derived saphenol (phenazine alkaloid) for Delta and Chaetomium globosum-derived chaetoglobosin E (quinoline alkaloid) for Omicron were identified as potential spike-inhibitors. Conclusion: Our data therefore, strongly warrants further experimental validations of cladosin K, saphenol and chaetoglobosin E, especially against the Omicron and Delta spikes.

Terpenoid phytocompounds from mangrove plant Xylocarpus moluccensis as possible inhibitors against SARS-CoV-2: In silico strategy

COVID-19 shook the world during the pandemic, where the climax it reached was vaccine manufacturing at an unfathomable pace. Alternative promising solutions to prevent infection from SARS-CoV-2 and its variants will remain crucial in the years to come. Due to its key role in viral replication, the major protease (Mpro) enzyme of SARS-CoV-2 can be an attractive therapeutic target. In the present work, natural terpenoids from mangrove medicinal plant Xylocarpus moluccensis (Lam.) M. Roem. were screened using computational methods for inhibition of Mpro protein. Out of sixty-seven terpenoids, Angolensic acid methyl ester, Moluccensin V, Thaixylomolin F, Godavarin J, and Xylomexicanolide A were shortlisted based on their docking scores and interaction affinities (- 13.502 to - 15.52 kcal/mol). The efficacy was validated by the 100 ns molecular dynamics study. Lead terpenoids were within the acceptable range of RMSD and RMSF with a mean value of 2.5 Å and 1.5 Å, respectively indicating that they bound tightly within Mpro and there was minimal fluctuation and stability of Mpro upon binding of these terpenoids. The utmost favorable binding strengths as calculated by MM-GBSA, were of Angolensic acid methyl ester and Moluccensin V with binding free energies (ΔGbind) of - 39.084, and - 43.160 kcal/mol, respectively. The terpenoids showed no violations in terms of Drug Likeliness and ADMET predictions. Overall, the findings indicate that Angolensic acid methyl ester and Moluccensin V are effective terpenoids having strong binding interaction with Mpro protein, which must be tested in vitro as an effective anti-SARS-CoV-2 drug.

On the Path to Optimal Alchemistry

Alchemical free energy calculations have become a standard and widely used tool, in particular for calculating and comparing binding affinities of drugs. Although methods to compute such free energies have improved significantly over the last decades, the choice of path between the end states of interest is usually still the same as two decades ago. We will show that there is a fundamentally arbitrary, implicit choice of parametrization of this path. To address this, the notion of the length of a path or a metric is required. A metric recently introduced in the context of the accelerated weight histogram method also proves to be very useful here. We demonstrate that this metric can not only improve the efficiency of sampling along a given path, but that it can also be used to improve the actual choice of path. For a set of relevant use cases, the combination of these improvements can increase the efficiency of alchemical free energy calculations by up to a factor 16.

Natural defense against multi-drug resistant Pseudomonas aeruginosa: Cassia occidentalis L. in vitro and in silico antibacterial activity

Cassia occidentalis L. is widely used in indigenous and traditional medicine, but its impact on multi-drug resistant (MDR) bacterial infections mostly remains unknown. Therefore, this study aimed to evaluate the in vitro antibacterial efficiency of methanol and ethyl acetate extracts of C. occidentalis L. leaves (MECOL and EAECOL) against multi-drug resistant Pseudomonas aeruginosa and to identify potential antibacterial agents through computational studies targeting the LasR protein. Initially, 82 compounds were identified using GC-MS analysis, and the functional groups were determined through FT-IR analysis. Both extracts of the plant exhibited dose-dependent antibacterial activity, with MICs of 104.16 ± 36.08 μg mL-1 for MECOL and 83.33 ± 36.08 μg mL-1 for EAECOL, and an MBC of 125 μg mL-1. Among the 82 compounds, 12 potential compounds were identified based on binding scores using molecular docking with the LasR protein and MM-GBSA analysis. Furthermore, screening for ADME properties, including physicochemical features, water solubility, lipophilicity, RO5 compliance, and toxicity, identified the top three compounds: methyl dihydrojasmonate, methyl benzoate, and 4a-methyl-4,4a,5,6,7,8-hexahydro-2(3H)-naphthalenone, which also demonstrated binding affinity with the active site residues of the LpxC protein of the bacteria. Additionally, molecular dynamics (MD) simulations confirmed the binding reliability of these three phytochemicals to LasR's active pocket, comparable to the protein native inhibitory ligands (C12-HSL). The study offers scientific support for the traditional use of C. occidentalis in treating bacterial infections, highlighting the potential of the three compounds as leads for developing LasR inhibitors to combat multi-drug resistant P. aeruginosa.

Computer-aided identification of dengue virus NS2B/NS3 protease inhibitors: an integrated molecular modelling approach for screening of phytochemicals

Globally, dengue (DENV) fever has appeared as the most widespread vector-borne disease, affecting more than 100 million individuals annually. No approved anti-DENV therapy or preventive vaccine is available yet. DENV NS3 protein is associated with protease activity and is essential for viral replication process within the host cell. NS2B is linked with NS3 protein as a cofactor. Hence, NS3/NS2B is a potential druggable target for developing inhibitors against dengue virus. In the present study, a dataset of Beta vulgaris L.-based natural compounds was developed. Virtual ligand screening of 30 phytochemicals was carried out to find novel inhibitors against the NS2B/NS3 protein. Spatial affinity, drug-likeness, and binding behaviors of selected phytochemicals were analyzed. Post-simulation analysis, including Principal Component Analysis (PCA), MMGBSA, and Co-relation analysis, was also performed to provide deep insight for elucidating protein-ligand complexes. This computer-aided screening scrutinized four potent phytochemicals, including betavulgaroside II, vitexin xyloside, epicatechin, and isovitexin2-O-xyloside inhibitors exhibiting optimal binding with viral NS3/NS2B protein. Our study brings novel scaffolds against DENV NS2B/NS3 of serotype-2 to act as lead molecules for further biological optimization. In future, this study will prompt the exploration and development of adjuvant anti-DENV therapy based on natural compounds.Communicated by Ramaswamy H. Sarma.

Design and Preclinical Characterization Program toward Asundexian (BAY 2433334), an Oral Factor XIa Inhibitor for the Prevention and Treatment of Thromboembolic Disorders

Activated coagulation factor XI (FXIa) is a highly attractive antithrombotic target as it contributes to the development and progression of thrombosis but is thought to play only a minor role in hemostasis so that its inhibition may allow for decoupling of antithrombotic efficacy and bleeding time prolongation. Herein, we report our major efforts to identify an orally bioavailable, reversible FXIa inhibitor. Using a protein structure-based de novo design approach, we identified a novel micromolar hit with attractive physicochemical properties. During lead modification, a critical problem was balancing potency and absorption by focusing on the most important interactions of the lead series with FXIa while simultaneously seeking to improve metabolic stability and the cytochrome P450 interaction profile. In clinical trials, the resulting compound from our extensive research program, asundexian (BAY 2433334), proved to possess the desired DMPK properties for once-daily oral dosing, and even more importantly, the initial pharmacological hypothesis was confirmed.

Identification of novel scaffolds targeting SIRT3 through molecular modeling techniques for the treatment of Hepatocellular carcinoma

Hepatocellular carcinoma is one of the top causes of cancer-related death globally. SIRT3 belongs to the Sirtuin family of proteins, a collection of NAD+-dependent enzymes that play a role in controlling several cellular functions, including metabolism, aging, and stress response. SIRT3 expression has been discovered to be often downregulated in HCC tissues relative to normal liver tissues. Hence, SIRT3 may function as a tumor suppressor in HCC. In the present study, pharmacophore-based virtual screening of a small molecule database was performed initially, and then the screened hits were docked to the active site of SIRT3 to choose the best binding modes. One co-crystal ligand (PDB name: 1NQ) was utilized as a template to generate pharmacophore model query. A total of 0.2 million compounds from the VITAS-M Lab database were downloaded and prepared for virtual screening. Following database preparation, ligand-based virtual screening was performed using the pharmacophore query model generated in the previous phase. The compounds with the same pharmacophoric characteristics as the query at the same distance were screened. There were a total of 74 hits that matched the query model. These compounds were then docked to the SIRT3 using the standard precision protocol of the glide tool. To select hits with high binding affinities, a threshold of -8 kcal/mol was used. Based on the glide gscore, two hits were chosen. These two hits were selected to investigate the stability of the protein-ligand complex by molecular dynamics simulation. All of these findings indicate that the selected hit compounds C1 and C2 can serve as lead compounds in inhibiting the biological activity of SIRT3 requiring further detailed investigations.Communicated by Ramaswamy H. Sarma.

Calculations of Absolute Solvation Free Energies with Transformato─Application to the FreeSolv Database Using the CGenFF Force Field

We recently introduced transformato, an open-source Python package for the automated setup of large-scale calculations of relative solvation and binding free energy differences. Here, we extend the capabilities of transformato to the calculation of absolute solvation free energy differences. After careful validation against the literature results and reference calculations with the PERT module of CHARMM, we used transformato to compute absolute solvation free energies for most molecules in the FreeSolv database (621 out of 642). The force field parameters were obtained with the program cgenff (v2.5.1), which derives missing parameters from the CHARMM general force field (CGenFF v4.6). A long-range correction for the Lennard-Jones interactions was added to all computed solvation free energies. The mean absolute error compared to the experimental data is 1.12 kcal/mol. Our results allow a detailed comparison between the AMBER and CHARMM general force fields and provide a more in-depth understanding of the capabilities and limitations of the CGenFF small molecule parameters.

Pharmacophore-based virtual screening, molecular docking, and molecular dynamics studies for the discovery of novel FLT3 inhibitors

FLT3 is considered a potential target of acute myeloid leukemia therapy. In this study, we applied a computer-aided methodology unifying molecular docking and pharmacophore screening to identify potent inhibitors against FLT3. To investigate the pharmacophore area and binding mechanism of FLT3, the reported co-crystallized Gilteritinib ligand was docked into the active site using Glide XP. Based on the docking results, we identified structure-based pharmacophore characteristics resistant to potent FLT3 inhibitors. The best hypothesis was corroborated using test and decoy sets, and the verified hypo was utilized to screen the chemical database. The hits from the pharmacophore-based screening were then screened again using a structure-based method that included molecular docking at various precisions; the selected molecules were further examined and refined using drug-like filters and ADMET analysis. Finally, two hits were picked out for molecular dynamic simulation. The results showed two hits were expected to have potent inhibitory activity and excellent ADMET characteristics, and they might be used as new leads in the development of FLT3 inhibitors.Communicated by Ramaswamy H. Sarma.

Electro-organic synthesis of C-5 sulfenylated amino uracils: Optimization and exploring topoisomerase-I based anti-cancer profile

Cancer is spreading worldwide and is one of the leading causes of death. The use of existing chemotherapeutic agents is frequently limited due to side effects. As a result, it is critical to investigate new agents for cancer treatment. In this context, we developed an electrochemical method for the synthesis of a series of thiol-linked pyrimidine derivatives (3a-3p) and explored their anti-cancer potential. The biological profile of the synthesized compounds was evaluated against breast (MDAMB-231 and MCF-7) and colorectal (HCT-116) cancer cell lines. 3b and 3d emerged to be the most potent agents, with IC50 values ranging between 0.98 to 2.45 µM. Target delineation studies followed by secondary anticancer parameters were evaluated for most potent compounds, 3b and 3d. The analysis revealed compounds possess DNA intercalation potential and selective inhibition towards human topoisomerase (hTopo1). The analysis was further corroborated by DNA binding studies and in silico-based molecular modeling studies that validated the intercalating binding mode between the compounds and the DNA.

Acetylsalicylic acid-sulfa drugs conjugates as potential urease inhibitors and anti-inflammatory agents: bio-oriented drug synthesis, molecular docking, and dynamics simulation studies

To explore the new mode of action and reduce side effects, making conjugates of existing drugs is becoming an attractive tool in the realm of medicinal chemistry. In this work, we exploited this approach and synthesized new conjugates to assess their activities against the enzymes involved in different pathological conditions. Specifically, we design and synthesized conjugates involving acetylsalicylic acid and sulfa drugs, validating the newly crafted conjugates using techniques like IR, 1HNMR, 13CNMR, and elemental analysis. These conjugates underwent assessment for their ability to inhibit cyclooxygenase-2 (COX-2), urease enzymes, and their anti-inflammatory potential. A competitive mode of urease inhibition was observed for acetylsalicylic acid conjugated with sulfanilamide, sulfacetamide, and sulfadiazine with IC50 of 2.49 ± 0.35 µM, 6.21 ± 0.28 µM, and 6.57 ± 0.44 µM, respectively. Remarkably, the acetylsalicylic acid-sulfamethoxazole conjugate exhibited exceptional anti-inflammatory activity, effectively curtailing induced edema by 83.7%, a result akin to the reference anti-inflammatory drug indomethacin's performance (86.8%). Additionally, it demonstrated comparable COX-2 inhibition (75.8%) to the reference selective COX-2 inhibitor celecoxib that exhibited 77.1% inhibition at 10 µM concentration. To deepen our understanding, we employed molecular docking techniques to predict the binding interactions of competitive inhibitors with COX-2 and urease receptors. Additionally, MD simulations were carried out, confirming the stability of inhibitor-target complexes throughout the simulation period, devoid of significant conformational changes. Collectively, our research underscores the potential of coupling approved medicinal compounds to usher in novel categories of pharmacological agents, holding promise for addressing a wide spectrum of pathological disorders involving COX-2 and urease enzymes.Communicated by Ramaswamy H. Sarma.

Self-Consistent Implementation of a Solvation Free Energy Framework to Predict the Salt Solubilities of Six Alkali Halides

To assess the salt solubilities of six alkali halides in aqueous systems, we proposed a thermodynamic cycle and an efficient molecular modeling methodology. The Gibbs free energy changes for vaporization, dissociation, and dissolution were calculated using the experimental data of ionic thermodynamic properties obtained from the NBS tables. Additionally, the Marcus' and Tissandier's solvation free energy data for Li+, Na+, K+, Cl-, and Br- ions were compared with the conventional solvation free energies by substituting into our self-consistent thermodynamic cycle. Furthermore, Tissandier's absolute solvation free energy data were used as the training set to refit the Lennard-Jones parameters of OPLS-AA force field for ions. To predict salt solubilities, an assumption of a pseudo-solvent was proposed to characterize the coupling work of a solute with its environment from infinitely diluted to saturated solutions, indicating that the Gibbs energy change of solvation process is a function of ionic strength. Following the self-consistency of the cycle, the newly derived formulas were used to determine the salt solubilities by interpolating the intersection of Gibbs free energy of dissolution and the zero free energy line. The refined ion parameters can also predict the structure and thermodynamic properties of aqueous electrolyte solutions, such as densities, pair correlation functions, hydration numbers, mean activity coefficients, vapor pressures, and the radial dependences of the net charge at 298.15 K and 1 bar. Our method can be used to characterize the solid-liquid equilibria of ions or charged particles in aqueous systems. Furthermore, for highly concentrated strong electrolyte systems, it is essential to introduce accurate water models and polarizable force fields.

Bioassay-guided isolation and in silico study of antihyperlipidemic compounds from Onosma hispidum Wall

Isolation of bioactive compounds from plants and their therapeutic evaluation is crucial in the pursuit of novel phytochemicals and contributes an indispensable role in drug discovery and design. The literature has documented the hypolipidemic effect of numerous Onosma species. Taking that into consideration, the current study was designed to isolate, purify and evaluate the antihyperlipidemic potential of leaves of Onosma hispidum Wall. For the first time, the bioassay-guided isolation led to the separation of 3 compounds that were identified by spectroscopic techniques as o-phthalic acid bis-(2-ethyl decyl)-ester (1), bis (2-ethyloctyl) phthalate (2), and 1,2 benzenedicarboxylic acid bis(2-methyl heptyl) ester (3). Lipase inhibition assay was utilized to scrutinize the antihyperlipidemic potential of methanolic extract fractions and subsequently isolated compounds. Further, the isolated compounds were employed for in silico studies via molecular docking, molecular mechanics with generalized born and surface area solvation (MM-GBSA), and MD simulations with Pancreatic Lipase Colipase (PDB ID: 1LPB). Molecular docking and MM-GBSA of isolated compounds were employed to explain the mode of binding between the protein-ligand complex and binding free energy calculation, respectively. Since compound (3) displayed the best docking score of -6.689 kcal/mol as compared to orlistat -5.529 kcal/mol with PDB: 1LPB. So, it was chosen for MD simulations to evaluate ligand stability and flexibility of the complex which was validated by the fluctuation of α-carbon chain, root mean square deviation (RMSD), root mean square fluctuation (RMSF), and type of interactions involved which authenticated the in vitro lipase inhibitory potential. Overall, in silico and in vitro results validated that compound (3) could be exploited as a promising pancreatic lipase inhibitor.Communicated by Ramaswamy H. Sarma.

Exploring the potential of propanamide-sulfonamide based drug conjugates as dual inhibitors of urease and cyclooxygenase-2: biological and their in silico studies

Derivative synthesis has been a crucial method for altering the effects of already-approved medications, especially to lessen adverse effects and enhance results. Making use of this multi-target approach, a series of naproxen-sulfa drug conjugates was designed and synthesized. The newly designed conjugates were confirmed by spectroscopic techniques like IR, 1HNMR, 13CNMR, and elemental analysis. The conjugates were screened for anti-inflammatory, urease, and cyclooxygenase-2 (COX-2) inhibition. Naproxen conjugated with sulfanilamide, sulfathiazole, and sulfaguanidine was found potent and showed a competitive mode of urease inhibition, with IC50 (µM) values 6.69 ± 0.11, 5.82 ± 0.28, 5.06 ± 0.29, respectively. When compared to other screened conjugates, the naproxen-sulfamethoxazole conjugation showed better anti-inflammatory action by inhibiting induced edema by 82.8%, which is comparable to the medication indomethacin (86.8% inhibition). Whereas it exhibited 75.4% inhibition of COX-2 at 10 µM concentration which is comparable with the reference drug (celecoxib, 77.1% inhibition). Moreover, the binding modes of competitive inhibitors with the urease and COX-2 receptor were predicted through molecular docking studies and their stability analysis through MD simulations showed that these compounds made stable complexes with the respective targets and there were no conformational changes that occurred during simulation. The obtained results showed that the conjugates of approved therapeutic molecules may lead to the development of novel types of pharmacological agents in the treatment of several pathological disorders where urease and COX-2 enzymes are involved.

Hit identification of novel small molecules interfering with MALAT1 triplex by a structure-based virtual screening

Nowadays, RNA is an attractive target for the design of new small molecules with different pharmacological activities. Among several RNA molecules, long noncoding RNAs (lncRNAs) are extensively reported to be involved in cancer pathogenesis. In particular, the overexpression of lncRNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) plays an important role in the development of multiple myeloma (MM). Starting from the crystallographic structure of the triple-helical stability element at the 3'-end of MALAT1, we performed a structure-based virtual screening of a large commercial database, previously filtered according to the drug-like properties. After a thermodynamic analysis, we selected five compounds for the in vitro assays. Compound M5, characterized by a diazaindene scaffold, emerged as the most promising molecule enabling the destabilization of the MALAT1 triplex structure and antiproliferative activity on in vitro models of MM. M5 is proposed as a lead compound to be further optimized for improving its affinity toward MALAT1.

New Acetamide-Sulfonamide-Containing Scaffolds: Antiurease Activity Screening, Structure-Activity Relationship, Kinetics Mechanism, Molecular Docking, and MD Simulation Studies

The development of novel scaffolds that can increase the effectiveness, safety, and convenience of medication therapy using drug conjugates is a promising strategy. As a result, drug conjugates are an active area of research and development in medicinal chemistry. This research demonstrates acetamide-sulfonamide scaffold preparation after conjugation of ibuprofen and flurbiprofen with sulfa drugs, and these scaffolds were then screened for urease inhibition. The newly designed conjugates were confirmed by spectroscopic techniques such as IR, 1HNMR, 13CNMR, and elemental analysis. Ibuprofen conjugated with sulfathiazole, flurbiprofen conjugated with sulfadiazine, and sulfamethoxazole were found to be potent and demonstrated a competitive mode of urease inhibition, with IC50 (µM) values of 9.95 ± 0.14, 16.74 ± 0.23, and 13.39 ± 0.11, respectively, and urease inhibition of 90.6, 84.1, and 86.1% respectively. Ibuprofen conjugated with sulfanilamide, sulfamerazine, and sulfacetamide, whereas flurbiprofen conjugated with sulfamerazine, and sulfacetamide exhibited a mixed mode of urease inhibition. Moreover, through molecular docking experiments, the urease receptor-binding mechanisms of competitive inhibitors were anticipated, and stability analysis through MD simulations showed that these compounds made stable complexes with the respective targets and that no conformational changes occurred during the simulation. The findings demonstrate that conjugates of approved therapeutic molecules may result in the development of novel classes of pharmacological agents for the treatment of various pathological conditions involving the urease enzyme.

A Computational Physics-based Approach to Predict Unbound Brain-to-Plasma Partition Coefficient, Kp,uu

The blood-brain barrier (BBB) plays a critical role in preventing harmful endogenous and exogenous substances from penetrating the brain. Optimal brain penetration of small-molecule central nervous system (CNS) drugs is characterized by a high unbound brain/plasma ratio (K_p,uu). While various medicinal chemistry strategies and in silico models have been reported to improve BBB penetration, they have limited application in predicting K_p,uu directly. We describe a physics-based computational approach, a quantum mechanics (QM)-based energy of solvation (E-sol), to predict K_p,uu. Prospective application of this method in internal CNS drug discovery programs highlights the utility and accuracy of this new method, which showed a categorical accuracy of 79% and an R² of 0.61 from a linear regression model.

Uncovering Novel Capsaicin Inhibitory Activity towards Human Carbonic Anhydrase Isoforms IX and XII by Combining In Silico and In Vitro Studies

Hot pepper (Capsicum annuum) represents one of the most widespread functional foods of the Mediterranean diet, and is associated with a reduced risk of developing cardiovascular disease, cancer, and mental disorders. In particular, its bioactive spicy molecules, named Capsaicinoids, exhibit polypharmacological properties. Among them, Capsaicin (trans-8-methyl-N-vanillyl-6-nonenamide) is the most studied and reported in variegated scientific contributions for its beneficial effects, often linked to mechanisms of action unrelated to the activation of Transient Receptor Potential Vanilloid 1 (TRPV1). In this study, we present the application of in silico methods to Capsaicin for evaluating its inhibitory activity against the tumor-associated human (h) expressed CA IX and XII. In vitro assays confirmed Capsaicin inhibitory activity towards the most relevant tumor-related hCA isoforms. In particular, the hCAs IX and XII showed an experimental K_I value of 0.28 μM and 0.064 μM, respectively. Then, an A549 model of non-small cell lung cancer, typically characterized by an elevated expression of hCA IX and XII, was employed to test the inhibitory effects of Capsaicin in vitro under both normoxic and hypoxic conditions. Finally, the migration assay revealed that Capsaicin [10 µM] inhibits cells from moving in the A549 cells model.

Structure-based virtual identification of natural inhibitors of SARS-CoV-2 and its Delta and Omicron variant proteins

Aim

Structure-based identification of natural compounds against SARS-CoV-2, Delta and Omicron target proteins.

Materials & methods

Several known antiviral natural compounds were subjected to molecular docking and MD simulation against SARS-CoV-2 Mpro, Helicase and Spike, including Delta and Omicron Spikes.

Results

Of the docked ligands, 20 selected for each complex exhibited overall good binding affinities (-7.79 to -5.06 kcal/mol) with acceptable physiochemistry following Lipinski's rule. Finally, two best ligands from each complex upon simulation showed structural stability and compactness.

Conclusion

Quercetin-3-acetyl-glucoside, Rutin, Kaempferol, Catechin, Orientin, Obetrioside and Neridienone A were identified as potential inhibitors of SARS-CoV-2 Mpro, Helicase and Spike, while Orientin and Obetrioside also showed good binding affinities with Omicron Spike. Catechin and Neridienone A formed stable complexes with Delta Spike.

Investigation of antioxidant and antibacterial effects of citrus fruits peels extracts using different extracting agents: Phytochemical analysis with in silico studies

The peels extracted from various citrus species are major source of phenols, flavonoids and anti-microbial agents. The purpose of this study was a detailed investigation of the phytochemical and pharmacological character of the ethanolic (80%), methanolic and acetone extracts of the peel of local variants of orange (lemon, grape fruit, mousami, fruiter, and shikri malta). The extracts were studied to find out the total phenolic contents (TPC), and total flavonoids (TF) present. The antioxidant activities were assessed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging effect, and the reducing power was determined through free radical scavenging activity (FRAP) assays. The sensitivity of four bacterial strains to peels extracts was examined by applying the diffusion disc on agar medium method. It was found that ethanol was the best extracting agent for TPC and TF in fruit peels under study. The highest TPC (21.33 ± 0.06 mg GAE/g) was quantified in orange peels, whereas fruiter contained the lowest TPC (20.40 ± 0.03 mg GAE/g) in ethanolic extract. The highest amount of TF (2.02 ± 0.08 mg QE/g) was quantified in lemon peels, whereas shikri malta contained lowest quantity of TF (1.04 ± 0.02 mg QE/g). The highest free radical scavenging activity (93.1%) of DPPH was exhibited by lemon peels, whereas the least activity (78.6%) was shown by mousami peels. Ethanolic extract of orange peels demonstrated more reducing power while showing an absorption of 1.98, followed by methanolic (1.11) and acetone (0.81) extracts. The inhibition effect of methanolic extract of lemon peels (inhibition zone = 18 mm) against B. subtilis was considerable and comparable to that of ciprofloxacin. Gas chromatography/mass spectrometry (GC/MS) was used to detect the compounds in ethanolic extract and up to 14 compounds were detected. These compounds were also assessed for their docking scores. Plausible binding modes with polyphenol oxidase and four best compounds were selected for molecular dynamics (MD) simulation to analyze their structural stability with receptor.

Exploiting the co-crystal ligands shape, features and structure-based approaches for identification of SARS-CoV-2 Mpro inhibitors

SARS-CoV-2 enters the host cell through the ACE2 receptor and replicates its genome using an RNA-Dependent RNA Polymerase (RDRP). The functional RDRP is released from pro-protein pp1ab by the proteolytic activity of Main protease (Mpro) which is encoded within the viral genome. Due to its vital role in proteolysis of viral polyprotein chains, it has become an attractive potential drug target. We employed a hierarchical virtual screening approach to identify small synthetic protease inhibitors. Statistically optimized molecular shape and color-based features (various functional groups) from co-crystal ligands were used to screen different databases through various scoring schemes. Then, the electrostatic complementarity of screened compounds was matched with the most active molecule to further reduce the hit molecules' size. Finally, five hundred eighty-seven molecules were docked in Mpro catalytic binding site, out of which 29 common best hits were selected based on Glide and FRED scores. Five best-fitting compounds in complex with Mpro were subjected to MD simulations to analyze their structural stability and binding affinities with Mpro using MM/GB(PB)SA models. Modeling results suggest that identified hits can act as the lead compounds for designing better active Mpro inhibitors to enhance the chemical space to combat COVID-19.Communicated by Ramaswamy H. Sarma.

Development of a Covalent Inhibitor of c-Jun N-Terminal Protein Kinase (JNK) 2/3 with Selectivity over JNK1

The c-Jun N-terminal kinases (JNKs) are members of the mitogen-activated protein kinase (MAPK) family, which includes JNK1-JNK3. Interestingly, JNK1 and JNK2 show opposing functions, with JNK2 activity favoring cell survival and JNK1 stimulating apoptosis. Isoform-selective small molecule inhibitors of JNK1 or JNK2 would be useful as pharmacological probes but have been difficult to develop due to the similarity of their ATP binding pockets. Here, we describe the discovery of a covalent inhibitor YL5084, the first such inhibitor that displays selectivity for JNK2 over JNK1. We demonstrated that YL5084 forms a covalent bond with Cys116 of JNK2, exhibits a 20-fold higher Kinact/KI compared to that of JNK1, and engages JNK2 in cells. However, YL5084 exhibited JNK2-independent antiproliferative effects in multiple myeloma cells, suggesting the existence of additional targets relevant in this context. Thus, although not fully optimized, YL5084 represents a useful chemical starting point for the future development of JNK2-selective chemical probes.

Allosteric modulation of a human odorant receptor

Odor perception is first determined by how the myriad of environmental volatiles are detected at the periphery of the olfactory system. The combinatorial activation of dedicated odorant receptors generates enough encoding power for the discrimination of tens of thousands of odorants. Recent studies have revealed that odorant receptors undergo widespread inhibitory modulation of their activity when presented with mixtures of odorants, a property likely required to maintain discrimination and ensure sparsity of the code for complex mixtures. Here, we establish the role of human OR5AN1 in the detection of musks and identify distinct odorants capable of enhancing its activity in binary mixtures. Chemical and pharmacological characterization indicate that specific α-β unsaturated aliphatic aldehydes act as positive allosteric modulators. Sensory experiments show decreased odor detection threshold in humans, suggesting that allosteric modulation of odorant receptors is perceptually relevant and likely adds another layer of complexity to how odors are encoded in the peripheral olfactory system.

Mechanistic Insight into the Inhibition of Choline Acetyltransferase by Proton Pump Inhibitors

Various pharmacoepidemiological investigational studies have indicated that Proton Pump Inhibitors (PPIs) may increase the likelihood of developing Alzheimer's disease (AD) and non-AD related dementias. Previously, we have reported the inhibition of the acetylcholine biosynthesizing enzyme choline acetyltransferase (ChAT) by PPIs, for which omeprazole, lansoprazole, and pantoprazole exhibited IC₅₀ values of 0.1, 1.5, and 5.3 μM, respectively. In this study we utilize a battery of computational tools to perceive a mechanistic insight into the molecular interaction of PPIs with the ChAT binding pocket that may further help in designing novel ChAT ligands. Various in-silico tools make it possible for us to elucidate the binding interaction, conformational stability, and dynamics of the protein-ligand complexes within a 200 ns time frame. Further, the binding free energies for the PPI-ChAT complexes were explored. The results suggest that the PPIs exhibit equal or higher binding affinity toward the ChAT catalytic tunnel and are stable throughout the simulated time and that the pyridine ring of the PPIs interacts primarily with the catalytic residue His₃₂₄. A free energy landscape analysis showed that the folding process was linear, and the residue interaction network analysis can provide insight into the roles of various amino acid residues in stabilization of the PPIs in the ChAT binding pocket. As a major factor for the onset of Alzheimer's disease is linked to cholinergic dysfunction, our previous and the present findings give clear insight into the PPI interaction with ChAT. The scaffold can be further simplified to develop novel ChAT ligands, which can also be used as ChAT tracer probes for the diagnosis of cholinergic dysfunction and to initiate timely therapeutic interventions to prevent or delay the progression of AD.

Discovery of potential FGFR3 inhibitors via QSAR, pharmacophore modeling, virtual screening and molecular docking studies against bladder cancer

BACKGROUND

Fibroblast growth factor receptor 3 is known as a favorable aim in vast range of cancers, particularly in bladder cancer treatment. Pharmacophore and QSAR modeling approaches are broadly utilized for developing novel compounds for the determination of inhibitory activity versus the biological target. In this study, these methods employed to identify FGFR3 potential inhibitors.

METHODS

To find the potential compounds for bladder cancer targeting, ZINC and NCI databases were screened. Pharmacophore and QSAR modeling of FGFR3 inhibitors were utilized for dataset screening. Then, with regard to several factors such as Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties and Lipinski's Rule of Five, the recognized compounds were filtered. In further step, utilizing the flexible docking technique, the obtained compounds interactions with FGFR3 were analyzed.

RESULTS

The best five compounds, namely ZINC09045651, ZINC08433190, ZINC00702764, ZINC00710252 and ZINC00668789 were selected for Molecular Dynamics (MD) studies. Off-targeting of screened compounds was also investigated through CDD search and molecular docking. MD outcomes confirmed docking investigations and revealed that five selected compounds could make steady interactions with the FGFR3 and might have effective inhibitory potencies on FGFR3.

CONCLUSION

These compounds can be considered as candidates for bladder cancer therapy with improved therapeutic properties and less adverse effects.