Large-scale prediction of binding affinity in protein-small ligand complexes: the PRODIGY-LIG web server

Unveiling a Comprehensive Multi-epitope Subunit Vaccine Strategy Against Salmonella subsp. enterica: Bridging Core, Subtractive Proteomics, and Immunoinformatics

Salmonella subsp. enterica (SE) presents a significant global health challenge in both developed and developing countries. Current SE vaccines have limitations, targeting specific strains and demonstrating moderate efficacy in adults, while also being unsuitable for young children and often unaffordable in regions with lower income levels where the disease is prevalent. To address these challenges, this study employed a computational approach integrating core proteomics, subtractive proteomics, and immunoinformatics to develop a universal SE vaccine and identify potential drug targets. Analysis of the core proteome of 185 SE strains revealed 1964 conserved proteins. Subtractive proteomics identified 9 proteins as potential vaccine candidates and 41 as novel drug targets. Using reverse vaccinology-based immunoinformatics, four multi-epitope-based subunit vaccine constructs (MESVCs) were designed, aiming to stimulate cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte responses. These constructs underwent comprehensive evaluations for antigenicity, immunogenicity, toxicity, hydropathicity, and physicochemical properties. Predictive modeling, refinement, and validation were conducted to determine the secondary and tertiary structures of the SE-MESVCs, followed by docking studies with MHC-I, MHC-II, and TLR4 receptors. Molecular docking assessments showed favorable binding with all three receptors, with SE-MESVC-4 exhibiting the most promising binding energy. Molecular dynamics simulations confirmed the binding affinity and stability of SE-MESVC-4 with the TLR4/MD2 complex. Additionally, codon optimization and in silico cloning verified the efficient translation and successful expression of SE-MESVC-4 in Escherichia coli (E. coli) str. K12. Subsequent in silico immune simulation evaluated the efficacy of SE-MESVC-4 in triggering an effective immune response. These results suggest that SE-MESVC-4 may induce both humoral and cellular immune responses, making it a potential candidate for an effective SE vaccine. However, further experimental investigations are necessary to validate the immunogenicity and efficacy of SE-MESVC-4, bringing us closer to effectively combating SE infections.

Serine/Threonine Protein Kinases as Attractive Targets for Anti-Cancer Drugs-An Innovative Approach to Ligand Tuning Using Combined Quantum Chemical Calculations, Molecular Docking, Molecular Dynamic Simulations, and Network-like Similarity Graphs

Serine/threonine protein kinases (CK2, PIM-1, RIO1) are constitutively active, highly conserved, pleiotropic, and multifunctional kinases, which control several signaling pathways and regulate many cellular functions, such as cell activity, survival, proliferation, and apoptosis. Over the past decades, they have gained increasing attention as potential therapeutic targets, ranging from various cancers and neurological, inflammation, and autoimmune disorders to viral diseases, including COVID-19. Despite the accumulation of a vast amount of experimental data, there is still no "recipe" that would facilitate the search for new effective kinase inhibitors. The aim of our study was to develop an effective screening method that would be useful for this purpose. A combination of Density Functional Theory calculations and molecular docking, supplemented with newly developed quantitative methods for the comparison of the binding modes, provided deep insight into the set of desirable properties responsible for their inhibition. The mathematical metrics helped assess the distance between the binding modes, while heatmaps revealed the locations in the ligand that should be modified according to binding site requirements. The Structure-Binding Affinity Index and Structural-Binding Affinity Landscape proposed in this paper helped to measure the extent to which binding affinity is gained or lost in response to a relatively small change in the ligand's structure. The combination of the physico-chemical profile with the aforementioned factors enabled the identification of both "dead" and "promising" search directions. Tests carried out on experimental data have validated and demonstrated the high efficiency of the proposed innovative approach. Our method for quantifying differences between the ligands and their binding capabilities holds promise for guiding future research on new anti-cancer agents.

Role of death-associated protein kinase 1 (DAPK1) in retinal degenerative diseases: an in-silico approach towards therapeutic intervention

The Death-associated protein kinase 1 (DAPK1) has emerged as a crucial player in the pathogenesis of degenerative diseases. As a serine/threonine kinase family member, DAPK1 regulates critical signaling pathways, such as apoptosis and autophagy. In this study, we comprehensively analyzed DAPK1 interactors and enriched molecular functions, biological processes, phenotypic expression, disease associations, and aging signatures to elucidate the molecular networks of DAPK1. Furthermore, we employed a structure-based virtual screening approach using the PubChem database, which enabled the identification of potential bioactive compounds capable of inhibiting DAPK1, including caspase inhibitors and synthetic analogs. Three selected compounds, CID24602687, CID8843795, and CID110869998, exhibited high docking affinity and selectivity towards DAPK1, which were further investigated using molecular dynamics simulations to understand their binding patterns. Our findings establish a connection between DAPK1 and retinal degenerative diseases and highlight the potential of these selected compounds for the development of novel therapeutic strategies. This study provides valuable insights into the molecular mechanisms underlying DAPK1-related diseases, and offers new opportunities for the discovery of effective treatments for retinal degeneration.Communicated by Ramaswamy H. Sarma.

Molecular screening of phytocompounds targeting the interface between influenza A NS1 and TRIM25 to enhance host immune responses

BACKGROUND

Influenza A virus causes severe respiratory illnesses, especially in developing nations where most child deaths under 5 occur due to lower respiratory tract infections. The RIG-I protein acts as a sensor for viral dsRNA, triggering interferon production through K63-linked poly-ubiquitin chains synthesized by TRIM25. However, the influenza A virus's NS1 protein hinders this process by binding to TRIM25, disrupting its association with RIG-I and preventing downstream interferon signalling, contributing to the virus's evasion of the immune response.

METHODS

In our study we used structural-based drug designing, molecular simulation, and binding free energy approaches to identify the potent phytocompounds from various natural product databases (>100,000 compounds) able to inhibit the binding of NS1 with the TRIM25.

RESULTS

The molecular screening identified EA-8411902 and EA-19951545 from East African Natural Products Database, NA-390261 and NA-71 from North African Natural Products Database, SA-65230 and SA- 4477104 from South African Natural Compounds Database, NEA- 361 and NEA- 4524784 from North-East African Natural Products Database, TCM-4444713 and TCM-6056 from Traditional Chinese Medicines Database as top hits. The molecular docking and binding free energies results revealed that these compounds have high affinity with the specific active site residues (Leu95, Ser99, and Tyr89) involved in the interaction with TRIM25. Additionally, analysis of structural dynamics, binding free energy, and dissociation constants demonstrates a notably stronger binding affinity of these compounds with the NS1 protein. Moreover, all selected compounds exhibit exceptional ADMET properties, including high water solubility, gastrointestinal absorption, and an absence of hepatotoxicity, while adhering to Lipinski's rule.

CONCLUSION

Our molecular simulation findings highlight that the identified compounds demonstrate high affinity for specific active site residues involved in the NS1-TRIM25 interaction, exhibit exceptional ADMET properties, and adhere to drug-likeness criteria, thus presenting promising candidates for further development as antiviral agents against influenza A virus infections.

Omecamtiv mecarbil and Mavacamten target the same myosin pocket despite opposite effects in heart contraction

Inherited cardiomyopathies are common cardiac diseases worldwide, leading in the late stage to heart failure and death. The most promising treatments against these diseases are small molecules directly modulating the force produced by β-cardiac myosin, the molecular motor driving heart contraction. Omecamtiv mecarbil and Mavacamten are two such molecules that completed phase 3 clinical trials, and the inhibitor Mavacamten is now approved by the FDA. In contrast to Mavacamten, Omecamtiv mecarbil acts as an activator of cardiac contractility. Here, we reveal by X-ray crystallography that both drugs target the same pocket and stabilize a pre-stroke structural state, with only few local differences. All-atom molecular dynamics simulations reveal how these molecules produce distinct effects in motor allostery thus impacting force production in opposite way. Altogether, our results provide the framework for rational drug development for the purpose of personalized medicine.

Targeting the GPI transamidase subunit GPAA1 abrogates the CD24 immune checkpoint in ovarian cancer

CD24 is frequently overexpressed in ovarian cancer and promotes immune evasion by interacting with its receptor Siglec10, present on tumor-associated macrophages, providing a "don't eat me" signal that prevents targeting and phagocytosis by macrophages. Factors promoting CD24 expression could represent novel immunotherapeutic targets for ovarian cancer. Here, using a genome-wide CRISPR knockout screen, we identify GPAA1 (glycosylphosphatidylinositol anchor attachment 1), a factor that catalyzes the attachment of a glycosylphosphatidylinositol (GPI) lipid anchor to substrate proteins, as a positive regulator of CD24 cell surface expression. Genetic ablation of GPAA1 abolishes CD24 cell surface expression, enhances macrophage-mediated phagocytosis, and inhibits ovarian tumor growth in mice. GPAA1 shares structural similarities with aminopeptidases. Consequently, we show that bestatin, a clinically advanced aminopeptidase inhibitor, binds to GPAA1 and blocks GPI attachment, resulting in reduced CD24 cell surface expression, increased macrophage-mediated phagocytosis, and suppressed growth of ovarian tumors. Our study highlights the potential of targeting GPAA1 as an immunotherapeutic approach for CD24+ ovarian cancers.

Effects of Chrysin and Chrysin-7-sulfate on Ochratoxin A-Albumin Interactions and on the Plasma and Kidney Levels of the Mycotoxin in Rats

The nephrotoxic mycotoxin ochratoxin A (OTA) is a common food contaminant. OTA binds to the Sudlow's Site I region of serum albumin with very high affinity, resulting in its slow elimination. The displacement of OTA from albumin may be beneficial due to the faster excretion of the mycotoxin, while it may also lead to the increased tissue uptake of OTA. Furthermore, it is challenging to displace the mycotoxin from albumin even with high-affinity Site I ligands. In this study, we tested the impacts of Site I and Heme site ligands on OTA-albumin interactions by applying fluorescence spectroscopic, ultracentrifugation, and modeling studies. Chrysin-7-sulfate (C7S) strongly displaced OTA from both human and rat albumins; therefore, the impacts of C7S (single intravenous administration) and the parent flavonoid chrysin (repeated peroral treatment) were examined on the plasma and kidney levels of OTA in rats. Chrysin barely influenced the concentrations of mycotoxin in plasma and kidneys. In the first few hours, C7S significantly decreased the plasma levels of OTA compared to the control animals; while after 24 h, only minor differences were noticed. Our study highlights the superior displacing ability of C7S vs OTA regarding human and rat albumins.

Chitosan-Coated Silver Nanoparticles Inhibit Adherence and Biofilm Formation of Uropathogenic Escherichia coli

Urinary tract infections are commonly caused by uropathogenic Escherichia coli (UPEC), which usually presents multiple virulence and resistance mechanisms, making it difficult to treat. It has been demonstrated that silver and polymeric nanoparticles had potential against these pathogens. In this study, we synthesized thiol chitosan-coated silver nanoparticles (SH-Cs-AgNPs) and evaluated their antibacterial, antibiofilm and antiadherence activity against clinical isolates of UPEC. The SH-Cs-AgNPs showed a spherical shape with a size of 17.80 ± 2.67 nm and zeta potential of 18 ± 2 mV. We observed a potent antibacterial and antibiofilm activity as low as 12.5 μg/mL, as well as a reduction in the adherence of UPEC to mammalian cells at concentrations of 1.06 and 0.53 μg/mL. These findings demonstrate that SH-Cs-AgNPs have potential as a new therapeutic compound against infections caused by UPEC.

'Computational studies on coumestrol-ArlR interaction to target ArlRS signaling cascade involved in MRSA virulence'

Two component signaling system ArlRS (Autolysis-related locus) regulates adhesion, biofilm formation and virulence in methicillin resistant Staphylococcus aureus. It consists of a histidine kinase ArlS and response regulator ArlR. ArlR is composed of a N-terminal receiver domain and DNA-binding effector domain at C-terminal. ArlR receiver domain dimerizes upon signal recognition and activates DNA binding by effector domain and subsequent virulence expression. In silico simulation and structural data suggest that coumestrol, a phytochemical found in Pueraria montana, forges a strong intermolecular interaction with residues involved in dimer formation and destabilizes ArlR dimerization, an essential conformational switch required for downstream effector domain to bind to virulent loci. Structural and energy profiles of simulated ArlR-coumestrol complexes suggest lower affinity between ArlR monomers due to structural rigidity at the dimer interface hindering the conformational rearrangements relevant for dimer formation. These analyses could be an attractive strategy to develop therapeutics and potent leads molecules response regulators of two component systems in which are involved in MRSA virulence as well as other drug-resistant pathogens.Communicated by Ramaswamy H. Sarma.

A Multi-epitope Vaccine Candidate Against Bolivian Hemorrhagic fever Caused by Machupo Virus

Bolivian hemorrhagic fever (BHF) caused by Machupo virus (MACV) is a New World arenavirus having a reported mortality rate of 25-35%. The BHF starts with fever, followed by headache, and nausea which rapidly progresses to severe hemorrhagic phase within 7 days of disease onset. One of the key promoters for MACV viral entry into the cell followed by viral propagation is performed by the viral glycoprotein (GPC). GPC is post-transcriptionally cleaved into GP1, GP2 and a signal peptide. These proteins all take part in the viral infection in host body. Therefore, GPC protein is an ideal target for developing therapeutics against MACV infection. In this study, GPC protein was considered to design a multi-epitope, multivalent vaccine containing antigenic and immunogenic CTL and HTL epitopes. Different structural validations and physicochemical properties were analysed to validate the vaccine. Docking and molecular dynamics simulations were conducted to understand the interactions of the vaccine with various immune receptors. Finally, the vaccine was codon optimised in silico and along with which immune simulation studies was performed in order to evaluate the vaccine's effectiveness in triggering an efficacious immune response against MACV.

Butterfly Effect in Cytarabine: Combined NMR-NQR Experiment, Solid-State Computational Modeling, Quantitative Structure-Property Relationships and Molecular Docking Study

Cytarabine (Ara-C) is a synthetic isomer of cytidine that differs from cytidine and deoxycytidine only in the sugar. The use of arabinose instead of deoxyribose hinders the formation of phosphodiester linkages between pentoses, preventing the DNA chain from elongation and interrupting the DNA synthesis. The minor structural alteration (the inversion of hydroxyl at the 2' positions of the sugar) leads to change of the biological activity from anti-depressant and DNA/RNA block builder to powerful anti-cancer. Our study aimed to determine the molecular nature of this phenomenon. Three 1H-14N NMR-NQR experimental techniques, followed by solid-state computational modelling (Quantum Theory of Atoms in Molecules, Reduced Density Gradient and 3D Hirshfeld surfaces), Quantitative Structure-Property Relationships, Spackman's Hirshfeld surfaces and Molecular Docking were used. Multifaceted analysis-combining experiments, computational modeling and molecular docking-provides deep insight into three-dimensional packing at the atomic and molecular levels, but is challenging. A spectrum with nine lines indicating the existence of three chemically inequivalent nitrogen sites in the Ara-C molecule was recorded, and the lines were assigned to them. The influence of the structural alteration on the NQR parameters was modeled in the solid (GGA/RPBE). For the comprehensive description of the nature of these interactions several factors were considered, including relative reactivity and the involvement of heavy atoms in various non-covalent interactions. The binding modes in the solid state and complex with dCK were investigated using the novel approaches: radial plots, heatmaps and root-mean-square deviation of the binding mode. We identified the intramolecular OH···O hydrogen bond as the key factor responsible for forcing the glycone conformation and strengthening NH···O bonds with Gln97, Asp133 and Ara128, and stacking with Phe137. The titular butterfly effect is associated with both the inversion and the presence of this intramolecular hydrogen bond. Our study elucidates the differences in the binding modes of Ara-C and cytidine, which should guide the design of more potent anti-cancer and anti-viral analogues.

Structural mechanisms for VMAT2 inhibition by tetrabenazine

The vesicular monoamine transporter 2 (VMAT2) is a proton-dependent antiporter responsible for loading monoamine neurotransmitters into synaptic vesicles. Dysregulation of VMAT2 can lead to several neuropsychiatric disorders including Parkinson's disease and schizophrenia. Furthermore, drugs such as amphetamine and MDMA are known to act on VMAT2, exemplifying its role in the mechanisms of actions for drugs of abuse. Despite VMAT2's importance, there remains a critical lack of mechanistic understanding, largely driven by a lack of structural information. Here, we report a 3.1 Å resolution cryo-electron microscopy (cryo-EM) structure of VMAT2 complexed with tetrabenazine (TBZ), a non-competitive inhibitor used in the treatment of Huntington's chorea. We find TBZ interacts with residues in a central binding site, locking VMAT2 in an occluded conformation and providing a mechanistic basis for non-competitive inhibition. We further identify residues critical for cytosolic and lumenal gating, including a cluster of hydrophobic residues which are involved in a lumenal gating strategy. Our structure also highlights three distinct polar networks that may determine VMAT2 conformational dynamics and play a role in proton transduction. The structure elucidates mechanisms of VMAT2 inhibition and transport, providing insights into VMAT2 architecture, function, and the design of small-molecule therapeutics.

Proxy-approach in understanding the bisubstrate activity of strictosidine synthases

Besides tryptamine (1) and secologanin (2), non-cognate substrates also undergo a Pictet-Spengler reaction (PSR) catalyzed by strictosidine synthases (STR) with differing catalytic properties. We characterized the bisubstrate binding aspect of catalysis - order, affinity, and cooperativity - with STR orthologs from Rauvolfia serpentina (RsSTR) and Ophiorrhiza pumila (OpSTR) by an isothermal titration calorimetry (ITC) based 'proxy approach' that employed a non-reactive tryptamine analog (m1) to capture its inert ternary complexes with STRs and (2). ITC studies with OpSTR and (2) revealed 'tryptamine-first' cooperative binding with (1) and a simultaneous cooperative binding with (m1). Binding cooperativity among (m1) and (2) towards OpSTR was higher than RsSTR. Crystallographic study of RsSTR-(m1) complex helped to understand the unreactive binding of (m1) in terms of orientation and interactions in the RsSTR pocket. PSR with (m1) was revealed to be energetically unfeasible by the density functional theory (DFT) scans of the first hydrogen abstraction by RsSTR. The effect of pH on the bisubstrate binding to OpSTR was deciphered by molecular dynamics simulations (MDS), which also provided a molecular basis for the stability of complex of OpSTR with (m1) and (2). Therefore, we investigated STRs from a substrate binding perspective to inform drug-design and rational enzyme engineering efforts.

Machine learning and molecular simulation-based protocols to identify novel potential inhibitors for reverse transcriptase against HIV infections

Acquired immunodeficiency syndrome (AIDS) is a potentially fatal condition affecting the human immune system, which is attributed to the human immunodeficiency virus (HIV). The suppression of reverse transcriptase activity is a promising and feasible strategy for the therapeutic management of AIDS. In this study, we employed machine learning algorithms, such as support vector machines (SVM), k-nearest neighbor (k-NN), random forest (RF), and Gaussian naive base (GNB), which are fast and effective tools commonly used in drug design. For model training, we initially obtained a dataset of 5,159 compounds from BindingDB. The models were assessed using tenfold cross-validation to ensure their accuracy and reliability. Among these compounds, 1,645 compounds were labeled as active, having an IC50 below 0.49 µM, while 3,514 compounds were labeled "inactive against reverse transcriptase. Random forest achieved 86% accuracy on the train and test set among the different machine learning algorithms. Random forest model was then applied to an external ZINC dataset. Subsequently, only three hits-ZINC1359750464, ZINC1435357562, and ZINC1545719422-were selected based on the Lipinski Rule, docking score, and good interaction. The stability of these molecules was further evaluated by deploying molecular dynamics simulation and MM/GBSA, which were found to be -38.6013 ± 0.1103 kcal/mol for the Zidovudine/RT complex, -59.1761 ± 2.2926 kcal/mol for the ZINC1359750464/RT complex, -47.6292 ± 2.4206 kcal/mol for the ZINC1435357562/RT complex, and -50.7334 ± 2.5713 kcal/mol for the ZINC1545719422/RT complex.Communicated by Ramaswamy H. Sarma.

In silico and structural investigation of sulfonamides targeting VraSR two component system in methicillin-resistant Staphylococcus aureus

Drug-resistant Staphylococcus aureus strains are global health concerns. Several studies have shown that these strains can develop defences against cell wall antibiotics such as β-lactams, glycopeptides and daptomycin which target cell wall biosynthesis. The coordination of these responses have been associated with two component system (TCS) regulated by histidine kinase protein (VraS) and its cognate regulator VraR which influences the target DNA upon signal recognition. Computer-based screening methods, predictions and simulations have emerged as more efficient and quick ways to identify promising new compound leads from large databases against emerging drug targets thus allowing prediction of small select set of molecules for further validations. These combined approaches conserve valuable time and resources. Due to methicillin resistance, sulfonamide-derivative medications have been found to be effective treatment strategy to treat S. aureus infections. The current study used ligand-based virtual screening (LBVS) to identify powerful sulfonamide derivative inhibitors from an antibacterial compound library against VraSR signaling components, VraS and VraR. We identified promising sulfonamide derivative [compound 5: (4-[(1-{[(3,5-Dimethoxyphenyl)Carbamoyl]Methyl}-2,4-Dioxo-1,2,3,4-Tetrahydroquinazolin-3-Yl)Methyl]-N-[(Furan-2-Yl)Methyl]Benzamide)] with reasonable binding parameters of -31.38 kJ/mol and ΔGbind score of -294.32 kJ/mol against ATP binding domain of sensor kinase VraS. We further identified four compounds N1 (PCID83276726), N3 (PCID83276757), N9 (PCID3672584), and N10 (PCID20900589) against VraR DNA binding domain (VraRC) with ΔGbind energies of -190.27, -237.54, -165.21, and -190.88 kJ/mol, respectively. Structural and simulation analyses further suggest their stable interactions with DNA interacting residues and potential to disrupt DNA binding domain dimerization; therefore, it is prudent to further investigate and characterize them as VraR dimer disruptors and inhibit other promoter binding site. Interestingly, the discovery of drugs that target VraS and VraR may open new therapeutic avenues for drug-resistant S. aureus. These predictions based on screening, simulations and binding affinities against VraSR components hold promise for opening novel therapeutic avenues against drug-resistant S. aureus and present opportunities for repositioning efforts. These efforts aim to create analogs with enhanced potency and selectivity against two-component signaling systems that significantly contribute to virulence in MRSA or VRSA. These analyses contribute valuable insights into potential avenues for combating antibiotic-resistant S. aureus through computationally driven drug discovery strategies.Communicated by Ramaswamy H. Sarma.

Investigation of the potential effects of estrogen receptor modulators on immune checkpoint molecules

Immune checkpoints regulate the immune system response. Recent studies suggest that flavonoids, known as phytoestrogens, may inhibit the PD-1/PD-L1 axis. We explored the potential of estrogens and 17 Selective Estrogen Receptor Modulators (SERMs) as inhibiting ligands for immune checkpoint proteins (CTLA-4, PD-L1, PD-1, and CD80). Our docking studies revealed strong binding energy values for quinestrol, quercetin, and bazedoxifene, indicating their potential to inhibit PD-1 and CTLA-4. Quercetin and bazedoxifene, known to modulate EGFR and IL-6R alongside estrogen receptors, can influence the immune checkpoint functionality. We discuss the impact of SERMs on PD-1 and CTLA-4, suggesting that these SERMs could have therapeutic effects through immune checkpoint inhibition. This study highlights the potential of SERMs as inhibitory ligands for immune checkpoint proteins, emphasizing the importance of considering PD-1 and CTLA-4 inhibition when evaluating SERMs as therapeutic agents. Our findings open new avenues for cancer immunotherapy by exploring the interaction between various SERMs and immune checkpoint pathways.

Structural mechanisms for VMAT2 inhibition by tetrabenazine

The vesicular monoamine transporter 2 (VMAT2) is a proton-dependent antiporter responsible for loading monoamine neurotransmitters into synaptic vesicles. Dysregulation of VMAT2 can lead to several neuropsychiatric disorders including Parkinson's disease and schizophrenia. Furthermore, drugs such as amphetamine and MDMA are known to act on VMAT2, exemplifying its role in the mechanisms of actions for drugs of abuse. Despite VMAT2's importance, there remains a critical lack of mechanistic understanding, largely driven by a lack of structural information. Here we report a 3.1 Å resolution cryo-EM structure of VMAT2 complexed with tetrabenazine (TBZ), a non-competitive inhibitor used in the treatment of Huntington's chorea. We find TBZ interacts with residues in a central binding site, locking VMAT2 in an occluded conformation and providing a mechanistic basis for non-competitive inhibition. We further identify residues critical for cytosolic and lumenal gating, including a cluster of hydrophobic residues which are involved in a lumenal gating strategy. Our structure also highlights three distinct polar networks that may determine VMAT2 conformational dynamics and play a role in proton transduction. The structure elucidates mechanisms of VMAT2 inhibition and transport, providing insights into VMAT2 architecture, function, and the design of small-molecule therapeutics.

Binding order of substrate and cofactor in sulfonamide monooxygenase during sulfa drug degradation: in silico studies

For decades, sulfonamide antibiotics have been used across industries such as agriculture and animal husbandry. However, the use and inadvertent misuse of these antibiotics have resulted in the advent of sulfonamide-drug-resistant strains due to antibiotic pollution. Enzymatic bioremediation of antibiotics remains a potential emerging solution to combat antibiotic pollution. Here, we propose an enzymatic model for the degradation of sulfonamides by Microbacterium sp. We have employed a multi-pronged computational strategy involving - protein structure modelling, ligand docking and molecular dynamics simulations to decipher a plausible binding order for the enzymatic degradation of sulfonamides by the bacterial sulfonamide monooxygenase, SulX. Our results enable us to predict that this degradation is achieved through the sequential binding of the antibiotic sulfonamide followed by the reduced flavin cofactor FMNH2, thereby laying the computational foundation for further advancements in enzyme-mediated degradation of the antibiotic. We also provide a list of experiments which may be performed to verify and follow-up on our in-silico studies.Communicated by Ramaswamy H. Sarma.

Exploring the natural products chemical space to abrogate the F3L-dsRNA interface of monkeypox virus to enhance the immune responses using molecular screening and free energy calculations

Amid the ongoing monkeypox outbreak, there is an urgent need for the rapid development of effective therapeutic interventions capable of countering the immune evasion mechanisms employed by the monkeypox virus (MPXV). The evasion strategy involves the binding of the F3L protein to dsRNA, resulting in diminished interferon (IFN) production. Consequently, our current research focuses on utilizing virtual drug screening techniques to target the RNA binding domain of the F3L protein. Out of the 954 compounds within the South African natural compound database, only four demonstrated notable docking scores: -6.55, -6.47, -6.37, and -6.35 kcal/mol. The dissociation constant (KD) analysis revealed a stronger binding affinity of the top hits 1-4 (-5.34, -5.32, -5.29, and -5.36 kcal/mol) with the F3L in the MPXV. All-atom simulations of the top-ranked hits 1 to 4 consistently exhibited stable dynamics, suggesting their potential to interact effectively with interface residues. This was further substantiated through analyses of parameters such as radius of gyration (Rg), Root Mean Square Fluctuation, and hydrogen bonding. Cumulative assessments of binding free energy confirmed the top-performing candidates among all the compounds, with values of -35.90, -52.74, -28.17, and -32.11 kcal/mol for top hits 1-4, respectively. These results indicate that compounds top hit 1-4 could hold significant promise for advancing innovative drug therapies, suggesting their suitability for both in vivo and in vitro experiments.

Coevolution-based computational approach to detect resistance mechanism of epidermal growth factor receptor

Tyrosine kinase epidermal growth factor receptor (EGFR) correlates the neoplastic cell metastasis, angiogenesis, neoplastic incursion, and apoptosis. Due to the involvement of EGFR in these biological processes, it becomes a most potent target for treating non-small cell lung cancer (NSCLC). The tyrosine kinase inhibitors (TKI) have endorsed high efficacy and anticipation to patients but unfortunately, within a year of treatment, drug targets develop resistance due to mutations. The present study detected the compensatory mutations in EGFR to know the evolutionary mechanism of drug resistance. The results of this study demonstrate that compensatory mutations enlarge the drug-binding pocket which may lead to the altered orientation of the ligand (gefitinib and erlotinib) causing drug resistance. This indicates that coevolutionary forces play a significant role in fine-tuning the structure of EGFR protein against the drugs. The analysis provides insight into the evolution-induced structural aspects of drug resistance changes in EGFR which in turn be useful in designing drugs with better efficacy.

Molecular simulation for food protein-ligand interactions: A comprehensive review on principles, current applications, and emerging trends

In recent years, investigations on molecular interaction mechanisms between food proteins and ligands have attracted much interest. The interaction mechanisms can supply much useful information for many fields in the food industry, including nutrient delivery, food processing, auxiliary detection, and others. Molecular simulation has offered extraordinary insights into the interaction mechanisms. It can reflect binding conformation, interaction forces, binding affinity, key residues, and other information that physicochemical experiments cannot reveal in a fast and detailed manner. The simulation results have proven to be consistent with the results of physicochemical experiments. Molecular simulation holds great potential for future applications in the field of food protein-ligand interactions. This review elaborates on the principles of molecular docking and molecular dynamics simulation. Besides, their applications in food protein-ligand interactions are summarized. Furthermore, challenges, perspectives, and trends in molecular simulation of food protein-ligand interactions are proposed. Based on the results of molecular simulation, the mechanisms of interfacial behavior, enzyme-substrate binding, and structural changes during food processing can be reflected, and strategies for hazardous substance detection and food flavor adjustment can be generated. Moreover, molecular simulation can accelerate food development and reduce animal experiments. However, there are still several challenges to applying molecular simulation to food protein-ligand interaction research. The future trends will be a combination of international cooperation and data sharing, quantum mechanics/molecular mechanics, advanced computational techniques, and machine learning, which contribute to promoting food protein-ligand interaction simulation. Overall, the use of molecular simulation to study food protein-ligand interactions has a promising prospect.

In-silico prediction of anti-breast cancer activity of ginger (Zingiber officinale) using machine learning techniques

INTRODUCTION

Indonesian civilization extensively uses traditional medicine to cure illnesses and preserve health. The lack of knowledge on the security and efficacy of medicinal plants is still a significant concern. Although the precise chemicals responsible for this impact are unknown, ginger is a common medicinal plant in Southeast Asia that may have anticancer qualities.

METHOD

Using data from Dudedocking, a machine-learning model was created to predict possible breast anticancer chemicals from ginger. The model was used to forecast substances that block KIT and MAPK2 proteins, essential elements in breast cancer.

RESULT

Beta-carotene, 5-Hydroxy-74'-dimethoxyflavone, [12]-Shogaol, Isogingerenone B, curcumin, Trans-[10]-Shogaol, Gingerenone A, Dihydrocurcumin, and demethoxycurcumin were all superior to the reference ligand for MAPK2, according to molecular docking studies. Lycopene, [8]-Shogaol, [6]-Shogaol, and [1]-Paradol exhibited low toxicity and no Lipinski violations, but beta carotene had toxic predictions and Lipinski violations. It was anticipated that all three substances would have anticarcinogenic qualities.

CONCLUSION

Overall, this study shows the value of machine learning in drug development and offers insightful information on possible anticancer chemicals from ginger.

Rifabutin but not rifampicin can partly out-balance P-glycoprotein induction by concurrent P-glycoprotein inhibition through high affinity binding to the inhibitory site

Physiology-based pharmacokinetic modeling suggests that rifabutin can out-balance P-glycoprotein (P-gp) induction by concurrent P-gp inhibition. However, clinical or experimental evidence for this Janus-faced rifabutin effect is missing. Consequently, LS180 cells were exposed to a moderately (2 µM) and strongly (10 µM) P-gp-inducing concentration of rifampicin or rifabutin for 6 days. Cellular accumulation of the fluorescent P-gp substrate rhodamine 123 was evaluated using flow cytometry, either without (induction only) or with adding rifamycin drug to the cells during the rhodamine 123 efflux phase (induction + potential inhibition). Rhodamine 123 accumulation was decreased similarly by both drugs after 6-day exposure (2 µM: 55% residual fluorescence compared to non-induced cells, P < 0.01; 10 µM: 30% residual fluorescence compared to non-induced cells, P < 0.001), indicating P-gp induction. Rhodamine 123 influx transporters mRNA expressions were not affected, excluding off-target effects. Acute re-exposure to rifabutin, however, considerably re-increased rhodamine 123 accumulation (2 µM induction: re-increase by 55%, P < 0.01; 10 µM induction: 49% re-increase, P < 0.001), suggesting P-gp inhibition. In contrast, rifampicin only had weak effects (2 µM induction: no re-increase; 10 µM induction: 16% re-increase; P < 0.05). Molecular docking analysis eventually revealed that rifabutin has a higher binding affinity to the inhibitor binding site of P-gp than rifampicin (ΔG (kcal/mol) = -11.5 vs -5.3). Together, this study demonstrates that rifabutin can at least partly mask P-gp induction by P-gp inhibition, mediated by high affinity binding to the inhibitory site of P-gp.

Promiscuous Yet Specific: A Methionine-Aromatic Interaction Drives the Reaction Scope of the Family 1 Glycosyltransferase GmUGT88E3 from Soybean

Family 1 glycosyltransferases (GT1s, UGTs) catalyze the regioselective glycosylation of natural products in a single step. We identified GmUGT88E3 as a particularly promising biocatalyst able to produce a variety of pure, single glycosidic products from polyphenols with high chemical yields. We investigated this particularly desirable duality toward specificity, i.e., promiscuous toward acceptors while regiospecific. Using high-field NMR, kinetic characterization, molecular dynamics simulations, and mutagenesis studies, we uncovered that the main molecular determinant of GmUGT88E3 specificity is a methionine-aromatic bridge, an interaction often present in protein structures but never reported for enzyme-substrate interactions. Here, mutating Met127 led to inactive proteins or 100-fold reduced activity.

Computational Screening of Neuropilin-1 Unveils Novel Potential Anti-SARS-CoV-2 Therapeutics

Neuropilin 1 (NRP-1) inhibition has shown promise in reducing the infectivity of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and preventing the virus entry into nerve tissues, thereby mitigating neurological symptoms in COVID-19 patients. In this study, we employed virtual screening, including molecular docking, Molecular Dynamics (MD) simulation, and Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculations, to identify potential NRP-1 inhibitors. From a compendium of 1930 drug-like natural compounds, we identified five potential leads: CNP0435132, CNP0435311, CNP0424372, CNP0429647, and CNP0427474, displaying robust binding energies of -8.2, -8.1, -10.7, -8.2, and -8.2 kcal/mol, respectively. These compounds demonstrated interactions with critical residues Tyr297, Trp301, Thr316, Asp320, Ser346, Thr349, and Tyr353 located within the b1 subdomain of NRP-1. Furthermore, MD simulations and MM-PBSA calculations affirmed the stability of the complexes formed, with average root mean square deviation, radius of gyration, and solvent accessible surface area values of 0.118 nm, 1.516 nm, and 88.667 nm2 , respectively. Notably, these lead compounds were estimated to penetrate the blood-brain barrier and displayed antiviral properties, with Pa values ranging from 0.414 to 0.779. The antagonistic effects of these lead compounds merit further investigation, as they hold the potential to serve as foundational scaffolds for the development of innovative therapeutics aimed at reducing the neuroinfectivity of SARS-CoV-2.

Exploring potent aldose reductase inhibitors for anti-diabetic (anti-hyperglycemic) therapy: integrating structure-based drug design, and MMGBSA approaches

Aldose reductase (AR) is an important target in the development of therapeutics against hyper-glycemia-induced health complications such as retinopathy, etc. In this study, we employed a combination of structure-based drug design, molecular simulation, and free energy calculation approaches to identify potential hit molecules against anti-diabetic (anti-hyperglycemic)-induced health complications. The 3D structure of aldoreductase was screened for multiple compound libraries (1,00,000 compounds) and identified as ZINC35671852, ZINC78774792 from the ZINC database, Diamino-di nitro-methyl dioctyl phthalate, and Penta-o-galloyl-glucose from the South African natural compounds database, and Bisindolylmethane thiosemi-carbazides and Bisindolylme-thane-hydrazone from the Inhouse database for this study. The mode of binding interactions of the selected compounds later predicted their aldose reductase inhibitory potential. These com-pounds interact with the key active site residues through hydrogen bonds, salt bridges, and π-π interactions. The structural dynamics and binding free energy results further revealed that these compounds possess stable dynamics with excellent binding free energy scores. The structures of the lead inhibitors can serve as templates for developing novel inhibitors, and in vitro testing to confirm their anti-diabetic potential is warranted. The current study is the first to design small molecule inhibitors for the aldoreductase protein that can be used in the development of therapeutic agents to treat diabetes.

Stereoselective Voltammetric Biosensor for Myo-Inositol and D-Chiro-Inositol Recognition

This paper describes the development of a simple voltammetric biosensor for the stereoselective discrimination of myo-inositol (myo-Ins) and D-chiro-inositol (D-chiro-Ins) by means of bovine serum albumin (BSA) adsorption onto a multi-walled carbon nanotube (MWCNT) graphite screen-printed electrode (MWCNT-GSPE), previously functionalized by the electropolymerization of methylene blue (MB). After a morphological characterization, the enantioselective biosensor platform was electrochemically characterized after each modification step by differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS). The results show that the binding affinity between myo-Ins and BSA was higher than that between D-chiro-Ins and BSA, confirming the different interactions exhibited by the novel BSA/MB/MWCNT/GSPE platform towards the two diastereoisomers. The biosensor showed a linear response towards both stereoisomers in the range of 2-100 μM, with LODs of 0.5 and 1 μM for myo-Ins and D-chiro-Ins, respectively. Moreover, a stereoselectivity coefficient α of 1.6 was found, with association constants of 0.90 and 0.79, for the two stereoisomers, respectively. Lastly, the proposed biosensor allowed for the determination of the stereoisomeric composition of myo-/D-chiro-Ins mixtures in commercial pharmaceutical preparations, and thus, it is expected to be successfully applied in the chiral analysis of pharmaceuticals and illicit drugs of forensic interest.

Omecamtiv mecarbil and Mavacamten target the same myosin pocket despite antagonistic effects in heart contraction

Inherited cardiomyopathies are amongst the most common cardiac diseases worldwide, leading in the late-stage to heart failure and death. The most promising treatments against these diseases are small-molecules directly modulating the force produced by β-cardiac myosin, the molecular motor driving heart contraction. Two of these molecules that produce antagonistic effects on cardiac contractility have completed clinical phase 3 trials: the activator Omecamtiv mecarbil and the inhibitor Mavacamten. In this work, we reveal by X-ray crystallography that both drugs target the same pocket and stabilize a pre-stroke structural state, with only few local differences. All atoms molecular dynamics simulations reveal how these molecules can have antagonistic impact on the allostery of the motor by comparing β-cardiac myosin in the apo form or bound to Omecamtiv mecarbil or Mavacamten. Altogether, our results provide the framework for rational drug development for the purpose of personalized medicine.

Selective modifications of lactose and N-acetyllactosamine with sulfate and aromatic bulky groups unveil unique structural insights in galectin-1-ligand recognition

Galectins, a family of endogenous glycan-binding proteins, play crucial roles in a broad range of physiological and pathological processes. Galectin-1 (Gal-1), a proto-type member of this family, is overexpressed in several cancers and plays critical roles in tumor-immune escape, angiogenesis and metastasis. Thus, generation of high-affinity Gal-1 inhibitors emerges as an attractive therapeutic approach for a wide range of neoplastic conditions. Small-molecule carbohydrate inhibitors based on lactose (Lac) and N-acetyllactosamine (LacNAc) structures have been tested showing different results. In this study, we evaluated Lac- and LacNAc-based compounds with specific chemical modifications at key positions as Gal-1 ligands by competitive solid-phase assays (SPA) and isothermal titration calorimetry (ITC). Both assays showed excellent correlation, highlighting that lactosides bearing bulky aromatic groups at the anomeric carbon and sulfate groups at the O3' position exhibited the highest binding affinities. To dissect the atomistic determinants for preferential affinity of the different tested Gal-1 ligands, molecular docking simulations were conducted and PRODIGY-LIG structure-based method was employed to predict binding affinity in protein-ligand complexes. Notably, calculated binding free energies derived from the molecular docking were in accordance with experimental values determined by SPA and ITC, showing excellent correlation between theoretical and experimental approaches. Moreover, this analysis showed that 3'-O-sulfate groups interact with residues of the Gal-1 subsite B, mainly with Asn33, while the ester groups of the aromatic anomeric group interact with Gly69 and Thr70 at Gal-1 subsite E, extending deeper into the pocket, which could account for the enhanced binding affinity. This study contributes to the rational design of highly optimized Gal-1 inhibitors to be further studied in cancer models and other pathologic conditions.

Herbal Compounds Dauricine and Isoliensinine Impede SARS-CoV-2 Viral Entry

Targeting viral entry has been the focal point for the last 3 years due to the continued threat posed by SARS-CoV-2. SARS-CoV-2's entry is highly dependent on the interaction between the virus's Spike protein and host receptors. The virus's Spike protein is a key modulator of viral entry, allowing sequential cleavage of ACE2 at the S1/S2 and S2 sites, resulting in the amalgamation of membranes and subsequent entry of the virus. A Polybasic insertion (PRRAR) conveniently located at the S1/S2 site can also be cleaved by furin or by serine protease, TMPRSS2, at the cell surface. Since ACE2 and TMPRSS2 are conveniently located on the surface of host cells, targeting one or both receptors may inhibit receptor-ligand interaction. Here, we show that Dauricine and Isoliensinine, two commonly used herbal compounds, were capable of inhibiting SARS-CoV-2 viral entry by reducing Spike-ACE2 interaction but not suppressing TMPRSS2 protease activity. Further, our biological assays using pseudoviruses engineered to express Spike proteins of different variants revealed a reduction in infection rates following treatment with these compounds. The molecular modeling revealed an interconnection between R403 of Spike protein and both two compounds. Spike mutations at residue R403 are critical, and often utilized by ACE2 to gain cell access. Overall, our findings strongly suggest that Dauricine and Isoliensinine are effective in blocking Spike-ACE2 interaction and may serve as effective therapeutic agents for targeting SARS-CoV-2's viral entry.

In silico pharmacological study of AQP2 inhibition by steroids contextualized to Ménière's disease treatments

Ménière's disease (MD) is characterized by an abnormal dilatation of the endolymphatic compartment called endolymphatic hydrops and is associated with fluctuating hearing losses and vertigo. Corticosteroid treatment is typically administered for its anti-inflammatory effects to MD patients. However, we recently described for the first time a direct interaction of two corticosteroids (dexamethasone and cortisol) with human AQP2 which strongly inhibited water fluxes. From these initial studies, we proposed an AQPs Corticosteroids Binding Site (ACBS). In the present work, we tested the interaction of 10 molecules associated to the steroid family for this putative ACBS. We observed a wide diversity of affinity and inhibitory potential of these molecules toward AQP2 and discussed the implications for inner ear physiology. Among the tested compounds, cholecalciferol, calcitriol and oestradiol were the most efficient AQP2 water permeability inhibitors.

Exploring the impact of CYP11A1's missense SNPs on the interaction between CYP11A1 and cholesterol: A comprehensive structural analysis and MD simulation study

The process of steroidogenesis plays a vital role in human physiology as it governs the biosynthesis of mineralocorticoids, glucocorticoids, and androgens. These three classes of steroid hormones are primarily produced in the adrenal and gonadal glands through steroidogenesis pathways. Initiated by the side chain cleavage of cholesterol (CLR), this process leads to the conversion of cholesterol into pregnenolone and isocaproic aldehyde. The enzyme CYP11A1, encoded by the CYP11A1 gene, plays a key role in catalyzing the side chain cleavage of CLR. Several single nucleotide polymorphisms (SNPs) have been identified in the CYP11A1 gene, which may predispose carriers to disorders associated with abnormal steroidogenesis. Specifically, missense SNPs in the CYP11A1 gene have the potential to negatively impact the interaction between CYP11A1 and CLR, thus affecting the overall metabolome of steroid hormones. In this computational study, we focused on a specific set of missense SNPs reported in the CYP11A1 gene, aiming to identify variants that directly impact the interaction between CYP11A1 and CLR. The three-dimensional structure of the CYP11A1-CLR complex was obtained from the RCSB Protein Data Bank, while missense SNPs in the CYP11A1 gene were retrieved from Ensembl. To predict the most deleterious variants, we utilized the ConSurf server, SIFT, and PolyPhen. Furthermore, we assessed the impact of induced amino acid (AA) substitutions on the CYP11A1-CLR interaction using the PRODIGY server, PyMol, and Ligplot programs. Additionally, molecular dynamics (MD) simulations were conducted to analyze the effects of deleterious variants on the structural dynamics of the CYP11A1-CLR complex. Among the 8096 retrieved variants, we identified ten missense SNPs (E91K, W147G, R151W, R151Q, S391C, V392M, Q395K, Q416E, R460W, and R460Q) as deleterious for the interaction between CYP11A1 and CLR. MD simulations of the CYP11A1-CLR complexes carrying these deleterious AA substitutions revealed that Q416E, W147G, R460Q, and R460W had the most pronounced impacts on the structural dynamics of the complex. Consequently, these missense SNPs were considered the most deleterious ones. Further functional tests are recommended to assess the impact of these four missense SNPs on the enzymatic activity of CYP11A1. Moreover, Genome-Wide Association Studies (GWAS) should be conducted to determine the significance of their association with abnormal steroidogenesis diseases in various patient groups.

Identification of small molecule modulators of class II transactivator-I using computational approaches

Major histocompatibility complex II (MHCII), a mediator of the innate and adaptive immune system, plays a central role in regulating inflammation and its progression. Class II transactivator (CIITA) is a master regulator of MHCII expression and controls antigen presentation followed by T-cell activation. Regulation of inflammation by modulation of CIITA has been suggested as a promising intervention for several disorders, including neuroinflammation, rheumatoid arthritis and other autoimmune diseases. This study aimed to (i) identify possible pharmacological agents which could bind to and inhibit isoform I of CIITA (CIITA-I) and (ii) determine their strength of interactions. The structure of CIITA-I isoform was predicted using phyre2 and refined via 3D refine. Loops were refined using ModBase, followed by quality assessment based on ERRAT value. The refined 3D structure was subjected to docking via Maestro (from Schrodinger) using glide module against small molecule databases. Molecules having the least glide score and favorable ADME properties were subjected to molecular simulation by GROMACS. We used the 3D refined structure of CIITA-I, with a score of 83.4% in ERRAT for docking studies. The ligand 4-(2-((6-oxo-4-phenyl-1,6-dihydropyrimidin-2-yl) thio) acetamido) benzamide (ZINC5154833), showed maximum glide score (-6.591) followed by N-[4-(3-oxo-3-{4-[3-(trifluoromethyl) phenyl] piperazin-1-yl} propyl)-1,3-thiazol-2-yl] benzamide (F5254-0161, glide score -6.41). Simulation studies using GROMACS showed F5254-0161 to have a more stable interaction with CIITA-I. Based on our analysis, we propose ZINC5154833 and F5254-0161 as potential modulators for CIITA-I.Communicated by Ramaswamy H. Sarma.

The lipoprotein-associated phospholipase A2 inhibitor Darapladib sensitises cancer cells to ferroptosis by remodelling lipid metabolism

Arachidonic and adrenic acids in the membrane play key roles in ferroptosis. Here, we reveal that lipoprotein-associated phospholipase A2 (Lp-PLA2) controls intracellular phospholipid metabolism and contributes to ferroptosis resistance. A metabolic drug screen reveals that darapladib, an inhibitor of Lp-PLA2, synergistically induces ferroptosis in the presence of GPX4 inhibitors. We show that darapladib is able to enhance ferroptosis under lipoprotein-deficient or serum-free conditions. Furthermore, we find that Lp-PLA2 is located in the membrane and cytoplasm and suppresses ferroptosis, suggesting a critical role for intracellular Lp-PLA2. Lipidomic analyses show that darapladib treatment or deletion of PLA2G7, which encodes Lp-PLA2, generally enriches phosphatidylethanolamine species and reduces lysophosphatidylethanolamine species. Moreover, combination treatment of darapladib with the GPX4 inhibitor PACMA31 efficiently inhibits tumour growth in a xenograft model. Our study suggests that inhibition of Lp-PLA2 is a potential therapeutic strategy to enhance ferroptosis in cancer treatment.

Targeting SARS-CoV-2 Macrodomain-1 to Restore the Innate Immune Response Using In Silico Screening of Medicinal Compounds and Free Energy Calculation Approaches

Among the different drug targets of SARS-CoV-2, a multi-domain protein known as NSP3 is a critical element of the translational and replication machinery. The macrodomain-I, in particular, has been reported to have an essential role in the viral attack on the innate immune response. In this study, we explore natural medicinal compounds and identify potential inhibitors to target the SARS-CoV-2-NSP3 macrodomain-I. Computational modeling and simulation tools were utilized to investigate the structural-dynamic properties using triplicates of 100 ns MD simulations. In addition, the MM/GBSA method was used to calculate the total binding free energy of each inhibitor bound to macrodomain-I. Two significant hits were identified: 3,5,7,4'-tetrahydroxyflavanone 3'-(4-hydroxybenzoic acid) and 2-hydroxy-3-O-beta-glucopyranosyl-benzoic acid. The structural-dynamic investigation of both compounds with macrodomain-I revealed stable dynamics and compact behavior. In addition, the total binding free energy for each complex demonstrated a robust binding affinity, of ΔG -61.98 ± 0.9 kcal/mol for Compound A, while for Compound B, the ΔG was -45.125 ± 2.8 kcal/mol, indicating the inhibitory potential of these compounds. In silico bioactivity and dissociation constant (KD) determination for both complexes further validated the inhibitory potency of each compound. In conclusion, the aforementioned natural products have the potential to inhibit NSP3, to directly rescue the host immune response. The current study provides the basis for novel drug development against SARS-CoV-2 and its variants.

Non-target biotransformation enzymes as a target for triazole-zinc mixtures

Triazoles inhibit lanosterol 14α-demethylase and block ergosterol biosynthesis in fungal pathogens. However, they also interact with other cytochrome P450 enzymes and influence non-target metabolic pathways. Disturbingly, triazoles may interact with essential elements. The interaction of penconazole (Pen), cyproconazole (Cyp) and tebuconazole (Teb) with Zn2+ results in the formation of deprotonated ligands in their complexes or in the creation of complexes with Cl- as a counterion or doubly charged complexes. Triazoles, as well as their equimolar cocktails with Zn2+ (10-6 mol/L), decreased the activities of the non-target enzymes CYP19A1 and CYP3A4. Pen most decreased CYP19A1 activity and was best bound to its active centre to block the catalytic cycle in computational analysis. For CYP3A4, Teb was found to be the most effective inhibitor by both, activity assay and interaction with the active centre. Teb/Cyp/Zn2+ and Teb/Pen/Cyp/Zn2+ cocktails also decreased the CYP19A1 activity, which was in correlation with the formation of numerous triazole-Zn2+ complexes.

An in silico insight on the mechanistic aspects of gelsenicine toxicity: A reverse screening study pointing to the possible involvement of acetylcholine binding receptor

Gelsedine-type alkaloids are highly toxic plant secondary metabolites produced by shrubs belonging to the Gelsemium genus. Gelsenicine is one of the most concerning gelsedine-type alkaloids with a lethal dose lower than 1 mg/Kg in mice. Several reported episodes of poisoning in livestock and fatality cases in humans due to the usage of Gelsemium plants extracts were reported. Also, gelsedine-type alkaloids were found in honey constituting a potential food safety issue. However, their toxicological understanding is scarce and the molecular mechanism underpinning their toxicity needs further investigations. In this context, an in silico approach based on reverse screening, docking and molecular dynamics successfully identified a possible gelsenicine biological target shedding light on its toxicodynamics. In line with the available crystallographic data, it emerged gelsenicine could target the acetylcholine binding protein possibly acting as a partial agonist against α7 nicotinic acetylcholine receptor (AChR). Overall, these results agreed with evidence previously reported and prioritized AChR for further dedicated analysis.

An in-silico approach to the potential modulatory effect of taurine on sclerostin (SOST) and its probable role during osteoporosis

The cysteine-knot containing negative regulator of the Wnt (Wingless-related integration site) signaling pathway, sclerostin (SOST) is an emerging therapeutic target for osteoporosis. Its inhibition is responsible for the promotion of osteoblastogenesis. In this study, taurine, an amino sulfonic acid was used to study its mechanism of action for the inhibition of the SOST protein. Molecular docking and dynamic studies were performed as a part of the study whereby, it was observed that taurine binds to a probable allosteric pocket which allows it to modulate the structure of the SOST protein affecting all of the loops - loops 1, loop 2, and loop 3 - as well as the cysteine residues forming the cysteine-knot. The study also identified a set of seven taurine analogues that have better pharmacological activity than their parent compound using screening techniques. The conclusions derived from the study support that taurine has a probable antagonistic effect on the SOST protein directly through the modulation of HNQS motif and loops 2 and 3 and indirectly through its influence on the cysteine residues - 134, 165 and 167 C. Based on the results, it can be assumed that the binding of taurine with SOST protein probably reduces its binding affinity to the LRP6 protein greatly, while also inhibiting the target protein from anchoring to LRP4. Furthermore, it was noted that probable additional binding with any small molecule inhibitor (SMI) at the active site (PNAIG motif), in the presence of an already allosterically bound taurine, of the SOST protein would result in a complete potential antagonism of the target protein. Additionally, the study also uncovers the possible role of the GKWWRPS motif in providing stability to the PNAIG motif for the purpose of binding with LRP6.Communicated by Ramaswamy H. Sarma.

Exploring the Traditional Chinese Medicine (TCM) database chemical space to target I7L protease from monkeypox virus using molecular screening and simulation approaches

In the current study, we used molecular screening and simulation approaches to target I7L protease from monkeypox virus (mpox) from the Traditional Chinese Medicines (TCM) database. Using molecular screening, only four hits TCM27763, TCM33057, TCM34450 and TCM31564 demonstrated better pharmacological potential than TTP6171 (control). Binding of these molecules targeted Trp168, Asn171, Arg196, Cys237, Ser240, Trp242, Glu325, Ser326, and Cys328 residues and may affect the function of I7L protease in in vitro assay. Moreover, molecular simulation revealed stable dynamics, tighter structural packing and less flexible behaviour for all the complexes. We further reported that the average hydrogen bonds in TCM27763, TCM33057, TCM34450 and TCM31564I7L complexes remained higher than the control drug. Finally, the BF energy results revealed -62.60 ± 0.65 for the controlI7L complex, for the TCM27763I7L complex -71.92 ± 0.70 kcal/mol, for the TCM33057I7L complex the BF energy was -70.94 ± 0.70 kcal/mol, for the TCM34450I7L the BF energy was -69.94 ± 0.85 kcal/mol while for the TCM31564I7L complex the BF energy was calculated to be -69.16 ± 0.80 kcal/mol. Although, we used stateoftheart computational methods, these are theoretical insights that need further experimental validation.

In Silico Identification of Potential Inhibitors of the SARS-CoV-2 Main Protease among a PubChem Database of Avian Infectious Bronchitis Virus 3CLPro Inhibitors

Remarkable structural homologies between the main proteases of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the avian infectious bronchitis virus (IBV) were revealed by comparative amino-acid sequence and 3D structural alignment. Assessing whether reported IBV 3CLPro inhibitors could also interact with SARS-CoV-2 has been undertaken in silico using a PubChem BioAssay database of 388 compounds active on the avian infectious bronchitis virus 3C-like protease. Docking studies of this database on the SARS-CoV-2 protease resulted in the identification of four covalent inhibitors targeting the catalytic cysteine residue and five non-covalent inhibitors for which the binding was further investigated by molecular dynamics (MD) simulations. Predictive ADMET calculations on the nine compounds suggest promising pharmacokinetic properties.

Computational design of medicinal compounds to inhibit RBD-hACE2 interaction in the Omicron variant: unveiling a vulnerable target site

The COVID-19 pandemic, caused by SARS-CoV-2, has globally affected both human health and economy. Several variants with a high potential for reinfection and the ability to evade immunity were detected shortly after the initial reported case of COVID-19. A total of 30 mutations in the spike protein (S) have been reported in the SARS-CoV-2 (BA.2) variant in India and South Africa, while half of these mutations are in the receptor-binding domain and have spread rapidly throughout the world. Drug repurposing offers potential advantages over the discovery of novel drugs, and one is that it can be delivered quickly without lengthy assessments and time-consuming clinical trials. In this study, computational drug design, such as pharmacophore-based virtual screening and MD simulation has been concentrated, in order to find a novel small molecular inhibitor that prevents hACE2 from binding to the receptor binding domain (RBD). three medicinal compound databases: North-East African, North African, and East African were screened and carried out a multi-step screening approach that identified three compounds, which are thymoquinol 2-O-beta-glucopyranoside (C1), lanneaflavonol (C2), and naringenin-4'-methoxy-7-O-Alpha-L-rhamnoside (C3), with excellent anti-viral properties against the RBD of the omicron variant. Furthermore, PAIN assay interference, computation bioactivity prediction, binding free energy, and dissociation constant were used to validate the top hits, which indicated good antiviral activity. The three compounds that were found may be useful against COVID-19, though more research is required. These findings could aid the development of novel therapeutic drugs against the emerging Omicron variant of SARS-CoV-2.

Genomic variability correlates with biofilm phenotypes in multidrug resistant clinical isolates of Pseudomonas aeruginosa

The multifactorial nature of Pseudomonas aeruginosa biofilm development and genomic variabilities implicates its resistance to conventional antimicrobials and virulence. Therefore, genetic determinants need to be extensively studied to block the early steps of biofilm or already formed biofilms. In this study, a total of 20 multidrug resistant (MDR) clinical P. aeruginosa isolates were evaluated for their biofilm forming abilities and related genes. Of the isolates tested, all of them showed surface attachment tendencies in nutrient limiting conditions, and classified as strong (SBF = 45%), moderate (MBF = 30%) and weak (WBF = 25%) biofilm formers. Complete genome sequencing of representative strong (DMC-27b), moderate (DMC-20c) and weak biofilm former (DMC-30b) isolates was performed. Analysis of biofilm related genes in the sequenced genomes revealed that, 80 of the 88 biofilm related genes possess 98-100% sequence identity to the reference PAO1 strain. Complete and partial sequence data of LecB proteins from tested isolates indicate that isolates containing PA14-like LecB sequences produced strong biofilms. All of the 7 pel operon protein coding genes in weak biofilm former isolate 30b showed significant nucleotide sequence variation with other tested isolates, and their corresponding proteins are 99% identical with the pel operon proteins of PA7. Bioinformatics analyses identified divergent sequence and structural features that separate PA7 like pel operon proteins from reference PAO1-like pel operon. Congo red and pellicle forming assays revealed that the sequence and structure variations may have interfered with the Pel production pathway and resulted in impaired Pel production in isolate 30b that has a PA7 like pel operon. Expression analysis also showed that both pelB and lecB genes were about 5 to 6 folds upregulated after 24 h in SBF 27b in comparison with WBF 30b. Our findings indicate significant genomic divergence in biofilm related genes of P. aeruginosa strains that affect their biofilm phenotypes.

Balancing Functional Tradeoffs between Protein Stability and ACE2 Binding in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB Lineages: Dynamics-Based Network Models Reveal Epistatic Effects Modulating Compensatory Dynamic and Energetic Changes

Evolutionary and functional studies suggested that the emergence of the Omicron variants can be determined by multiple fitness trade-offs including the immune escape, binding affinity for ACE2, conformational plasticity, protein stability and allosteric modulation. In this study, we systematically characterize conformational dynamics, structural stability and binding affinities of the SARS-CoV-2 Spike Omicron complexes with the host receptor ACE2 for BA.2, BA.2.75, XBB.1 and XBB.1.5 variants. We combined multiscale molecular simulations and dynamic analysis of allosteric interactions together with the ensemble-based mutational scanning of the protein residues and network modeling of epistatic interactions. This multifaceted computational study characterized molecular mechanisms and identified energetic hotspots that can mediate the predicted increased stability and the enhanced binding affinity of the BA.2.75 and XBB.1.5 complexes. The results suggested a mechanism driven by the stability hotspots and a spatially localized group of the Omicron binding affinity centers, while allowing for functionally beneficial neutral Omicron mutations in other binding interface positions. A network-based community model for the analysis of epistatic contributions in the Omicron complexes is proposed revealing the key role of the binding hotspots R498 and Y501 in mediating community-based epistatic couplings with other Omicron sites and allowing for compensatory dynamics and binding energetic changes. The results also showed that mutations in the convergent evolutionary hotspot F486 can modulate not only local interactions but also rewire the global network of local communities in this region allowing the F486P mutation to restore both the stability and binding affinity of the XBB.1.5 variant which may explain the growth advantages over the XBB.1 variant. The results of this study are consistent with a broad range of functional studies rationalizing functional roles of the Omicron mutation sites that form a coordinated network of hotspots enabling a balance of multiple fitness tradeoffs and shaping up a complex functional landscape of virus transmissibility.

In silico study on evaluation of corosolic acid of Lagerstroemia speciosa against Alzheimer’s disease

Purpose

Alzheimer’s disease (AD), the most common cause of dementia, is a neurodegenerative disorder caused by the aggregation of amyloid-beta (Aβ) at outside of neuron cells and also due to tau aggregation inside the cell. Corosolic acid is aimed to be selected as a main active constituent of Lagerstroemia speciosa for the study.

Design/methodology/approach

In the present study, molecular docking of corosolic acid and tau protein was examined using PyRx-v.0.8 software. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties were described and a molecular dynamics study of the bound complex was performed using Desmond.

Findings

The docking score and interactions suggested that the corosolic acid (CID:6918774) could bind to tau protein to prevent the fibrillar network, to prevent AD. During simulation corosolic acid-bound protein root mean square deviation (RMSD) values showed more stability when compared to the Apo form of protein. Molecular dynamics study of tau protein and corosolic acid complex gave the insights to develop a drug-like candidate against AD.

Originality/value

The use of corosolic acid of Lagerstroemia speciosa to prevent AD is supported by preliminary analysis on a computational basis. This compound should explore in terms of experimental strategies for the further drug development process. However, in vitro and in vivo evaluation studies are required to suggest the use of corosolic acid against AD.

Structure-based design of promising natural products to inhibit thymidylate kinase from Monkeypox virus and validation using free energy calculations

Monkeypox (MPXV) is a globally growing public health concern with 80,328 active cases and 53 deaths have been reported. No specific vaccine or drug is available for the treatment of MPXV. Hence, the current study also employed structure-based drug designing, molecular simulation, and free energy calculation methods to identify potential hit molecules against the TMPK of MPXV, which is a replicatory protein that helps the virus to replicate its DNA and increase the number of DNAs in the host cell. The 3D structure of TMPK was modeled with AlphaFold and screening of multiple natural products libraries (4,71,470 compounds) identified TCM26463, TCM2079, and TCM29893 from traditional Chinese medicines database (TCM), SANC00240, SANC00984, and SANC00986 South African natural compounds database (SANCDB), NPC474409, NPC278434 and NPC158847 from NPASS (natural product activity and species source database) while CNP0404204, CNP0262936, and CNP0289137 were shortlisted from coconut database (collection of open natural products) as the best hits. These compounds interact with the key active site residues through hydrogen bonds, salt bridges, and pie-pie interactions. The structural dynamics and binding free energy results further revealed that these compounds possess stable dynamics with excellent binding free energy scores. Moreover, the dissociation constant (K_D) and bioactivity analysis revealed stronger activity of these compounds exhibit stronger biological activity against MPXV and may inhibit it in in vitro conditions. All the results demonstrated that the designed novel compounds possess stronger inhibitory activity than the control complex (TPD-TMPK) from the vaccinia virus. The current study is the first to design small molecule inhibitors for the replication protein of MPXV which may help in controlling the current epidemic and also overcome the challenge of vaccine evasion.

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.

Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins

The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies in silico. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body.Communicated by Ramaswamy H. Sarma.

Machine learning and molecular simulation ascertain antimicrobial peptide against Klebsiella pneumoniae from public database

Antimicrobial peptides (AMPs) are short peptides with a broad spectrum of antimicrobial activity. They play a key role in the host innate immunity of many organisms. The growing threat of microorganisms resistant to antimicrobial agents and the lack of new commercially available antibiotics have made in silico discovery of AMPs increasingly important. Machine learning (ML) has improved the speed and efficiency of AMP discovery while reducing the cost of experimental approaches. Despite various ML platforms developed, there is still a lack of integrative use of ML platforms for AMP discovery from publicly available protein databases. Therefore, our study aims to screen potential AMPs with antibiofilm properties from databases using ML platforms, followed by protein-peptide molecular docking analysis and molecular dynamics (MD) simulations. A total of 5850 peptides classified as non-AMP were screened from UniProtKB and analyzed using various online ML platforms (e.g., CAMPr3, DBAASP, dPABBs, Hemopred, and ToxinPred). Eight potential AMP peptides against Klebsiella pneumoniae with antibiofilm, non-toxic and non-hemolytic properties were then docked to MrkH, a transcriptional regulator of type 3 fimbriae involved in biofilm formation. Five of eight peptides bound more strongly than the native MrkH ligand when analyzed using HADDOCK and HPEPDOCK. Following the docking studies, our MD simulated that a Neuropeptide B (Peptide 3) bind strongly to the MrkH active sites. The discovery of putative AMPs that exceed the binding energies of the native ligand underscores the utility of the combined ML and molecular simulation strategies for discovering novel AMPs with antibiofilm properties.

SARS-CoV-2 proteases Mpro and PLpro: Design of inhibitors with predicted high potency and low mammalian toxicity using artificial neural networks, ligand-protein docking, molecular dynamics simulations, and ADMET calculations

The main (Mpro) and papain-like (PLpro) proteases are highly conserved viral proteins essential for replication of the COVID-19 virus, SARS-COV-2. Therefore, a logical plan for producing new drugs against this pathogen is to discover inhibitors of these enzymes. Accordingly, the goal of the present work was to devise a computational approach to design, characterize, and select compounds predicted to be potent dual inhibitors - effective against both Mpro and PLpro. The first step employed LigDream, an artificial neural network, to create a virtual ligand library. Ligands with computed ADMET profiles indicating drug-like properties and low mammalian toxicity were selected for further study. Initial docking of these ligands into the active sites of Mpro and PLpro was done with GOLD, and the highest-scoring ligands were redocked with AutoDock Vina to determine binding free energies (ΔG). Compounds 89-00, 89-07, 89-32, and 89-38 exhibited favorable ΔG values for Mpro (-7.6 to -8.7 kcal/mol) and PLpro (-9.1 to -9.7 kcal/mol). Global docking of selected compounds with the Mpro dimer identified prospective allosteric inhibitors 89-00, 89-27, and 89-40 (ΔG -8.2 to -8.9 kcal/mol). Molecular dynamics simulations performed on Mpro and PLpro active site complexes with the four top-scoring ligands from Vina demonstrated that the most stable complexes were formed with compounds 89-32 and 89-38. Overall, the present computational strategy generated new compounds with predicted drug-like characteristics, low mammalian toxicity, and high inhibitory potencies against both target proteases to form stable complexes. Further preclinical studies will be required to validate the in silico findings before the lead compounds could be considered for clinical trials.