Various posttranslational modifications like hyperphosphorylation, O-GlcNAcylation, and acetylation have been attributed to induce the abnormal folding in tau protein. Recent in vitro studies revealed the possible involvement of N-glycosylation of tau protein in the abnormal folding and tau aggregation. Hence, in this study, we performed a microsecond long all atom molecular dynamics simulation to gain insights into the effects of N-glycosylation on Asn-359 residue which forms part of the microtubule binding region. Trajectory analysis of the stimulations coupled with essential dynamics and free energy landscape analysis suggested that tau, in its N-glycosylated form tends to exist in a largely folded conformation having high beta sheet propensity as compared to unmodified tau which exists in a large extended form with very less beta sheet propensity. Residue interaction network analysis of the lowest energy conformations further revealed that Phe378 and Lys353 are the functionally important residues in the peptide which helped in initiating the folding process and Phe378, Lys347, and Lys370 helped to maintain the stability of the protein in the folded state.
Objectives: The aim of the present study is to illustrate compatibility testing of ganciclovir (GCV) with some common excipients that would be used to manufacture solid oral dosage forms. Different spectroscopy techniques were utilized to see the interaction of GCV with excipients such as lactose, microcrystalline cellulose (MCC), magnesium stearate, and talc, and dicalcium phosphate. Further, a molecular docking study was also done to know the interaction of GCV with excipients. In vitro study of a physical mixture of GCV with excipients was performed to get the release of drug. Material and Methods: A number of analytical techniques (differential scanning calorimetry [DSC] using DSC-Q20, TA instruments, Fourier-transform infrared spectroscopy [FTIR] spectroscopy using Spectrum RX 1, nuclear magnetic resonance [NMR] using Bruker Advance Neo 500 MHz NMR spectrometer, etc.) have been used to explore the drug-excipient compatibility. Further, a suspected interaction was evaluated by thin-layer chromatography (TLC). In vitro dissolution studies in different sets of experiments were accomplished to determine the influence of hydrophobic and hydrophilic attributes of excipients (MCC, lactose, dicalcium phosphate, and talc) on the dissolution profile of GCV using USP1-type dissolution apparatus. Furthermore, in silico molecular docking studies were also performed to evaluate any probable molecular interactions among drugs and excipients using Auto Dock VINA 1.2.0 software and GROMACS 5.0 software. Results: Comparing FTIR and 1 H NMR spectra of GCV and physical mixtures of GCV and excipients, no significant deviation of characteristic peaks in infrared spectroscopy and 1 H NMR signals was observed. The DSC of GCV showed two sharp endothermic peaks at 238.82°C and 255°C. The endothermic peak of GCV in DSC thermogram of physical mixtures was observed in nearly the same position except with lactose and dicalcium phosphate. A slightly deviated peak of GCV with a physical mixture of drug and lactose and dicalcium phosphate indicated that there were suspected interactions between the drug with lactose and dicalcium phosphate. These interactions were evaluated by thin-layer chromatography (TLC) and it confirmed that there was no interaction between drugs and excipients. In vitro dissolution studies determined the influence of hydrophobic and hydrophilic attributes of excipients on the dissolution profile of GCV. The physical mixture of GCV with MCC displayed a maximum amount (66.48%) of drug release in 10 min. On the other hand, a physical mixture of GCV with talc showed a minimum amount (12.08%) of drug release in 10 min. Docking study predicted that the number of interactions were more between GCV and lactose (four nos.) in comparison to GCV and MCC (two nos.). This interaction supported the in vitro drug release of a physical mixture of GCV with MCC which was higher than a mixture of GCV with lactose. Conclusion: Compatibility testing of GCV with used excipients by analytical techniques confirmed that GCV should be compatible with used excipients. Drug dissolution of GCV and physical mixture of MCC exhibited the maximum amount of drug release whereas a mixture of GCV with talc released the minimum amount of drug for both short (10 min.) and long (60 min.) periods. Docking studies disclosed that the lactose complex showed less deviation with less root mean square deviation value in comparison to the microcrystalline complex. Thus, the lactose complex has more hydrogen bonds and it was more stable as compared with the MCC complex. GCV indicates that the total energy of the MCC complex is less than that of the lactose complex. This indicates that GCV is more soluble when combined with the microcrystalline complex. Therefore, GCV and used excipients could be used for solid dosage formulations.
1 Summary The spike protein of SARS-CoV-2 is a highly flexible membrane receptor that triggers the translocation of the virus into cells by attaching to the human receptors. Like other type I membrane receptors, this protein has several extracellular domains connected by flexible hinges. The presence of these hinges results in high flexibility, which consequently results in challenges in defining the conformation of the protein. Here, We developed a new method to define the conformational space based on a few variables inspired by the robotic field’s methods to determine a robotic arm’s forward kinematics. Using newly performed atomistic molecular dynamics (MD) simulations and publicly available data, we found that the Denavit-Hartenberg (DH) parameters can reliably show the changes in the local conformation. Furthermore, the rotational and translational components of the homogenous transformation matrix constructed based on the DH parameters can identify the changes in the global conformation of the spike and also differentiate between the conformation with a similar position of the spike head, which other types of parameters, such as spherical coordinates, fail to distinguish between such conformations. Finally, the new method will be beneficial for looking at the conformational heterogeneity in all other type I membrane receptors.
A few decades ago, drug discovery and development were limited to a bunch of medicinal chemists working in a lab with enormous amount of testing, validations, and synthetic procedures, all contributing to considerable investments in time and wealth to get one drug out into the clinics. The advancements in computational techniques combined with a boom in multi-omics data led to the development of various bioinformatics/pharmacoinformatics/cheminformatics tools that have helped speed up the drug development process. But with the advent of artificial intelligence (AI), machine learning (ML) and deep learning (DL), the conventional drug discovery process has been further rationalized. Extensive biological data in the form of big data present in various databases across the globe acts as the raw materials for the ML/DL-based approaches and helps in accurate identifications of patterns and models which can be used to identify therapeutically active molecules with much fewer investments on time, workforce and wealth. In this review, we have begun by introducing the general concepts in the drug discovery pipeline, followed by an outline of the fields in the drug discovery process where ML/DL can be utilized. We have also introduced ML and DL along with their applications, various learning methods, and training models used to develop the ML/DL-based algorithms. Furthermore, we have summarized various DL-based tools existing in the public domain with their application in the drug discovery paradigm which includes DL tools for identification of drug targets and drug-target interaction such as DeepCPI, DeepDTA, WideDTA, PADME DeepAffinity, and DeepPocket. Additionally, we have discussed various DL-based models used in protein structure prediction, de novo design of new chemical scaffolds, virtual screening of chemical libraries for hit identification, absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction, metabolite prediction, clinical trial design, and oral bioavailability prediction. In the end, we have tried to shed light on some of the successful ML/DL-based models used in the drug discovery and development pipeline while also discussing the current challenges and prospects of the application of DL tools in drug discovery and development. We believe that this review will be useful for medicinal and computational chemists searching for DL tools for use in their drug discovery projects.
Objectives: The objective of this present study is to know the compatibility of valacyclovir hydrochloride (VCH) with common excipients that would be utilized to develop solid oral dosage forms. Several spectroscopy techniques were used to know the possible interactions of VCH with excipients. More, a molecular docking study was also carried out to see the interaction of VCH with excipients. In vitro study of a physical mixture of VCH with excipients was executed to know the release of a drug. Material and Methods: Several analytical techniques such as differential scanning calorimetry, nuclear magnetic resonance spectrometer, and Fourier-transform infrared (FTIR) spectroscopy have been utilized to know the drug-excipient compatibility. Further, possible interactions between valacyclovir and different excipients were assessed by thin-layer chromatography. In vitro dissolution studies in different sets of experiments were done to determine the influence of the hydrophobic and hydrophilic nature of excipients (on the dissolution profile of VCH using USP II-type dissolving apparatus). Moreover, in silico molecular docking studies were also done to know any possible molecular interactions among drugs and excipients using AutoDock VINA 1.2.0 software and GROMACS 5.0 software. Results: FTIR and 1 H NMR spectra of VCH and physical mixtures of VCH and excipients were compared and it was observed that no significant deviation of characteristic peaks in infrared spectroscopy and 1 H NMR signals was detected. The endothermic peak of VCH in the physical mixtures of drugs and excipients was found in approximately the same position. In vitro dissolution studies displayed the influence of the hydrophobic and hydrophilic nature of excipients on the dissolution profile of VCH. For the physical mixture of VCH with lactose (LAC) and dicalcium phosphate (DP), % drug release was found to be 31.96% and 33.16% at 10 min, whereas the amount of % drug released for the mixture of VCH and talc was 25.00%. For two other excipients such as LAC and DP, the % drug release was determined to be 42.96% and 41.64%, respectively, for 30 min. The docking study also provided insights into the lowest energy conformations. Docking study anticipated that the number of interactions were more between valacyclovir and LAC (four nos.) in comparison to valacyclovir and microcrystalline cellulose (MCC) (two nos.). This interaction showed that in vitro drug release for the physical mixture of VCH with MCC was higher than a mixture of valacyclovir with LAC. Conclusion: A compatibility study of VCH by analytical techniques established that VCH was compatible with utilized excipients. Drug dissolution of VCH and physical mixture of MCC exhibited the maximum amount of drug release whereas a mixture of VCH with magnesium stearate released the minimum amount of drug for both short (10 min.) and long (30 min.) period. Docking studies disclosed that the LAC complex showed less deviation with less root mean square deviation value in comparison to the microcrystalline complex. Thus, the LAC complex has more hydrogen bonds and it was more stable as compared with the MCC complex. Therefore, VCH and used excipients could be used for solid dose formulations.
Various post translational modifications like hyper phosphorylation, O-GlycNAcylation, and acetylation have been attributed to induce the abnormal folding in tau protein. Recent in vitro studies revealed the possible involvement of N–glycosylation of tau protein in the abnormal folding and tau aggregation. Hence in this study, we performed microsecond long all atom molecular dynamics simulation to gain insights into the effects of N-glycosylation on Asn-359residue which forms part of the microtubule binding region. Trajectory analysis of the stimulations coupled with essential dynamics and free energy landscape analysis suggested that tau, in its N-glycosylated form tend to exist in a largely folded conformation having high beta sheet propensity as compared to unmodified tau which exists in a large extended form with very less beta sheet propensity. Residue interaction network analysis of the lowest energy conformations further revealed that Phe378 and Lys353 are the functionally important residues in the peptide which helped in initiating the folding process and Phe378, Lys347&Lys370 helped maintaining the stability of the protein in the folded state.
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