Large-Scale Analysis of Hydrogen Bond Interaction Patterns in Protein–Ligand Interfaces

Using Multiscale Molecular Modeling to Analyze Possible NS2b-NS3 Protease Inhibitors from Philippine Medicinal Plants

Within the field of Philippine folkloric medicine, the utilization of indigenous plants like Euphorbia hirta (tawa-tawa), Carica papaya (papaya), and Psidium guajava (guava) as potential dengue remedies has gained attention. Yet, limited research exists on their comprehensive effects, particularly their anti-dengue activity. This study screened 2944 phytochemicals from various Philippine plants for anti-dengue activity. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling provided 1265 compounds demonstrating pharmacokinetic profiles suitable for human use. Molecular docking targeting the dengue virus NS2b-NS3 protease's catalytic triad (Asp 75, Ser 135, and His 51) identified ten ligands with higher docking scores than reference compounds idelalisib and nintedanib. Molecular dynamics simulations confirmed the stability of eight of these ligand-protease complexes. Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) analysis highlighted six ligands, including veramiline (-80.682 kJ/mol), cyclobranol (-70.943 kJ/mol), chlorogenin (-63.279 kJ/mol), 25beta-Hydroxyverazine (-61.951 kJ/mol), etiolin (-59.923 kJ/mol), and ecliptalbine (-56.932 kJ/mol) with favorable binding energies, high oral bioavailability, and drug-like properties. This integration of traditional medical knowledge with advanced computational drug discovery methods paves new pathways for the development of treatments for dengue.

Sulfonamide Derivatives: Recent Compounds with Potent Anti-alzheimer's Disease Activity

Facile synthetic procedures and broad spectrum of biological activities are special attributes of sulfonamides. Sulfonamide derivatives have demonstrated potential as a class of compounds for the treatment of Alzheimer's disease (AD). Recent sulfonamide derivatives have been reported as prospective anti-AD agents, with a focus on analogues that significantly inhibit the function of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes and exhibit remarkable antioxidant and anti-inflammatory properties, all of which are critical for the treatment of AD. Sulfonamide- mediated activation of nuclear factor erythroid 2-related factor 2 (NRF2), a key regulator of the endogenous antioxidant response, has also been suggested as a potential therapeutic approach in AD. Additionally, it has been discovered that a number of sulfonamide derivatives show selectivity for the β- and γ-secretase enzymes and a significant reduction of amyloid B (Aβ) aggregation, which have been implicated in AD. The comparative molecular docking of benzenesulfonamide and donepezil, an AD reference drug showed comparable anti-AD activities. These suggest that sulfonamide derivatives may represent a new class of drugs for the treatment of AD. Thus, the current review will focus on recent studies on the chemical synthesis and evaluation of the anti-AD properties, molecular docking, pharmacological profile, and structure-activity relationship (SAR) of sulfonamide derivatives, as well as their potential anti-AD mechanisms of action. This paper offers a thorough assessment of the state of the art in this field of study and emphasizes the potential of sulfonamide derivatives synthesized during the 2012-2023 period as a new class of compounds for the treatment of AD.

Fn-HMGB1 Adsorption Behavior Initiates Early Immune Recognition and Subsequent Osteoinduction of Biomaterials

Implantable biomaterials are widely used in bone tissue engineering, but little is still known about how they initiate early immune recognition and the initial dynamics. Herein, the early immune recognition and subsequent osteoinduction of biphasic calcium phosphate (BCP) after implantation to the protein adsorption behavior is attributed. By liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis, the biomaterial-related molecular patterns (BAMPs) formed after BCP implantation are mapped, dominated by the highly expressed extracellular matrix protein fibronectin (Fn) and the high mobility group box 1 (HMGB1). Molecular dynamics simulations show that Fn has the ability to bind more readily to the BCP surface than HMGB1. The preferential binding of Fn provides a higher adsorption energy for HMGB1. Furthermore, multiple hydrogen bonding sites between HMGB1 and Fn are demonstrated using a molecular docking approach. Ultimately, the formation of BAMPs through HMGB1 antagonist glycyrrhizic acid (GA), resulting in impaired immune recognition of myeloid differentiation factor 88 (MYD88) mediated dendritic cells (DCs) and macrophages (Mφs), as well as failed osteoinduction processes is obstructed. This study introduces a mechanism for early immune recognition of implant materials based on protein adsorption, providing perspectives for future design and application of tissue engineering materials.

Screening of phytochemicals from Clerodendrum inerme (L.) Gaertn as potential anti-breast cancer compounds targeting EGFR: an in-silico approach

Breast cancer (BC) is the most prevalent malignancy among women around the world. The epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor (RTK) of the ErbB/HER family. It is essential for triggering the cellular signaling cascades that control cell growth and survival. However, perturbations in EGFR signaling lead to cancer development and progression. Hence, EGFR is regarded as a prominent therapeutic target for breast cancer. Therefore, in the current investigation, EGFR was targeted with phytochemicals from Clerodendrum inerme (L.) Gaertn (C. inerme). A total of 121 phytochemicals identified by gas chromatography-mass spectrometry (GC-MS) analysis were screened against EGFR through molecular docking, ADMET analyses (Absorption, Distribution, Metabolism, Excretion, and Toxicity), PASS predictions, and molecular dynamics simulation, which revealed three potential hit compounds with CIDs 10586 [i.e. alpha-bisabolol (-6.4 kcal/mol)], 550281 [i.e. 2,(4,4-Trimethyl-3-hydroxymethyl-5a-(3-methyl-but-2-enyl)-cyclohexene) (-6.5 kcal/mol)], and 161271 [i.e. salvigenin (-7.4 kcal/mol)]. The FDA-approved drug gefitinib was used to compare the inhibitory effects of the phytochemicals. The top selected compounds exhibited good ADMET properties and obeyed Lipinski's rule of five (ROF). The molecular docking analysis showed that salvigenin was the best among the three compounds and formed bonds with the key residue Met 793. Furthermore, the molecular mechanics generalized born surface area (MMGBSA) calculations, molecular dynamics simulation, and normal mode analysis validated the binding affinity of the compounds and also revealed the strong stability and compactness of phytochemicals at the docked site. Additionally, DFT and DOS analyses were done to study the reactivity of the compounds and to further validate the selected phytochemicals. These results suggest that the identified phytochemicals possess high inhibitory potential against the target EGFR and can treat breast cancer. However, further in vitro and in vivo investigations are warranted towards the development of these constituents into novel anti-cancer drugs.Communicated by Ramaswamy H. Sarma.

An insight from computational approach to explore novel, high-affinity phosphodiesterase 10A inhibitors for neurological disorders

The enzyme Phosphodiesterase 10A (PDE10A) plays a regulatory role in the cAMP/protein kinase A (PKA) signaling pathway by means of hydrolyzing cAMP and cGMP. PDE10A emerges as a relevant pharmacological drug target for neurological conditions such as psychosis, schizophrenia, Parkinson's, Huntington's disease, and other memory-related disorders. In the current study, we subjected a set of 1,2,3-triazoles to be explored as PDE10A inhibitors using diverse computational approaches, including molecular docking, classical molecular dynamics (MD) simulations, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations, steered MD, and umbrella sampling simulations. Molecular docking of cocrystallized ligands papaverine and PFJ, along with a set of in-house synthesized molecules, suggested that molecule 3i haded the highest binding affinity, followed by 3h and 3j. Furthermore, the structural stability studies using MD and MM-PBSA indicated that the 3h and 3j formed stable complexes with PDE10A. The binding free energy of -240.642 kJ/mol and -201.406 kJ/mol was observed for 3h and 3j, respectively. However, the cocrystallized ligands papaverine and PFJ exhibited comparitively higher binding free energy values of -202.030 kJ/mol and -138.764 kJ/mol, respectively. Additionally, steered MD and umbrella sampling simulations provided conclusive evidence that the molecules 3h and 3j could be exploited as promising candidates to target PDE10A.Communicated by Ramaswamy H. Sarma.

Unveiling the potential of marine compounds as quorum sensing inhibitors targeting Pseudomonas aeruginosa's LasI: A computational study using molecular docking and molecular dynamics

Antimicrobial resistance (AMR) poses a significant threat to global public health, with multidrug-resistant Pseudomonas aeruginosa being a leading cause of mortality, accounting for 18%-61% of deaths annually. The quorum sensing (QS) systems of P. aeruginosa, particularly the LasI-LasR system, play a crucial role in promoting biofilm formation and expression of virulent genes, which contribute to the development of AMR. This study focuses on LasI, the mediator of biofilm formation for identifying its inhibitors from a marine compound database comprising of 32 000 compounds using molecular docking and molecular simulation techniques. The virtual screening and docking experiments demonstrated that the top 10 compounds exhibited favorable docking scores of <-7.19 kcal/mol compared to the reported inhibitor 3,5,7-Trihydroxyflavone with a docking score of -3.098 kcal/mol. Additionally, molecular mechanics/Poisson-Boltzmann generalized born surface area (MM-GBSA) analyses were conducted to assess these compounds' suitability for further investigation. Out of 10 compounds, five compounds demonstrated high MM-GBSA binding energy (<-35.33 kcal/mol) and were taken up for molecular dynamics simulations to evaluate the stability of the protein-ligand complex over a 100 ns period. Based on root mean square deviation, root mean square fluctuation, radius of gyration, and hydrogen bond interactions analysis, three marine compounds, namely MC-2 (CMNPD13419) and MC-3 (CMNPD1068), exhibited consistent stability throughout the simulation. Therefore, these compounds show potential as promising LasI inhibitors and warrant further validation through in vitro and in vivo experiments. By exploring the inhibitory effects of these marine compounds on P. aeruginosa's QS system, this research aims to contribute to the development of novel strategies to combat AMR.

Design, Synthesis, and Bioassay for the Thiadiazole-Bridged Thioacetamide Compound as Cy-FBP/SBPase Inhibitors Based on Catalytic Mechanism Virtual Screening

Cyanobacterial fructose-1,6-/sedoheptulose-1,7-bisphosphatase (Cy-FBP/SBPase) was an important regulatory enzyme in cyanobacterial photosynthesis and was a potential target enzyme for screening to obtain novel inhibitors against cyanobacterial blooms. In this study, we developed a novel pharmacophore screening model based on the catalytic mechanism and substrate structure of Cy-FBP/SBPase and screened 26 S series compounds with different structures and pharmacophore characteristics from the Specs database by computer-assisted drug screening. These compounds exhibited moderate inhibitory activity against Cy-FBP/SBPase, with 9 compounds inhibiting >50% at 100 μM. Among them, compound S5 showed excellent inhibitory activity against both Cy-FBP/SBPase and Synechocystis sp. PCC6803 (IC50 = 6.7 ± 0.7 μM and EC50 = 7.7 ± 1.4 μM). The binding mode of compound S5 to Cy-FBP/SBPase was predicted using the molecular docking theory and validated by sentinel mutation and enzyme activity analysis. Physiochemical, gene transcription level, and metabolomic analyses showed that compound S5 significantly reduced the quantum yield of photosystem II and the maximum electron transfer rate, downregulated transcript levels of related genes encoding the Calvin cycle and photosystem, reduced the photosynthetic efficiency of cyanobacteria, thus inhibited metabolic pathways, such as the Calvin cycle and tricarboxylic acid cycle, and eventually achieved an efficient algicide. In addition, compound S5 had a high safety profile for human-derived cells and zebrafish. In summary, the novel pharmacophore screening model obtained from the current work provides an effective solution to the cyanobacterial bloom problem.

Evaluation of the cytotoxicity and genotoxicity potential of synthetic diacetyl food flavoring in silico, in vivo, and in vitro

Diacetyl is a common ingredient that creates a buttery flavor in baked goods and other food products. The cytotoxic impact of diacetyl on a normal human liver cell line (THLE2) indicated an IC₅₀ value of 41.29 mg/ml through MTT assay and a cell cycle arrest in the G₀/G₁ phase relative to the control. Administration of diacetyl at two-time points (acute-chronic) led to a significant increase in DNA damage indicated by the increase in tail length, tail DNA%, and tail moment. The mRNA and protein expression levels of genes in the rats' livers were then measured using real-time PCR and western blotting. The results showed an activation of the apoptotic and necrosis mechanism, with an upregulation of p53, Caspase 3, and RIP1 and a downregulation of Bcl-2 at the mRNA level. The ingestion of diacetyl disrupted the liver's oxidant/antioxidant balance, as evidenced by alterations in levels of GSH, SOD, CAT, GPx, GR, MDA, NO, and peroxynitrite. Additionally, heightened levels of inflammatory cytokines were shown. Histopathological examinations revealed necrotic foci and congested portal areas in the rats' liver cells after treatment with diacetyl. Diacetyl may interact moderately with Caspase, RIP1, and p53 core domain through In-silico, possibly resulting in upregulated gene expression.

Molecular insights into the behavior of the allosteric and ATP-competitive inhibitors in interaction with AKT1 protein: A molecular dynamics study

AKT1 is a family of serine/threonine kinases that play a key role in regulating cell growth, proliferation, metabolism, and survival. Two significant classes of AKT1 inhibitors (allosteric and ATP-competitive) are used in clinical development, and both of them could be effective in specific conditions. In this study, we investigated the effect of several different inhibitors on two conformations of the AKT1 by computational approach. We studied the effects of four inhibitors, including MK-2206, Miransertib, Herbacetin, and Shogaol, on the inactive conformation of AKT1 protein and the effects of four inhibitors, Capivasertib, AT7867, Quercetin, and Oridonin molecules on the active conformation of AKT1 protein. The results of simulations showed that each inhibitor creates a stable complex with AKT1 protein, although AKT1/Shogaol and AKT1/AT7867 complexes showed less stability than other complexes. Based on RMSF calculations, the fluctuation of residues in the mentioned complexes is higher than in other complexes. As compared to other complexes in either of its two conformations, MK-2206 has a stronger binding free energy affinity in the inactive conformation, -203.446 kJ/mol. MM-PBSA calculations showed that the van der Waals interactions contribute more than the electrostatic interactions to the binding energy of inhibitors to AKT1 protein.

Investigation of the inhibitory behavior of XFE and mitoxantrone molecules in interaction with AKT1 protein: a molecular dynamics simulation study

The PI3K/Akt/mTOR pathway is one of the important pathways in many cancers. Akt is a serine-threonine kinase protein identified as a drug target for cancer treatment. Therefore, anticancer drugs are essential therapeutic targets for this pathway. In the current study, the inhibitory effect of two anticancer molecules, XFE and mitoxantrone, on AKT1 protein that can impact the activity of the AKT1 protein was investigated by using molecular docking and molecular dynamics (MD) simulations. The molecular docking results presented a relatively higher binding affinity of the mitoxantrone molecule in interaction with AKT1 than the XFE molecule. These results were validated by the MM/PBSA technique that was performed on obtained trajectories of 25 ns MD simulations. The mitoxantrone molecule has an intense binding energy of - 880.536 kcal/mol with AKT1 protein, while the XFE molecule shows a binding energy value of - 83.569 kcal/mol. Our findings from molecular dynamics simulations indicated that both molecules have favorite interactions with AKT1 protein. Other analyses, such as RMSF and hydrogen binding on trajectories obtained from MD simulations, indicated that the mitoxantrone molecule could be a relatively potent inhibitor for AKT1. Based on the results of this study and the structure of mitoxantrone, it is expected to be a good candidate for cancer treatment as a (PI3K)/Akt/mTOR inhibitor.

Enzyme-substrate interactions in orotate-mimetic OPRT inhibitor complexes: a QM/MM analysis

Orotate phosphoribosyltransferase (OPRT) catalyses the reversible phosphoribosyl transfer from α-D-5-phosphoribosyl-1-pyrophosphate (PRPP) to orotic acid (OA) to yield orotidine 5'-monophosphate (OMP) during the de novo synthesis of nucleotides. Numerous studies have reported the inhibition of this reaction as a strategy to check diseases like tuberculosis, malaria and cancer. Insight into the inhibition of this reaction is, therefore, of urgent interest. In this study, we implemented a QM/MM framework on OPRT derived from Saccharomyces cerevisiae to obtain insights into the competitive binding of OA and OA-mimetic inhibitors by quantifying their interactions with OPRT. 4-Hydroxy-6-methylpyridin-2(1H) one showed the best inhibiting activity among the structurally similar OA-mimetic inhibitors, as quantified from the binding energetics. Our analysis of protein-ligand interactions unveiled the association of this inhibitory ligand with a strong network of hydrogen bonds, a large contribution of hydrophobic contacts, and bridging water molecules in the binding site. The ortho-substituted CH₃ group in the compound resulted in a large population of π-electrons in the aromatic ring of this inhibitor, supporting the ligand binding further.

In Silico Identification of 1-DTP Inhibitors of Corynebacterium diphtheriae Using Phytochemicals from Andrographis paniculata

A number of phytochemicals have been identified as promising drug molecules against a variety of diseases using an in-silico approach. The current research uses this approach to identify the phyto-derived drugs from Andrographis paniculata (Burm. f.) Wall. ex Nees (AP) for the treatment of diphtheria. In the present study, 18 bioactive molecules from Andrographis paniculata (obtained from the PubChem database) were docked against the diphtheria toxin using the AutoDock vina tool. Visualization of the top four molecules with the best dockscore, namely bisandrographolide (-10.4), andrographiside (-9.5), isoandrographolide (-9.4), and neoandrographolide (-9.1), helps gain a better understanding of the molecular interactions. Further screening using molecular dynamics simulation studies led to the identification of bisandrographolide and andrographiside as hit compounds. Investigation of pharmacokinetic properties, mainly ADMET, along with Lipinski's rule and binding affinity considerations, narrowed down the search for a potent drug to bisandrographolide, which was the only molecule to be negative for AMES toxicity. Thus, further modification of this compound followed by in vitro and in vivo studies can be used to examine itseffectiveness against diphtheria.

Exploring isofunctional molecules: Design of a benchmark and evaluation of prediction performance

Identification of novel chemotypes with biological activity similar to a known active molecule is an important challenge in drug discovery called 'scaffold hopping'. Small-, medium-, and large-step scaffold hopping efforts may lead to increasing degrees of chemical structure novelty with respect to the parent compound. In the present paper, we focus on the problem of large-step scaffold hopping. We assembled a high quality and well characterized dataset of scaffold hopping examples comprising pairs of active molecules and including a variety of protein targets. This dataset was used to build a benchmark corresponding to the setting of real-life applications: one active molecule is known, and the second active is searched among a set of decoys chosen in a way to avoid statistical bias. This allowed us to evaluate the performance of computational methods for solving large-step scaffold hopping problems. In particular, we assessed how difficult these problems are, particularly for classical 2D and 3D ligand-based methods. We also showed that a machine-learning chemogenomic algorithm outperforms classical methods and we provided some useful hints for future improvements.

Identification of New L-Heptanoylphosphatidyl Inositol Pentakisphosphate Derivatives Targeting the Interaction with HIV-1 Gag by Molecular Modelling Studies

The HIV-1 Gag protein binds to the host cell membrane and assembles into immature particles. Then, in the course of immature virion budding, activated protease cleaves Gag into its main components: MA, CA, NC, and p6 proteins. The highly basic residues of MA predominantly interact with the acidic head of phosphatidyl-inositol-4,5-bisphosphate (PI(4,5)P2) inserted into the membrane. Our research group developed L-Heptanoylphosphatidyl Inositol Pentakisphosphate (L-HIPPO) and previously confirmed that this compound bound to the MA more strongly than PI(4,5)P2 and inositol hexakisphosphate (IP6) did. Therefore, herein we rationally designed eight new L-HIPPO derivatives based on the fact that the most changeable parts of L-HIPPO were two acyl chains. After that, we employed molecular docking for eight compounds via Maestro software using high-resolution crystal structures of MA in complex with IP6 (PDB IDs: 7E1I, 7E1J, and 7E1K), which were recently elucidated by our research group. The most promising docking scores were obtained with benzene-inserted compounds. Thus, we generated a library containing 213 new aromatic group-inserted L-HIPPO derivatives and performed the same molecular docking procedure. According to the results, we determined the nine new L-HIPPO derivatives most effectively binding to the MA with the most favorable scoring functions and pharmacokinetic properties for further exploration.

FastGrow: on-the-fly growing and its application to DYRK1A

Fragment-based drug design is an established routine approach in both experimental and computational spheres. Growing fragment hits into viable ligands has increasingly shifted into the spotlight. FastGrow is an application based on a shape search algorithm that addresses this challenge at high speeds of a few milliseconds per fragment. It further features a pharmacophoric interaction description, ensemble flexibility, as well as geometry optimization to become a fully fledged structure-based modeling tool. All features were evaluated in detail on a previously reported collection of fragment growing scenarios extracted from crystallographic data. FastGrow was also shown to perform competitively versus established docking software. A case study on the DYRK1A kinase, using recently reported new chemotypes, illustrates FastGrow's features in practice and its ability to identify active fragments. FastGrow is freely available to the public as a web server at https://fastgrow.plus/ and is part of the SeeSAR 3D software package.

Investigation of Major Flavonoids from Artemisia argyi as a Potential COVID-19 Drug: Molecular Docking and DFT Calculations

Flavonoids from natural products are well-identified as potential antiviral agents in the treatment of SARS-CoV-2 (COVID-19) infection and related diseases. However, some major species of flavonoids from Chinese traditional folk medicine, such as of Artemisia argyi (A. argyi), have not been evaluated yet. Here, we choose five major flavonoids obtained from A. argyi, namely, Jaceosidin (1), Eupatilin (2), Apigenin (3), Eupafolin (4), and 5,6-Dihydroxy-7,3′,4′-trimethoxyflavone (5), compared to the well-studied Baicalein (6), as potential inhibitors analogs for COVID-19 by computational modeling strategies. The frontier molecular orbitals (FMOs), chemical reactivity descriptors, and electrostatic surface potential (ESP) were performed by density functional theory (DFT) calculations. Additionally, these flavonoids were docked on the main protease (PDB: 6LU7) of SARS-CoV-2 to evaluate the binding affinities. Computational analysis predicted that all of these compounds show a high affinity and might serve as potential inhibitors to SARS-CoV-2, among which compound (5) exhibits the least binding energy (−155.226 kcal/mol). The high binding affinity could be enhanced by increasing the electron repulsion due to the valence shell electron pair repulsion model (VSEPR). Consequently, the major flavonoids in Artemisia argyi have a significant ability to reduce the deterioration of COVID-19 in the terms of DFT calculations and molecular docking.

Investigation of antidiabetic properties of shikonin by targeting aldose reductase enzyme: In silico and in vitro studies

Diabetes is a complicated multifactorial disorder in which the patient generally observes polyphagia, polydipsia, and polyuria due to uncontrolled growth in blood sugar levels. For its management, the pharmaceutical industry is working day and night to find a better drug with no or least toxicity. That's why nowadays a more focused branch is to use herbal phytoconstituents for its prevention. Shikonin is a naphthoquinone natural dye that is isolated from the plants of the Boraginaceae family and has proven its role as an anti-cancer, anti-inflammatory, and anti-gonadotrophic agent. In our previous study, we have published its anti-diabetic action by inhibiting the enzyme protein tyrosine phosphatase 1B. In this study, we were more focused on finding out the role of Shikonin and its pharmacophores by inhibiting the action of aldose reductase (AR) enzyme. The study was conducted using pharmacophore modeling, molecular docking, and molecular dynamics simulation studies. The absorption, distribution, metabolism, excretion (ADME), and toxicity profile were also evaluated in this study. Along with all the computational biology parameters we also focused on the in vitro activity and kinetic study of inhibitory activity of Shikonin against aldose reductase.

Differences in Gluco and Galacto Substrate-Binding Interactions in a Dual 6Pβ-Glucosidase/6Pβ-Galactosidase Glycoside Hydrolase 1 Enzyme from Bacillus licheniformis

Bacterial glycoside hydrolase 1 (GH1) enzymes with 6-phospho-β-galactosidase and 6-phospho-β-glucosidase activities have the important task of releasing phosphorylated and nonphosphorylated monosaccharides into the cytoplasm. Curiously, dual 6-phospho-β-galactosidase/6-phospho-β-glucosidase (dual-phospho) enzymes have broad specificity and are able to hydrolyze galacto- and gluco-derived substrates. This study investigates the structure and substrate specificity of a GH family 1 enzyme from Bacillus licheniformis, hereafter known as BlBglC. The enzyme structure has been solved, and sequence analysis, molecular dynamics simulations, and binding free energy calculations offered evidence of dual-phospho activity. Both test ligands p-nitrophenyl-β-d-galactoside-6-phosphate (PNP6Pgal) and p-nitrophenyl-β-d-glucoside-6-phosphate (PNP6Pglc) demonstrated strong binding to BlBglC although the pose and interactions of the PNP6Pglc triplicates were slightly more consistent. Interestingly, known specificity-inducing residues, Gln23 and Trp433, bind strongly to the ligand O3 hydroxyl group in the PNP6Pgal-BlBglC complex and to the ligand O4 hydroxyl group in the PNP6Pglc-BlBglC complex. Additionally, the BlBglC-His124 residue is a major contributor of hydrogen bonds to the PNP6Pgal O3 hydroxyl group but does not form any hydrogen bonds with PNP6Pglc. On the other hand, BlBglC residues Tyr173, Tyr301, Gln302, and Thr321 form hydrogen bonds with PNP6Pglc but not PNP6Pgal. These findings provide important details of the broad specificity of dual-phospho activity GH1 enzymes.

Camptothecin shows better promise than Curcumin in the inhibition of the Human Telomerase: A computational study

OBJECTIVES

The Human Telomerase enzyme has become a drug target in the treatment of cancers and age-related disorders. This study aims to identify potential natural inhibitors of the Human Telomerase from compounds derived from edible African plants.

MATERIALS AND METHODS

A library of 1,126 natural compounds was molecularly docked against the Telomerase Reverse Transcriptase (PDB ID: 5ugw), the catalytic subunit of the target protein. Curcumin, a known Telomerase inhibitor was used as the standard. The front-runner compounds were screened for bioavailability, pharmacokinetic properties, and bioactivity using the SWISSADME, PKCSM, and Molinspiration webservers respectively. The molecular dynamic simulation and analyses of the apo and holo proteins were performed by the Galaxy supercomputing webserver.

RESULTS

The results of the molecular docking and virtual screening reveal Augustamine and Camptothecin as lead compounds. Augustamine has better drug-likeness and pharmacokinetic properties while Camptothecin showed better bioactivity and stronger binding affinity (-8.2 kcal/mol) with the target. The holo structure formed by Camptothecin showed greater inhibitory activity against the target with a total RMSF of 169.853, B-Factor of 20.164, and 108 anti-correlating residues.

CONCLUSION

Though they both act at the same binding site, Camptothecin induces greater Telomerase inhibition and better molecular stability than the standard, Curcumin. Further tests are required to investigate the inhibitory activities of the lead compounds.

Docking Screens of Noncovalent Interaction Motifs of the Human Subtype-D2 Receptor-75 Schizophrenia Antipsychotic Complexes with Physicochemical Appraisal of Antipsychotics

Chemoinformatics appraisal and molecular docking were employed to investigate 225 complexes of 75 schizophrenia antipsychotics with the dopamine receptor subtypes D2R, D3R, and D4R. Considering the effective noncovalent interactions in the subtype-D2 receptor selectivity of antipsychotics, this study evaluated the possible physicochemical properties of ligands underlying the design of safer and more effective antipsychotics. The pan-assay interference compounds (PAINs) include about 25% of typical antipsychotics and 5% of atypicals. Popular antipsychotics like haloperidol, clozapine, risperidone, and aripiprazole are not PAINs. They have stronger interactions with D2R and D4R, but their interactions with D3R are slightly weaker, which is similar to the behavior of dopamine. In contrast to typical antipsychotics, atypical antipsychotics exhibit more noncovalent interactions with D4R than with D2R. These results suggest that selectivity to D2R and D4R comes from the synergy between hydrophobic and hydrogen-bonding interactions through their concomitant occurrence in the form of a hydrogen-bonding site adorned with hydrophobic contacts in antipsychotic-receptor complexes. All the antipsychotics had more synergic interactions with D2R and D4R in comparison with D3R. The atypical antipsychotics made a good distinction between the subtype D2 receptors with high selectivity to D4R. Among the popular antipsychotics, haloperidol, clozapine, and risperidone have hydrophobic-hydrogen-bonding synergy with D4R, while aripiprazole profits with D2R. The most important residue participating in the synergic interactions was threonine for D2R and cysteine for D4R. This work could be useful in informing and guiding future drug discovery and development studies aimed at receptor-specific antipsychotics.

Polyphenols Weaken Pea Protein Gel by Formation of Large Aggregates with Diminished Noncovalent Interactions

Polyphenols are well-known native cross-linkers and gel strengthening agents for many animal proteins. However, their role in modifying plant protein gels remains unclear. In this study, multiple techniques were applied to unravel the influence of green tea polyphenols (GTP) on pea protein gels and the underlying mechanisms. We found that the elasticity and viscosity of pea protein gels decreased with increased GTP. The protein backbone became less rigid when GTP was present based on shortened T_1ρ^H in relaxation solid-state NMR measurements. Electron microscopy and small-angle X-ray scattering showed that gels weakened by GTP possessed disrupted networks with the presence of large protein aggregates. Solvent extraction and molecular dynamic simulation revealed a reduction in hydrophobic interactions and hydrogen bonds among proteins in gels containing GTP. The current findings may be applicable to other plant proteins for greater control of gel structures in the presence of polyphenols, expanding their utilization in food and biomedical applications.

Toward an efficient and eco-friendly route for the synthesis of dimeric 2,4-diacetyl phloroglucinol and its potential as a SARS-CoV-2 main protease antagonist: insight from in silico studies

Dimeric 2,4-diacetyl phloroglucinol derivatives were synthesized under green chemistry protocols and found to be the potential inhibitor of 3CLpro of SARS-CoV-2.

Protein folding stability and binding interactions through the lens of evolution: a dynamical perspective

While the function of a protein depends heavily on its ability to fold into a correct 3D structure, billions of years of evolution have tailored proteins from highly stable objects to flexible molecules as they adapted to environmental changes. Nature maintains the fine balance of protein folding and stability while still evolving towards new function through generations of fine-tuning necessary interactions with other proteins and small molecules. Here we focus on recent computational and experimental studies that shed light onto how evolution molds protein folding and the functional landscape from a conformational dynamics' perspective. Particularly, we explore the importance of dynamic allostery throughout protein evolution and discuss how the protein anisotropic network can give rise to allosteric and epistatic interactions.

A Consistent Scheme for Gradient-Based Optimization of ProteinLigand Poses

Scoring and numerical optimization of protein-ligand poses is an integral part of docking tools. Although many scoring functions exist, many of them are not continuously differentiable and they are rarely explicitly analyzed with respect to their numerical optimization behavior. Here, we present a consistent scheme for pose scoring and gradient-based pose optimization. It consists of a novel variant of the BFGS algorithm enabling step-length control, named LSL-BFGS (limited step length BFGS), and the empirical JAMDA scoring function designed for pose prediction and good numerical optimizability. The JAMDA scoring function shows a high pose prediction performance in the CASF-2016 docking power benchmark, top-ranking a pose with an RMSD of ≤2 Å in about 89% of the cases. The combination of JAMDA scoring with the LSL-BFGS algorithm shows a significantly higher optimization locality (i.e., no excessive movement of poses) than with the classical BFGS algorithm while retaining the characteristically low number of scoring function evaluations. The JAMDA scoring and optimization scheme is freely available for noncommercial use and academic research.

Searching Hit Potential Antimicrobials in Natural Compounds Space against Biofilm Formation

Biofilms are communities of microorganisms that can colonize biotic and abiotic surfaces and thus play a significant role in the persistence of bacterial infection and resistance to antimicrobial. About 65% and 80% of microbial and chronic infections are associated with biofilm formation, respectively. The increase in infections by multi-resistant bacteria instigates the need for the discovery of novel natural-based drugs that act as inhibitory molecules. The inhibition of diguanylate cyclases (DGCs), the enzyme implicated in the synthesis of the second messenger, cyclic diguanylate (c-di-GMP), involved in the biofilm formation, represents a potential approach for preventing the biofilm development. It has been extensively studied using PleD protein as a model of DGC for in silico studies as virtual screening and as a model for in vitro studies in biofilms formation. This study aimed to search for natural products capable of inhibiting the Caulobacter crescentus enzyme PleD. For this purpose, 224,205 molecules from the natural products ZINC15 database, have been evaluated through molecular docking and molecular dynamic simulation. Our results suggest trans-Aconitic acid (TAA) as a possible starting point for hit-to-lead methodologies to obtain new inhibitors of the PleD protein and hence blocking the biofilm formation.

Shape-Based Descriptors for Efficient Structure-Based Fragment Growing

Structure-based fragment growing is one of the key techniques in fragment-based drug design. Fragment growing is commonly practiced based on structural and biophysical data. Computational workflows are employed to predict which fragment elaborations could lead to high-affinity binders. Several such workflows exist but many are designed to be long running noninteractive systems. Shape-based descriptors have been proven to be fast and perform well at virtual-screening tasks. They could, therefore, be applied to the fragment-growing problem to enable an interactive fragment-growing workflow. In this work, we describe and analyze the use of specific shape-based directional descriptors for the task of fragment growing. The performance of these descriptors that we call ray volume matrices (RVMs) is evaluated on two data sets containing protein-ligand complexes. While the first set focuses on self-growing, the second measures practical performance in a cross-growing scenario. The runtime of screenings using RVMs as well as their robustness to three dimensional perturbations is also investigated. Overall, it can be shown that RVMs are useful to prefilter fragment candidates. For up to 84% of the 3299 generated self-growing cases and for up to 66% of the 326 generated cross-growing cases, RVMs could create poses with less than 2 Å root-mean-square deviation to the crystal structure with average query speeds of around 30,000 conformations per second. This opens the door for fast explorative screenings of fragment libraries.

ProteinsPlus: interactive analysis of protein-ligand binding interfaces

Due to the increasing amount of publicly available protein structures searching, enriching and investigating these data still poses a challenging task. The ProteinsPlus web service (https://proteins.plus) offers a broad range of tools addressing these challenges. The web interface to the tool collection focusing on protein–ligand interactions has been geared towards easy and intuitive access to a large variety of functionality for life scientists. Since our last publication, the ProteinsPlus web service has been extended by additional services as well as it has undergone substantial infrastructural improvements. A keyword search functionality was added on the start page of ProteinsPlus enabling users to work on structures without knowing their PDB code. The tool collection has been augmented by three tools: StructureProfiler validates ligands and active sites using selection criteria of well-established protein–ligand benchmark data sets, WarPP places water molecules in the ligand binding sites of a protein, and METALizer calculates, predicts and scores coordination geometries of metal ions based on surrounding complex atoms. Additionally, all tools provided by ProteinsPlus are available through a REST service enabling the automated integration in structure processing and modeling pipelines.

Screening of potential drug for Alzheimer's disease: a computational study with GSK-3 β inhibition through virtual screening, docking, and molecular dynamics simulation

The global impact of Alzheimer's disease (AD) necessitates intensive research to find appropriate and effective drugs. Many studies in AD suggested beta-amyloid plaques and neurofibrillary tangles-associated tau protein as the key targets for drug development. On the other hand, it is proved that triggering of Glycogen Synthase Kinase-3β (GSK-3β) also cause AD, therefore, GSK-3β is a potential drug target to combat AD. We, in this study, investigated the ability of small molecules to inhibit GSK-3β through virtual screening, Absorption, Distribution, Metabolism, and Excretion (ADME), induced-fit docking (IFD), molecular dynamics simulation, and binding free energy calculation. Besides, molecular docking was performed to reveal the binding and interaction of the ligand at the active site of GSK-3β. We found two compounds such as 6961 and 6966, which exhibited steady-state interaction with GSK-3β for 30 ns in molecular dynamics simulation. The compounds (6961 and 6966) also achieved a docking score of -9.05 kcal/mol and -8.11 kcal/mol, respectively, which is relatively higher than the GSK-3β II inhibitor (-6.73 kcal/mol). The molecular dynamics simulation revealed that the compounds have a stable state during overall simulation time, and lesser root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) values compared with co-crystal. In conclusion, we suggest the two compounds (6966 and 6961) as potential leads that could be utilized as effective inhibitors of GSK-3β to combat AD.

Charting Hydrogen Bond Anisotropy

A hydrogen bond (HB) is an essential interaction in countless phenomena, regulating the chemistry of life. HBs are characterized by two features, strength and directionality, with a high degree of heterogeneity across different chemical groups. These characteristics are dependent on the electronic configuration of the atoms involved in the interaction, which, in turn, is influenced strongly by the local molecular environment. Studies based on the analysis of HB in the solid phase, such as X-ray crystallography, suffer from significant biases due to packing forces. These will tend to better describe strong HBs at the expenses of weak ones, which will be either distorted or under-represented. Using quantum mechanics (QM), we calculated interaction energies for about a hundred acceptors and donors in a rigorously defined set of geometries. We performed 180,000 independent QM calculations, covering all relevant angular components, mapping strength and directionality in a context free from external biases, with both single-site and cooperative HBs. By quantifying directionality, we show that there is no correlation with strength; therefore, these two components need to be addressed separately. Results demonstrate that there are very strong HB acceptors (e.g., dimethyl sulfoxide) with nearly isotropic interactions and weak ones (e.g., thioacetone) with a sharp directional profile. Similarly, groups can have comparable directional propensity but be very distant in the strength spectrum (e.g., thioacetone and pyridine). Results provide a new perspective on the way HB directionality is described, with implications for biophysics and molecular recognition that ultimately can influence chemical biology, protein engineering, and drug design.

On the evolution of protein-adenine binding

Proteins' interactions with ancient ligands may reveal how molecular recognition emerged and evolved. We explore how proteins recognize adenine: a planar rigid fragment found in the most common and ancient ligands. We have developed a computational pipeline that extracts protein-adenine complexes from the Protein Data Bank, structurally superimposes their adenine fragments, and detects the hydrogen bonds mediating the interaction. Our analysis extends the known motifs of protein-adenine interactions in the Watson-Crick edge of adenine and shows that all of adenine's edges may contribute to molecular recognition. We further show that, on the proteins' side, binding is often mediated by specific amino acid segments ("themes") that recur across different proteins, such that different proteins use the same themes when binding the same adenine-containing ligands. We identify numerous proteins that feature these themes and are thus likely to bind adenine-containing ligands. Our analysis suggests that adenine binding has emerged multiple times in evolution.

How Significant Are Unusual Protein-Ligand Interactions? Insights from Database Mining

We present a new approach to derive interaction propensities of protein-ligand atom pairs from mining of the Protein Data Bank. To ensure solid statistics, we use a line-of-sight contact filter and normalize the observed frequency of hits by a statistical null model based on exposed surface areas of atom types in the protein-ligand binding site. This allows us to investigate which intermolecular interactions and geometries are found more often than expected by chance in protein-ligand complexes. We focus our study on some of the unusual interactions that were postulated to be favorable, including σ-hole bonding of halogen and sulfur atoms, weak hydrogen bonding with fluorine as acceptor, and different types of dipolar interactions. Our results confirm some and challenge other common assumptions on these interactions and highlight other contact types that are yet underexplored in structure-based drug design.

The architecture of hydrogen and sulfur σ-hole interactions explain differences in the inhibitory potency of C-β-d-glucopyranosyl thiazoles, imidazoles and an N-β-d glucopyranosyl tetrazole for human liver glycogen phosphorylase and offer new insights to structure-based design

C-Glucopyranosyl imidazoles, thiazoles, and an N-glucopyranosyl tetrazole were assessed in vitro and ex vivo for their inhibitory efficiency against isoforms of glycogen phosphorylase (GP; a validated pharmacological target for the development of anti-hyperglycaemic agents). Imidazoles proved to be more potent inhibitors than the corresponding thiazoles or the tetrazole. The most potent derivative has a 2-naphthyl substituent, a K_i value of 3.2 µM for hepatic glycogen phosphorylase, displaying also 60% inhibition of GP activity in HepG2 cells, compared to control vehicle treated cells, at 100 μM. X-Ray crystallography studies of the protein - inhibitor complexes revealed the importance of the architecture of inhibitor associated hydrogen bonds or sulfur σ-hole bond interactions to Asn284 OD1, offering new insights to structure-based design efforts. Moreover, while the 2-glucopyranosyl-tetrazole seems to bind differently from the corresponding 1,2,3-triazole compound, the two inhibitors are equipotent.

SmoPSI: Analysis and Prediction of Small Molecule Binding Sites Based on Protein Sequence Information

The analysis and prediction of small molecule binding sites is very important for drug discovery and drug design. The traditional experimental methods for detecting small molecule binding sites are usually expensive and time consuming, and the tools for single species small molecule research are equally inefficient. In recent years, some algorithms for predicting binding sites of protein-small molecules have been developed based on the geometric and sequence characteristics of proteins. In this paper, we have proposed SmoPSI, a classification model based on the XGBoost algorithm for predicting the binding sites of small molecules, using protein sequence information. The model achieved better results with an AUC of 0.918 and an ACC of 0.913. The experimental results demonstrate that our method achieves high performances and outperforms many existing predictors. In addition, we also analyzed the binding residues and nonbinding residues and finally found the PSSM; hydrophilicity, hydrophobicity, charge, and hydrogen bonding have obviously different effects on the binding-site predictions.

In vitro and in silico anti-dengue activity of compounds obtained from Psidium guajava through bioprospecting

BACKGROUND

For decades, bioprospecting has proven to be useful for the identification of compounds with pharmacological potential. Considering the great diversity of Colombian plants and the serious worldwide public health problem of dengue-a disease caused by the dengue virus (DENV)-in the present study, we evaluated the anti-DENV effects of 12 ethanolic extracts derived from plants collected in the Colombian Caribbean coast, and 5 fractions and 5 compounds derived from Psidium guajava.

METHODS

The cytotoxicity and antiviral effect of 12 ethanolic extracts derived from plants collected in the Colombian Caribbean coast was evaluated in epithelial VERO cells. Five fractions were obtained by open column chromatography from the ethanolic extract with the highest selectivity index (SI) (derived from P. guajava, SI: 128.2). From the fraction with the highest selectivity (Pg-YP-I-22C, SI: 35.5), five compounds were identified by one- and two-dimensional nuclear magnetic resonance spectroscopy. The antiviral effect in vitro of the fractions and compounds was evaluated by different experimental strategies (Pre- and post-treatment) using non-toxic concentrations calculated by MTT method. The DENV inhibition was evaluated by plate focus assay. The results were analyzed by means of statistical analysis using Student's t-test. Finally the antiviral effect in Silico was evaluated by molecular docking.

RESULTS

In vitro evaluation of these compounds showed that three of them (gallic acid, quercetin, and catechin) were promising antivirals as they inhibit the production of infectious viral particles via different experimental strategies, with the best antiviral being catechin (100% inhibition with a pre-treatment strategy and 91.8% with a post-treatment strategy). When testing the interactions of these compounds with the viral envelope protein in silico by docking, only naringin and hesperidin had better scores than the theoretical threshold of - 7.0 kcal/mol (- 8.0 kcal/mol and - 8.2 kcal/mol, respectively). All ligands tested except gallic acid showed higher affinity to the NS5 protein than the theoretical threshold.

CONCLUSION

Even though bioprospecting has recently been replaced by more targeted tools for identifying compounds with pharmacological potential, our results show it is still useful for this purpose. Additionally, combining in vitro and in silico evaluations allowed us to identify promising antivirals as well as their possible mechanisms of action.

Underestimated Noncovalent Interactions in Protein Data Bank

Noncovalent interactions (NCIs) play essential roles in the structure and function of biomacromolecules. There are various NCIs, e.g., hydrogen bonds (HBs), cation-π and π-π interactions, and ionic bonds, among which HBs are the most widespread and well-studied. By utilizing the ratio of the observed HBs over pseudo HBs (1.0 Å longer than the HB distance criteria without angle constraints), we demonstrated that HBs in both protein-ligand and protein-protein interfaces are overlooked in structures deposited in PDB. After the QM/MM optimization of 12 protein-ligand complexes, we showed that the overlooked HBs could be recovered. With a systematic search in the PDB, we found that the HB number per residue (N_HB/R) in proteins decreases as structural resolution becomes lower, implying that HBs are overlooked even today, regardless of the type of refinement approach used. Similarly, cation-π, π-π, and ionic interactions were found to be significantly lost, manifesting the universal underestimation of various NCIs. Considering the vital role of NCIs, it is important to recover the NCIs to facilitate drug design, to explore protein-protein interaction, and to study protein structure and function.

Halogens in Protein-Ligand Binding Mechanism: A Structural Perspective

Halogen atoms have been at the center of many rational medicinal chemistry applications in drug design. While fluorine and chlorine atoms are often added to enhance physicochemical properties, bromine and iodine elements are generally inserted to improve selectivity. Favorable halogen interactions such as halogen bond have been thoroughly studied through quantum mechanics and statistical analyses. Although most of the studies focus on halogen interaction through its σ-hole, hydrogen bonding also has a significant impact. Here, we present an analysis describing the interacting environment of halogen atoms in protein-ligand context. With consideration of structural redundancy in the PDB, tendencies toward specific molecular interactions consideration have been refined and implications for rational drug design with halogens further discussed. Finally, we highlight the moderate occurrence of halogen bonding and present the other roles of halogen in protein-ligand complexes, completing the medicinal chemistry guide to rational halogen interactions.

The interplay and strength of the π⋯HF, C⋯HF, F⋯HF and F⋯HC hydrogen bonds upon the formation of multimolecular complexes based on C2H2⋯HF and C2H4⋯HF small dimers

The conception of this theoretical research was idealized aiming to unveil the intermolecular structures of complexes formed by acetylene or ethylene and hydrofluoric acid. At light of computational calculations by using the B3LYP/6-311++G(d,p) method, the geometries of the C₂H₂⋯(HF), C₂H₂⋯2(HF), C₂H₂⋯4(HF), C₂H₄⋯(HF), C₂H₄⋯2(HF) and C₂H₄⋯4(HF) hydrogen-bonded complexes were fully optimized. Moreover, the Post-Hartree-Fock calculations MP2/6-311++G(d,p), MP2/aug-cc-pVTZ, MP4(SDQ)/6-311++G(d,p) and CCSD/6-311++G(d,p) also were also used. The infrared spectra were analyzed in order to identify the new vibrational modes and frequencies of the proton donors shifted to red region. Through the modeling of charge-fluxes on the basis of the Quantum Theory of Atoms In Molecules (QTAIM) and, by contradicting the expectation of the hydrofluorination mechanisms of acetylene or ethylene, C⋯HF was recognized as a new type of hydrogen bond instead of the already well known π⋯H. The calculations of the Natural Bonding Orbital (NBO) and Charges derived from the Electrostatic Potential Grid-based (ChElPG) were also applied to interpret the shifting frequencies as well as measuring of the punctual charge-transfer after the formation of the complexes. Finally, the determination of the stabilization energy was carried out through the arguments of the Fock matrix in NBO basis and through the supermolecule approach. Also it is worthwhile to notice that some algebraic formulations were used for determining the electronic cooperative effect (CE).

DUckCov: a Dynamic Undocking-Based Virtual Screening Protocol for Covalent Binders

Thanks to recent guidelines, the design of safe and effective covalent drugs has gained significant interest. Other than targeting non‐conserved nucleophilic residues, optimizing the noncovalent binding framework is important to improve potency and selectivity of covalent binders toward the desired target. Significant efforts have been made in extending the computational toolkits to include a covalent mechanism of protein targeting, like in the development of covalent docking methods for binding mode prediction. To highlight the value of the noncovalent complex in the covalent binding process, here we describe a new protocol using tethered and constrained docking in combination with Dynamic Undocking (DUck) as a tool to privilege strong protein binders for the identification of novel covalent inhibitors. At the end of the protocol, dedicated covalent docking methods were used to rank and select the virtual hits based on the predicted binding mode. By validating the method on JAK3 and KRas, we demonstrate how this fast iterative protocol can be applied to explore a wide chemical space and identify potent targeted covalent inhibitors.

A systematic analysis of atomic protein-ligand interactions in the PDB

As the protein databank (PDB) recently passed the cap of 123 456 structures, it stands more than ever as an important resource not only to analyze structural features of specific biological systems, but also to study the prevalence of structural patterns observed in a large body of unrelated structures, that may reflect rules governing protein folding or molecular recognition. Here, we compiled a list of 11 016 unique structures of small-molecule ligands bound to proteins - 6444 of which have experimental binding affinity - representing 750 873 protein-ligand atomic interactions, and analyzed the frequency, geometry and impact of each interaction type. We find that hydrophobic interactions are generally enriched in high-efficiency ligands, but polar interactions are over-represented in fragment inhibitors. While most observations extracted from the PDB will be familiar to seasoned medicinal chemists, less expected findings, such as the high number of C-H···O hydrogen bonds or the relatively frequent amide-π stacking between the backbone amide of proteins and aromatic rings of ligands, uncover underused ligand design strategies.