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Sirtuin 2 (SIRT2), an NAD+-dependent deacetylase, is crucial for regulating vital physiological processes, including aging, DNA repair, and cell cycle progression. Its abnormal activity is linked to diseases such as Parkinson's disease, cancer, and metabolic disorders, making it a potential target for therapeutic intervention. While small molecule inhibitors have been studied, peptide-based inhibitors offer a promising alternative due to their selectivity and bioavailability. This study explores the effects of converting the naturally occurring cyclic inhibitor peptide of SIRT2 (S2iL5) into a non-cyclic form by replacing a residue with FAK (LYS + CF3CO−). The new peptide sequence, Tyr-His-Thr-Tyr-His-Val-FAK (LYS)-Arg-Arg-Thr-Asn-Tyr-Tyr-Cys, was modeled to confirm its stable conformation. Docking studies and MM/GBSA calculations showed that the non-cyclic peptide had a better binding free energy (−50.66 kcal/mol) compared to the cyclic S2iL5 (−49.44 kcal/mol). Further mutations generated 160,000 unique peptides, screened using a machine learning-based QSAR model. Three promising peptides (Peptide 1: YGGNNVKRRTNYYC, Peptide 2: YMGEWVKRRTNYYC, and Peptide 3: YGGNGVKRRTNYYC) were selected and further modeled. Molecular dynamics (MD) analyses demonstrated that Peptide 1 and Peptide 2 had significant potential as SIRT2 inhibitors, showing moderate stability and some structural flexibility. Their best binding free energies were −59.07 kcal/mol and −46.01 kcal/mol, respectively. The study aimed to enhance peptide flexibility and binding affinity, suggesting that optimized peptide-based inhibitors can interact effectively with SIRT2. However, further experimental validation is necessary to confirm these computational predictions and evaluate the therapeutic potential of the identified peptides. [ABSTRACT FROM AUTHOR]

Abstract Cytosolic Glycerol-3-phosphate dehydrogenase 1 (GPD1, EC 1.1.1.8) plays a pivotal role in regulating the Embden-Meyerhof glucose glycolysis pathway (E-M pathway), as well as in conditions such as Huntington’s disease, cancer, and its potential role as a specific marker for Dormant Glioma Stem Cells. In this study, we conducted virtual screening using the ZINC database ( http://zinc.docking.org/ ) and the GPD1 structure to identify potential GPD1 modulators. The investigation involved screening active candidate ligands using ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) parameters, combined with molecular docking, pose analysis, and interaction analysis based on Lipinski and Veber criteria. Subsequently, the top 10 ligands were subjected to 200 ns all-atom molecular dynamics (M.D.) simulations, and binding free energies were calculated. The findings revealed that specific residues, namely TRP14, PRO94, LYS120, ASN151, THR264, ASP260, and GLN298, played a crucial role in ensuring system stability. Furthermore, through a comprehensive analysis involving molecular docking, molecular M.D., and DeLA-Drug, we identified 10 promising small molecules. These molecules represent potential lead compounds for developing effective therapeutics targeting GPD1-associated diseases, thereby contributing to a deeper understanding of GPD1-associated mechanisms. This study's significance lies in identifying key residues associated with GPD1 and discovering valuable small molecules, providing a foundation for further research and development.

Cytosolic Glycerol-3-phosphate dehydrogenase 1 (GPD1, EC 1.1.1.8) plays a pivotal role in regulating the Embden-Meyerhof glucose glycolysis pathway (E-M pathway), as well as in conditions such as Huntington's disease, cancer, and its potential role as a specific marker for Dormant Glioma Stem Cells. In this study, we conducted virtual screening using the ZINC database (http://zinc.docking.org/) and the GPD1 structure to identify potential GPD1 modulators. The investigation involved screening active candidate ligands using ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) parameters, combined with molecular docking, pose analysis, and interaction analysis based on Lipinski and Veber criteria. Subsequently, the top 10 ligands were subjected to 200 ns all-atom molecular dynamics (M.D.) simulations, and binding free energies were calculated. The findings revealed that specific residues, namely TRP14, PRO94, LYS120, ASN151, THR264, ASP260, and GLN298, played a crucial role in ensuring system stability. Furthermore, through a comprehensive analysis involving molecular docking, molecular M.D., and DeLA-Drug, we identified 10 promising small molecules. These molecules represent potential lead compounds for developing effective therapeutics targeting GPD1-associated diseases, thereby contributing to a deeper understanding of GPD1-associated mechanisms. This study's significance lies in identifying key residues associated with GPD1 and discovering valuable small molecules, providing a foundation for further research and development. [ABSTRACT FROM AUTHOR]

Sirtuin 2 (SIRT2), an NAD+-dependent deacetylase, is crucial for regulating vital physiological processes, including aging, DNA repair, and cell cycle progression. Its abnormal activity is linked to diseases such as Parkinson’s disease, cancer, and metabolic disorders, making it a potential target for therapeutic intervention. While small molecule inhibitors have been studied, peptide-based inhibitors offer a promising alternative due to their selectivity and bioavailability. This study explores the effects of converting the naturally occurring cyclic inhibitor peptide of SIRT2 (S2iL5) into a non-cyclic form by replacing a residue with FAK (LYS + CF3CO−). The new peptide sequence, Tyr-His-Thr-Tyr-His-Val-FAK (LYS)-Arg-Arg-Thr-Asn-Tyr-Tyr-Cys, was modeled to confirm its stable conformation. Docking studies and MM/GBSA calculations showed that the non-cyclic peptide had a better binding free energy (−50.66 kcal/mol) compared to the cyclic S2iL5 (−49.44 kcal/mol). Further mutations generated 160,000 unique peptides, screened using a machine learning-based QSAR model. Three promising peptides (Peptide 1: YGGNNVKRRTNYYC, Peptide 2: YMGEWVKRRTNYYC, and Peptide 3: YGGNGVKRRTNYYC) were selected and further modeled. Molecular dynamics (MD) analyses demonstrated that Peptide 1 and Peptide 2 had significant potential as SIRT2 inhibitors, showing moderate stability and some structural flexibility. Their best binding free energies were −59.07 kcal/mol and −46.01 kcal/mol, respectively. The study aimed to enhance peptide flexibility and binding affinity, suggesting that optimized peptide-based inhibitors can interact effectively with SIRT2. However, further experimental validation is necessary to confirm these computational predictions and evaluate the therapeutic potential of the identified peptides.

Dengue fever presents a major health concern, and the lack of an effective vaccine or definite therapeutic regimen has led the research community to identify safe-by-design potential targets for drug discovery. Since the association of the NS2B co-factor with the protease domain of NS3 is imperative for the catalytic activity of the enzyme complex, inhibitors blocking their interaction could provide an alternative strategy to combat the dengue virus. In this context, the present study is aimed at exploring computer-assisted modeling of significant physicochemical features required for the inhibition of the dengue virus protease complex. First of all, alanine scanning was utilized to map hot spot residues critical for the association of the two subunits, NS2B and NS3pro, by studying their energy profiles. Then, consensus score-based virtual screening was performed to search through the commercially available chemical datasets. After screening, 1,575 small molecules were moved forward into docking studies to investigate their interactions with crucial interfacial residues (i.e., Tyr23, Lys26, Phe46, and Leu58), with only 233 molecules passing that stage. The top 30 molecules were selected based on a detailed profile of intermolecular interactions. After that, the top five molecules were selected for detailed mechanistic studies via molecular dynamics simulations followed by subsequent binding free energy calculations, principal component analysis in conjunction with free energy landscape. To the best of our knowledge, this is the first systematic and comprehensive investigation to identify protein–protein interaction blockers against the target protein at such a large scale, using integrated computational tools. Our results highlight the enhanced stability and good binding affinities towards the target protein of these compounds, which might act as new scaffolds for NS2B–NS3 protease inhibition. Future studies will be directed to explore the detailed atomistic-based structural and energetic framework of the mutation-induced affinity change between the protease domain of the DENV-2 NS3 protein and its cofactor NS2B. The detailed insight in turn might suggest precise and focused targeted points for the structure-based drug design but the computational cost may be a challenge. [ABSTRACT FROM AUTHOR]

Fibroblast growth factor receptor 2 (FGFR2), as a transmembrane receptor tyrosine kinase, is implicated in a plethora of human cancers, including intrahepatic cholangiocarcinomas, breast cancers, and non-small cell lung cancer. The clinically relevant V564F gatekeeper mutation conferred resistance to current FGFR2 drug − Infigratinib. In this study, the protein − ligand interactions between FGFR2 kinase domain (wild-type and V564F) and Infigratinib were compared through an integrated computational method. The multiple, large-scale molecular dynamics (MD) simulations, together with dynamic cross-correlation analysis and binding free energy calculations suggested that the resistant mutation may not trigger the conformational changes of the FGFR2 kinase domain. The simulation results also indicated that the driving force to decrease the binding affinity of Infigratinib to the FGFR2 V564F variant derived from the difference in the protein − ligand hydrogen bonding interactions. Moreover, the per-residue free energy decomposition analysis revealed that the reduced contributions from several residues in the ATP-binding site of FGFR2, especially Glu565 and Ala567 located at the kinase hinge domain, were the key residues responsible for the loss of binding affinity of Infigratinib to the V564F variant. This study may offer useful information for the design of novel selective kinase inhibitors targeting FGFR2. [ABSTRACT FROM AUTHOR]

AbstractFibroblast growth factor receptor 2 (FGFR2), as a transmembrane receptor tyrosine kinase, is implicated in a plethora of human cancers, including intrahepatic cholangiocarcinomas, breast cancers, and non-small cell lung cancer. The clinically relevant V564F gatekeeper mutation conferred resistance to current FGFR2 drug − Infigratinib. In this study, the protein − ligand interactions between FGFR2 kinase domain (wild-type and V564F) and Infigratinib were compared through an integrated computational method. The multiple, large-scale molecular dynamics (MD) simulations, together with dynamic cross-correlation analysis and binding free energy calculations suggested that the resistant mutation may not trigger the conformational changes of the FGFR2 kinase domain. The simulation results also indicated that the driving force to decrease the binding affinity of Infigratinib to the FGFR2 V564F variant derived from the difference in the protein − ligand hydrogen bonding interactions. Moreover, the per-residue free energy decomposition analysis revealed that the reduced contributions from several residues in the ATP-binding site of FGFR2, especially Glu565 and Ala567 located at the kinase hinge domain, were the key residues responsible for the loss of binding affinity of Infigratinib to the V564F variant. This study may offer useful information for the design of novel selective kinase inhibitors targeting FGFR2.

As one of the crucial targets of epigenetics, histone lysine-specific demethylase 1 (LSD1) is significant in the occurrence and development of various tumors. Although several irreversible covalent LSD1 inhibitors have entered clinical trials, the large size and polarity of the FAD-binding pocket and undesired toxicity have focused interest on developing reversible LSD1 inhibitors. In this study, targeting the substrate-binding pocket of LSD1, structure-based and ligand-based virtual screenings were adopted to expand the potential novel structures with molecular docking and pharmacophore model strategies, respectively. Through drug-likeness evaluation, ADMET screening, molecular dynamics simulations, and binding free energy screening, we screened out one and four hit compounds from the databases of 2,029,554 compounds, respectively. Generally, these hit compounds can be divided into two categories, amide (Lig2 and Comp2) and 1,2,4-triazolo-4,3-α-quinazoline (Comp3, Comp4, Comp7). Among them, Comp4 exhibits the strongest binding affinity. Finally, the binding mechanisms of the hit compounds were further calculated in detail by the residue free energy decomposition. It was found that van der Waals interactions contribute most to the binding, and FAD is also helpful in stabilizing the binding and avoiding off-target effects. We believe this work not only provides a solid theoretical foundation for the design of LSD1 substrate reversible inhibitors, but also expands the diversity of parent nucleus, offering new insights for synthetic chemists. [ABSTRACT FROM AUTHOR]

RNA-dependent RNA polymerase, non-structural protein 5B (NS5B), is an essential enzyme of HCV for viral transcription and genome replication. Its initial validation as a promising target for the treatment of chronic hepatitis and hepatocellular carcinoma has consequently prompted different research institutes and the pharmaceutical industry to find potential inhibitors for human therapies. Among those, anthranilic acid derivatives received increasing attention because of their promising drug-like properties. In order to design promising drug candidates, the structural determinants of NS5B inhibitors were determined by a robust fingerprint-based quantitative structure-activity relationship (QSAR) model which was depicted on atomic effect contribution maps to provide visual aids for medicinal chemists. In the present work, we used a combination of computational chemistry methods including ensemble docking, binding free energy calculations, and a fingerprint-based QSAR model. We built a robust in silico protocol to accelerate the structure-based design of HCV NS5B inhibitors. The QSAR model, kpls_linear_3, constructed by KPLS fitting with linear fingerprints produced the best predictive performance (a correlation coefficient for the training set R2 = 0.8900, and a correlation coefficient Q² = 0.9234 and RMSE = 0.3032 for the test compounds). The atomic effect contribution map that was generated based on this model showed a good agreement between the predictions and the experimental data. To the best of our knowledge, we illustrated for the first time the use of the atomic effect contribution map as a visual aid for assessing the structural determinants of NS5B inhibitors. The computational strategy represented herein can assist pharmaceutical chemists in the rapid identification of the important features to design novel inhibitors of other protein targets as well. [ABSTRACT FROM AUTHOR]

Introduction: Coronavirus disease 2019 (COVID-19) is an unprecedented pandemic, threatening human health worldwide. The need to produce novel small-molecule inhibitors against the ongoing pandemic has resulted in the use of drugs such as chloroquine, azithromycin, dexamethasone, favipiravir, ribavirin, remdesivir and azithromycin. Moreover, the reports of the clinical trials of these drugs proved to produce detrimental effects on patients with side effects like nephrotoxicity, retinopathy, cardiotoxicity and cardiomyopathy. Recognizing the need for effective and non-harmful therapeutic candidates to combat COVID-19, we aimed to develop promising drugs against SARS-COV-2. Discussion: In the current investigation, high-throughput virtual screening was performed using the Comprehensive Marine Natural Products Database against five non-structural proteins: Nsp3, Nsp5, Nsp12, Nsp13 and Nsp15. Furthermore, standard precision (SP) docking, extra precision (XP) docking, binding free energy calculation and absorption, distribution, metabolism, excretion and toxicity studies were performed using the Schrӧdinger suite. The top-ranked 5 hits obtained by computational studies exhibited to possess a greater binding affinity with the selected non-structural proteins. Amongst the five hits, CMNPD5804, CMNPD20924 and CMNPD1598 hits were utilized to design a novel molecule (D) that has the capability of interacting with all the key residues in the pocket of the selected non-structural proteins. Furthermore, 200 ns of molecular dynamics simulation studies provided insight into the binding modes of D within the catalytic pocket of selected proteins. Conclusion: Hence, it is concluded that compound D could be a promising inhibitor against these non-structural proteins. Nevertheless, there is still a need to conduct in vitro and in vivo studies to support our findings. [ABSTRACT FROM AUTHOR]

Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-CoV-2 mutations resulting in the emergence of new viral strains that can be resistant to the drugs used currently in the clinic necessitate the development of novel potent and broad therapeutic agents targeting different vulnerable spots of the viral proteins. In this study, two deep learning generative models were developed and used in combination with molecular modeling tools for de novo design of small molecule compounds that can inhibit the catalytic activity of SARS-CoV-2 main protease (Mpro), an enzyme critically important for mediating viral replication and transcription. As a result, the seven best scoring compounds that exhibited low values of binding free energy comparable with those calculated for two potent inhibitors of Mpro, via the same computational protocol, were selected as the most probable inhibitors of the enzyme catalytic site. In light of the data obtained, the identified compounds are assumed to present promising scaffolds for the development of new potent and broad-spectrum drugs inhibiting SARS-CoV-2 Mpro, an attractive therapeutic target for anti-COVID-19 agents. [ABSTRACT FROM AUTHOR]

Various organic derivatives of 1,3-dimethylbarbituric acid attract widespread interest as biologically active compounds, medicinal agents, and precursors in organic synthesis. The chemical reactivity of the cyclobutane moiety in 1,3-dimethyl-5-methylidenebarbituric acid dimer (2) was examined at room temperature toward various primary aliphatic amines (benzylamine, 4-methoxybenzylamine, and 3-fluorobenzylamine) and hydroxide ion, as well as in acidic medium. New compounds were prepared by ring-opening of the cyclobutane moiety via nucleophile attack on the exocyclic methylene group. The structures of the synthesized compounds were elucidated by employing 1H and 13C NMR (including DEPT) and mass spectrometric techniques. Molecular docking revealed a high binding affinity (–9.0 kcal/mol) of one of the obtained compounds (6). In addition, the molecular dynamics simulation and binding free energy calculation data confirmed that compound 6 is the most stable among the others. [ABSTRACT FROM AUTHOR]

Simple Summary: Carbonic anhydrases are a family of enzymes that catalyze an essential physiological reaction for living organisms: the reversible conversion of CO2 to bicarbonate ion. In humans, these enzymes impact many physiological and pathological processes including respiration, pH and CO2 homeostasis, electrolyte secretion, gluconeogenesis, ureagenesis, lipogenesis, bone resorption, and tumorigenicity. For this reason, several human carbonic anhydrases have become therapeutic targets for the treatment of many disorders. In recent years, a huge number of carbonic anhydrase inhibitors have been developed for therapeutics aims, such as diuretic, antiglaucoma, antiobesity, and anticonvulsant agents, and for the diagnosis and treatment of cancer diseases. The authors report a combined crystallographic and computational study on a promising class of carbonic anhydrase inhibitors to clarify their mechanism of action and to obtain useful information for the drug design of new effective and selective molecules. Aliphatic sulfonamides are an interesting class of carbonic anhydrase inhibitors (CAIs) proven to be effective for several carbonic anhydrase (CA) isoforms involved in pathologic states. Here we report the crystallographic structures of hCA II in complex with two aliphatic sulfonamides incorporating coumarin rings, which showed a good inhibition and selectivity for this isoform. Although these two molecules have a very similar chemical structure, differing only in the substitution of the two aliphatic hydrogen atoms with two fluorine atoms, they adopt a significantly different binding mode within the enzyme active site. Theoretical binding free energy calculations, performed to rationalize these data, showed that a delicate balance of electrostatic and steric effects modulate the protein-ligand interactions. Data presented here can be fruitfully used for the rational design of novel and effective isozyme-specific inhibitor molecules. [ABSTRACT FROM AUTHOR]

As a member of the receptor tyrosine kinase family, rearranged during transfection (RET) kinase has received increased interest as a therapeutic target for the treatment of thyroid cancer and non-small cell lung cancer (NSCLC). Selpercatinib has recently been approved by the US FDA for the treatment of RET fusion-positive thyroid cancer and NSCLC. However, the RET double mutation V804M/Y806C confers resistance to selpercatinib. Here, multiple μs molecular dynamics (MD) simulations and binding free energy calculations were performed to reveal the mechanism of selpercatinib resistance to the RET double mutant V804M/Y806C. Our results show that the double mutation has a minor effect on the overall conformational dynamics of the RET kinase domain. Obviously, the binding free energies calculated by the MM/GBSA method based on the MD simulations reveal that the dominant energy contributions for selpercatinib binding derive from the van der Waals interactions. Moreover, the per-residue free energy decomposition analysis unveils that Tyr806 at the hinge region plays an important role in the binding of selpercatinib through hydrophobic interactions. This study will provide useful information for understanding the mechanism of selpercatinib resistance to the RET double mutant V804M/Y806C. [ABSTRACT FROM AUTHOR]

Although dengue is a disease that affects more than 100 countries and puts almost 400 million lives at risk each year, there is no approved antiviral in the treatment of this pathology. In this context, proteases are potential biological targets since they are essential in the replication process of this virus. In this study, a library of more than 3,000 structures was used to explore the allosteric inhibition of the NS2B/NS3 protease complex using consensual docking techniques. The results show four best ranked structures that were selected for molecular dynamics and free energy simulations. The present analysis corroborates with other studies (experimental and theoretical) presented in the literature. Thus, the computational approach used here proved to be useful for planning new inhibitors in the combat against Dengue disease.

In the present study, the anti-diabetic potential of Ocimum tenuiflorum was investigated using computational techniques for α-glucosidase, α-amylase, aldose reductase, and glycation at multiple stages. It aimed to elucidate the mechanism by which phytocompounds of O. tenuiflorum treat diabetes mellitus using concepts of druglikeness and pharmacokinetics, molecular docking simulations, molecular dynamics simulations, and binding free energy studies. Isoeugenol is a phenylpropene, propenyl-substituted guaiacol found in the essential oils of plants. During molecular docking modelling, isoeugenol was found to inhibit all the target enzymes, with a higher binding efficiency than standard drugs. Furthermore, molecular dynamic experiments revealed that isoeugenol was more stable in the binding pockets than the standard drugs used. Since our aim was to discover a single lead molecule with a higher binding efficiency and stability, isoeugenol was selected. In this context, our study stands in contrast to other computational studies that report on more than one compound, making it difficult to offer further analyses. To summarize, we recommend isoeugenol as a potential widely employed lead inhibitor of α-glucosidase, α-amylase, aldose reductase, and glycation based on the results of our in silico studies, therefore revealing a novel phytocompound for the effective treatment of hyperglycemia and diabetes mellitus. [ABSTRACT FROM AUTHOR]

Xyloglucan endotransglycosylases (XETs) play key roles in the remodelling and reconstruction of plant cell walls. These enzymes catalyse homo-transglycosylation reactions with xyloglucan-derived donor and acceptor substrates and hetero-transglycosylation reactions with a variety of structurally diverse polysaccharides. In this work, we describe the basis of acceptor substrate binding specificity in non-specific Tropaeolum majus (TmXET6.3) and specific Populus tremula x tremuloides (PttXET16A) XETs, using molecular docking and molecular dynamics (MD) simulations combined with binding free energy calculations. The data indicate that the enzyme-donor (xyloglucan heptaoligosaccharide or XG-OS7)/acceptor complexes with the linear acceptors, where a backbone consisted of glucose (Glc) moieties linked via (1,4)- or (1,3)-β-glycosidic linkages, were bound stably in the active sites of TmXET6.3 and PttXET16A. Conversely, the acceptors with the (1,6)-β-linked Glc moieties were bound stably in TmXET6.3 but not in PttXET16A. When in the (1,4)-β-linked Glc containing acceptors, the saccharide moieties were replaced with mannose or xylose, they bound stably in TmXET6.3 but lacked stability in PttXET16A. MD simulations of the XET-donor/acceptor complexes with acceptors derived from (1,4;1,3)-β-glucans highlighted the importance of (1,3)-β-glycosidic linkages and side chain positions in the acceptor substrates. Our findings explain the differences in acceptor binding specificity between non-specific and specific XETs and associate theoretical to experimental data. [ABSTRACT FROM AUTHOR]

Diabetes mellitus is a major global health concern in the current scenario which is chiefly characterized by the rise in blood sugar levels or hyperglycemia. In the context, DPP4 enzyme plays a critical role in glucose homeostasis. DPP4 targets and inactivates incretin hormones such as glucagon-like peptide-1 (GLP-1) and gastric inhibitory polypeptide (GIP) as physiological substrates, which are essential to regulate the amount of insulin that is secreted after eating. Since the inactivation of incretins occurs, the hyperglycemic conditions continue to rise, and result in adverse physiological conditions linked with diabetes mellitus. Hence, inhibition of DPP4 has been the center of focus in the present antidiabetic studies. Although few DPP4 inhibitor drugs, such as alogliptin, saxagliptin, linagliptin, and sitagliptin, are available, their adverse effects on human metabolism are undeniable. Therefore, it becomes essential for the phytochemical intervention of the disease using computational methods prior to performing in vitro and in vivo studies. In this regard, we used an in-silico approach involving molecular docking, molecular dynamics simulations, and binding free energy calculations to investigate the inhibitory potential of Ocimum tenuiflorum phytocompounds against DPP4. In this regard, three phytocompounds (1S-α-pinene, β-pinene, and dehydro-p-cymene) from O. tenuiflorum have been discovered as the potential inhibitors of the DPP4 protein. To summarize, from our in-silico experiment outcomes, we propose dehydro-p-cymene as the potential lead inhibitor of DPP4 protein, thereby discovering new a phytocompound for the effective management of hyperglycemia and diabetes mellitus. The reported compound can be taken for in vitro and in vivo analyses in near future. [ABSTRACT FROM AUTHOR]

As one of the crucial targets of epigenetics, histone lysine-specific demethylase 1 (LSD1) is significant in the occurrence and development of various tumors. Although several irreversible covalent LSD1 inhibitors have entered clinical trials, the large size and polarity of the FAD-binding pocket and undesired toxicity have focused interest on developing reversible LSD1 inhibitors. In this study, targeting the substrate-binding pocket of LSD1, structure-based and ligand-based virtual screenings were adopted to expand the potential novel structures with molecular docking and pharmacophore model strategies, respectively. Through drug-likeness evaluation, ADMET screening, molecular dynamics simulations, and binding free energy screening, we screened out one and four hit compounds from the databases of 2,029,554 compounds, respectively. Generally, these hit compounds can be divided into two categories, amide (Lig2 and Comp2) and 1,2,4-triazolo-4,3-α-quinazoline (Comp3, Comp4, Comp7). Among them, Comp4 exhibits the strongest binding affinity. Finally, the binding mechanisms of the hit compounds were further calculated in detail by the residue free energy decomposition. It was found that van der Waals interactions contribute most to the binding, and FAD is also helpful in stabilizing the binding and avoiding off-target effects. We believe this work not only provides a solid theoretical foundation for the design of LSD1 substrate reversible inhibitors, but also expands the diversity of parent nucleus, offering new insights for synthetic chemists.

The crystal compound was synthesized and characterized using conventional analytical techniques. The compound C19H21O3 crystallizes in a monoclinic crystal system with the space group P21/c. The crystal structure is stabilized by C-H...O interactions. The structure is further reinforced by π-π interactions. During in vitro inhibition of α-glucosidase, the crystal compound exhibited a significant inhibition of the enzyme (IC50: 10.30 ± 0.25 µg/mL) in comparison with the control, acarbose (IC50: 12.00 ± 0.10 µg/mL). Molecular docking studies were carried out for the crystal compound with the α-glucosidase protein model, which demonstrated that the crystal molecule has a good binding affinity (−10.8 kcal/mol) compared with that of acarbose (−8.2 kcal/mol). The molecular dynamics simulations and binding free energy calculations depicted the stability of the crystal molecule throughout the simulation period (100 ns). Further, a Hirshfeld analysis was carried out in order to understand the packing pattern and intermolecular interactions. The energy difference between the frontier molecular orbitals (FMO) was 4.95 eV. [ABSTRACT FROM AUTHOR]

Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease characterized by progressive degeneration of motor neurons, resulting in respiratory failure and mortality within 3–5 years. Mutations in the Angiogenin (ANG) cause loss of ribonucleolytic and nuclear translocation activities, contributing to ALS pathogenesis. This study focused on investigating two uncharacterized ANG mutations, T11S and R122H, newly identified in the Project Mine consortium. Using extensive computational analysis, including structural modeling and microsecond-timescale molecular dynamics (MD) simulations, we observed conformational changes in the catalytic residue His114 of ANG induced by T11S and R122H mutations. These alterations impaired ribonucleolytic activity, as inferred through molecular docking and binding free energy calculations. Gibbs free energy landscape and residue-residue interaction network analysis further supported our findings, revealing the energetic states and allosteric pathway from the mutated site to His114. Additionally, we assessed the binding of NCI-65828, an inhibitor of ribonucleolytic activity of ANG, and found reduced effectiveness in binding to T11S and R122H mutants when His114 assumed a non-native conformation. This highlights the crucial role of His114 and its association with ALS. Elucidating the relationship between physical structure and functional dynamics of frequently mutated ANG mutants is essential for understanding ALS pathogenesis and developing more effective therapeutic interventions. [Display omitted] • ALS leads to motor neuron degeneration, respiratory failure, death in 3–5 years. • ANG mutations: T11S, R122H contribute to ALS by impairing ribonucleolytic activity. • Computational analysis reveals conformational changes induced by mutations. • Mutations hinder NCI-65828 binding efficacy, emphasizing significance of His114. • Understanding structural dynamics of ANG mutants may aid in therapy development. [ABSTRACT FROM AUTHOR]

Aliphatic sulfonamides are an interesting class of carbonic anhydrase inhibitors (CAIs) proven to be effective for several carbonic anhydrase (CA) isoforms involved in pathologic states. Here we report the crystallographic structures of hCA II in complex with two aliphatic sulfonamides incorporating coumarin rings, which showed a good inhibition and selectivity for this isoform. Although these two molecules have a very similar chemical structure, differing only in the substitution of the two aliphatic hydrogen atoms with two fluorine atoms, they adopt a significantly different binding mode within the enzyme active site. Theoretical binding free energy calculations, performed to rationalize these data, showed that a delicate balance of electrostatic and steric effects modulate the protein-ligand interactions. Data presented here can be fruitfully used for the rational design of novel and effective isozyme-specific inhibitor molecules.

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (RBDCoV2) has a higher binding affinity to the human receptor angiotensin-converting enzyme 2 (ACE2) than the SARS-CoV RBD (RBDCoV). Here, we performed molecular dynamics (MD) simulations, binding free energy (BFE) calculations, and interface residue contact network (IRCN) analysis to explore the mechanistic origin of different ACE2-binding affinities of the two RBDs. The results demonstrate that, when compared to the RBDCoV2-ACE2 complex, RBDCoV-ACE2 features enhanced dynamicsand inter-protein positional movements and increased conformational entropy and conformational diversity. Although the inter-protein electrostatic attractive interactions are the primary determinant for the high ACE2-binding affinities of both RBDs, the significantly enhanced electrostatic attractive interactions between ACE2 and RBDCoV2 determine the higher ACE2-binding affinity of RBDCoV2 than of RBDCoV. Comprehensive comparative analyses of the residue BFE components and IRCNs between the two complexes reveal that it is the residue changes at the RBD interface that lead to the overall stronger inter-protein electrostatic attractive force in RBDCoV2-ACE2, which not only tightens the interface packing and suppresses the dynamics of RBDCoV2-ACE2, but also enhances the ACE2-binding affinity of RBDCoV2. Since the RBD residue changes involving gain/loss of the positively/negatively charged residues can greatly enhance the binding affinity, special attention should be paid to the SARS-CoV-2 variants carrying such mutations, particularly those near or at the binding interfaces with the potential to form hydrogen bonds and/or salt bridges with ACE2. [ABSTRACT FROM AUTHOR]

FXR bioactive states are responsible for the regulation of metabolic pathways, which are modulated by agonists and co-activators. The synergy between agonist binding and ‘co-activator’ recruitment is highly conformationally driven. The characterization of conformational dynamics is essential for mechanistic and therapeutic understanding. To shed light on the conformational ensembles, dynamics, and structural determinants that govern the activation process of FXR, molecular dynamic (MD) simulation is employed. Atomic insights into the ligand binding domain (LBD) of FXR revealed significant differences in inter/intra molecular bonding patterns, leading to structural anomalies in different systems of FXR. The sole presence of an agonist or ‘co-activator’ fails to achieve the essential bioactive conformation of FXR. However, the presence of both establishes the bioactive conformation of FXR as they modulate the internal wiring of key residues that coordinate allosteric structural transitions and their activity. We provide a precise description of critical residue positioning during conformational changes that elucidate the synergy between its binding partners to achieve an FXR activation state. Our study offers insights into the associated modulation occurring in FXR at bound and unbound forms. Thereafter, we also identified hot-spots that are critical to arrest the activation mechanism of FXR that would be helpful for the rational design of its agonists.

Xyloglucan endotransglycosylases (XETs) play key roles in the remodelling and reconstruction of plant cell walls. These enzymes catalyse homo-transglycosylation reactions with xyloglucan-derived donor and acceptor substrates and hetero-transglycosylation reactions with a variety of structurally diverse polysaccharides. In this work, we describe the basis of acceptor substrate binding specificity in non-specific Tropaeolum majus (TmXET6.3) and specific Populus tremula x tremuloides (PttXET16A) XETs, using molecular docking and molecular dynamics (MD) simulations combined with binding free energy calculations. The data indicate that the enzyme-donor (xyloglucan heptaoligosaccharide or XG-OS7)/acceptor complexes with the linear acceptors, where a backbone consisted of glucose (Glc) moieties linked via (1,4)- or (1,3)-β-glycosidic linkages, were bound stably in the active sites of TmXET6.3 and PttXET16A. Conversely, the acceptors with the (1,6)-β-linked Glc moieties were bound stably in TmXET6.3 but not in PttXET16A. When in the (1,4)-β-linked Glc containing acceptors, the saccharide moieties were replaced with mannose or xylose, they bound stably in TmXET6.3 but lacked stability in PttXET16A. MD simulations of the XET-donor/acceptor complexes with acceptors derived from (1,4;1,3)-β-glucans highlighted the importance of (1,3)-β-glycosidic linkages and side chain positions in the acceptor substrates. Our findings explain the differences in acceptor binding specificity between non-specific and specific XETs and associate theoretical to experimental data.

Diabetes mellitus is a major global health concern in the current scenario which is chiefly characterized by the rise in blood sugar levels or hyperglycemia. In the context, DPP4 enzyme plays a critical role in glucose homeostasis. DPP4 targets and inactivates incretin hormones such as glucagon-like peptide-1 (GLP-1) and gastric inhibitory polypeptide (GIP) as physiological substrates, which are essential to regulate the amount of insulin that is secreted after eating. Since the inactivation of incretins occurs, the hyperglycemic conditions continue to rise, and result in adverse physiological conditions linked with diabetes mellitus. Hence, inhibition of DPP4 has been the center of focus in the present antidiabetic studies. Although few DPP4 inhibitor drugs, such as alogliptin, saxagliptin, linagliptin, and sitagliptin, are available, their adverse effects on human metabolism are undeniable. Therefore, it becomes essential for the phytochemical intervention of the disease using computational methods prior to performing in vitro and in vivo studies. In this regard, we used an in-silico approach involving molecular docking, molecular dynamics simulations, and binding free energy calculations to investigate the inhibitory potential of Ocimum tenuiflorum phytocompounds against DPP4. In this regard, three phytocompounds (1S-α-pinene, β-pinene, and dehydro-p-cymene) from O. tenuiflorum have been discovered as the potential inhibitors of the DPP4 protein. To summarize, from our in-silico experiment outcomes, we propose dehydro-p-cymene as the potential lead inhibitor of DPP4 protein, thereby discovering new a phytocompound for the effective management of hyperglycemia and diabetes mellitus. The reported compound can be taken for in vitro and in vivo analyses in near future.

Neuroblastoma (NB), as a metastatic form of solid tumor, has a high fatality rate found in early childhood. The two anaplastic lymphoma kinase (ALK) neoepitopes nonamer and decamer used in cancer immunotherapy against NB cancer can selectively bind to the human leukocyte antigen (HLA-B*15:01) groove with high affinities, whereas the native self-peptide is unable to interact with the HLA-B*15:01. Here, we performed molecular dynamics (MD) simulations and subsequent molecular mechanics-generalized born surface area (MM-GBSA) binding free energy calculations to explore the selective binding mechanisms of nonamer and decamer to the HLA-B*15:01 against the self-peptide. MD simulations revealed the significant conformational dynamics of the self-peptide in the HLA-B*15:01 groove against the nonamer and decamer. Binding free energy calculations showed that the binding affinities of HLA-B*15:01-neoepitope complexes were followed in the order decamer > nonamer > self-peptide. Detailed analysis of HLA-B*15:01-neoepitope structural complexes showed that compared to the nonamer, the self-peptide tended to move outward to the solvent, whereas the decamer moved deep to the HLA-B*15:01 groove. These different dynamic observations of the ALK neoepitopes can explain the distinct binding affinities of self-peptide, nonamer, and decamer to the HLA-B*15:01. The results may be useful for the design of more selective ALK neoepitopes. [ABSTRACT FROM AUTHOR]

Recent studies identified the benzoxaborole moiety as a new zinc-binding group able to interact with carbonic anhydrase (CA) active site. Here, we report a structural analysis of benzoxaboroles containing urea/thiourea groups, showing that these molecules are very versatile since they can bind the enzyme assuming different binding conformations and coordination geometries of the catalytic zinc ion. In addition, theoretical calculations of binding free energy were performed highlighting the key role of specific residues for protein-inhibitor recognition. Overall, these data are very useful for the development of new inhibitors with higher selectivity and efficacy for various CAs.

The crystal compound was synthesized and characterized using conventional analytical techniques. The compound C19H21O3 crystallizes in a monoclinic crystal system with the space group P21/c. The crystal structure is stabilized by C-H…O interactions. The structure is further reinforced by π-π interactions. During in vitro inhibition of α-glucosidase, the crystal compound exhibited a significant inhibition of the enzyme (IC50: 10.30 ± 0.25 µg/mL) in comparison with the control, acarbose (IC50: 12.00 ± 0.10 µg/mL). Molecular docking studies were carried out for the crystal compound with the α-glucosidase protein model, which demonstrated that the crystal molecule has a good binding affinity (−10.8 kcal/mol) compared with that of acarbose (−8.2 kcal/mol). The molecular dynamics simulations and binding free energy calculations depicted the stability of the crystal molecule throughout the simulation period (100 ns). Further, a Hirshfeld analysis was carried out in order to understand the packing pattern and intermolecular interactions. The energy difference between the frontier molecular orbitals (FMO) was 4.95 eV.

The design of new host–guest complexes represents a fundamental challenge in supramolecular chemistry. At the same time, it opens new opportunities in material sciences or biotechnological applications. A computational tool capable of automatically predicting the binding free energy of any host–guest complex would be a great aid in the design of new host systems, or to identify new guest molecules for a given host. We aim to build such a platform and have used the SAMPL7 challenge to test several methods and design a specific computational pipeline. Predictions will be based on machine learning (when previous knowledge is available) or a physics-based method (otherwise). The formerly delivered predictions with an RMSE of 1.67 kcal/mol but will require further work to identify when a specific system is outside of the scope of the model. The latter is combines the semiempirical GFN2B functional, with docking, molecular mechanics, and molecular dynamics. Correct predictions (RMSE of 1.45 kcal/mol) are contingent on the identification of the correct binding mode, which can be very challenging for host–guest systems with a large number of degrees of freedom. Participation in the blind SAMPL7 challenge provided fundamental direction to the project. More advanced versions of the pipeline will be tested against future SAMPL challenges. [ABSTRACT FROM AUTHOR]

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (RBDCoV2) has a higher binding affinity to the human receptor angiotensin-converting enzyme 2 (ACE2) than the SARS-CoV RBD (RBDCoV). Here, we performed molecular dynamics (MD) simulations, binding free energy (BFE) calculations, and interface residue contact network (IRCN) analysis to explore the mechanistic origin of different ACE2-binding affinities of the two RBDs. The results demonstrate that, when compared to the RBDCoV2-ACE2 complex, RBDCoV-ACE2 features enhanced dynamicsand inter-protein positional movements and increased conformational entropy and conformational diversity. Although the inter-protein electrostatic attractive interactions are the primary determinant for the high ACE2-binding affinities of both RBDs, the significantly enhanced electrostatic attractive interactions between ACE2 and RBDCoV2 determine the higher ACE2-binding affinity of RBDCoV2 than of RBDCoV. Comprehensive comparative analyses of the residue BFE components and IRCNs between the two complexes reveal that it is the residue changes at the RBD interface that lead to the overall stronger inter-protein electrostatic attractive force in RBDCoV2-ACE2, which not only tightens the interface packing and suppresses the dynamics of RBDCoV2-ACE2, but also enhances the ACE2-binding affinity of RBDCoV2. Since the RBD residue changes involving gain/loss of the positively/negatively charged residues can greatly enhance the binding affinity, special attention should be paid to the SARS-CoV-2 variants carrying such mutations, particularly those near or at the binding interfaces with the potential to form hydrogen bonds and/or salt bridges with ACE2.

Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges provide routes to compare chemical quantities determined using computational chemistry approaches to experimental measurements that are shared after the competition. For this effort, several computational methods have been used to calculate the binding energies of Octa Acid (OA) and exo-Octa Acid (exoOA) host–guest systems for SAMPL7. The initial poses for molecular dynamics (MD) were generated by molecular docking. Binding free energy calculations were performed using molecular mechanics combined with Poisson–Boltzmann or generalized Born surface area solvation (MMPBSA/MMGBSA) approaches. The factors that affect the utility of the MMPBSA/MMGBSA approaches including solvation, partial charge, and solute entropy models were also analyzed. In addition to MD calculations, quantum mechanics (QM) calculations were performed using several different density functional theory (DFT) approaches. From SAMPL6 results, B3PW91-D3 was found to overestimate binding energies though it was effective for geometry optimizations, so it was considered for the DFT geometry optimizations in the current study, with single-point energy calculations carried out with B2PLYP-D3 with double-, triple-, and quadruple-ζ level basis sets. Accounting for dispersion effects, and solvation models was deemed essential for the predictions. MMGBSA and MMPBSA correlated better to experiment when used in conjunction with an empirical/linear correction. [ABSTRACT FROM AUTHOR]

Andrographis Paniculata (AP) is well known for its antiviral and potential AIDS therapeutic property. Based on the experimental evidence we determined to find the potential molecule from AP against HIV-1 viral fusion. Hence the reported compounds present in the AP has been chosen for virtual screening and the results indicate that the molecules Bis-andrographolide ether and Beta-ducosterol forms required intermolecular interactions and have better binding affinity towards NHR of HIV-1 gp41 fusion inhibition. Further molecular docking, MD simulation, free energy calculations and ADME prediction have been carried out. The RMSD, RMSF, DSSP and PCA analysis reveals that mutation and binding mode of the molecules has high impact on the flexibility of gp41. Especially Intermolecular interactions and binding free energy values of these two molecules conveyed that the molecules will affect the viral fusion and six helix bundle formation. The ADME results proved their drug likeness properties. The present study indicates that the molecules can be the promising small molecule inhibitors of HIV-1 viral fusion and further drug designing. [ABSTRACT FROM AUTHOR]

Recent studies identified the benzoxaborole moiety as a new zinc-binding group able to interact with carbonic anhydrase (CA) active site. Here, we report a structural analysis of benzoxaboroles containing urea/thiourea groups, showing that these molecules are very versatile since they can bind the enzyme assuming different binding conformations and coordination geometries of the catalytic zinc ion. In addition, theoretical calculations of binding free energy were performed highlighting the key role of specific residues for protein-inhibitor recognition. Overall, these data are very useful for the development of new inhibitors with higher selectivity and efficacy for various CAs. [ABSTRACT FROM AUTHOR]

Heparanase (Hpse) is an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains. Its upregulated expression is implicated in tumor growth, metastasis and angiogenesis, thus making it an attractive target in cancer therapeutics. Currently, a few small molecule inhibitors have been reported to inhibit Hpse, with promising oral administration and pharmacokinetic (PK) properties. In the present study, a ligand-based pharmacophore model was generated from a dataset of well-known active small molecule Hpse inhibitors which were observed to display favorable PK properties. The compounds from the InterBioScreen database of natural (69,034) and synthetic (195,469) molecules were first filtered for their drug-likeness and the pharmacophore model was used to screen the drug-like database. The compounds acquired from screening were subjected to molecular docking with Heparanase, where two molecules used in pharmacophore generation were used as reference. From the docking analysis, 33 compounds displayed higher docking scores than the reference and favorable interactions with the catalytic residues. Complex interactions were further evaluated by molecular dynamics simulations to assess their stability over a period of 50 ns. Furthermore, the binding free energies of the 33 compounds revealed 2 natural and 2 synthetic compounds, with better binding affinities than reference molecules, and were, therefore, deemed as hits. The hit compounds presented from this in silico investigation could act as potent Heparanase inhibitors and further serve as lead scaffolds to develop compounds targeting Heparanase upregulation in cancer.

Sulphamate and sulphamide derivatives have been largely investigated as carbonic anhydrase inhibitors (CAIs) by means of different experimental techniques. However, the structural determinants responsible for their different binding mode to the enzyme active site were not clearly defined so far. In this paper, we report the X-ray crystal structure of hCA II in complex with a sulphamate inhibitor incorporating a nitroimidazole moiety. The comparison with the structure of hCA II in complex with its sulphamide analogue revealed that the two inhibitors adopt a completely different binding mode within the hCA II active site. Starting from these results, we performed a theoretical study on sulphamate and sulphamide derivatives, demonstrating that electrostatic interactions with residues within the enzyme active site play a key role in determining their binding conformation. These findings open new perspectives in the design of effective CAIs using the sulphamate and sulphamide zinc binding groups as lead compounds.

The emergence of new Mycobacterium tuberculosis ( Mtb ) strains resistant to the key drugs currently used in the clinic for tuberculosis treatment can substantially reduce the probability of therapy success, causing the relevance and importance of studies on the development of novel potent antibacterial agents targeting different vulnerable spots of Mtb . In this study, 28,860 compounds from the library of bioactive molecules were screened to identify novel potential inhibitors of β-ketoacyl-acyl carrier protein synthase I (KasA), one of the key enzymes involved in the biosynthesis of mycolic acids of the Mtb cell wall. In doing so, we used a structure-based virtual screening approach to drug repurposing that included high-throughput docking of the C171Q KasA enzyme with compounds from the library of bioactive molecules including the FDA-approved drugs and investigational drug candidates, assessment of the binding affinity for the docked ligand/C171Q KasA complexes, and molecular dynamics simulations followed by binding free energy calculations. As a result, post-modeling analysis revealed 6 top-ranking compounds exhibiting a strong attachment to the malonyl binding site of the enzyme, as evidenced by the values of binding free energy which are significantly lower than those predicted for the KasA inhibitor TLM5 used in the calculations as a positive control. In light of the data obtained, the identified compounds are suggested to form a good basis for the development of new antitubercular molecules of clinical significance with activity against the KasA enzyme of Mtb .Communicated by Ramaswamy H. Sarma.

The spike (S) glycoprotein and nucleocapsid (N) proteins are the crucial pathogenic proteins of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS CoV-2) virus during its interaction with the host. Even FDA-approved drugs like dexamethasone and grazoprevir are not able to curb the viral progression inside the host and are reported with adverse effects on body metabolism. In this context, we aim to report corilagin a novel, potential dual inhibitor of S and N proteins from Terminalia chebula. The bioactive compounds of T. chebula were subjected to a series of computational investigations including molecular docking simulations, molecular dynamics (MD) simulations, binding free energy calculations, and PASS pharmacological analysis. The results obtained from these studies revealed that corilagin was highly interactive with the S (-8.9 kcal/mol) and N (-9.2 kcal/mol) proteins, thereby showing dual inhibition activity. It was also found to be stable enough to induce biological activity inside the inhibitor binding pocket of the target enzymes throughout the dynamics simulation run for 100 ns. This is also confirmed by the changes in the protein conformations, evaluated using free energy landscapes. Outcomes from this investigation identify corilagin as the lead potential dual inhibitor of S and N proteins of SARS-CoV-2, which could be taken for biological studies in near future.Communicated by Ramaswamy H. Sarma.

Histone-modifying proteins have been identified as promising targets to treat several diseases including cancer and parasitic ailments. In silico methods have been incorporated within a variety of drug discovery programs to facilitate the identification and development of novel lead compounds. In this study, we explore the binding modes of a series of benzhydroxamates derivatives developed as histone deacetylase inhibitors of Schistosoma mansoni histone deacetylase (smHDAC) using molecular docking and binding free energy (BFE) calculations. The developed docking protocol was able to correctly reproduce the experimentally established binding modes of resolved smHDAC8–inhibitor complexes. However, as has been reported in former studies, the obtained docking scores weakly correlate with the experimentally determined activity of the studied inhibitors. Thus, the obtained docking poses were refined and rescored using the Amber software. From the computed protein–inhibitor BFE, different quantitative structure–activity relationship (QSAR) models could be developed and validated using several cross-validation techniques. Some of the generated QSAR models with good correlation could explain up to ~73% variance in activity within the studied training set molecules. The best performing models were subsequently tested on an external test set of newly designed and synthesized analogs. In vitro testing showed a good correlation between the predicted and experimentally observed IC50 values. Thus, the generated models can be considered as interesting tools for the identification of novel smHDAC8 inhibitors.

Purpose: Several tracers have been designed for tracking the abnormal accumulation of tau pathology in vivo. Recently, concerns have been raised about the sources of off-target binding for these tracers; inconclusive data propose binding for some tracers to monoamine oxidase B (MAO-B). Methods: Molecular docking and dynamics simulations were used to estimate the affinity and free energy for the binding of several tau tracers (FDDNP, THK523, THK5105, THK5317, THK5351, T807 [aka AV-1451, flortaucipir], T808, PBB3, RO-948, MK-6240, JNJ-311 and PI-2620) to MAO-B. These values were then compared with those for safinamide (MAO-B inhibitor). PET imaging was used with the tau tracer [18F]THK5317 and the MAO-B tracer [11C]DED in five patients with Alzheimer's disease to investigate the MAO-B binding component of this first generation tau tracer in vivo. Results: The computational modelling studies identified a binding site for all the tau tracers on MAO-B; this was the same site as that for safinamide. The binding affinity and free energy of binding for the tau tracers to MAO-B was substantial and in a similar range to those for safinamide. The most recently developed tau tracers MK-6240, JNJ-311 and PI-2620 appeared, in silico, to have the lowest relative affinity for MAO-B. The in vivo investigations found that the regional distribution of binding for [18F]THK5317 was different from that for [11C]DED, although areas of suspected off-target [18F]THK5317 binding were detected. The binding relationship between [18F]THK5317 and [11C]DED depended on the availability of the MAO-B enzyme. Conclusions: The developed tau tracers show in silico and in vivo evidence of cross-interaction with MAO-B; the MAO-B component of the tracer binding was dependent on the regional concentration of the enzyme. [ABSTRACT FROM AUTHOR]

Abstract In the current work, we applied computational methods to analyze the membrane-associated inhibitory kinase PKMYT1 and small molecule inhibitors. PKMYT1 regulates the cell cycle at G2/M transition and phosphorylates Thr14 and Tyr15 in the Cdk1-cyclin B complex. A combination of in silico and in vitro screening was applied to identify novel PKMYT1 inhibitors. The computational approach combined structural analysis, molecular docking, binding free energy calculations, and quantitative structure–activity relationship (QSAR) models. In addition, a computational fragment growing approach was applied to a set of previously identified diaminopyrimidines. Based on the derived computational models, several derivatives were synthesized and tested in vitro on PKMYT1. Novel inhibitors active in the sub-micromolar range were identified which provide the basis for further characterization of PKMYT1 as putative target for cancer therapy. Graphical abstract Image 1 Highlights • We generated several computational models in order to predict the biological activity of novel PKMYT1 inhibitors. • The binding free energy calculations were significant to predict the activities of the compounds. • Then, the applied fragment growing allowed to design a first set of diaminopyrimidine derivatives, which are active in the sub-micromolar range (e.g. compound 5l). • Thus, we were able to assess first structure-activity relationships of the diaminopyrimidine derivatives. • The derived results provide now the basis for further chemical modifications to design more potent PKMYT1 inhibitors. [ABSTRACT FROM AUTHOR]

Monoamine oxidase B (MAOB) is expressed in the mitochondrial membrane and has a key role in degrading various neurologically active amines such as benzylamine, phenethylamine and dopamine with the help of Flavin adenine dinucleotide (FAD) cofactor. The Parkinson’s disease associated symptoms can be treated using inhibitors of MAO-B as the dopamine degradation can be reduced. Currently, many inhibitors are available having micromolar to nanomolar binding affinities. However, still there is demand for compounds with superior binding affinity and binding specificity with favorable pharmacokinetic properties for treating Parkinson’s disease and computational screening methods can be majorly recruited for this. However, the accuracy of currently available force-field methods for ranking the inhibitors or lead drug-like compounds should be improved and novel methods for screening compounds need to be developed. We studied the performance of various force-field-based methods and data driven approaches in ranking about 3753 compounds having activity against the MAO-B target. The binding affinities computed using autodock and autodock-vina are shown to be non-reliable. The force-field-based MM-GBSA also under-performs. However, certain machine learning approaches, in particular KNN, are found to be superior, and we propose KNN as the most reliable approach for ranking the complexes to reasonable accuracy. Furthermore, all the employed machine learning approaches are also computationally less demanding.

Activin-like kinase 5 (ALK-5) is involved in the physiopathology of several conditions, such as pancreatic carcinoma, cervical cancer and liver hepatoma. Cellular events that are landmarks of tumorigenesis, such as loss of cell polarity and acquisition of motile properties and mesenchymal phenotype, are associated to deregulated ALK-5 signaling. ALK-5 inhibitors, such as SB505154, GW6604, SD208, and LY2157299, have recently been reported to inhibit ALK-5 autophosphorylation and induce the transcription of matrix genes. Due to their ability to impair cell migration, invasion and metastasis, ALK-5 inhibitors have been explored as worthwhile hits as anticancer agents. This work reports the development of a structure-based virtual screening (SBVS) protocol aimed to prospect promising hits for further studies as novel ALK-5 inhibitors. From a lead-like subset of purchasable compounds, five molecules were identified as putative ALK-5 inhibitors. In addition, molecular dynamics and binding free energy calculations combined with pharmacokinetics and toxicity profiling demonstrated the suitability of these compounds to be further investigated as novel ALK-5 inhibitors.

The drug/proton antiporter AcrB, engine of the major efflux pump AcrAB(Z)-TolC of Escherichia coli and other bacteria, is characterized by its impressive ability to transport chemically diverse compounds, conferring a multi-drug resistance (MDR) phenotype. Although hundreds of small molecules are known to be AcrB substrates, only a few co-crystal structures are available to date. Computational methods have been therefore intensively employed to provide structural and dynamical fingerprints related to transport and inhibition of AcrB. In this work, we performed a systematic computational investigation to study the interaction between representative carbapenem antibiotics and AcrB. We focused on the interaction of carbapenems with the so-called distal pocket, a region known for its importance in binding inhibitors and substrates of AcrB. Our findings reveal how the different physico-chemical nature of these antibiotics is reflected on their binding preference for AcrB. The molecular-level information provided here could help design new antibiotics less susceptible to the efflux mechanism.